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Assessing the Carcinogenic Potential of Low Dose Exposures to Chemical Mixtures in the Environment: The Challenge Ahead

June 2015
Carcinogenesis 36(S1):S254–S296

DOI:10.1093/carcin/bgv039

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CC BY-NC 4.0

Authors:

William H. Goodson

Leroy Lowe

David Orlo Carpenter

University at Albany, The State University of New York

Michael Gilbertson

Retired from International Joint Commission

Show all 174 authorsHide

Lifestyle factors are responsible for a considerable portion of cancer incidence worldwide, but credible estimates from the World Health Organization and the International Agency for Research on Cancer (IARC) suggest that the fraction of cancers attributable to toxic environmental exposures is between 7% and 19%. To explore the hypothesis that low-dose exposures to mixtures of chemicals in the environment may be combining to contribute to environmental carcinogenesis, we reviewed 11 hallmark phenotypes of cancer, multiple priority target sites for disruption in each area and prototypical chemical disruptors for all targets, this included dose-response characterizations, evidence of low-dose effects and cross-hallmark effects for all targets and chemicals. In total, 85 examples of chemicals were reviewed for actions on key pathways/mechanisms related to carcinogenesis. Only 15% (13/85) were found to have evidence of a dose-response threshold, whereas 59% (50/85) exerted low-dose effects. No dose-response information was found for the remaining 26% (22/85). Our analysis suggests that the cumulative effects of individual (non-carcinogenic) chemicals acting on different pathways, and a variety of related systems, organs, tissues and cells could plausibly conspire to produce carcinogenic synergies. Additional basic research on carcinogenesis and research focused on low-dose effects of chemical mixtures needs to be rigorously pursued before the merits of this hypothesis can be further advanced. However, the structure of the World Health Organization International Programme on Chemical Safety 'Mode of Action' framework should be revisited as it has inherent weaknesses that are not fully aligned with our current understanding of cancer biology. © The Author 2015. Published by Oxford University Press.

. Aggregated evidence of cross-hallmark effects for selected chemical disruptors

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Volume 36 Supplement 1 June 2015

www.carcin.oxfordjournals.org

Assessing the Carcinogenic Potential of Low-Dose Exposures

to Chemical Mixtures in the Environment: The Challenge Ahead

Volume 36 Supplement 1 June 2015

Carcinogenesis Integrative Cancer Research

CARCINOGENESIS SUPPLEMENT

Assessing the Carcinogenicity of Low-Dose

Exposures to Chemical Mixtures in the

Environment: The Challenge Ahead

Editor-in-Chief

Curtis C. Harris

We gratefully acknowledge the support of the National Institute of Health (NIH)-National Institute of

Environmental Health Sciences (NIEHS) conference grant travel support [R13ES023276]

EDITORIAL

Cause and Prevention of Human Cancer

Curtis C Harris ..............................................................................S1

REVIEWS

Mechanisms of environmental chemicals that enable the cancer hallmark of evasion of growth

suppression

RitaNahta, FahdAl-Mulla, RabeahAl-Temaimi, AmedeoAmedei, RafaelaAndrade-Vieira, SarahBay,

DustinG.Brown, GloriaM.Calaf, RobertC.Castellino, KarineA.Cohen-Solal, AnnamariaColacci,

NicholaCruickshanks, PaulDent, RiccardoDiFiore, StefanoForte, GaryS.Goldberg, RoslidaA.Hamid,

HariniKrishnan, DaleW.Laird, AhmedLasfar, PaolaA.Marignani, LorenzoMemeo, ChiaraMondello,

ChristianC.Naus, RichardPonce-Cusi, JayadevRaju, DebasishRoy, RabindraRoy, ElizabethP.Ryan,

HosniK.Salem, A.IvanaScovassi, NeetuSingh, MonicaVaccari, RenzaVento, JanVondráček, MarkWade,

JordanWoodrick, and WilliamH.Bisson...........................................................S2

Disruptive chemicals, senescence and immortality

AmancioCarnero, CarmenBlanco-Aparicio, HiroshiKondoh, MatildeE.Lleonart, JuanFernando

Martinez-Leal, ChiaraMondello, A.IvanaScovassi, WilliamH.Bisson, AmedeoAmedei, RabindraRoy,

JordanWoodrick, AnnamariaColacci, MonicaVaccari, JayadevRaju, FahdAl-Mulla, RabeahAl-Temaimi,

HosniK.Salem, LorenzoMemeo, StefanoForte, NeetuSingh, RoslidaA.Hamid, ElizabethP.Ryan,

DustinG.Brown, JohnPierceWiseSr, SandraS.Wise, and HemadYasaei ...............................S19

The potential for chemical mixtures from the environment to enable the cancer hallmark of

sustained proliferative signalling

WilhelmEngström, PhilippaDarbre, StaffanEriksson, LindaGulliver, ToveHultman, MichalisV.Karamouzis,

JamesE.Klaunig, RekhaMehta, KimMoorwood, ThomasSanderson, HidekoSone, PankajVadgama,

GerardWagemaker, AndrewWard, NeetuSingh, FahdAl-Mulla, RabeahAl-Temaimi, AmedeoAmedei,

AnnaMariaColacci, MonicaVaccari, ChiaraMondello, A.IvanaScovassi, JayadevRaju, RoslidaA.Hamid,

LorenzoMemeo, StefanoForte, RabindraRoy, JordanWoodrick, HosniK.Salem, ElizabethRyan,

DustinG.Brown, and WilliamH.Bisson .........................................................S38

Causes of genome instability: the effect of low dose chemical exposures in modern society

SabineA.S.Langie, GudrunKoppen, DanielDesaulniers, FahdAl-Mulla, RabeahAl-Temaimi, AmedeoAmedei,

AmayaAzqueta, WilliamH.Bisson, DustinBrown, GunnarBrunborg, AmeliaK.Charles, TaoChen,

AnnamariaColacci, FirouzDarroudi, StefanoForte, LaetitiaGonzalez, RoslidaA.Hamid, LisbethE.Knudsen,

LucLeyns, AdelaLopezdeCerainSalsamendi, LorenzoMemeo, ChiaraMondello, CarmelMothersill,

Ann-KarinOlsen, SoaPavanello, JayadevRaju, EmilioRojas, RabindraRoy, ElizabethRyan, Patricia

Ostrosky-Wegman, HosniK.Salem, IvanaScovassi, NeetuSingh, MonicaVaccari, FrederikJ.VanSchooten,

MaharaValverde, JordanWoodrick, LuopingZhang, NikvanLarebeke, MichelineKirsch-Volders,

and AndrewR.Collins........................................................................S61

Disruptive environmental chemicals and cellular mechanisms that confer resistance to celldeath

KannanBadriNarayanan, ManafAli, BarryJ.Barclay, QiangCheng, LeandroD’Abronzo, Rita

Dornetshuber-Fleiss, ParamitaM.Ghosh, MichaelJ.GonzalezGuzman, Tae-JinLee, PoSingLeung, LinLi,

SuidjitLuanpitpong, EdwardRatovitski, YonRojanasakul, MariaFiammettaRomano, SimonaRomano,

RanjeetKumarSinha, ClementYedjou, FahdAl-Mulla, RabeahAl-Temaimi, AmedeoAmedei, DustinG.

Brown, ElizabethP.Ryan, AnnamariaColacci, RoslidaA.Hamid, ChiaraMondello, JayadevRaju, HosniK.Salem,

JordanWoodrick, IvanaScovassi, NeetuSingh, MonicaVaccari, RabindraRoy, StefanoForte, LorenzoMemeo,

SeoYunKim, WilliamH.Bisson, LeroyLowe, and HyunHoPark.......................................S89

JOURNAL OF CARCINOGENESIS

VOLUME 36, SUPPLEMENT 1

MAY 2015

Contents

Chemical compounds from anthropogenic environment and immune evasion

mechanisms: potential interactions

JuliaKravchenko, EmanuelaCorsini, MarcA.Williams, WilliamDecker, MasoudH.Manjili, TakemiOtsuki,

NeetuSingh, FahaAl-Mulla, RabeahAl-Temaimi, AmedeoAmedei, AnnaMariaColacci, MonicaVaccari,

ChiaraMondello, A.IvanaScovassi, JayadevRaju, RoslidaA.Hamid, LorenzoMemeo, StefanoForte,

RabindraRoy, JordanWoodrick, HosniK.Salem, ElizabethP.Ryan, DustinG.Brown, WilliamH.Bisson,

LeroyLowe, and H.KimLyerly ................................................................S111

The impact of low-dose carcinogens and environmental disruptors on tissue invasion and metastasis

JosiahOchieng, GladysN.Nangami, OlugbemigaOgunkua, IsabelleR.Miousse, IgorKoturbash, ValerieOdero-

Marah, LisaMcCawley, PratimaNangia-Makker, NuzhatAhmed, YunusLuqmani, ZhenbangChen,

SilvanaPapagerakis, GregoryT.Wolf, ChenfangDong, BinhuaP.Zhou, DustinG.Brown, AnnamariaColacci,

RoslidaA.Hamid, ChiaraMondello, JayadevRaju, ElizabethP.Ryan, JordanWoodrick, IvanaScovassi,

NeetuSingh, MonicaVaccari, RabindraRoy, StefanoForte, LorenzoMemeo, HosniK.Salem, AmedeoAmedei,

RabeahAl-Temaimi, FahdAl-Mulla, WilliamH.Bisson, and SakinaE.Eltom............................S128

The effect of environmental chemicals on the tumor microenvironment

StephanieC.Casey, MonicaVaccari, FahdAl-Mulla, RabeahAl-Temaimi, AmedeoAmedei, MaryHelen

Barcellos-Hoff, DustinG.Brown, MarionChapellier, JosephChristopher, ColleenCurran, StefanoForte,

RoslidaA.Hamid, PetrHeneberg, DanielC.Koch, P.K.Krishnakumar, EzioLaconi, VeroniqueMaguer-Satta,

FabioMarongiu, LorenzoMemeo, ChiaraMondello, JayadevRaju, JesseRoman, RabindraRoy, ElizabethP.Ryan,

SandraRyeom, HosniK.Salem, A.IvanaScovassi, NeetuSingh, LauraSoucek, LouisVermeulen, JonathanR.

Whiteld, JordanWoodrick, AnnamariaColacci, WilliamH.Bisson, and DeanW.Felsher...................S160

Assessing the carcinogenic potential of low-dose exposures to chemical mixtures in the

environment: focus on the cancer hallmark of tumor angiogenesis

ZhiweiHu, SamiraA.Brooks, ValérianDormoy, Chia-WenHsu, Hsue-YinHsu, Liang-TzungLin,

ThierryMassfelder, W.KimrynRathmell, MenghangXia, FahdAl-Mulla, RabeahAl-Temaimi,

AmedeoAmedei, DustinG.Brown, KalanR.Prudhomme, AnnamariaColacci, RoslidaA.Hamid,

ChiaraMondello, JayadevRaju, ElizabethP.Ryan, JordanWoodrick, A.IvanaScovassi, NeetuSingh,

MonicaVaccari, RabindraRoy, StefanoForte, LorenzoMemeo, HosniK.Salem, LeroyLowe, LasseJensen,

WilliamH.Bisson, and NicoleKleinstreuer.......................................................S184

Metabolic reprogramming and dysregulated metabolism: cause, consequence and/or enabler of

environmental carcinogenesis?

R.BrooksRobey, JudithWeisz, NancyKuemmerle, AnnaC.Salzberg, ArthurBerg, DustinBrown, LauraKubik,

RobertaPalorini, FahdAl-Mulla, RabeahAl-Temaimi, AnnamariaColacci, ChiaraMondello, JayadevRaju,

JordanWoodrick, IvanaScovassi, NeetuSingh, MonicaVaccari, RabindraRoy, StefanoForte, LorenzoMemeo,

HosniK.Salem, AmedeoAmedei, RoslidaA.Hamid, GraemeP.Williams, LeroyLowe, JoelMeyer,

FrancisL.Martin, WilliamH.Bisson, FerdinandoChiaradonna, and ElizabethP.Ryan ....................S203

Environmental immune disruptors, inammation and cancerrisk

PatriciaA.Thompson, MahinKhatami, CarolynJ.Baglole, JunSun, ShelleyHarris, Eun-YiMoon, FahdAl-Mulla,

RabeahAl-Temaimi, DustinBrown, AnnamariaColacci, ChiaraMondello, JayadevRaju, ElizabethRyan,

JordanWoodrick, IvanaScovassi, NeetuSingh, MonicaVaccari, RabindraRoy, StefanoForte, LorenzoMemeo,

HosniK.Salem, AmedeoAmedei, RoslidaA.Hamid, LeroyLowe, and WilliamH.Bisson ....................S232

Assessing the carcinogenic potential of low-dose exposures to chemical mixtures in the environment:

the challengeahead

WilliamH.GoodsonIII, LeroyLowe, DavidO.Carpenter, MichaelGilbertson, AbdulManafAli,

AdelaLopezdeCerainSalsamendi, AhmedLasfar, AmancioCarnero, AmayaAzqueta, AmedeoAmedei, AmeliaK.

Charles, AndrewR.Collins, AndrewWard, AnnaC.Salzberg, AnnamariaColacci, Ann-KarinOlsen, ArthurBerg,

BarryJ.Barclay, BinhuaP.Zhou, CarmenBlanco-Aparicio, CarolynBaglole, ChenfangDong, ChiaraMondello,

Chia-WenHsu, ChristianC.Naus, ClementYedjou, ColleenS.Curran, DaleW.Laird, DanielC.Koch, DanielleJ.

Carlin, DeanW.Felsher, DebasishRoy, DustinBrown, EdwardRatovitski, ElizabethP.Ryan, EmanuelaCorsini,

EmilioRojas, Eun-YiMoon, EzioLaconi, FabioMarongiu, FahdAl-Mulla, FerdinandoChiaradonna, FirouzDarroudi,

FrancisL.Martin, FrederikJ.VanSchooten, GaryS.Goldberg, GerardWagemaker, GladysNangami, GloriaM.

Calaf, GraemeWilliams, GregoryT.Wolf, GudrunKoppen, GunnarBrunborg, H.KimLyerly, HariniKrishnan,

HasiahAbHamid, HemadYasaei, HidekoSone, HiroshiKondoh, HosniK.Salem, Hsue-YinHsu, HyunHoPark,

IgorKoturbash, IsabelleR.Miousse, IvanaScovassi, JamesEKlaunig, JanVondráček, JayadevRaju, JesseRoman,

JohnPierceWiseSr., JonathanR.Whiteld, JordanWoodrick, JosephChristopher, JosiahOchieng,

JuanFernandoMartinez-Leal, JudithWeisz, JuliaKravchenko, JunSun, KalanR.Prudhomme,

KannanBadriNarayanan, KarineA.Cohen-Solal, KimMoorwood, LaetitiaGonzalez, LauraSoucek,

LeJian, LeandroS.D’Abronzo, Liang-TzungLin, LinLi, LindaGulliver, LisaJ.McCawley,

LorenzoMemeo, LouisVermeulen, LucLeyns, LuopingZhang, MaharaValverde, MahinKhatami,

MariaFiammettaRomano, MarionChapellier, MarcA.Williams, MarkWade, MasoudH.Manjili,

MatildeLleonart, MenghangXia, MichaelJGonzalez, MichalisV.Karamouzis, MichelineKirsch-

Volders, MonicaVaccari, NancyB.Kuemmerle, NeetuSingh, NicholaCruickshanks, NicoleKleinstreuer,

NikvanLarebeke, NuzhatAhmed, OlugbemigaOgunkua, P.K.Krishnakumar, PankajVadgama,

PaolaA.Marignani, ParamitaM.Ghosh, PatriciaOstrosky-Wegman, PatriciaThompson, PaulDent,

PetrHeneberg, PhilippaDarbre, PoSingLeung, PratimaNangia-Makker, Qiang(Shawn)Cheng,

R.BrooksRobey, RabeahAl-Temaimi, RabindraRoy, RafaelaAndrade-Vieira, RanjeetK.Sinha,

RekhaMehta, RenzaVento, RiccardoDiFiore, RichardPonce-Cusi, RitaDornetshuber-Fleiss,

RitaNahta, RobertC.Castellino, RobertaPalorini, RoslidaAbdHamid, SabineA.S.Langie,

SakinaEltom, SamiraA.Brooks, SandraRyeom, SandraS.Wise, SarahN.Bay, ShelleyHarris,

SilvanaPapagerakis, SimonaRomano, SoaPavanello, StaffanEriksson, StefanoForte,

StephanieC.Casey, SudjitLuanpitpong, Tae-JinLee, TakemiOtsuki, TaoChen, ThierryMassfelder,

ThomasSanderson, TizianaGuarnieri, ToveHultman, ValérianDormoy, ValerieOdero-Marah,

VenkataSabbisetti, VeroniqueMaguer-Satta, W.KimrynRathmell, WilhelmEngström, WilliamK.

Decker, WilliamH.Bisson, YonRojanasakul, YunusLuqmani, ZhenbangChen, and ZhiweiHu ..............S254

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respective authors and contributors and not of Carcinogenesis or Oxford

University Press. Neither Oxford University Press nor Carcinogenesis make any

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errors or omissions that may be made. The reader should make his/her own

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Theo Colborn (March 28, 1927 - December 14, 2014)

We dedicate this special issue on the challenges associated with assessing the carcinogenic potential of low dose exposures to

chemical mixtures in the environment, to the memory of Dr Theodora (Theo) Colborn. Theo was a pioneer in the science of the

effects of low dose exposures to environmental chemicals and for the past twenty-ve years, was instrumental in the develop-

ment and integration of the eld of endocrine disruption. Theo introduced us to one another about four-years-ago which led to the

founding of Getting to Know Cancer, and ultimately the launch of the Halifax Project (which has been a tremendously productive

collaboration for the integration of cancer biology and environmental toxicology). So we want to thank her for her legacy of work in

this area, her inuence on our research, and her encouragement.

Theo was well known internationally for her tireless commitment to the protection of public health, but not everyone knew that

she was also a tremendously generous and insightful scientist who assembled researchers from a variety of specialties and allowed

them to discover for themselves what she had understood about the inuences of low-dose exposures to certain environmental

chemicals on embryonic and fetal development. Indeed, she nurtured cross-disciplinary collaboration and it was that collegiality

and spirit of sharing that produced seminal insights that opened up the entire eld of endocrine disruption. So we have attempted

to use a similar approach to help us understand the importance of ongoing low dose exposures to mixtures of chemicals in the

environment and their relevance for cancer and carcinogenesis. In other words, this is truly an extension of her work, and we want

to pay tribute and offer thanks for her wisdom, her generosity and her legacy.

Leroy Lowe and Michael Gilbertson,

Cofounders, Getting To Know Cancer

June, 2015

Carcinogenesis, 2015, Vol. 36, Supplement 1, S1

doi: 10.1093/carcin/bgv047

Editorial

Copyedited by: <CE_Initials>

Editorial

Cause and Prevention of Human Cancer

The relative contribution of the environment, genetic suscepti-

bility and DNA replication errors to cancer causation has been

a longstanding area of investigation in the elds of molecular

epidemiology of cancer and carcinogenesis. A recent report by

Tomasetti etal. (1) attributing DNA replication errors within stem

cells and ‘bad luck’ as a major cause of a select group of cancers

has stirred debate within community of cancer researchers espe-

cially those in cancer prevention (2–7). Tomasetti et al. (8) have

also written a balanced response to many of these concerns.

Carcinogenesis is joining this debate by publishing in this

issue a series of reviews on the carcinogenic potential of expo-

sure to low doses and mixtures of chemicals. The reviews utilize

a framework of the Hallmarks of Cancer (9) and are the prod-

uct of the Halifax Project Task Force initiated by Leroy Lowe

and Michael Gilbertson. They engaged international teams with

input of nearly 200 cancer biologists and toxicologist to review

the literature in each of the 11 Hallmarks of Cancer. The reviews

are multiauthored, condensed by a peer review and extensively

referenced. The primary recommendation is a research and

regulatory strategy using the Hallmarks of Cancer framework to

identify priority mixtures of chemicals, i.e. ‘….those with sub-

stantial carcinogenic relevance’, for future investigations ‘…. to

inform risk assessment practices worldwide’ (10).

Carcinogenesis will also publish a review of cancer prevention

this summer, which will be written by Christopher Wild, Director

of the International Agency on Research of Cancer.

References

1. Tomasetti, C. etal. (2015) Cancer etiology. Variation in cancer

risk among tissues can be explained by the number of stem

cell divisions. Science, 347, 78–81.

2. Crossan, G.P. etal. (2015) Do mutational dynamics in stem cells

explain the origin of common cancers? Cell Stem Cell, 16, 111–112.

3. O’Callaghan, M. (2015) Cancer risk: accuracy of literature. Sci-

ence, 347, 729.

4. Ashford, N.A. et al. (2015) Cancer risk: role of environment.

Science, 347, 727.

5. Song, M. etal. (2015) Cancer risk: many factors contribute. Sci-

ence, 347, 728–729.

6. Potter, J.D. etal. (2015) Cancer risk: tumors excluded. Science,

347, 727.

7. Wild, C. etal. (2015) Cancer risk: role of chance overstated. Sci-

ence, 347, 728.

8. Tomasetti, C. etal. (2015) Cancer risk: role of environment—

response. Science, 347, 729–731.

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57–70.

10. Goodson, W.H. III, etal. (2015) Assessing the carcinogenesis

potential of low dose exposures to chemical mixtures in the

environment: the challenge ahead. Carcinogenesis.

Curtis CHarris,

Editor-in-Chief

Received: August 7, 2014; Revised: January 23, 2015; Accepted: January 31, 2015

Carcinogenesis, 2015, Vol. 36, Supplement 1, S254–S296

doi:10.1093/carcin/bgv039

Review

S254

This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License

(http://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any

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

Assessing the carcinogenic potential of low-dose

exposures to chemical mixtures in the environment: the

challengeahead

William H.Goodson III*, LeroyLowe1,2, David O.Carpenter3,

MichaelGilbertson4, AbdulManaf Ali5,

AdelaLopez de Cerain Salsamendi6, AhmedLasfar7,

AmancioCarnero8, AmayaAzqueta6, AmedeoAmedei9,

Amelia K.Charles10, Andrew R.Collins11, AndrewWard12,

Anna C.Salzberg13, AnnamariaColacci14, Ann-KarinOlsen15,

ArthurBerg13, Barry J.Barclay16, Binhua P.Zhou17,

CarmenBlanco-Aparicio18, Carolyn J.Baglole19, ChenfangDong17,

ChiaraMondello20, Chia-WenHsu21, Christian C.Naus22,

ClementYedjou23, Colleen S.Curran24, Dale W.Laird25, Daniel C.Koch26,

Danielle J.Carlin27, Dean W.Felsher28, DebasishRoy29,

Dustin G.Brown30, EdwardRatovitski31, Elizabeth P.Ryan30,

EmanuelaCorsini32, EmilioRojas33, Eun-YiMoon34, EzioLaconi35,

FabioMarongiu35, FahdAl-Mulla36,

FerdinandoChiaradonna37,38, FirouzDarroudi39, Francis L.Martin2,

Frederik J.Van Schooten40, Gary S.Goldberg41,

GerardWagemaker42, GladysNangami43, Gloria M.Calaf44,45,

GraemeWilliams46, Gregory T.Wolf47, GudrunKoppen48,

GunnarBrunborg15, H.Kim Lyerly49, HariniKrishnan41,

HasiahAb Hamid50, HemadYasaei51, HidekoSone52,

HiroshiKondoh53, Hosni K.Salem54, Hsue-YinHsu55,

Hyun HoPark56, IgorKoturbash57, Isabelle R.Miousse57, A.IvanaScovassi20,

James E.Klaunig58, JanVondráček59, JayadevRaju60, JesseRoman61,62,

John PierceWise Sr.63, Jonathan R.Whiteld64,

JordanWoodrick65, Joseph A.Christopher66, JosiahOchieng43,

Juan FernandoMartinez-Leal67, JudithWeisz68, JuliaKravchenko49,

JunSun69, Kalan R.Prudhomme70, Kannan BadriNarayanan56,

Karine A.Cohen-Solal71, KimMoorwood12, LaetitiaGonzalez72,

LauraSoucek64,73, LeJian74,75, Leandro S.D’Abronzo76, Liang-TzungLin77,

W.H.Goodson et al. | S255

Carcinogenesis, 2015, Vol. 36, Supplement 1, S254–S296

doi:10.1093/carcin/bgv039

Review

LinLi78, LindaGulliver79, Lisa J.McCawley80, LorenzoMemeo81,

LouisVermeulen82, LucLeyns72, LuopingZhang83,

MaharaValverde33, MahinKhatami84,

Maria FiammettaRomano85, MarionChapellier86, Marc A.Williams87,

MarkWade88, Masoud H.Manjili89, MatildeLleonart90, MenghangXia21,

Michael J.Gonzalez91, Michalis V.Karamouzis92,

MichelineKirsch-Volders72, MonicaVaccari14, Nancy B.Kuemmerle93,94,

NeetuSingh95, NicholaCruickshanks96, NicoleKleinstreuer97,

Nikvan Larebeke98, NuzhatAhmed99, OlugbemigaOgunkua43,

P.K.Krishnakumar100, PankajVadgama101, Paola A.Marignani102,

Paramita M.Ghosh76, PatriciaOstrosky-Wegman33, PatriciaThompson103,

PaulDent96, PetrHeneberg104, PhilippaDarbre105, PoSing Leung78,

PratimaNangia-Makker106, Qiang (Shawn)Cheng107, R.BrooksRobey93,94,

RabeahAl-Temaimi108, RabindraRoy65, RafaelaAndrade-Vieira102,

Ranjeet K.Sinha109, RekhaMehta60, RenzaVento110,111, RiccardoDi Fiore110,

RichardPonce-Cusi45, RitaDornetshuber-Fleiss112,113, RitaNahta114,

Robert C.Castellino115,116, RobertaPalorini37,38, RoslidaAbd Hamid50,

Sabine A.S.Langie48, SakinaEltom43, Samira A.Brooks117, SandraRyeom118,

Sandra S.Wise63, Sarah N.Bay119, Shelley A.Harris120,121,

SilvanaPapagerakis47, SimonaRomano85, SoaPavanello122,

StaffanEriksson123, StefanoForte81, Stephanie C.Casey26,

SudjitLuanpitpong124, Tae-JinLee125, TakemiOtsuki126, TaoChen127,

ThierryMassfelder128, ThomasSanderson129, TizianaGuarnieri130,131,132,

Tove  Hultman133, ValérianDormoy128,134, ValerieOdero-Marah135,

VenkataSabbisetti136, VeroniqueMaguer-Satta87,

W.KimrynRathmell117, WilhelmEngström137, William K.Decker138,

William H.Bisson70, YonRojanasakul139, YunusLuqmani140,

ZhenbangChen43 and ZhiweiHu141

California Pacic Medical Center Research Institute, 2100 Webster Street #401, San Francisco, CA 94115, USA, 1Getting to

Know Cancer, Room 229A, 36 Arthur Street, Truro, Nova Scotia B2N 1X5, Canada, 2Lancaster Environment Centre, Lancaster

University, Bailrigg, Lancaster LA1 4AP, UK, 3Institute for Health and the Environment, University at Albany, 5 University

Pl., Rensselaer, NY 12144, USA, 4Getting to Know Cancer, Guelph N1G 1E4, Canada, 5School of Biotechnology, Faculty of

Agriculture Biotechnology and Food Sciences, Sultan Zainal Abidin University, Tembila Campus, 22200 Besut, Terengganu,

Malaysia, 6Department of Pharmacology and Toxicology, Faculty of Pharmacy, University of Navarra, Pamplona 31008,

Spain, 7Department of Pharmacology and Toxicology, Ernest Mario School of Pharmacy, Rutgers, State University of New

Jersey, Piscataway, NJ 08854, USA, 8Instituto de Biomedicina de Sevilla, Consejo Superior de Investigaciones Cienticas.

Hospital Universitario Virgen del Rocio, Univ. de Sevilla., Avda Manuel Siurot sn. 41013 Sevilla, Spain, 9Department of

Experimental and Clinical Medicine, University of Firenze, Florence 50134, Italy, 10School of Biological Sciences, University

of Reading, Hopkins Building, Reading, Berkshire RG6 6UB, UK, 11Department of Nutrition, University of Oslo, Oslo, Norway,

12Department of Biochemistry and Biology, University of Bath, Claverton Down, Bath BA2 7AY, UK, 13Department of Public

Health Sciences, College of Medicine, Pennsylvania State University, Hershey, PA 17033, USA, 14Center for Environmental

Carcinogenesis and Risk Assessment, Environmental Protection and Health Prevention Agency, 40126 Bologna, Italy,

15Department of Chemicals and Radiation, Division of Environmental Medicine, Norwegian Institute of Public Health, Oslo

N-0403, Norway, 16Planet Biotechnologies Inc., St Albert, Alberta T8N 5K4, Canada, 17Department of Molecular and Cellular

Biochemistry, University of Kentucky, Lexington, KY 40508, USA, 18Spanish National Cancer Research Centre, CNIO, Melchor

Fernandez Almagro, 3, 28029 Madrid, Spain, 19Department of Medicine, McGill University, Montreal, Quebec H4A 3J1,

Canada, 20Istituto di Genetica Molecolare, CNR, Via Abbiategrasso 207, 27100 Pavia, Italy, 21Division of Preclinical Innovation,

National Center for Advancing Translational Sciences, National Institutes of Health, 9800 Medical Center Drive, Bethesda,

MD 20892–3375, USA, 22Department of Cellular and Physiological Sciences, Life Sciences Institute, Faculty of Medicine,

The University of British Columbia, Vancouver, British Columbia V5Z 1M9, Canada, 23Department of Biology, Jackson State

University, Jackson, MS 39217, USA, 24Department of Molecular and Environmental Toxicology, University of Wisconsin-

Madison, Madison, WI 53706, USA, 25Department of Anatomy and Cell Biology, University of Western Ontario, London,

S256 | Carcinogenesis, 2015, Vol. 36, Supplement 1

Ontario N6A 3K7, Canada, 26Stanford University Department of Medicine, Division of Oncology, Stanford, CA 94305, USA,

27Superfund Research Program, National Institute of Environmental Health Sciences, Research Triangle Park, NC 27560,

USA, 28Department of Medicine, Oncology and Pathology, Stanford University, Stanford, CA 94305, USA, 29Department of

Natural Science, The City University of New York at Hostos Campus, Bronx, NY 10451, USA, 30Department of Environmental

and Radiological Health Sciences, Colorado State University, Fort Collins, CO 80523–1680, USA, 31Department of Head and

Neck Surgery/Head and Neck Cancer Research, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA,

32Department of Pharmacological and Biomolecular Sciences, Università degli Studi di Milano, 20133 Milan, Italy,

33Department of Genomic Medicine and Environmental Toxicology, Institute for Biomedical Research, National Autonomous

University of Mexico, Mexico City 04510, México, 34Department of Bioscience and Biotechnology, Sejong University, Seoul

143–747, Korea, 35Department of Biomedical Sciences, University of Cagliari, 09124 Cagliari, Italy, 36Department of Pathology,

Kuwait University, Safat 13110, Kuwait, 37Department of Biotechnology and Biosciences, University of Milano-Bicocca, 20126

Milan, Italy, 38SYSBIO Centre of Systems Biology, Department of Biotechnology and Biosciences, University of Milano-Bicocca,

20126 Milan, Italy, 39Human Safety and Environmental Research, Department of Health Sciences, College of North Atlantic,

Doha 24449, State of Qatar, 40Department of Toxicology, NUTRIM School for Nutrition, Toxicology and Metabolism, Maastricht

University, Maastricht 6200, The Netherlands, 41Department of Molecular Biology, School of Osteopathic Medicine, Rowan

University, Stratford, NJ 08084, USA, 42Hacettepe University, Center for Stem Cell Research and Development, Ankara 06640,

Turkey, 43Department of Biochemistry and Cancer Biology, Meharry Medical College, Nashville, TN 37208, USA, 44Center for

Radiological Research, Columbia University Medical Center, New York, NY 10032, USA, 45Instituto de Alta Investigacion,

Universidad de Tarapaca, Arica, Chile, 46School of Biological Sciences, University of Reading, Reading, RG6 6UB, UK,

47Department of Otolaryngology - Head and Neck Surgery, University of Michigan Medical School, Ann Arbor, MI 48109, USA,

48Environmental Risk and Health Unit, Flemish Institute for Technological Research, 2400 Mol, Belgium, 49Department of

Surgery, Pathology, Immunology, Duke University Medical Center, Durham, NC 27710, USA, 50Department of Biomedical

Sciences, Faculty of Medicine and Health Sciences, 43400 Universiti Putra Malaysia, Serdang, Selangor, Malaysia,

51Department of Life Sciences, College of Health and Life Sciences and the Health and Environment Theme, Institute of

Environment, Health and Societies, Brunel University Kingston Lane, Uxbridge, Middlesex UB8 3PH, UK, 52National Institute

for Environmental Studies, 16-2 Onogawa, Tsukuba, Ibraki 3058506, Japan, 53Department of Geriatric Medicine, Kyoto

University Hospital 54 Kawaharacho, Shogoin, Sakyo-ku Kyoto, 606–8507, Japan, 54Department of Urology, Kasr Al-Ainy School

of Medicine, Cairo University, El Manial, Cairo 11559, Egypt, 55Department of Life Sciences, Tzu-Chi University, Hualien 970,

Taiwan, 56School of Biotechnology, Yeungnam University, Gyeongbuk 712-749, South Korea, 57Department of Environmental

and Occupational Health, University of Arkansas for Medical Sciences, Little Rock, AR 72205, USA, 58Department of

Environmental Health, Indiana University, School of Public Health, Bloomington, IN 47405, USA, 59Department of Cytokinetics,

Institute of Biophysics Academy of Sciences of the Czech Republic, Brno, CZ-61265, Czech Republic, 60Regulatory Toxicology

Research Division, Bureau of Chemical Safety, Food Directorate, Health Canada, Ottawa, Ontario K1A 0K9, Canada,

61Department of Medicine, University of Louisville, Louisville, KY 40202, USA, 62Robley Rex VA Medical Center, Louisville, KY

40202, USA, 63Department of Applied Medical Sciences, University of Southern Maine, 96 Falmouth St., Portland, ME 04104,

USA, 64Mouse Models of Cancer Therapies Group, Vall d’Hebron Institute of Oncology (VHIO), 08035 Barcelona, Spain,

65Lombardi Comprehensive Cancer Center, Georgetown University Medical Center, Washington DC 20057, USA, 66Cancer

Research UK. Cambridge Institute, University of Cambridge, Robinson Way, Cambridge CB2 0RE, UK, 67Department of Cell

Biology, Pharmamar-SAU, Avda. De los Reyes, 1.28770-Colmenar Viejo, Madrid, Spain, 68Departments of Obstetrics and

Gynecology and Pathology, Pennsylvania State University College of Medicine, Hershey PA 17033, USA, 69Department of

Biochemistry, Rush University, Chicago, IL 60612, USA, 70Environmental and Molecular Toxicology, Environmental Health

Science Center, Oregon State University, Corvallis, OR 97331, USA, 71Department of Medicine/Medical Oncology, Rutgers

Cancer Institute of New Jersey, New Brunswick, NJ 08903, USA, 72Laboratory for Cell Genetics, Vrije Universiteit Brussel, 1050

Brussels, Belgium, 73Catalan Institution for Research and Advanced Studies (ICREA), Barcelona 08010, Spain, 74School of Public

Health, Curtin University, Bentley, WA 6102, Australia, 75Public Health and Clinical Services Division, Department of Health,

Government of Western Australia, WA 6004, Australia, 76Department of Urology, University of California Davis, Sacramento,

CA 95817, USA, 77Department of Microbiology and Immunology, School of Medicine, College of Medicine, Taipei Medical

University, Taipei 11031, Taiwan, 78School of Biomedical Sciences, The Chinese University of Hong Kong, Shatin, NT, Hong

Kong SAR, The People’s Republic of China, 79Faculty of Medicine, University of Otago, Dunedin 9054, New Zealand,

80Department of Biomedical Engineering and Cancer Biology, Vanderbilt University, Nashville, TN 37235, USA, 81Department of

Experimental Oncology, Mediterranean Institute of Oncology, Via Penninazzo 7, Viagrande (CT) 95029, Italy, 82Center for

Experimental Molecular Medicine, Academic Medical Center, Meibergdreef 9, Amsterdam 1105 AZ, The Netherlands,

83Division of Environmental Health Sciences, School of Public Health, University of California, Berkeley, CA 94720-7360, USA,

84Inammation and Cancer Research, National Cancer Institute (NCI) (Retired), National Institutes of Health, Bethesda, MD

20892, USA, 85Department of Molecular Medicine and Medical Biotechnology, Federico II University of Naples, 80131 Naples,

Italy, 86Centre De Recherche En Cancerologie, De Lyon, Lyon, U1052-UMR5286, France, 87United States Army Institute of Public

Health, Toxicology Portfolio-Health Effects Research Program, Aberdeen Proving Ground, Edgewood, MD 21010-5403, USA,

88Center for Genomic Science of IIT@SEMM, Fondazione Istituto Italiano di Tecnologia, Via Adamello 16, 20139 Milano, Italy,

89Department of Microbiology and Immunology, Virginia Commonwealth University, Massey Cancer Center, Richmond, VA

23298, USA, 90Institut De Recerca Hospital Vall D’Hebron, Passeig Vall d’Hebron, 119–129, 08035 Barcelona, Spain, 91University

of Puerto Rico, Medical Sciences Campus, School of Public Health, Nutrition Program, San Juan 00921, Puerto Rico,

92Department of Biological Chemistry, Medical School, University of Athens, Institute of Molecular Medicine and Biomedical

Research, 10676 Athens, Greece, 93White River Junction Veterans Affairs Medical Center, White River Junction, VT 05009, USA,

W.H.Goodson et al. | S257

94Geisel School of Medicine at Dartmouth, Hanover, NH 03755, USA, 95Advanced Molecular Science Research Centre (Centre

for Advanced Research), King George’s Medical University, Lucknow, Uttar Pradesh 226 003, India, 96Departments of

Neurosurgery and Biochemistry and Massey Cancer Center, Virginia Commonwealth University, Richmond, VA 23298, USA,

97Integrated Laboratory Systems Inc., in support of the National Toxicology Program Interagency Center for the Evaluation of

Alternative Toxicological Methods, RTP, NC 27709, USA, 98Analytische, Milieu en Geochemie, Vrije Universiteit Brussel, Brussel

B1050, Belgium, 99Department of Obstetrics and Gynecology, University of Melbourne, Victoria 3052, Australia, 100Center for

Environment and Water, Research Institute, King Fahd University of Petroleum and Minerals, Dhahran 3126, Saudi Arabia,

101School of Engineering and Materials Science, Queen Mary University of London, Mile End Road, London, E1 4NS, UK,

102Department of Biochemistry and Molecular Biology, Dalhousie University, Halifax, Nova Scotia B3H 4R2, Canada,

103Department of Pathology, Stony Brook School of Medicine, Stony Brook University, The State University of New York, Stony

Brook, NY 11794-8691, USA, 104Charles University in Prague, Third Faculty of Medicine, CZ-100 00 Prague 10, Czech Republic,

105School of Biological Sciences, The University of Reading, Whiteknights, Reading RG6 6UB, England, 106Department of

Pathology, Wayne State University, Detroit, MI 48201, USA, 107Computer Science Department, Southern Illinois University,

Carbondale, IL 62901, USA, 108Human Genetics Unit, Department of Pathology, Faculty of Medicine, Kuwait University, Jabriya

13110, Kuwait, 109Department of Molecular and Experimental Medicine, The Scripps Research Institute, La Jolla, CA 92037,

USA, 110Department of Biological, Chemical, and Pharmaceutical Sciences and Technologies, Polyclinic Plexus, University of

Palermo, Palermo 90127, Italy, 111Sbarro Institute for Cancer Research and Molecular Medicine, Temple University,

Philadelphia, PA 19122, USA, 112Department of Pharmacology and Toxicology, University of Vienna, Vienna A-1090, Austria,

113Institute of Cancer Research, Department of Medicine, Medical University of Vienna, Wien 1090, Austria, 114Departments of

Pharmacology and Hematology and Medical Oncology, Emory University School of Medicine and Winship Cancer Institute,

Atlanta, GA 30322, USA, 115Division of Hematology and Oncology, Department of Pediatrics, Children’s Healthcare of Atlanta,

GA 30322, USA, 116Department of Pediatrics, Emory University School of Medicine, Emory University, Atlanta, GA 30322, USA,

117Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, NC 27599, USA, 118Department of

Cancer Biology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA 19104, USA, 119Program in

Genetics and Molecular Biology, Graduate Division of Biological and Biomedical Sciences, Emory University, Atlanta, GA

30322, USA, 120Population Health and Prevention, Research, Prevention and Cancer Control, Cancer Care Ontario, Toronto,

Ontario, M5G 2L7, Canada, 121Departments of Epidemiology and Occupational and Environmental Health, Dalla Lana School

of Public Health, University of Toronto, Toronto, Ontario, M5T 3M7, Canada, 122Department of Cardiac, Thoracic and Vascular

Sciences, Unit of Occupational Medicine, University of Padova, Padova 35128, Italy, 123Department of Anatomy, Physiology and

Biochemistry, The Swedish University of Agricultural Sciences, PO Box 7011, VHC, Almas Allé 4, SE-756 51, Uppsala, Sweden,

124Siriraj Center of Excellence for Stem Cell Research, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok 10700,

Thailand, 125Department of Anatomy, College of Medicine, Yeungnam University, Daegu 705–717, South Korea,126Department

of Hygiene, Kawasaki Medical School, Matsushima Kurashiki, Okayama 701-0192, Japan, 127Division of Genetic and Molecular

Toxicology, National Center for Toxicological Research, United States Food and Drug Administration, Jefferson, AR 72079, USA,

128INSERM U1113, team 3‘Cell Signalling and Communication in Kidney and Prostate Cancer’, University of Strasbourg,

Faculté de Médecine, 67085 Strasbourg, France, 129INRS-Institut Armand-Frappier, 531 Boulevard des Prairies, Laval, QC H7V

1B7, Canada, 130Department of Biology, Geology and Environmental Sciences, Alma Mater Studiorum Università di Bologna,

Via Francesco Selmi, 3, 40126 Bologna, Italy, 131Center for Applied Biomedical Research, S.Orsola-Malpighi University Hospital,

Via Massarenti, 9, 40126 Bologna, Italy, 132National Institute of Biostructures and Biosystems, Viale Medaglie d’ Oro, 305, 00136

Roma, Italy, 133Department of Biosciences and Veterinary Public Health, Faculty of Veterinary Medicine, Swedish University of

Agricultural Sciences, PO Box 7028, 75007 Uppsala, Sweden, 134Department of Cell and Developmental Biology, University of

California, Irvine, CA 92697, USA, 135Department of Biology/Center for Cancer Research and Therapeutic Development, Clark

Atlanta University, Atlanta, GA 30314, USA, 136Harvard Medical School/Brigham and Women’s Hospital, Boston, MA 02115,

USA, 137Department of Biosciences and Veterinary Public Health, Faculty of Veterinary Medicine, Swedish University of

Agricultural Sciences, PO Box 7028, 75007 Uppsala, Sweden, 138Baylor College of Medicine, Houston, TX 77030, USA,

139Department of Pharmaceutical Sciences, West Virginia University, Morgantown, WV, 26506, USA 140Department of

Pharmaceutical Chemistry, Faculty of Pharmacy, Kuwait University, PO Box 24923, Safat 13110, Kuwait and 141Department of

Surgery, The Ohio State University College of Medicine, The James Comprehensive Cancer Center, Columbus, OH 43210, USA

*To whom correspondence should be addressed. William H.Goodson III, California Pacic Medical Center Research Institute, 2100 Webster Street #401,

San Francisco, CA 94115, USA. Tel:+41 59 233925; Fax: +41 57 761977; Email: whg3md@att.net

Correspondence may also be addressed to Leroy Lowe. Tel:+90 28 935362; Fax: +90 28 935610; Email: leroy.lowe@gettingtoknowcancer.org

Part of the special issue on ‘Assessing the Carcinogenic Potential of Low-Dose Exposures to Chemical Mixtures in the Environment: The Challenge Ahead’

Abstract

Lifestyle factors are responsible for a considerable portion of cancer incidence worldwide, but credible estimates from the

World Health Organization and the International Agency for Research on Cancer (IARC) suggest that the fraction of cancers

attributable to toxic environmental exposures is between 7% and 19%. To explore the hypothesis that low-dose exposures to

mixtures of chemicals in the environment may be combining to contribute to environmental carcinogenesis, we reviewed

11 hallmark phenotypes of cancer, multiple priority target sites for disruption in each area and prototypical chemical

S258 | Carcinogenesis, 2015, Vol. 36, Supplement 1

disruptors for all targets, this included dose-response characterizations, evidence of low-dose effects and cross-hallmark

effects for all targets and chemicals. In total, 85 examples of chemicals were reviewed for actions on key pathways/

mechanisms related to carcinogenesis. Only 15% (13/85) were found to have evidence of a dose-response threshold, whereas

59% (50/85) exerted low-dose effects. No dose-response information was found for the remaining 26% (22/85). Our analysis

suggests that the cumulative effects of individual (non-carcinogenic) chemicals acting on different pathways, and a variety

of related systems, organs, tissues and cells could plausibly conspire to produce carcinogenic synergies. Additional basic

research on carcinogenesis and research focused on low-dose effects of chemical mixtures needs to be rigorously pursued

before the merits of this hypothesis can be further advanced. However, the structure of the World Health Organization

International Programme on Chemical Safety ‘Mode of Action’ framework should be revisited as it has inherent weaknesses

that are not fully aligned with our current understanding of cancer biology.

Introduction

Cancer is a burden on humanity and among the leading causes

of morbidity and mortality worldwide, with ~14 million new

cases and 8.2 million cancer-related deaths in 2012 (1). In gen-

eral, both genetic and environmental factors play a role in an

individual’s cancer susceptibility (2,3), so there has been a long-

standing emphasis on avoidable ‘lifestyle’ factors (i.e. those

that can be modied to reduce the incidence of the disease) and

a parallel focus on exogenous chemical exposures (e.g. agricul-

tural, occupational and so on) (4). But advances in our under-

standing of the complexity of cancer biology have resulted in

serious critiques of current risk assessment practices related

to exogenous exposures (5) along with calls for an expanded

focus on research that will allow us to evaluate the (potentially

carcinogenic) effects of in-utero exposures and low-level expo-

sures to combinations of chemicals that occur throughout our

lifetime (6,7).

The 2008–09 President’s Cancer Panel Annual Report in the

USA (8) opined that the ‘true burden of environmentally induced

cancer has been grossly underestimated’ (7), whereas Parkin

etal. (9) estimated in a British study that the fraction of cancer

that can now be attributed to both lifestyle and environmen-

tal factors is only 43% (i.e. the underlying cause of 57% of all

cancers is still unexplained). However, an expanded focus on

research that will allow us to evaluate the (potentially carcino-

genic) contribution of low-level exposures to combinations of

chemicals that occur in utero and throughout our lifetime is not

a trivial undertaking.

First of all, the number of chemicals to which we are exposed

is substantial, and many have not been adequately tested.

Christiani (6) cited increased and persistently high incidence

rates of various cancers and called on the National Institutes of

Health to expand their investigation of environmental causes

of cancer noting that ‘Massive gaps exist in toxicologic data,

even in the case of widely used synthetic chemicals. Only about

50% of chemicals classied by the Environmental Protection

Agency (EPA) as “high production volume” have undergone

even minimal testing for carcinogenicity’. But even though the

incidence of cancer attributable to environmental exposures

has not been denitively established (3,6), it remains an impor-

tant focus of our prevention efforts [with credible estimates

from the World Health Organization [WHO] and the IARC sug-

gesting that the fraction of cancers attributable to toxic envi-

ronmental exposures is between 7% and 19%] (10,11).

The possibility that unanticipated low-dose effects (LDE) are

also a factor in environmental carcinogenesis further compli-

cates matters. Vandenberg etal. (12) recently reviewed the accu-

mulating evidence that points to LDE that occur at levels that are

well below those used for traditional toxicological studies. This

review identied several hundred examples of non-monotonic

dose-response relationships (i.e. examples where the relation-

ship between dose and effect is complex and the slope of the

curve changes sign—from positive to negative or vice versa—

somewhere within the range of doses examined). Drawing on

the known actions of natural hormones and selected environ-

mental chemicals examined in cell cultures, animals and epi-

demiology, the authors emphasized that when non-monotonic

dose-response curves occur, the effects of low doses cannot be

predicted by the effects observed at high doses. However, endo-

crine disruption research to this point has been aimed primarily

at chemicals that disrupt developmental processes through a rel-

atively small subset of hormones (e.g. estrogen, androgen, thyroid

and so on), and thus, many commonly encountered chemicals

have not been tested at all for these effects (at environmentally

relevant dose levels) and, to date, mechanisms that relate to car-

cinogenesis have typically not been the focus of these studies.

Generally for chemical risk assessments, toxicity stud-

ies are conducted with individual chemicals in animal mod-

els based on regulatory test guidelines [e.g. Organization for

Economic Co-operation and Development (OECD) test guide-

lines (13)] with a key objective of providing a dose-response

assessment that estimates a point of departure [traditionally

the no-observed-adverse-effect level or the lowest-observed-

adverse-effect level (LOAEL)], which is then used to extrapo-

late the quantity of substance above which adverse effects can

be expected in humans. The no-observed-adverse-effect level,

combined with uncertainty factors (which acknowledge gaps

in the available data), is then used to establish safety criteria

Abbreviations

AhR aryl hydrocarbon receptor

BPA bisphenol A

EMT epithelial-mesenchymal transition

EPA environmental protection agency

HTS high-throughput screening

IARC International Agency for Research on Cancer

IL interleukin

LDE low-dose effects

LOAEL lowest-observed-adverse-effect level

LOEL lowest observed effect level

miRNA microRNAs

4-NP nonylphenol

MXC methoxychlor

NF-κB nuclear factor-κB

PBDE polybrominated diphenyl ethers

PPAR peroxisome proliferator-activated receptor

ROS reactive oxygen species

W.H.Goodson et al. | S259

for human exposure. However, in order to be able to detect

adverse effects utilizing classical toxicological endpoints, dose

selection has historically involved the use of high dose levels

and appropriate dose level spacing to obtain the LOAEL or no-

observed-adverse-effect level thresholds. Techniques such as

linear extrapolation or benchmark dose modeling (14) are then

employed to predict safety margins for low-dose exposures.

This approach to risk assessment depends on the use of appro-

priate and sensitive endpoints, and on valid assumptions for

extrapolation estimates (e.g. dose-response linearity) and cal-

culations, and on the existence of thresholds of effects (15–17).

So when the potential for non-linear dose-response relation-

ships is combined with the possibility of synergism between

and amongst low doses of mixtures of individual chemicals in

the environment, it appears plausible that chemicals that are

not individually carcinogenic may be capable of producing car-

cinogenic synergies that would be missed using current risk

assessment practices.

The complex nature of the biology of cancer adds another

layer of complexity for risk assessment. In a landmark paper

in 1979, Ames (18) noted that damage to DNA appeared to

be a major cause of most cancers and suggested that natu-

ral chemicals in the human diet and the tens of thousands

of man-made chemicals that had been introduced into the

environment in the preceding decades be tested for their abil-

ity to damage DNA. In doing so, he sketched out the difculty

of dealing with complex chemical mixtures and he proposed

the use of rapid mutagenicity assays to identify environ-

mental mutagens and carcinogens. The strategy was sound

at the time, but it led to a scientic and regulatory emphasis

on ‘mutagens as carcinogens’, whereas the issue of complex

environmental mixtures, or carcinogens that are not muta-

gens, was never vigorously pursued. Instead, what followed

was an international quest to nd individual chemicals and

a few well-dened mixtures (e.g. diesel exhaust) that could be

shown to be ‘complete’ carcinogens (i.e. substances that could

cause cancer on theirown).

However, advances in cancer biology have revealed the

limitations of this approach. Armitage and Doll rst laid out

a multistage theory of carcinogenesis in 1954 (19), and by

1990, initiation and promotion were well established as dis-

crete steps in the evolution towards malignancy, along with

the inuence of ‘free radicals’, proto-oncogenes, oncogenes,

epigenetic mechanisms and other synergistic or antagonistic

factors (20). In 2000, Hanahan etal. (21) gave structure to this

rapidly growing eld of research with the proposal that ‘the

vast catalog of cancer cell genotypes [could be organized into]

a manifestation of six essential alterations in cell physiology

that collectively dictate malignant growth’. They called these

alterations the Hallmarks of Cancer, dened as ‘… acquired

capabilities’ common to most cancers that ‘… incipient cancer

cells … [must acquire to] enable them to become tumorigenic

and ultimately malignant.’ The hallmarks delineated at the

time were as follows:

• Self-sufciency in growth signals (later renamed proliferative

signaling)—cancer cells grow at a seemingly unlimited rate.

• Insensitivity to antigrowth signals (evading growth suppres-

sors)—cancer cells are not subject to antigrowth signals or

withdrawal of normal growth signals.

• Evading apoptosis (resisting cell death)—cancer cells avoid the

usual process whereby abnormal or redundant cells trigger

internal self-destroying (as opposed to cell death) mecha-

nisms.

• Limitless replicative potential (enabling replicative immortal-

ity)—cancer cells do not senesce (or age) and die after a lim-

ited number of cell divisions.

• Sustained angiogenesis (inducing angiogenesis)—cancer cells

elicit new blood vessels to sustain growth.

• Tissue invasion and metastasis (activating invasion and

metastasis)—in situ or non-invasive cancers, e.g. ductal carci-

noma in situ in the breast or carcinoma in situ in colon polyps,

grow into pre-existing spaces but invasive tumors must cre-

ate a space to expand into normal tissue.

From this perspective risk assessments based on limited ‘mode

of action’ information, assumptions of linear dose-response

relationships and a focus on individual chemicals (as complete

carcinogens) appeared to be inadequate to estimate human can-

cer risks. So in 2005, a scientist at the United States EPA called

for a shift in risk assessment practices that would move the eld

towards the development of biomarkers directly related to the

pathways found within the Hallmarks of Cancer framework (22).

The Hallmarks of Cancer framework was subsequently revis-

ited by Hanahan et al. (21) and expanded to encompass addi-

tional areas suggested by subsequent cancer research (23). This

expansion included the following:

• Two enabling characteristics:

• Genome instability and mutation, which allows changes in one

cell to pass to daughter cells through mutation or epigenetic

changes in the parent cell DNA.

• Tumor-promoting inammation, which helps cancer cells grow

via the same growth signals normal cells provide to each

other during wound healing and embryonic growth; inam-

mation further contributes to the survival of malignant cells,

angiogenesis, metastasis and the subversion of adaptive

immunity (24).

• Two ‘emerging’ hallmarks:

• Avoiding immune destruction whereby tumor cells avoid

immune surveillance that would otherwise mark them for

destruction.

• Dysregulated metabolism, one of the most recognizable fea-

tures of cancer; its exclusion from the original list of hall-

marks (21) probably represented a signicant oversight, as it

constitutes one of the earliest described hallmarks of cancer

(25,26). It is needed to support the increased anabolic and cat-

abolic demands of rapid proliferation and is likely an enabler

of cancer development and its other associated hallmarks.

Unfortunately, risk assessment practices that are currently used

to assess the carcinogenic potential of chemicals have changed

very little (despite the vast literature that now underpins the

main tenants of the Hallmarks of Cancer framework). For exam-

ple, a chemical that disrupts DNA repair capacity might prove

to be non-carcinogenic at any level of exposure (when tested on

its own), but that very same chemical may have the potential to

be an important contributor to carcinogenesis (e.g. in the pres-

ence of mutagens that cause DNA damage). Similarly, a chemical

that has immuno-suppressive qualities may not be carcinogenic

on its own, but if it acts to suppress the immune response, it

may contribute to carcinogenesis (by dismantling an important

layer of defense) in the presence of other disruptive chemicals.

Considering the multistep nature of cancer and the acquired

capabilities implied by each of these hallmarks, it is therefore

a very small step to envision how a series of complementary

exposures acting in concert might prove to be far more carci-

nogenic than predictions related to any single exposure might

suggest (see Figure 1). Interacting contributors need not act

S260 | Carcinogenesis, 2015, Vol. 36, Supplement 1

simultaneously or continuously, they might act sequentially or

discontinuously. So a sustained focus on the carcinogenicity of

individual chemicals may miss the sorts of synergies that might

reasonably be anticipated to occur when combinations of disrup-

tive chemicals (i.e. those that can act in concert on the key mech-

anisms/pathways related to these hallmarks) are encountered.

To address the biological complexity issue associated with

chronic diseases, the EPA and other agencies have begun to pursue

risk assessment models that incorporate biological information.

This is the basis of the Adverse Outcome Pathway concept, a con-

struct that is gaining momentum because it ties existing knowl-

edge of disease pathology (i.e. concerning the linkage between

a direct molecular initiating event and an adverse outcome at a

biological level of organization) to risk assessment (27,28). This

line of thinking inspired a recent initiative by the EPA, where

the agency tested a proposal for characterizing the carcinogenic

potential of chemicals in humans, using in-vitro high-through-

put screening (HTS) assays. The selected HTS assays speci-

cally matched key targets and pathways within the Hallmarks

of Cancer framework. The authors tested 292 chemicals in 672

assays and were successfully able to correlate the most disrup-

tive chemicals (i.e. those that were most active across the vari-

ous hallmarks) with known levels of carcinogenicity. Chemicals

were classied as ‘possible’/‘probable’/‘likely’ carcinogens or des-

ignated as ‘not likely’ or with ‘evidence of non-carcinogenicity’

and then compared with in-vivo rodent carcinogenicity data in

the Toxicity Reference Database to evaluate their predictions. The

model proved to be a good predictive tool, but it was developed

only as a means to help the EPA prioritize many untested indi-

vidual chemicals for their carcinogenic potential (i.e. in order to

establish priorities for individual chemical testing (29)).

What is still needed, is an approach employing the Hallmarks

of Cancer framework that can be used to identify priority

mixtures (i.e. those with substantive carcinogenic potential).

Without a way to anticipate the carcinogenicity of complex

mixtures, an important gap in capability exists and it creates

a signicant weakness in current risk assessment practices.

Countries around the globe have made a signicant investment

in the regulatory infrastructure and risk assessment practices

that protect us from unwanted exposures to harmful chemicals

and carcinogens, so we wanted to review the biology of cancer

to map out the challenges associated with the development of

an approach that would help us assess the carcinogenic poten-

tial of low-dose exposures to chemical mixtures in the envi-

ronment. Such an approach was seen as a reasonable step to

provide impetus for progress in this area of research and ulti-

mately to inform risk assessment practices worldwide.

Materials and methods

In 2012, the non-prot organization ‘Getting to Know Cancer’ instigated

an initiative called ‘The Halifax Project’ to develop such an approach using

the ‘Hallmarks of Cancer’ framework as a starting point. The aim of the

project was to produce a series of overarching reviews of the cancer hall-

marks that would collectively assess biologically disruptive chemicals (i.e.

chemicals that are known to have the ability to act in an adverse manner

on important cancer-related mechanisms, but not deemed to be carcino-

genic to humans) that might be acting in concert with other seemingly

innocuous chemicals and contributing to various aspects of carcinogen-

esis (i.e. at levels of exposure that have been deemed to be safe via the

traditional risk assessment process). The reviews were to be written by 12

writingteams.

The writing teams were recruited by Getting to Know Cancer circu-

lating an email in July 2012 to a large number of cancer researchers, ask-

ing about their interest in the project. Respondents were asked to submit

personal details through a dedicated webpage that provided additional

project information. Atotal of 703 scientists responded to the email,

and from that group, 11 team leaders were selected to lead reviews of

each hallmark (10 Hallmarks plus an 11th team to consider the tumor

microenvironment as a whole) and one leader for the cross-validation

Figure1. Disruptive potential of environmental exposures to mixtures of chemicals. Note that some of the acquired hallmark phenotypes are known to be involved in

many stages of disease development, but the precise sequencing of the acquisition of these hallmarks and the degree of involvement that each has in carcinogenesis

are factors that have not yet been fully elucidated/dened. This depiction is therefore only intended to illustrate the ways in which exogenous actions might contribute

to the enablement of these phenotypes.

W.H.Goodson et al. | S261

team (see below). Writing group leaders were asked to form individual

teams drawn from the pool of researchers who expressed interest in

the project and from their own circles of collaborators. Leaders were

encouraged to engage junior researchers as well. Team leaders received

project participation guidelines and ongoing communication from the

project leaders, L.Lowe and M.Gilbertson. Each team included: a lead

author with a published expertise in the hallmark area; domain experts

who assisted in the production of the descriptive review of the biology;

environmental health specialists (e.g. specialists in toxicology, endo-

crine disruption, or other related disciplines) and support researchers.

Each writing team was charged to describe the hallmark, its systemic

and cellular dysfunctions and its relationships to other hallmarks. Apri-

ority list of relevant (i.e. prototypical) target sites for disruption was to

be developed by the team and a list of corresponding chemicals in the

environment that have been shown to have the potential to act on those

targets was requested, along with a discussion of related issues and future

research needed (in the context of project goals).

Selection of target sites for disruption

A ‘target’ was broadly dened as a procarcinogenic disruption at the sys-

tem level (e.g. the hypothalamic–pituitary–gonadal axis), organ level, tis-

sue level or cellular level. It was assumed from the outset that a project

intended to develop an approach for the assessment of the carcinogenic

potential of low-dose exposures to chemical mixtures in the environment

would encounter a practical upper limit to the number of potential targets

that any given team could realistically review. Therefore, each team was

asked to identify up to 10 relevant targets for their domain (bearing in

mind that each target would also serve as a starting point for the identi-

cation of a disruptive environmental chemical that had already shown

a demonstrated ability to act on that target). In theory, it was understood

that this could lead to as many as 110 targets for the entire project, and

as the teams were also asked to select one disruptive chemical for each

target, a maximum of 110 chemicals.

In this phase, teams were asked to focus on specic gene changes

common to many cancers as identied by The Cancer Genome Project

(30) in order to estimate how the function of specic genes might be

altered, not by specic gene mutations, but rather either by direct

action or by epigenetic changes that might lead to the same functional

ends. Most of these pathways and processes are found within both

the hallmarks of cancer and the genomic frameworks, so teams were

asked to evaluate both models and consider non-mutagenic/epigenetic

pathways of interference as well (given that epigenetic changes such as

DNA methylation and histone acetylation are relevant for cancer and

often inducible by chemicals and may be transmitted to daughter cells).

Selection of disruptive chemicals

Teams were then asked to identify ‘prototypical’ chemicals in the envi-

ronment that had demonstrated an ability to act on the selected targets.

During workshops in Halifax, the teams settled on the following criteria

to guide their choices:

• Chemicals should be ubiquitous in the environment because we

wanted the broadest possible relevance for the general popula-

tion.

• Chemicals should selectively disrupt individual targets such as

specic receptors, specic pathways or specic mechanisms. Hypo-

thetically speaking, a chemical could affect more than one pathway,

receptor and so on; indeed, we expected that most chemicals would

likely exert a multitude of actions. However, we used the term ‘selec-

tively disruptive’ to encourage teams to avoid choosing mutagens

that are randomly destructive in their action (i.e. unpredictable and

capable of producing varying types of damage across a wide range

of pathways).

• Chemicals should not be ‘lifestyle’ related, such as those encountered

from tobacco, poor diet choices (e.g. red meats, French fries, lack of

fruit and vegetables and so on), alcohol consumption, obesity, infec-

tions (e.g. human papillomavirus) and so on.

• Chemicals should not be known as ‘carcinogenic to humans’ (i.e. not

IARC Group1, carcinogens).

The choice to focus on environmental pollutants in this project was

intentionally restrictive. Countries around the globe have made sig-

nicant investments in regulatory infrastructure and risk assessment

practices to protect us from unwanted exposures to harmful chemicals

and carcinogens. Therefore, we focused on chemicals that are com-

monly encountered in the environment. Primarily, we wanted to gen-

erate insights that would be valuable for cancer researchers who are

specically interested in environmental chemical exposures to chemical

mixtures and/or those who are focused on risk assessment practices in

general.

Dose-response characterizations andLDE

Given that much of the evidence in the toxicological literature that docu-

ments the disruptive actions of various chemicals has been produced

under a wide range of differing experimental circumstances, we wanted

to assess the quality and relevance of data that were gathered for expo-

sures discussed in this review. Specically, for each chemical selected

and each mechanism identied, teams were additionally tasked to iden-

tify any dose-response characterization results and/or relevant low-dose

research evidence that might exist. The term ‘low dose’ was dened using

the European Food Safety Authority denition (i.e. responses that occur at

doses well below the traditional lowest dose of 1 mg/kg that are used in

toxicology tests) and the denition for ‘LDE’ was based on the EPA deni-

tion (31)—as follows:

Any biological changes occurring

(a) in the range of typical human exposuresor

(b) at doses lower than those typically used in standard testing proto-

cols, i.e. doses below those tested in traditional toxicology assess-

ments (32),or

been measured in the past, i.e. any dose below the lowest observed

effect level (LOEL) or LOAEL (33)

(d) occurring at a dose administered to an animal that produces blood

concentrations of that chemical in the range of what has been

measured in the general human population (i.e. not exposed oc-

cupationally, and often referred to as an environmentally relevant

dose because it creates an internal dose relevant to concentrations

of the chemical measured in humans) (34,35).

Each team was then asked to categorize each chemical by using one of

ve possible categories (to determine the relevance and relative strength

of the underlying evidence for each of the chemicals being considered).

The categories were as follows: (i) LDE (i.e. levels that are deemed relevant

given the background levels of exposure that exist in the environment);

(ii) linear dose-response with LDE; (iii) non-linear dose-response with LDE;

(iv) threshold (i.e. this action on this mechanism/pathway does not occur

at low-dose levels) and (v) unknown. Additional details of the descriptions

for each of these categories are shown in Table1.

Cross-hallmark relationships

In recognition of the network of signaling pathways involved and the

degree of overlap/interconnection between the acquired capabilities

described in each hallmark area, the project included a cross-validation

step to create a more complete mapping of the actions that might be

anticipated as the result of an action on the target sites identied or by

the disruptive effects of the chemicals selected. Given the diversity of the

targets involved in the 11 hallmark areas, it was anticipated that inhibit-

ing or stimulating a target relevant to one hallmark may have an impact

on other targets that are relevant, especially if both are linked via signal-

ing pathways.

Accordingly, the cross-validation team conducted additional back-

ground literature review of submitted targets and chemicals from each

writing team, searching for evidence to identify cross-hallmark activity.

Each potential target-hallmark or approach-hallmark interaction was

assessed to determine whether the inhibition or activation of each tar-

get and the corresponding biological activity of each chemical might

reasonably be expected to have either a procarcinogenic or anticarcinogenic

effect on key pathways/processes in the various hallmark areas.

S262 | Carcinogenesis, 2015, Vol. 36, Supplement 1

Table1. Dose-response characterization

Review team Chemical name Disruptive action on key mechanism/pathway Low-dose effect (LDE, LLDE, NLDE, threshold, unknown)

Angiogenesis Diniconazole Vascular cell adhesion molecule and cytokine signaling Threshold (H-PC) (36)

Ziram Vascular cell adhesion molecule and cytokine signaling Threshold (H-PC) (36,37)

Chlorothalonil Thrombomodulin, vascular proliferation and cytokine signaling Unknown (H-PC) (36), NLDE (A-in vivo) (38)

Biphenyl Angiogenic cytokine signaling Unknown (H-PC) (36)

Tributyltin chloride Vascular cell proliferation and adhesion molecule signaling Unknown (H-PC) (36)

Methylene bis(thiocyanate) Plasminogen activating system and cytokine signaling Unknown (H-PC) (36)

HPTE Vascular cell adhesion molecule and cytokine signaling Unknown (H-PC) (36), threshold (A-Ia) (39), LDE (A-Ia) (40)

PFOS Angiogenic cytokine signaling Threshold (H-PC) (36), LDE (H-CL) (41)

Bisphenol AF Matrix metalloproteinase expression and estrogen receptor signal-

ing

Unknown (H-PC) (36)

C.I.solvent yellow 14 AhR and hypoxic signaling Unknown (H-PC) (36)

Dysregulated metabolism Cypermethrin AR and ER expression, reduction of ATP and mitochondrial en-

zymes, mitochondrial membrane potential

LLDE (A-I) (42), NLDE (A-I) (42), NLDE (H-CL) (36,43,44)

Acrolein p53 activation, DNA repair inhibition, PERK phosphorylation, mito-

chondrial dysfunction, cell survival

LLDE (A-I, A-CL, H-PC, H-CL) (45–50), NLDE (49), threshold (46)

Rotenone Cell cycle, DNA damage response, proliferation, differentiation,

mitochondria

LLDE (H-CL) (51–53), NLDE (H-CL) (51,53), unknown (H-CL,H-

PC) (36)

Copper p53 activation, p21 up-regulation, cell viability LLDE (H-CL) (54–56)

Nickel Neutrophil apoptosis, E-cadherin regulation, matrix metallopepti-

dase (MMP) production

LLDE (H-CL) (57), NLDE (H-CL) (58), Threshold (H-CL) (58)

Cadmium p53-dependent apoptosis, cell proliferation LLDE (H-CL) (59), threshold (H-CL) (60)

Diazinon AChE activity, neuronal cytotoxicity Unknown (A-PC) (61), LLDE (H-CL) (62), threshold (H-CL) (36)

Iron KRAS mutations LLDE (A-I) (63)

Malathion Lymphocyte Mutations, Cytotoxicity Unknown (H-PC, H-E) (36,64)

Tissue invasion and

metastasis

BPA MMP-2 and MMP-9 expression, increased migration, invasion, EMT,

oxidative stress, ER signaling

LDE (H-CL) (65,66), threshold (H-CL, H-PC) (36)

Hexacholorobenzene Activation of c-Src, HER1, STAT5b and ERK1/2 signaling LLDE (H-CL, A-I) (67)

Sulfur dioxide MMP-9 expression Unknown (A-PC) (68)

Phthalates MMP-2 and MMP-9 expression LDE (H-CL) (66),Unknown (H-CL, H-PC) (36)

Iron ROI generation, NF-κB activation, uPA expression Unknown (H-CL) (69)

Biorhythms/melatonin GSK3β activation, EMT regulation Unknown (H-CL, H-E) (70,71)

Resistance to cell death BPA Inhibition of GJIC, activation of mTOR pathway, down-regulation of

p53, p21 and BAX, binding to ER-α, weakly binds to TH receptor

and AR, activation of ERK1/2 and p38

NLDE(H-CL, A-CL) (72–74)Threshold (H-CL, H-PC) (36)

Dibutyl phthalate Activation of PPAR-α, inhibition of GJIC, expression of cyclin D and

cdk-4, activation of AhR/HDAC6/c-Myc pathway

NLDE (H-CL) (75), unknown (H-CL, H-PC) (36)

Chlorothalonil Up-regulation of ErbB-2 tyrosine kinase and MAP kinase, aromatase

inhibitor

Threshold-based (i.e. non-linear) (A-I) (76), unknown (H-PC)

(36), threshold (H-CL) (36)

Lindane Induction of MAPK/ERK pathways Threshold-based (i.e. non-linear) (A-I) (77), threshold (H-CL)

(36)

Dichlorvos Expression of p16, Bcl-2 and c-myc LLDE (A-I) (78), threshold (H-CL) (36)

MXC Binding to ER-α receptor, up-regulation of cyclin D1, down-regula-

tion of p21

LLDE (H-CL, A-CL) (75,79), unknown (H-PC) (36), threshold

(H-CL) (36)

Oxyuorfen Expression of Cyp2b10 and Cyp4a10 transcripts (markers of PPAR-α

activation)

Threshold (A-I) (80), unknown (H-CL, H-PC) (36)

DEHP Activation of PPAR-α, inhibition of GJIC Threshold-based (i.e. non-linear) (A-I) (81)

Linuron Hypersecretion of LH, inhibition of GJIC Unknown (H-CL) (82)

W.H.Goodson et al. | S263

Review team Chemical name Disruptive action on key mechanism/pathway Low-dose effect (LDE, LLDE, NLDE, threshold, unknown)

Replicative immortality Nickel-derived compounds, (e.g.

nickel chloride)

Epigenetic silencing of p16 LLDE (H-CL, A-PC) (83)

Diethylstilbestrol Allelic loss and point mutation in ETRG-1 gene LLDE (A-I) (84)

Reserpine Epigenetic modications Unknown (A-PC) (85), threshold (H-CL) (36)

Phenobarbital Reduces expression of the CDKN1A product p21, CAR activation LLDE (A-I) (86,87)

Acetaminophen Cellular energy loss, mitochondrial damage, telomerase activation LDE (H-CL, A-I, A-CL) (88–92)

Cotinine Telomerase activation LLDE (H-PC) (93)

Nitric oxide p53 inactivation LLDE (H-PC, H-CL, A-CL, A-I) (94)

Na-selenite p53 promoter methylation LLDE (A-CL, A-I) (95,96)

Lead p53 inactivation LLDE (H-PC, H-CL, A-CL, A-I) (94)

Sustained proliferative

signaling

BPA Estrogen receptor activation, cell cycle/senescence LLDE (A-I, H-CL, H-E) (12,97), NLDE (A-I) (98,99), threshold (H-

CL) (36)

Cyprodinil Increased proliferation signaling, AhR activation Unknown (H-PC, H-CL) (36,100,101), threshold (H-CL) (36)

Imazalil AR signaling NLDE (A-I) (102,103), threshold (H-CL, H-PC) (36)

Maneb Nitric oxide signaling Unknown (A-CL, H-CL, H-PC) (36,104,105)

Methoxyclor ER signaling Threshold (H-CL) (36), LDE (A-I) (106,107), NLDE (A-I) (108)

PFOS Nuclear hormone receptors Threshold (H-CL) (36), LLDE (A-I) (109,110)

Phthalates CAR, ER signaling Unknown (H-CL) (36), LDE (A-I) (111–113)

Phosalone Increased proliferation, PXR signaling Unknown (H-PC, H-CL) (36,114,115)

PBDEs ER signaling LDE (A-I) (116,117)

Prochloraz ER signaling LDE (A-I) (118,119)

Trenbolone acetate Insulin-like growth hormone-1 and AR signaling Unknown, LDE (A-I, H-CL, H-E) (120,121)

Tumor-promoting inamma-

tion

BPA Immune cell proliferation, proinammatory cytokine induction Threshold (H-PC) (36), LDE (A-I, H-CL, H-E) (122–126)

Phthalates Immunomodulation of macrophages, lymphocytes, eosinophils and

neutrophils

Unknown (H-PC, H-CL, H-E) (36,127)

PBDEs Induction of pro-inammatory cytokines (IL-6, IL8 and CRP), inhibi-

tion of anti-inammatory cytokines (IL-10)

Threshold (H-PC, H-CL) (128–131)

Atrazine Immunomodulation of T cell and B cells, proinammatory cy-

tokines

Unknown (H-PC, A-I) (36,132,133)

Vinclozolin Proinammatory cytokine induction, NF-κB activation Unknown (H-PC, A-I) (36,134–136)

4-NP Proinammatory cytokine induction, NF-κB activation, iNOS induc-

tion

Unknown (A-CL, H-CL, H-PC) (36,137,138)

Immune system evasion Pyridaben Chemokine signaling, TGF-β, FAK, HIF-1a, IL-1a pathways Unknown (H-CL, H-PC, A-CL) (36,139,140), threshold (A-I) (141)

Triclosan Chemokine signaling, TGF-β, FAK, IL-1a pathways Threshold (H-CL, H-PC, A-I) (36,142–144), LDE (A-I, H-CL)

(145,146)

Pyraclostrobin Chemokine signaling, TGF-β, IL-1a pathways Unknown (H-CL, H-PC) (36)

Fluoxastrobin Chemokine signaling, EGR, HIF-1a, IL-1a pathways Unknown (H-CL, H-PC) (36)

BPA Chemokine signaling, TGF-β pathway Threshold (H-PC) (36), LDE (A-I) (12), NLDE (H-CL) (147), NLDE

(A-CL) (148–151), NLDE (A-I) (152–155)

Maneb PI3K/Akt signaling, chemokine signaling, TGF-β, FAK, IGF-1, IL-6,

IL-1a pathways

Unknown (H-CL, H-PC) (36,139,156–158), LDE (A-I) (159),

threshold (A-I) (139,160), threshold (A-CL, A-I) (161)

Table1. Continued

S264 | Carcinogenesis, 2015, Vol. 36, Supplement 1

Review team Chemical name Disruptive action on key mechanism/pathway Low-dose effect (LDE, LLDE, NLDE, threshold, unknown)

Evasion of antigrowth

signaling

DDT Induces MDM2, cyclin D1, E2F1 expression, disrupts gap junctions NLDE (A-I, H-CL, A-CL) (162–164)

Chlorpyrifos Increases proliferation LDE (H-CL, H-PC) (165,166)

Folpet Disrupts G1–S checkpoint kinases, down-regulates p53, promotes

proliferation

LDE(A-C) (167)

Atrazine Induces estrogen production and proliferation LDE(H-CL, A-I) (168–170)

BPA Reduced p53, reduced connexin 43 expression, increased prolifera-

tion

NLDE (H-CL, A-I) (171–174)

Tumor microenvironment Nickel ROS and cellular stress NLDE (A-I) (175)

BPA IL-6 expression, improper DC maturation and polarization, ROS

production

LLDE (A-I) (176), NLDE (A-I) (176)

Butyltins (such as tributyltin) NK cell inhibition LDE (A-I) (177)

MeHg Chronic oxidative stress LDE (H-PC, H-CL) (178,179)

Paraquat Chronic ROS production, cellular stress Unknown (A-I) (180)

Genome instability Lead Dysfunctional DNA repair, defect in telomere maintenance Unknown (A-CL) (181–183), threshold (H-CL, H-E) (184,185)

Acrylamide Inactivation of DNA repair proteins/enzymes Unknown (A-CL, A-I, H-CL) (186,187)

Quinones Affect free cysteine residues in catalytic center of DNA methyl-

transferases (DNMT)

Unknown (A-CL) (188)

Nickel Affect enzymes that modulate post-translational histone modica-

tion

LDE (H-E) (189,190), LDE (A-CL, H-CL) (191)

BPA Epigenetic changes via interactions with miRNA Threshold (H-PC) (192)

Alloy particles (tungsten/nickel/

cobalt)

Disruption of DNA damage/redox signaling involving Nrf, NF-κB,

Egr, and so on

LDE (A-I) (193)

Titanium dioxide NPs Decreased NADH levels and impaired mitochondrial membrane

potential and mitochondrial respiration, ROS generation

Unknown (A-PC) (194)

Benomyl Spindle defects leading to formation of micronuclei Threshold (H-CL) (195), Threshold (A-CL) (196)

Carbon nanotubes Spindle defects leading to formation of micronuclei LLDE (A-CL) (197,198), unknown (A-I) (198)

Each chemical in the table was categorized by using one of ve possible categories (to determine the relevance and relative strength of the underlying evidence for each of the chemicals being considered)—as follows: (1) LDE

(low-dose effect)—the ability of this chemical to exert this particular effect is not well characterized at a range of dose levels, but the evidence suggests that this chemical can exert this effect at low-dose levels (i.e. levels that

are deemed relevant given the background levels of exposure that exist in the environment and as further dened below). (2) LLDE (linear dose-response with low-dose effects)—the ability of this chemical to exert this particular

effect is well characterized at a range of dose levels and the evidence suggests that a linear dose-response relationship exists with effects at low-dose levels being evident (i.e. levels that are lower than the LOEL/LOAEL or thresh-

old and deemed relevant given the background levels of exposure that exist in the environment). Note: a linear dose-response model implies no threshold. Effects at low doses are the same as at higher doses even if at a lesser

extent. The effect is directly proportional to the dose. (3) NLDE (non-linear dose-response with low-dose effects)—the ability of this chemical to exert this particular effect is well characterized at a range of dose levels and the

evidence suggests that a non-linear dose-response relationship exists with exaggerated effects at low-dose levels being evident (i.e. levels that are lower than the LOEL/LOAEL or threshold and deemed relevant given the back-

ground levels of exposure that exist in the environment). Note: a non-linear dose-response with low-dose effect implies that the effect does not vary according to the dose of the agent. The effect at low doses may be the same

as at the higher doses or different. The non-linear dose-response may have or not have a threshold. It is represented by a sigmoid curve. The non-linear dose-response at low doses may be a non-monotonic dose-response. (4)

Threshold—the ability of this chemical to exert this particular effect is well characterized at a range of dose levels, and a threshold has been established for this chemical that suggests that this action on this mechanism/path-

way does not occur at low-dose levels (i.e. levels that are lower than the threshold and deemed relevant given the background levels of exposure that exist in the environment). (5) Unknown—although the ability of this chemi-

cal to exert this particular effect has been shown at higher dose levels, this effect is not well characterized at a range of dose levels, so a LOEL /LOAEL or a threshold has not been determined for this chemical and there is no

evidence showing that this chemical exerts this action at low-dose levels (i.e. levels that are lower than the LOEL/LOAEL or threshold and deemed relevant given the background levels of exposure that exist in the environment).

A-I, in-vivo animal models; A-CL, animal cell lines; A-PC, animal primary cells; H-PC, human primary cells; H-CL, human cell lines; H-E, human epidemiological studies. With respect to the human primary cell (H-PC) data from

ToxCast (36): unknown signies that the compound was tested across a range of doses and showed statistically signicant activity against the specied targets at the lowest test concentrations (~0.01µM); therefore, a threshold

could not be established. Threshold in this data set signies that there was no activity against the targets at one or more of the lowest concentrations tested.

aExtrapolated from in-vivo data on the parent compound, MXC.

Table1. Continued

W.H.Goodson et al. | S265

The cross-validation team also sought out controversial interactions

(i.e. mixed indications of hallmark-like effects) and instances where no

known relationship existed. It was our belief that target sites or chemicals

that demonstrated a substantial number of ‘anticarcinogenic’ effects in

other hallmark areas would be less suitable to serve as instigating con-

stituents in the design of carcinogenic mixtures (where procarcinogenic

synergy was being sought).

It is important to note that the cross-validation team was not

given any restrictions for literature selection for this effort, and con-

tributing authors were restricted neither to results from low-dose

testing, nor to that of cancer-related research. This approach was

taken because it was realized at the outset that this sort of breadth

and homogeneity (of low-dose evidence) does not yet exist in the lit-

erature. As a result, the types and sources of data gathered in this

effort varied considerably, resulting in an admixture of reviews and

original studies. Moreover, many studies that were cited in this effort

only considered a chemical’s ability to instigate or promote an action

that mimics a hallmark phenotype in a manner directionally consist-

ent with changes that have been associated with cancer. So, although

we have referred to these actions as procarcinogenic and anticarci-

nogenic, as these changes are frequently neither fixed nor specific

for cancer, the specificity of these changes and implications for car-

cinogenesis cannot and should not be immediately inferred from this

data set. Short-term toxicity and toxic responses—particularly in data

from in-vitro HTS platforms—must be distinguished from truly ‘carci-

nogenic’ long-term changes. In other words, the tabularized results

from this particular aspect of the project were only compiled to serve

as a starting point for future research. Where cross-hallmark effects

were reported (at any dose level and in any tissue type), we wanted

samples of that evidence to share with researchers who might be try-

ing to anticipate the types of effects that might be encountered in

future research on mixtures of chemicals (in a wide range of possible

research contexts).

Results

The results are presented roughly sequenced in a manner that

captures the acquired capabilities found in many/most cancers.

The section begins with two enabling characteristics found in

most cancers Genetic instability and Tumor-promoting inam-

mation, followed by Sustained proliferative signaling and

Insensitivity to antigrowth signals, the two related hallmarks

that ensure that proliferation is unabated in immortalized cells.

These sections are followed by Resistance to cell death and

Replicative immortality, two critical layers of defense that are

believed to be bypassed in all cancers and then by dysregulated

metabolism. Sections on Angiogenesis and Tissue invasion and

metastasis follow and speak to the progression of the disease,

and nally, the Tumor microenvironment and Avoiding immune

destruction sections offer summaries related to the very last

lines of defense that are defeated in most cancers. Additionally,

dose-response characterizations and evidence of LDE are then

presented for all of these areas and the results from the cross-

validation activity are summarized and reviewed.

Genetic instability

The phenotypic variations underlying cancer result from interac-

tions among many different environmental and genetic factors,

occurring over long time periods (199). One of the most important

effects of these interactions is genome instability—loosely dened

as an increased likelihood of the occurrence of potentially muta-

genic and carcinogenic changes in the genome. The term is used

to describe both the presence of markers of genetic change (such

as DNA damage and aneuploidy) and intrinsic factors that per-

mit or induce such change (such as specic gene polymorphisms,

defective DNA repair or changes in epigenetic regulation).

DNA damage—which can be caused by exposure to external

chemicals or radiation, or by endogenous agents such as reactive

oxygen or faulty replication—is an event that can initiate the

multistep process of carcinogenesis (200). Protection is afforded

at different levels; removal of damaging agents before they

reach the DNA, by antioxidant defenses and the phase I/phase

II xenobiotic metabolizing enzymes; a second line of defense,

DNA repair, operating on the damage that occurs despite the

primary protection; and as a last resort, apoptosis (programmed

cell death), disposing of heavily damagedcells.

A clear sign of genome instability is aneuploidy—a deviation

from the normal number of chromosomes (201). Aneuploidy is

a very common feature of human cancers. Another hallmark of

cancer is loss of the normal mechanism of telomere shortening,

which allows abnormal cells to escape senescence, by avoid-

ing the body’s ‘editing’ processes that normally eliminate aging

cells with their accumulated genome aberrations (202,203).

The genes of most signicance for cancer are the (proto)-

oncogenes which, if defective, or abnormally expressed, lead

to uncontrolled cell proliferation; tumor suppressor genes, the

normal products of which tend to switch off replication to allow

repair, and promote cell death if damage is excessive; and genes

such as those involved in DNA repair that can—if faulty—lead

to a ‘mutator phenotype’. Mutated proto-oncogenes and tumor

suppressor genes are found in most if not all cancers and

play key roles in cancer etiology (204–207). Rare mutations in

DNA repair genes greatly increase the risk of cancer (208,209).

However, the evidence for links between common variants of

repair genes and cancer is generally inconclusive (210).

The term ‘epigenetics’ refers to covalent modications of the

DNA (methylation of cytosine in ‘CpG islands’ within regula-

tory regions of genes) or of the histones. These modications

can control gene expression and the pattern of modications

is altered in many cancers (211,212). For instance, hypometh-

ylation of proto-oncogenes can lead to overexpression, which

is undesirable. MicroRNAs (miRNAs) are responsible for specic

down-regulation of gene expression at a post-transcriptional

level, by preventing translation from messenger RNAs. miRNAs

participate in DNA damage responses and some miRNAs are

deregulated in many cancers (213–215).

Mutations in germ and stem cells are potentially more seri-

ous than those in other cells as they are passed to the cells’

progeny within the developing embryo or regenerating tissue

(216,217). There is a presumed survival benet when stem cells

tend to show a particularly stringent maintenance of genome

integrity through cell cycle regulation and enhanced responses

to DNA damage (218).

The selected ‘chemical disruptors’ that induce genome

instability include chemicals that not only directly damage DNA

or cause mutations, but act indirectly, via pathways such as DNA

damage signaling, DNA repair, epigenetic regulation or mito-

chondrial function. They include the following:

Metals such as lead, nickel, cobalt and mercury (common

water pollutants) are known to disrupt DNA repair (181,219),

whereas nickel also affects epigenetic histone modication

(189,191) and lead causes defective telomere maintenance

(184,220). Alloy particles, containing tungsten, nickel and cobalt,

can be inhaled and disrupt redox signaling (193,221). Titanium

dioxide nanoparticles are also common in many consumer prod-

ucts and foods and have been reported to disrupt mitochondrial

function and increase oxidative stress, as well as inhibit DNA

repair and disrupt mitosis (194,222,223).

Acrylamide occurs in many fried and baked food products,

and (apart from the well-known DNA adduct formation) can

S266 | Carcinogenesis, 2015, Vol. 36, Supplement 1

inactivate many critical proteins by binding sulfhydryl groups

(186).

Bisphenol A (BPA) is a plasticizer used for manufactur-

ing polycarbonate plastics and epoxy resins, and it can leach

from plastics into food and water. It is implicated in disruption

of DNA methylation, histone acetylation and disturbance of

miRNA binding (192,224,225), redox signaling (226) and induc-

tion of micronuclei through spindle defects in mitosis (227).

The fungicide benomyl is metabolized to carbendazim;

both are classied as possible human carcinogens at present.

The route of exposure is most likely ingestion via residues in

crops. Benomyl disrupts the microtubules involved in the func-

tion of the spindle apparatus during cell division, leading to

production of micronuclei (Frame,S.R. etal., unpublished report,

Schneider,P.W. etal., unpublished report, (228)).

Halobenzoquinones are disinfection by-products in chlo-

rinated drinking water (229). Quinones are electrophilic com-

pounds, known to react with proteins and DNA to form adducts.

These electrophylic chemicals can interact with functional thiol

groups via Michaelis–Menton type addition, causing modica-

tion of enzymes involved in methylation and demethylation

(188). This mechanism might be shared by other xenobiotics

that increase reactive oxygen species(ROS).

Human exposure to nano-sized materials used in cosmetics,

biomedical compounds, textiles, food, plastics and paints has

increased not only in a conscious way but also passively by the

leakage of nanomaterials from different objects. Nanoparticles

can induce genome instability via mitochondrial-related apop-

tosis (230), decreased DNA repair (222,230,231), hypoacetyla-

tion of histones (232), disruption of DNA methylation (231),

up-regulation of miRNA (233), reducing telomerase activity

(220) and—more specically for carbon nanotubes—interact-

ing with components of the mitotic spindle during cell division

or interacting with proteins directly or indirectly involved in

chromosome segregation (197,234). Nano-sized materials can

also produce inammation and alteration of the antioxidant

defenses that can lead to genome instability.

Tumor-promoting inammation

One of the earliest hypothesized causes of tumors subsequently

supported experimentally was the irritation hypothesis pro-

posed by Virchow. Although it was recognized initially that injury

alone was insufcient for carcinogenesis, it was also recognized

that ‘irritation may have an accessory or predisposing inuence

in tumor formation, and that it may be enough nally to upset

the balance of a group of cells which for some other reason were

already hovering on the brink of abnormal growth’ (235). Indeed,

it is now recognized that inammatory responses, similar to

those associated with wound healing or infection, support the

development of invasive carcinomas by altering the microen-

vironment in favor of proliferation, cell survival, angiogenesis

and tumor cell dissemination while also disrupting antitumor

immune surveillance mechanisms. In other words, inamma-

tion plays a critical role in tumorigenesis (23,24).

Inammation is an immediate and necessary host defense

mechanism in response to infection or tissue injury by noxious

stimuli. In tumor-associated inammation, both the epithelium

and the immune cells express receptors that signal the activa-

tion and production of a wide array of biologically active proteins

most analogous to an unhealed wound. The sustained or uncon-

trolled release of potent and reactive molecules such as prosta-

glandins, cytokines, ROS and chemokines from both the tumor

cell and the microenvironment constituents lead to progressive

genomic instability, alterations in the integrity and function of

the microenvironment including alterations in the vasculature

(e.g. vascular hyperpermeability, neovascularization and angio-

genesis), as well as alterations in local immune dynamics. The

cellular and molecular mechanisms include a diverse array of

immune- and tumor-cell-derived effector molecules such as the

proinammatory reactive oxygen and nitrogen species, a num-

ber or cytokines, chemokines as well as cyclooxygenase-2 and

its product, prostaglandin E2.

In general, there is a paucity of experimentation, and when

present, inconsistent ndings for the role of environmental

chemicals as proinammatory molecules and more so for a pro-

inammatory action as a co-factors in carcinogenesis. However,

some recent studies provide a credible mechanistic basis, par-

ticularly early life exposures that might act by disrupting the

immune cell balance toward inammation, and that manifest in

adulthood. One example is BPA, one of the most abundant and

best studied environmental endocrine disruptors, and its con-

troversial role as an immune disruptor. Specically, studies in

male rats found that early life BPA exposure leads to the devel-

opment of prostate intraepithelial neoplasia (a prostate cancer

precursor lesion) through a pathological process that includes

BPA-dependent epigenetic reprogramming of genes involved in

the development of lateral prostate inammation in adulthood

(236,237).

This work in prostate is complemented by a much more

extensive study of BPA effects on immune cell components,

particularly the T-cell compartment, demonstrating that BPA

acts as an immune disruptor by promoting ‘immune’ cell pro-

liferation though the exact nature of the effect on specic cells

of the immune system is poorly delineated. Most interesting is

the work by Yan etal. (122), who reported ndings suggesting

that the timing of BPA exposure during development (prenatally,

early life or adult) alters the effect of BPA on regulatory T cells.

BPA actions also map over to the effects on the immune sys-

tem including the promiscuity of BPA for a number of nuclear

receptors relevant to immune cells such as the estrogen recep-

tor and the aryl hydrocarbon receptor (AhR). As well, bulky BPA

analogs may act as antagonists of members of the peroxisome

proliferator-activated receptor (PPAR) family, an important fam-

ily of nuclear receptors with potent anti-inammatory function

(238,239). Effects on the PPAR nuclear receptors may also explain

inammation-associated phenotypes observed with exposures

to certain phthalates and nonylphenol (4-NP).

A second example is the reported immunotoxic effects of

atrazine (6-chloro-N-ethyl-N-(1-methylethyl)-1,3,5-triazine-2,4-

diamine) (240), a chemical that is the most commonly detected

triazine herbicide in USA soil and water. Atrazine is banned

by the European Union and drinking water exposures are sup-

posed to be limited in the USA to <3µg/l (although exposures

exceed this limit regularly), but the use of this chemical is high

and increasing in Asia and other countries. Thus, atrazine is an

important pesticide to which humans are exposed. Atrazine

exhibits weak mutagenicity and low oncogenic properties, but

research by a number of authors is emerging that suggests that

immune system disruption might be a concern (132,240,241).

Although the majority of work on atrazine has been focused

on its endocrine disrupting properties, there is also evidence

to support immunotoxicity including effects on T-lymphocytes

composition with oral dosing (242,243), modulation of nitric

oxide production (244) and potential generation of ROS (245,246).

The local production of reactive nitrogen species and ROS

by mast cells and macrophages are among the better stud-

ied immune modulatory molecules for which recent evidence

W.H.Goodson et al. | S267

supports important roles both in the tumor microenvironment

and in the tumor progression (247–249). Notably, these reactive

species trigger oxidative/nitrosative modications, which can

initiate redox signaling that tightly modulates the inammatory

response in a manner that is highly relevant for carcinogenesis

(250,251).

We also looked at polybrominated diphenyl ethers (PBDEs)

and their effects on inammatory cytokines. Peltier etal. (128)

recently found that placental explants treated with a mix-

ture of the cogeners BDE-47, -99 and -100 and then exposed

to Escherichia coli were ‘reprogrammed’ toward a proinam-

matory response (increased IL-1β and tumor necrosis factor

α) and away from the expected anti-inammatory response

(decreased IL-10) compared with untreated placenta. Although

these studies are preliminary, chronic PBDE exposure may

lower the threshold for bacteria to stimulate a proinammatory

response, which has potential relevance given the established

link between bacteria and certain cancers (e.g. Helicobacter pylori

and gastric cancer), where tumor development is dependent on

inammation.

Vinclozolin was also of particular interest as an environmen-

tal chemical because transient early life exposures in utero have

been linked to both adult-onset disease and transgenerational

disease that involves inammation (134,135). For example, tran-

sient vinclozolin exposure in utero has been shown to promote

inammation in the prostate (prostatitis) of postpubertal rats

coupled with a down-regulation of the androgen receptor and

increase in nuclear factor-κB (NF-κB). The late or delayed effect

of exposure is hypothesized to reect a mechanism whereby

vinclozolin exposure during a critical development window

imprints an irreversible alteration in DNA methyltransferase

activity, leading to reprogramming of the androgen receptor (AR)

gene(s), which manifest as inammation in early adult life with

adverse effects on spermatid number.

Similarly, 4-NP has been shown to increase progenitor white

adipose levels, body weight and overall body size in rodents

exposed prenatally. Like vinclozolin, 4-NP effects on adipogen-

esis in the perinatal period confer transgenerational inheritance

of the obesogenic effects observable in F2 offspring, consistent

with genome reprogramming through an epigenetic process

(252) and others have reported immune and inammation-

related effects (137,138) making it relevant to carcinogenesis a

deserving further investigation.

Sustained proliferative signaling

Sustained proliferative potential is an essential component of

cancerous growth. Progressive conversion of normal cells into

cancer cells requires a series of genetic alterations, where each

alteration confers one or more types of growth advantage. One

such alteration that affords the transformed cell a distinct

growth advantage over its normal counterparts is the acquired

capacity of the cancer cell to proliferate in a sustained manner,

so as to crowd out and outnumber the normal cell population

(23). One of the fundamental differences between a normal and

a transformed cell is that normal cells halt proliferation when

subjected to growth inhibitory signals or in the absence of

growth stimulatory signals (253). But tumor cells act to sustain

proliferative signaling in several different ways. They can acti-

vate specic genes to produce relevant growth factors, which in

turn bind to signaling receptors giving rise to an autocrine loop

(254). Growth factors produced by tumor cells can also stimulate

the proliferation of stromal cells that in turn produce growth

factors to sustain tumor cell proliferation (255). Sustained pro-

liferation can additionally be maintained at the receptor level

by truncation of signaling receptor proteins whereby the ligand-

activated switch is missing (256). Alternatively, the number of

high-afnity receptor proteins may be increased to levels that

will sustain proliferative signaling in otherwise normal growth

factor levels. Finally, sustained proliferative signaling may well

be the result of perpetual activation of the intracellular sign-

aling chain independent of growth factors or receptors (e.g.

mutated ras (257) or truncated src (258) are intermediaries of a

normal proliferation signaling chain responsible for sustained

proliferation).

We hypothesized that disruptive environmental chemicals

acting in a procarcinogenic manner by inducing what is referred

to as ‘sustained cell proliferation’ likely exerted their action by

interfering with some basic control mechanisms (23,253). For

instance, they could achieve this by positively regulating tar-

gets within and outside the cell known to promote cell prolif-

eration or negatively regulating targets within and outside the

cell known to halt cell proliferation. In this way, such chemicals

could confer proliferative advantage to a distinct cell population

and contribute to that population’s capability to successfully

breach innate anticancer defense mechanisms and to become

progressively autonomous.

Specically, we identied a total of 15 ubiquitous chemical

disruptors capable of producing sustained cell proliferation. The

majority of these chemicals interacted with multiple targets,

and we have tabled this information in our review. In summary,

we identied several commonly used insecticides and fungi-

cides capable of causing sustained proliferation. These included

cyprodinil, etoxazole, imazalil, lactofen, maneb, methoxychlor

(MXC), phosalone, prochloraz and pyridaben, all of which tar-

geted estrogen receptor α and frequently other steroid hormone

receptors such as androgen receptor (102,259–275). Most of

these chemicals also targeted growth factors and their recep-

tors (264,267) and induced cytokines and cytokine receptors

(identied by ToxCast high throughput assay). Top disrupting

chemical fungicides and insecticides were MXC and cyprodinil,

which each interacted with a total of six individual targets that

further included the AhR (100), B-lymphocyte markers (ToxCast

2009 high-throughput assay, both chemicals), AP-1 proteins/

transcription/translation regulators, downstream signaling

molecules and cell cycle regulators (276,277). Other strong per-

formers for sustained proliferation were BPA (activated all tar-

gets activated by the insecticides and fungicides above except

growth factors and their receptors, B lymphocyte markers and

PPAR, but included cell cycle regulators alongside AP-1 proteins/

transcription/translation regulators and downstream signaling)

(272,276,278,279) (also identied in ToxCast high-throughput

assay, 2009), polyuorinated octinoid sulfate and polybromi-

nated diphenylethers (ame retardants) that either activated

AhR (280,281) or up to ve other targets that included steroid

receptors, growth factors, cytokines and cell cycle regulators

(109) (ToxCast high-throughput assay 2009). Three other con-

tenders were phthalates (plasticizers that acted via three tar-

gets that included AhR, steroid hormone receptors and PPAR)

(282–285), trenbolone acetate (a synthetic anabolic steroid

that unsurprisingly acted through steroid hormone receptors)

(120,286–290) and nally, edible oil adulterants (food contami-

nants produced during food processing that acted via down-

stream signaling) (291,292).

We have shown estrogen and androgen receptors to be

important targets in relation to sustained proliferative signaling

(293), and note that environmental estrogens and androgens are

frequently recognized as prototypical disruptor(s) of this hall-

mark. Although this is a small sample, there are a great number

S268 | Carcinogenesis, 2015, Vol. 36, Supplement 1

of chemicals in the environment, both naturally occurring and

man-made, are estrogenic, interact with estrogen receptor and

produce estrogen metabolites (just as naturally derived ovarian

estrogen does during metabolic breakdown). Catechol estrogens

(hydroxyl derivatives of estrogens), which are formed during

estradiol metabolism, are also potentially important mediators

of endogenous estradiol levels, and therefore of sustained pro-

liferative signaling and oncogenesis (294).

Insensitivity to antigrowth signals

Cell cycle arrest is important for maintaining genomic integrity

and for preventing genetic errors from being propagated. The

normal cell cycle contains multiple checkpoints to safeguard

against DNA-damaging agents. Specic proteins at these check-

points are activated in response to harmful stimuli, ensuring

that cellular proliferation, growth and/or division of cells with

damaged DNA are blocked.

There are multiple key mediators of growth inhibition that

may become compromised during carcinogenesis. Some, such

as p53, RB1, and checkpoint kinases cause cells to arrest at the

G1–S phase transition when they are activated by DNA damage.

Mutations in the p53 gene occur in ~50% of all cancers, although

certain tumor types, such as lung and colon, show a higher than

average incidence (295). Similarly, pRb hyperphosphorylation

(296), direct mutations (297), loss of heterozygosity (298) and dis-

ruption of the INK4–pRb pathway (INK4–CDK4/6–pRb–E2Fs) (299)

are common events in the development of most types of can-

cer. Cancer cells may also evade the growth inhibitory signals

of transforming growth factor-β (TGF-β) (300) and modulate the

action of downstream effectors as well as crosstalk with other

pathways.

Cells also receive growth inhibitory signals through intercel-

lular communication via gap junctions. Gap junctions disperse

and dilute growth-inhibiting signals, thereby suppressing cell

proliferation. In contrast, loss of gap junctions increases intra-

cellular signaling, leading to enhanced proliferation and tumor

formation. The molecular components of gap junctions are the

connexin proteins (301). Connexins are recognized as tumor sup-

pressors and have been documented to reduce tumor cell growth.

Numerous environmental stimuli have been reported to directly

affect gap junction intercellular communication. Adherens junc-

tion machinery mediates contact inhibition of growth, and loss

of contact inhibition is a mediator of tumor cell growth.

Chemicals that may contribute to insensitivity to antigrowth

signals through multiple targets of this hallmark are BPA, a

common constituent of everyday plastics, and pesticides such

as DDT, folpet and atrazine. BPA promotes proliferation by dis-

rupting the growth inhibitory signals of p53 and gap junction

communication (171,302). DDT has also been shown to enhance

proliferation by increasing the expression of Ccnd1 (cyclin D1)/

E2f, inducing phosphorylation of pRb, increasing the expression

of p53-degrading protein Mdm2 (a negative regulator of p53)

(162) and disrupting gap-junctional intercellular communica-

tion (163,164). Folpet down-regulates the functions of p53 and

ATM/ATR checkpoint kinases (167) and promotes proliferation,

whereas atrazine shows genotoxic effects at subacute dose on

Wistar rats. Genotoxicity was also associated with increased

transcription of connexin accompanied with increased oxida-

tive stress (303).

Resistance to celldeath

Cell death is an actively controlled and genetically regulated

program of cell suicide that is essential for maintaining tis-

sue homeostasis and for eliminating cells in the body that are

irreparably damaged. Cell death programs include: apoptosis,

necrosis, autophagy senescence and mitotic catastrophe (21).

Defects in these pathways are associated with initiation and

progression of tumorigenesis. Normally, cells accumulate from

an imbalance of cell proliferation and cell death, permissive cell

survival amidst antigrowth signals such as hypoxia and con-

tact inhibition, resistance to the killing mechanisms of immune

cell attack and anoikis resistance (304). Increased resistance to

apoptotic cell death involves inhibition of both intrinsic and

extrinsic apoptotic pathways.

The link between malignancy and apoptosis is exemplied

by the ability of oncogenes, such as MYC and RAS, and tumor

suppressor genes, such as TP53 and RB, to engage both apop-

tosis and the aberrant alterations of apoptosis regulatory pro-

teins such as BCL-2 and c-FLIP in various solid tumors (305). This

variety of signals driving tumor evolution provides the selective

pressure to alter apoptotic programs during tumor development.

Some chemical carcinogens and sources of radiation cause DNA

damage and increase genetic and/or epigenetic alterations of

oncogenes and tumor suppressor genes leading to loss of cel-

lular homeostasis (306). Other signals include growth/survival

factor depletion, hypoxia, oxidative stress, DNA damage, cell

cycle checkpoint defects, telomere malfunction and oncogenic

mutations, and exposure to chemotherapeutic agents and heavy

metals (307,308).

Cancer cells resist apoptotic cell death by up-regulation of

antiapoptotic molecules and the down-regulation, inactivation

or alteration of pro-apoptotic molecules. Activation of p53 usu-

ally induces expression of pro-apoptotic proteins (Noxa and

PUMA) and facilitates apoptotic cell death (309). Antiapoptotic

Bcl-2 family proteins suppress pro-apoptotic Bax/Bak [which

would otherwise inhibit mitochondrial outer membrane perme-

abilization]. Mitochondrial outer membrane permeabilization

releases cytochrome c and triggers apoptosis through an intrin-

sic pathway (310). Thus, regulation of apoptosis can be achieved

by inhibiting the antiapoptotic Bcl-2 family proteins and Bcl-XL

proteins as this restores a cell’s ability to undergo apoptosis. In

the process, mitochondrial outer membrane permeabilization,

mitochondrial proteins (Smac/DIABLO and Omi/HtrA2), which

inhibit the X-linked inhibitor of the apoptosis protein, are leaked

to trigger caspase activity in apoptosis (311,312).

Normal cellular metabolism is important for the sur-

vival of cells, whereas dysregulated metabolism in cells (see

Dysregulated metabolism) can induce either apoptosis or resist-

ance to apoptotic stimuli (313). In the liver, nearly every enzyme

in glycolysis, in the tricarboxylic acid cycle, in the urea cycle, in

gluconeogenesis and in fatty acid and glycogen metabolism is

found to be acetylated, and this N-α-acetylation confers sensi-

tivity to apoptotic stimuli (314). The antiapoptotic protein, Bcl-xL

reduces the efux of acetyl-CoA from the mitochondria to the

cytosol in the form of citrate and decreases N-α-acetylation of

apoptotic proteins, which enables cells less sensitive toward

apoptotic stimuli to mediate cell proliferation, growth and sur-

vival. Thus, N-α-acetylation might be a major factor in overcom-

ing apoptotic resistance in cancer cells (315,316).

Death receptor ligands such as TRAIL—which is bound to

DR4/DR5—induce receptor oligomerization and recruitment of

FADD and caspase-8 to form death-inducing signaling com-

plex, which leads to subsequent cell death via apoptosis. Thus,

expression of death receptors and their decoy receptors (Dcr1/2)

mediates apoptosis in tumor cells (317). When normal cells lose

contact with their extracellular matrix or neighboring cells, they

undergo an apoptotic cell death pathway known as ‘anoikis’

(304). During the metastatic process, cancerous cells acquire

W.H.Goodson et al. | S269

anoikis resistance and dissociate from primary sites, travel

through the vascular system and proliferate in distant target

organs.

A blockage of gap junction intracellular communication

(GJIC) between normal and preneoplastic cells also creates an

intra-tissue microenvironment in which tumor-initiated prene-

oplastic cells are isolated from growth controlling factors of nor-

mal surrounding cells resulting in clonal expansion (318). Gap

junction channels and Cxs control cell apoptosis by facilitating

the inux and ux of apoptotic signals between adjacent cells

and hemi-channels between the intracellular and extracellular

environments, and Cx proteins in conjunction with their intra-

cytoplasmic localization, may act as signaling effectors that are

able to activate the canonical mitochondrial apoptotic pathway

(319).

Several anthropogenic chemicals can affect resistance to cell

death. For example, BPA has been shown to strikingly impair

TP53 activity and its downstream targets, cell cycle regulators,

p21WAF1 and RB, or pro-apoptotic BAX, thereby enhancing the

threshold for apoptosis (172).

Chlorothalonil, a broad-spectrum fungicide that is used on

vegetables, fruit trees and agricultural crops, is considered to be

non-genotoxic but classied as ‘likely’ to be a human carcino-

gen by all routes of exposure (29). In a eukaryotic system, chlo-

rothalonil reacted with proteins and decreased cell viability by

formation of substituted chlorothalonil-reduced glutathione

derivatives and inhibition of specic nicotinamide adenine dinu-

cleotide thiol-dependent glycolytic and respiratory enzymes (320).

Caspases (cysteine-dependent proteases) and transglutaminase

are some of the thiol-dependent enzymes involved in apoptosis,

so inhibition of these thiol-dependent enzymes in tumor-initiated

cells may disrupt apoptotic cell death and aid in tumor survival.

Dibutyl phthalate and diethylhexyl phthalate (DEHP) are

diesters of phthalic acid and commonly referred to as phtha-

lates. In general, mimic the function or activity of the endoge-

nous estrogen 17β-estradiol (E2) and bind to estrogen receptors.

Interestingly, phthalates can mimic estrogen in the inhibition

of TAM-induced apoptosis in human breast cancer cell lines by

increasing intracellular Bcl-2/Bax ratio in breast cancer (321).

Lindane, an organochlorine pesticide, bioaccumulates in

wildlife and humans. Exposure to lindane induces tumor for-

mation in the mouse 42GPA9 Sertoli cell line by disrupting the

autophagic pathway and sustained activation of the mitogen-

activated protein kinase (MAPK)/extracellular signal-regulated

kinase (ERK) pathway (322).

MXC (1,1,1-trichloro-2,2-bis(4-methoxyphenyl)ethane) is a

DDT derivative that was developed after the ban of DDT and

it exhibits antiandrogenic and estrogenic activity. MXC stimu-

lates proliferation and human breast cancer cell growth by the

up-regulation of genes that involve cell cycle (cyclin D1), and the

down-regulation of genes p21 and Bax affecting G1/S transition

and apoptosis, respectively, through ERα signaling (323).

Replicative immortality

Cellular senescence is a state of irreversible arrest of cellular

proliferation characterized by changes in transcription, chro-

matin conformation, cytoplasmic and nuclear morphology,

DNA damage signaling and a strong increase in the secretion of

proinammatory cytokines (324) Senescence is the rst line of

defense against potentially transformed cells (325). Progression

to malignancy correlates with a bypass of cellular senescence.

Thus, senescence inhibits the activation of the tumorigenic

process (325). Senescence has been observed in vitro and in vivo

in response to various stimuli, including telomere shortening

(replicative senescence), oncogenic stress, oxidative stress and

chemotherapeutic agents (326).

Cellular senescence exhibits several layers of redundant

regulatory pathways. These pathways converge to arrest the cell

cycle through the inhibition of CDKs. The best-known effector

pathways are the p16INK4a/pRB, the p19ARF/p53/p21CIP1 and

the PI3K/mammalian target of rapamycin (mTOR)/FOXO path-

ways (327–330), which show a high degree of interconnection.

Additionally, the pRb and the mTOR pathways are two routes

that have been proposed to be responsible for permanent arrest

of the cell cycle (331). More pathways and genes are being dis-

covered, increasing the complexity of our knowledge of this

physiological process (329). Most, if not all of these genes have

been related to human tumorigenesis.

Despite the relevance of senescence as a gatekeeper in the

process of tumorigenesis, there is not a large body of infor-

mation exploring the effect of chemicals on this safeguard.

Little research has been undertaken on chemicals that alter

gene expression regulating senescence and few genes have

been identied (e.g. telomerase, p53, pRb, INK4a) (83,332,333).

Traditional protocols for the assessment of the carcinogenic

risk rely on the detection of tumors induced by agents that

alter many different pathways at the same time (includ-

ing senescence). These agents are mainly unspecic muta-

gens or epigenetic modiers. The effect of some compounds

is being explored including nickel-derived compounds (e.g.

nickel chloride), diethylstilbestrol, reserpine or phenobarbital

(83,334–337).

There may be environmental chemicals that are not muta-

gens or epigenetic modiers, but that target specic proteins on

the senescence pathways and may affect the initiation of tumo-

rigenesis by other compounds allowing senescence bypass. The

contribution of these compounds to the carcinogenesis process

is largely unknown. A few compounds bypass senescence in

this specic manner—acetaminophen, cotinine, nitric oxide,

Na-selenite and lead. Other chemicals known to alter senes-

cence only are mostly unknown (86,88–91,338–341).

Senescence has strong fail-safe mechanisms, and experi-

mental attempts to bypass senescence are usually recognized

as unwanted signals and trigger a senescence response anyway.

However, these conclusions are based on the interpretations of

experimental designs in which acute molecular or cellular alter-

ations are produced. There are few experiments regarding the

effects of chronic, low-dose alterations and even fewer studies

that consider the different cellular and molecular contexts that

can arise over the course of a lifetime.

Dysregulated metabolism

The highly glycolytic cancer phenotype described by Warburg

etal. (25) in the early 20th century determined much of the initial

direction in cancer research (26). Other characteristic metabolic

abnormalities have also been described (25,26,342,343) and have

recently garnered increased attention (344–348). These changes

are neither xed nor specic for cancer (349–351), but the uni-

versality of metabolic dysregulation suggests major roles in can-

cer genesis, maintenance and progression. Precise denitions of

what constitutes cancer metabolism, and when such changes

rst occur during the course of cancer development, are lacking.

From a teleological perspective, alterations in both intermediary

metabolism and its control are not surprising insofar as highly

proliferative cancer cells exhibit increased energy demands

and expanded requirements for macromolecular precursors to

S270 | Carcinogenesis, 2015, Vol. 36, Supplement 1

support nucleic acid and protein biosynthesis, as well as mem-

brane biogenesis, for increased biomass. Metabolic reprogram-

ming ostensibly equips cancer cells to cope with these demands,

as well as accompanying cellular stresses. Although much of

the attention on cancer metabolism has focused on enhanced

glucose utilization via glycolytic and pentose phosphate path-

ways, cancer cells are also capable of the oxidative utilization of

carbohydrates, lipids and peptides, and the metabolism of these

individual substrate classes remain intimately intertwined as in

normal cells (26,345,352).

Major control of glycolysis is traditionally ascribed to glu-

cose transport, hexokinase, phosphofructokinase and pyru-

vate kinase (352). Glyceraldehyde-3-phosphate dehydrogenase

also normally couples glycolytic ux to mitochondrial metabo-

lism in the presence of oxygen and to lactate generation in its

absence, but this relationship is fundamentally altered in can-

cer (26,345,353,354). Given the central importance of the pen-

tose phosphate pathway to anabolic metabolism and redox

homeostasis, glucose-6-phosphate dehydrogenase and its redox

coupling partners represent similarly attractive carcinogenic

targets (355). In addition, the enzymes of the tricarboxylic acid

cycle, such as fumarate hydratase, succinate dehydrogenase

and isocitrate dehydrogenase, play crucial roles in oxidative

energy metabolism and the interconversion of metabolic inter-

mediates, making them appealing candidates for study as well

(356,357).

The central importance of the mitochondrial electron trans-

port chain to oxidative energy metabolism and its established

role in toxic responses and dysregulated mitochondrial func-

tion in cancer makes its assembly and function attractive topics

for study (358–360). Despite well-established roles for lipid and

amino acid metabolism in cancer development and progression,

they have historically received less attention than carbohydrate

metabolism (26). Lipogenic, lipolytic and lipophagic pheno-

types are now widely recognized (344,361–363), so targets such

as acetyl-CoA carboxylase, fatty acid synthase, cellular lipases

and lipid transporters represent additional attractive targets

for study. Amino acid metabolism—particularly glutamine and

serine metabolism—also has well-established roles in cancer

(364–366), providing additional potential targets for study that

include 3-phosphoglycerate dehydrogenase (346,365,367,368)

and cellular transaminase coupling mechanisms. Study of

both lipid and protein metabolism must accommodate the fact

that cancer cells exhibit substrate preferences, including well-

described endogenous lipid- and protein-sparing effects of

exogenous glucose availability in cancercells.

The metabolic capacity of both normal cells and cancer cells

generally exceed their catabolic and anabolic requirements

(364,369,370), and only a fraction of the available potential energy is

ultimately required for cell survival (371,372). Moreover, very small

changes in metabolic ux can have profound phenotypic conse-

quences, and metabolic control analysis has suggested that the

importance of increased cancer-associated glycolytic and glutami-

nolytic uxes may lie not in their magnitudes, but in the mainte-

nance and control of smaller branched pathway uxes (364). For

these reasons, rigorous functional validation is needed for all can-

cer-associated changes in gene expression or metabolite accumu-

lation. Well-described moonlighting functions for many metabolic

enzymes (373–375), including the novel antiapoptotic roles of mito-

chondrial hexokinases (376), cannot be simply extrapolated from

our knowledge of classical roles in cellular metabolism.

These enzymes and their pathways constitute broad cat-

egories of potential targets for disruption that could serve to

enable the observed metabolic phenotypes of cancer cells (377).

Although metabolic control is broadly distributed over all indi-

vidual steps for a given pathway (352,378), the most obvious

targets for conceptual and experimental scrutiny involve major

rate-controlling elements of pathways capable of supporting the

anabolic and catabolic needs of rapidly proliferating cancercells.

Numerous studies have demonstrated cancer-associated

changes in metabolism or related gene expression (26). We

looked at acrolein, copper, cypermethrin, diazinon, hexythi-

azox, iron, malathion and rotenone as chemicals that had been

reported to show relevant disruptive potential (51,379–383);

however, the toxicological data that are available for many

suspected or known environmental disruptors, generally lacks

mechanistic information regarding their potential roles as

determinants of the observed metabolic hallmarks of cancer.

Even prior metabolic screening platforms, including tetrazolium

reduction assays, have limited specicity and can be profoundly

inuenced by experimental screening conditions. Unfortunately,

standardized chemical screening has typically not been con-

ducted under controlled or limiting substrate conditions that

would directly inform our understanding of the functional rel-

evance of observed changes. None have established unambigu-

ous causal relationships between specic chemical exposures

and the parallel or sequential development of dysregulated

metabolism of cancer in the same model, and most observed

changes in gene expression with potential relevance to cancer

metabolism have not been accompanied by validating func-

tional studies.

Angiogenesis

Angiogenesis, the process of formation of new blood vessels

from existing blood vessels, is a critical process for normal organ

function, tissue growth and regeneration (e.g. wound healing,

female menstruation, ovulation and pregnancy) as well as for

pathological conditions (e.g. cancer and numerous non-cancer-

ous diseases, such as age-related macular degeneration, dia-

betic retinopathy, rheumatoid arthritis, endometriosis, diabetes

and psoriasis) (384,385).

Tumor angiogenesis is an early critical event for tumor

development: Atumor cannot grow beyond 1 mm3 (by estimate)

without angiogenesis (386). Tumor growth, invasion and metas-

tasis depend on blood vessels and neovascular development

to provide nutrients, oxygen and removal of metabolic waste

as tumors grow in primary sites, invade adjacent tissues and

metastasize to distant organs (387,388). Inhibition or eradication

of tumor angiogenesis by antiangiogenic inhibitors (389,390) or

by antineovascular agents (such as vascular-disrupting agents

(391–393) and fVII/IgG Fc (394), the latter also called ICON (395–

397)) can treat pathological angiogenesis-dependent diseases,

including cancer and many non-cancerous diseases.

Under physiological conditions, angiogenesis is well bal-

anced and controlled by endogenous proangiogenic factors

and antiangiogenic factors. Factors produced by cancer cells

can shift the balance to favor tumor angiogenesis. Such factors

include vascular endothelial growth factor (VEGF) and tissue

factor (TF). VEGF, one of the most potent proangiogenic factors

produced by cancer stem cells and cancer cells, binds to vascular

endothelial cells via its receptor VEGFR, initiating VEGF/VEGFR

intracellular signal transduction pathways and activating many

gene transcriptions and translations toward angiogenesis. TF

is a transmembrane receptor (398) not expressed on quiescent

endothelial cells (399,400). Upon stimulation of VEGF, TF is selec-

tively expressed by angiogenic endothelial cells, the inner layer

of the tumor neovasculature. Thus, TF is a specic biomarker

for tumor angiogenesis (408–410). Both of the membrane-bound

W.H.Goodson et al. | S271

receptors VEGFR and TF can mediate separate intracellular sign-

aling pathways that contribute to tumor angiogenesis.

Environmental exposures can promote tumor development,

but the role of chemicals in tumor angiogenesis, particularly the

role of low-dose non-carcinogens, is largely unknown. Some food-

use pesticides that are non-genotoxic act as tumor promoters,

and other chemicals affect various hallmarks such as apoptosis,

proliferative signaling, evading growth suppression, enabling

replicative immortality, metastasis, avoiding immune destruc-

tion, tumor-promoting inammation and deregulating cellular

energetics—in addition to tumor angiogenesis.

Chemical disruptors that may promote tumor angiogenesis

included diniconazole, 2,2-bis-(p-hydroxyphenyl)-1,1,1-trichlo-

roethane (HPTE), methylene bis(thiocyanate), peruorooctane

sulfonate (PFOS), Ziram, biphenyl, chlorothalonil, tributyltin

chloride and bisphenol AF. Diniconazole (pesticide), for exam-

ple, targets certain angiogenic molecules (CXCL9, CXCL10,

MMP1, uPAR, VCAM1 and THBD) in vitro (29). MXC (the parent

compound to HPTE) induces histological expression of angio-

genic factors such as VEGF, VEGFR2 and ANG1 in rat pituitary

and uterus (39), and exposure to PFOS induces actin lament

remodeling, endothelial permeability changes and ROS produc-

tion in human microvascular endothelial cells (41). Ziram can

induce angiogenesis through activation of MAPK and decreases

cytolytic protein levels in human natural killer (NK) cells

(404,405).

Tissue invasion and metastasis

Tissue invasion and metastasis are also key processes of tumor

progression. In normal cells, E-cadherin holds the epithelial

cells together as a society of cells that are well differentiated

and otherwise quiescent (406). Carcinomas constitute almost

90% of cancers and upon oncogenic transformation, the process

of tissue invasion and metastasis begins with the down-regu-

lation of E-cadherin. Concomitant with this down-regulation of

E-cadherin is the conversion of epithelial to mesenchymal cells

(EMT) (407). The transcription factors that control EMT, such as

snail, slug, Twist and Zeb1/2, are some of the best-character-

ized signaling molecules in biology (408,409). During the pro-

cess of EMT, a number of inammatory cells are attracted to

the growing tumor mass (410). Upon attaining mesenchymal

characteristics, tumor cells are able to move out of their natu-

ral environment, aided by cross talk between them and stromal

cells, resulting in the secretion of matrix degrading enzymes

such as matrix metalloproteinases (411). This process is accel-

erated by chronic inammation mediated by NF-κB (410). Other

invasion mediating molecules include hepatocyte growth fac-

tor, secreted mainly by tumor-associated broblasts to signal

metastatic cells to move upon their interactions with their cell

surface receptor cMet (412).

Attracted by chemokines, metastatic cells move to the near-

est blood vessel or lymphatic vessel, where they complete the

process of intravasation, entering the capillaries and are then

transported to the capillary bed in their colonized site or new

environment (413). In this new location, tumor cells undergo

extravasation where they come out of the capillaries or lym-

phatic vessels, most likely again following the cues emanat-

ing from the chemokines in their new microenvironments. To

survive in their new home, they may have to revert back and

assume the cuboidal morphology of epithelial cells-undergo-

ing the reversal of EMT otherwise known as mesenchymal to

epithelial transition (414). At this point, they may remain dor-

mant for a very long time until conditions for their division and

growth become favorable.

Mounting evidence supports the involvement of exosomes

(nano-vesicles secreted by tumor or cancer-associated bro-

blasts) in adhesion and motility of metastatic cells. The secretion

of exosomes is accelerated by increases in intracellular cal-

cium ions, and low-dose environmental mixtures that increase

intracellular calcium may promote the secretion of exosomes

and the subsequent invasion and metastasis processes of the

tumorcells.

Environmental chemicals, such as tetrabromobisphenol

Aand its metabolites, BPA and tetrabromobisphenol Adimethyl

ether, which mediate the activation of EMT enzymes or drive

their synthesis, may also contribute to the process of tissue

invasion (415). Low-dose exposure to hexavalent chromium may

accelerate the EMT transition (416). Other contributing factors

may also be low-dose environmental contaminants, such as for-

maldehyde, or bacteria, e.g. H.pylori, that drive the transcription

of NF-κB and exacerbate the process (417,418).

Tumor microenvironment

The tumor microenvironment is a complex mix of cells in addi-

tion to tumor cells themselves; it is constructed of a complex

balance of blood vessels that feed the tumor, the extracellu-

lar matrix that provides structural and biochemical support,

signaling molecules that send messages, soluble factors such

as cytokines and many other cell types. Tumors can inuence

the microenvironment and vice versa. The micro-environmental

reaction to early tumor cells begins with the recruitment and

activation of multipotent stromal cells/mesenchymal stem cells,

broblasts, endothelial cell precursors, antigen-presenting cells

such as dendritic cells (DCs) and other white blood cells. All of

these tumor stromal cells secrete a variety of growth factors and

chemokines that, together with the tumor cells and secreted

factors, culminate in the generation of the tumor microenviron-

ment (419–422).

The tumor microenvironment is important because any cell

within this process has the potential to be affected by carcino-

gens, either alone or in mixtures, or by the inammation that

results from the carcinogenic insult (423). Although often asso-

ciated with infection, chronic inammation can be caused by

exposure to carcinogens such as irradiation or environmental

chemicals. Carcinogenesis can also be fostered via effects on the

tissue context surrounding preneoplastic lesions. For example,

transplantation experiments of preneoplastic cells have clearly

documented that a growth-constrained tissue microenviron-

ment can promote the growth and progression of preneoplastic

cell populations (424).

Several compounds appear to inuence the complex het-

erogeneity that forms the support network for cancer growth.

The exposure to nickel chloride has been associated with the

generation of ROS and inammation (425). ROS are impor-

tant because they can stimulate the induction of angiogenesis

growth factors, such as VEGF, and can promote cell proliferation

and immune evasion and play a role in cell survival (57,426–428).

Prenatal exposure to BPA in experimental animals disrupts ERα

and triggers angiogenesis, and other BPA exposure studies have

demonstrated that BPA interplays with cell proliferation (226),

genomic instability (429), inammation (430) and cell immor-

talization (431). Butyltins, and specically tributyltin, which is

suspected to act as an endocrine disruptor, have been found

to inhibit the cytotoxic activity of NK cells (432), affect inam-

mation (432) and disrupt membrane metalloproteinases (432).

Cooperatively, disruption of these processes can lead to prolif-

eration, migration and angiogenesis. Methylmercury (MeHg) is a

S272 | Carcinogenesis, 2015, Vol. 36, Supplement 1

neurotoxic compound deriving from metallic mercury through

bacteria-supported metabolism in an aquatic environment.

Bio-concentration in sh and shellsh poses a risk for sensi-

tive population categories such as pregnant women and infants.

MeHg-induced ROS production may be involved in inamma-

tion and apoptosis (433) as well as endothelial cell cytotoxicity

(434). We also looked at paraquat, which may also have rele-

vance for the tumor microenvironment via its role in oxidative

stress (435,436).

Avoiding immune destruction

The concept of immune surveillance suggests that the host

immune system could identify tumor cells and destroy them.

If this is true, tumor cells need to be poor stimulators of or

challenging targets for the host immune system. To provide

an effective immune response, multiple types of the cells are

involved within innate and adaptive immune ‘arm’ with some

cells (e.g. DCs and the NK cells) ‘bridging’ these two types

of immunity (437). To avoid a strong immune response of the

host, the expression of tumor antigens may be down-regulated

or altered (resulting in decreased or impossible recognition of

malignant cells) (438) and various soluble factors and cytokines

may be released resulting in subverted effectiveness of antitu-

mor immune response (439–441). Tumor cells can also escape

host immune response by inducing apoptosis in activated T

cells (442).

Multiple genes involved in immune evasion mechanisms

and, therefore, can interfere with chemical exposures from

anthropogenic environment: ADORA1 (adenosine A1 receptor),

AKT1 (v-akt murine thymoma viral oncogene homolog 1), CCL2

(chemokine C-C motif ligand 2), CCL26 (chemokine C-C motif

ligand 26), CD40, CD69, COL3A1 (type III collagen of extracellu-

lar matrix), CXCL10 (also called interferon-inducible protein-10),

CXCL9 (monokine induced by interferon-γ), EGR1 (early growth

response protein 1), HIF-1α (hypoxia-inducible factor), IGF1R

(insulin-like growth factor 1 receptor) and interleukins (IL) such

as IL-1α and IL-6. Based on available studies, several candi-

date signaling pathways that are related to the host immune

response can be identied for further study; e.g. the pathways

involving PI3K/Akt, chemokines, TGF-β, FAK, IGF-1, HIF-1α, IL-6,

IL-1α, CTLA-4 and PD-1/PDL-1.

Biologically disruptive environmental chemicals can affect

the host immune responses as follows: (i) if a certain chemical

is immunotoxic, and, in particular, if it affects activity of DCs, T

cells or NK cells, it is also likely to affect tumor immuno-surveil-

lance and enable malignant growth to proceed; (ii) if a chemi-

cal targets the immune system, it can increase the cancer risk

related to other factors/exposures; (iii) exposures to certain tox-

ins or toxicants can dramatically increase the number of can-

cerous cells and impact immuno-regulatory signals suppressing

the mechanisms of immune control. Collectively, these sorts of

actions suppress the immune system, so it cannot be effectively

stimulated and cannot eliminate tumor cells, thus allowing

some tumor cells to escape and metastasize.

We looked at several groups of environmentally ubiqui-

tous chemicals such as pesticides and personal care products

that might potentially interrelate with mechanisms of tumor

immuno-surveillance. Although none of them are recognized as

human carcinogens (443–445), the research on these chemicals

and their interactions with the immune response may be valu-

able. For example, the fungicide maneb is a cortisol disruptor

(446) that has shown a wide spectrum of potential effects on

multiple pathways, including some that are relevant to immune

evasion (139,156–158,447). By comparison, pyraclostrobin and

uoxastrobin (448) interfere with a narrower spectrum of can-

cer hallmarks (36,449–452). Atrazine has also shown potential

to impact immune system evasion by directly targeting matura-

tion of DCs and decreasing the levels of major histocompatibility

complex classImolecules (243,453). The insecticides pyridaben

and azamethiphos can also both be disruptive to immuno-sur-

veillance (139,140,454,455).

Commonly used in personal care products, triclosan and BPA

(456), are endocrine disruptors (457–459) that are often detected

in waters downstream in urban areas (460,461). In addition to

immune evasion mechanisms (36,142,145), they interfere with

wide spectrum of cancer-related mechanisms (36,173,429,462–

464). DEHP (472) is also an endocrine disruptor (466,467) that can

impact multiple hallmarks such as immune evasion, resistance

to cell death, evasion of antiproliferative signaling, sustained

proliferative signaling and tumor-promoting inammation

(36,288,468,469).

Knowing whether or not cumulative low-dose exposures to

these chemicals interfere with the host immune response can

help to stimulate further studies (e.g. on screening of lesions at

the pre-malignant stage of tumor development) to determine

the inuence of such exposures on host immunity and to evalu-

ate their potential to increase the risk of tumor cell survival.

Dose-response characterizations andLDE

For all the chemicals selected and target sites for disruption that

were identied, dose-response characterization results and/or

relevant low-dose research evidence were reviewed and catego-

rized using the criteria mentioned in the Materials and meth-

ods. Table1 sets out these results and the supporting references.

In total, 85 examples of environmental chemicals were

reviewed (for specic actions on key pathways/mechanisms that

are important for carcinogenesis) and 59% of them (i.e. 50/85)

were found to exert LDE (at levels that are deemed relevant given

the background levels of exposure that exist in the environment)

with 15 of the 50 demonstrating their LDE in a non-linear dose-

response pattern. Indeed, all of the teams selected at least one or

more disruptive chemicals that exerted their effects on the tar-

get sites at low-dose levels. In contrast, only 15% of the chemicals

reviewed (i.e. 13/85) showed evidence of a threshold.

The remaining 26% of the chemicals reviewed (i.e. 22/85)

were categorized as ‘unknown’. Some of these chemicals (5 of

the 22) had been tested using human primary cell data from

ToxCast and had showed statistically signicant activity across

a full range of doses against the specied targets (i.e. they

were active even at the lowest test concentrations of ~0.01µM).

However, even though no threshold could be discerned for these

chemicals, we did not characterize them as having LDE (because

it was not clear that the lowest test concentrations were low

enough to be equated to levels of exposure that are normally

seen in the environment).

Evidence of cross-hallmark relationships

Teams then evaluated the chemicals selected and target sites for

disruption for known effects on the other cancer hallmark path-

ways. Evidence in the literature that showed procarcinogenic

actions or anticarcinogenic actions in other hallmark areas were

reported, and in instances where no literature support was found,

this was documented as well. The same approach was used for

the chemicals that were reviewed. Asample of these cross-hall-

mark results is provided in Table 2—Sample of cross-hallmark

relationships of target pathways/mechanisms and in Table 3—

Cross-hallmark relationships of selected chemical disruptors.

W.H.Goodson et al. | S273

Table2. Sample of cross-hallmark relationships of target pathways/mechanisms

Insensitivity to antigrowth signals (targets) Antigrowth Dysreg metab Gen instab Angio Cell death Immun Immort Prolif Metas Inamm Tumor micro PRO ANTI MIX

p53 n/a +/− - +/− − +/− − − − + + 2 5 3

pRB n/a +/− − − − 0 − − − + + 2 6 1

TGF-βn/a + − + − + − + + + + 7 3 0

LKB1 n/a + − + +/− 0 0 + − + + 5 2 1

Connexins n/a − − 0 0 0 0 − +/− + + 2 3 1

Contact inhibition n/a +/− − 0 0 + 0 − − + − 2 4 1

One set of results (from the insensitivity to antigrowth signals review) is shown here without references to support a discussion on the range of effects that have been reported for the selected targets in each article. Specic

references supporting these effects for any given hallmark area can be found in the individual reviews within this special issue. Cross-hallmark relationships are reported in the rst 11 columns of the table—table

heading abbreviations are as follows:gen instab, genetic instability; dysreg metab, dysregulated metabolism; antigrowth, insensitivity to antigrowth signals; angio, angiogenesis; cell death, resistance to cell death; immun, avoid-

ing immune destruction; immort, replicative immortality; prolif, sustained proliferative signaling; metas, tissue invasion and metastasis; inamm, tumor-promoting inammation; tumor micro, tumor microenvironment. The

number of procarcinogenic (PRO), anticarcinogenic (ANTI) and mixed (MIX) (i.e. procarciniogenic and anticarcinogenic reports) cross-hallmark relationships for each target have been summed and are reported in the last three

columns of the table. Target pathways/mechanisms for each hallmark area were evaluated by each team for known effects in other cancer hallmark pathways. Targets that were found to have anticarcinogenic actions in another

hallmark area were indicated with ‘−’, whereas targets that were found to have procarcinogenic actions in another hallmark area were indicated with ‘+’. In instances where reports on relevant actions in other hallmark areas

were mixed (i.e. reports showing both procarcinogenic potential and anticarcinogenic potential), the symbol ‘+/−’ was used. Finally, in instances where no literature support was found to document the relevance of a target in a

particular aspect of cancer’s biology, we documented this as ‘0’.

Table3. Cross-hallmark relationships of selected chemical disruptors

Insensitivity to antigrowth signals (disruptors) Antigrowth Dereg metab Gen instab Angio Cell death Immun Immort Prolif Metas Inamm Tumor micro PRO ANTI MIX

BPA n/a + + + +/− 0 + + + + 0 7 0 1

DDT n/a 0 + + + + + + 0 + 0 7 0 0

Folpet n/a 0 + 0 + 0 0 + 0 + 0 4 0 0

Atrazine n/a 0 + 0 0 0 0 + 0 + 0 3 0 0

table heading abbreviations are as follows:gen instab, genetic instability; dereg metab, dysregulated metabolism; antigrowth, insensitivity to antigrowth signals; angio, angiogenesis; cell death, resistance to cell death; immun,

avoiding immune destruction; immort, replicative immortality; prolif, sustained proliferative signaling; metas, tissue invasion and metastasis; inamm, tumor-promoting inammation; tumor micro, tumor microenvironment.

The number of procarcinogenic (PRO), anticarcinogenic (ANTI) and mixed (MIX) (i.e. procarciniogenic and anticarcinogenic reports) cross-hallmark relationships for each target have been summed and are reported in the last

three columns of the table. Prototypical chemical disruptors selected by each team were evaluated for reported actions in other cancer hallmark pathways. Disruptors that were found to have anticarcinogenic actions in a

particular hallmark area were indicated with ‘−’, whereas disruptors that were found to have procarcinogenic actions in a particular hallmark area were indicated with ‘+’. In instances where reports on relevant actions in other

hallmarks were mixed (i.e. reports showing both procarcinogenic potential and anticarcinogenic potential), the symbol ‘+/−’ was used. Finally, in instances where no literature support was found to document the relevance of a

chemical in a particular aspect of cancer’s biology, we documented this as ‘0’. Specic references supporting these effects for any given area can be found in the individual reviews in this special issue.

S274 | Carcinogenesis, 2015, Vol. 36, Supplement 1

Table4. Aggregated evidence of cross-hallmark effects for selected pathways/mechanisms

Key targets Originating review Procarcinogenic Anticarcinogenic Mixed

Adenosine A1 receptor (ADORA1) ISE 3 1 0

AhR Ang 7 0 2

SPS 7 0 2

Bcl-2/p53 RCD 6 2 1

Cell cycle/cell division: spindle defect GI 6 0 1

Checkpoint kinase 1 and checkpoint kinase 2 (Chk1/2) EAS 4 3 1

Chemokine (C-C motif) ligand 2 (CCL2) Ang 8 1 0

Chemokine (C--XC motif) ligand 10 (CXCL10) Ang 4 1 1

Chemokine (C--XC motif) ligand 9 (CXCL9) Ang 3 2 0

Chemokine signaling pathway (CCL2, CCL26, CXCL9, CXCL10) ISE 6 1 2

Chronic oxidative stress TM 6 1 1

Clock-genes-mediated metastasis TIM 5 1 0

Collagen type III (COLIII) Ang 3 0 0

Contact inhibition EAS 4 3 0

cSrc/Her1/STAT5B/ERK1/2 TIM 3 1 1

Cyclin D, IL8, CXCL SPS 4 0 2

Cyclooxygenase expression and stimulation calcium signaling in migration. TIM 8 1 0

Cyclooxygenase-2 TPI 8 1 0

DNA damage signaling: disturbed by Redox signaling (NF-κB, Nrf, EGR) GI 8 1 0

DNA repair pathways GI 6 2 1

Eck fatty acid metabolism DM 6 1 2

Electron transport chain complexes II and IV DM 3 2 0

Epidermal growth factor receptor SPS 6 0 1

Epigenetic pathways

Disturbed miRNA binding GI 6 0 2

DNA methylation GI 7 0 1

Histone acetylation GI 6 1 1

EMT TIM 5 0 1

EMT, catenin-Wnt pathway TIM 6 1 1

ErbB-2/HER-2 tyrosine kinase RCD 6 1 0

ERK/MAPK RCD 8 2 0

Estrogen receptor TPI 5 3 1

Estrogen receptor α (binding to) RCD 5 1 1

Gap junction connexins EAS 2 2 2

GJIC RCD 2 1 1

Gluconeogenesis DM 5 3 0

Glycolysis DM 8 1 0

Hexokinase 2 DM 6 1 0

H-Ras SPS 6 1 2

Hypersecretion of luteinizing hormone by gonadotroph cells in pituitary gland RCD 2 1 0

HIF-1-α pathway ISE 8 0 2

Inducible nitric oxide synthase TPI 6 1 0

IGF-1 signaling pathway ISE 6 2 1

Intercellular adhesion molecule 1 (ICAM1) Ang 6 3 0

W.H.Goodson et al. | S275

Key targets Originating review Procarcinogenic Anticarcinogenic Mixed

IL-6 TPI 7 0 0

IL-6 expression, improper DC maturation and polarization TM 5 2 0

Jun/Fos/AP1 SPS 4 1 3

Lipid metabolism/cholesterol metabolism DM 4 2 1

Liver kinase B1 (Lkb1) EAS 4 2 2

MMP 1 Ang 6 1 0

MMP-9 activation TIM 5 1 1

Mitochondrial function GI 5 2 2

MAPK RCD 9 0 1

mTOR activation DM 7 1 1

mTOR inactivation RI 3 6 1

NK cell inhibition TM 4 3 0

NF-κB TPI 4 2 0

Oxidative stress and IL-6 production TM 3 1 1

P16/p53 RCD 4 4 0

P53 inactivation EAS 10 0 0

RCD 10 0 0

RI 10 0 0

PPAR SPS 5 2 0

PPAR-αRCD 3 3 1

PI3K/Akt signaling pathway ISE 9 0 1

Pyruvate dehydrogenase (PDH) DM 1 5 0

ROS (increase) DM 6 0 4

ROS and cellular stress TM 5 0 4

Retinoblastoma protein (pRb) inactivation EAS 9 0 0

RI 9 0 0

Steroid hormone receptors SPS 5 0 1

Telomerase activation RI 9 1 0

Telomere loss GI 4 4 0

The tricarboxylic acid cycle DM 5 4 0

Thrombomodulin Ang 2 3 0

Transforming growth factor βEAS 6 3 1

Tumor necrosis factor αTPI 8 0 1

Urokinase receptor (uPAR) Ang 6 2 0

Vascular cell adhesion molecule 1 (VCAM1) Ang 6 0 0

Aggregated number of procarcinogenic actions, anticarcinogenic actions and instances where mixed actions (i.e. procarciniogenic and anticarcinogenic) where cross-hallmark effects have been reported (for each pathway/

mechanism across the full range of hallmark domains—i.e. from all of the areas covered by the reviews in this special issue)—see samples of this data in Table2. Note: fully referenced data for these cross-hallmark effects can

be found in each of the reviews in this special issue. ANG, angiogenesis; DM, dysregulated metabolism; EAS, evasion of antigrowth signaling; GI, genetic instability; ISE, immune system evasion; RCD, resistance to cell death; RI,

replicative immortality; SPS, sustained proliferative signaling; TIM, tissue invasion and metastasis; TM, tumor microenvironment; TPI, tumor-promoting inammation.

Table4. Continued

S276 | Carcinogenesis, 2015, Vol. 36, Supplement 1

Note that Tables 2 and 3 contain just a single set of unref-

erenced results from the review on the hallmark insensitivity to

antigrowth signals. This is intended only to illustrate the catego-

ries of cross-hallmark effects that were reviewed and to show

how they were presented. Fully referenced results for each hall-

mark area can be found in each of the individual reviews within

this specialissue.

The decision to review target sites for disruption and proto-

typical disruptors for cross-hallmark effects was driven by the

fact that many individual studies and reviews of chemical expo-

sures fail to account systematically for the spectrum of inci-

dental actions that can result from exposures to a single given

chemical. It was our belief that this approach constitutes a bet-

ter way to ensure that we had assembled a reasonably complete

view of the literature (i.e. where any sort of evidence of cross-

hallmark activity had been reported). Future research will likely

involve empirical testing of mixtures, so we wanted to create a

heuristic that could serve as a starting point for other research-

ers who might be considering such research.

For researchers focused on low-dose exposure research

intended to produce carcinogenesis, we anticipated that there

would be interest in chemicals that had been reported to exhibit

a large number of procarcinogenic actions across a number of

hallmarks and we anticipated that a lack of anticarcinogenic

potential would be important to identify (as targets or approaches

that exert anticarcinogenic actions would potentially represent

a confounding inuence/factor in empirical research aimed at

the identication of carcinogenic synergies). To that end, Table4

provides a summary of the aggregated number of procarcino-

genic actions, anticarcinogenic actions and instances where

mixed actions (i.e. procarciniogenic and anticarcinogenic) have

been found for each pathway/mechanism (across the full range

of hallmark domains—i.e. from all of the areas covered by the

reviews in this special issue). Similarly, Table5 provides a sum-

mary of the aggregated number of procarcinogenic actions,

anticarcinogenic actions and mixed actions (i.e. procarcinogenic

and anticarcinogenic), where cross-hallmark effects have been

reported for each chemical (across the full range of hallmark

domains—i.e. from all of the areas covered by the reviews in this

special issue).

Note that, in some instances, the underlying evidence used

to support the indication of cross-hallmark relationships was

robust, consisting of multiple studies involving detailed in-vitro

and in-vivo ndings. In other instances, the underlying evidence

that was used to report the existence of a cross-hallmark rela-

tionship was quite weak (e.g. consisting of only a single in-vitro

study involving a single cell-type). The selected prototypical dis-

ruptors are likely biased towards agents that have been exten-

sively studied, and not necessarily those that will prove to be

the most important biologically. Finally, there are examples of

chemicals that are known to exert different effects at different

dose levels, but dose levels were not used to discriminate when

gathering evidence of cross-hallmark effects. So, the referenced

cross-validation results in the individual tables (reported in the

many reviews within this special issue) should be seen only as

a starting point for those who are pursuing mixtures research

(e.g. references would need to be further scrutinized to deter-

mine whether or not the dose levels noted for specic results

are suitable points of reference for the type of research that is

being undertaken).

Particular attention should also be given to results related to

the endocrine system due to mechanistic complexity. For exam-

ple, xeno-estrogen compounds are typically compared with

estradiol based on binding afnity strength. However, many

xeno-estrogens that are ‘weak’ by this measure can alter the

steroidogenic cascade (e.g. signicantly up-regulate the activ-

ity of P450 aromatase, the enzyme that increases intracellular

estradiol synthesis within estrogen-sensitive cells (470–473) or

alter levels of ERα or the ratio of ERα:ERβ (260)). In other words, a

weak xeno-estrogen can stimulate the production of estradiol, a

potent endogenous carcinogen (474) or alter the receptors with

which a cell will respond to estrogen.

Nonetheless, given that the overarching goal in this project

was to create a foundation that would allow researchers to look

systematically across the literature in each of these areas, the

tables should serve as a useful starting point as long as they

are approached with these caveats in mind. We believe that

this heuristic will be useful to consider synergies that might be

anticipated in testing that involves certain target sites for dis-

ruption and/or mixtures of chemical constituents that are being

considered for procarcinogenic effects. Future research efforts

to improve this approach could involve a large-scale collabora-

tive effort to generate high-quality in-vitro data and low-dose in-

vivo data in a range of predened tissues.

Discussion

Getting to Know Cancer hosted the initial project meeting in

Halifax, Nova Scotia giving participants an opportunity to have

presentations, break-out sessions, and chances for conversation

and debate among experts who came from a range of different

disciplines. Cancer biologists with specialized expertise in areas

related to individual hallmarks met with specialists from other

areas such as environmental health, toxicology and endocrinol-

ogy. Although some researchers in the eld of environmental

health are cancer scientists in their own right, many conference

participants commented on the novelty of having an oppor-

tunity to work so closely with cancer biology specialists. As a

result, many interdisciplinary barriers were removed and the

discussions that ensued were challenging but productive.

At the outset, participants overwhelmingly agreed that the

Hallmarks of Cancer provides a useful organizing heuristic for

systematic review of ways that biologically disruptive chemicals

might exert procarcinogenic and anticarcinogenic inuences in

biological systems. Most of the individual writing teams were

then readily able to identify ubiquitous environmental contami-

nants with disruptive potential in their respective areas of study.

The only teams that had signicant challenges in this regard

were the ones that focused on the bypassing of senescence (i.e.

replicative immortality) and dysregulated metabolism, both being

areas of cancer research that have not yet received a lot of atten-

tion from researchers in the eld of toxicology.

Considerable discussion was devoted to the criteria that

were used to select prototypical disruptors from the long list of

known potential contaminants. Indeed, it seems that much of

the population is now exposed to a wide variety of exogenous

chemicals that have some disruptive potential, but we did not

have any intention of implicating any of the selected chemicals

as being carcinogenic per se. It was simply agreed that chemi-

cals would be chosen that met the basic criteria and that then

could be used as ‘prototypical’ disruptors. In other words, the

chemicals that were selected for this review were not deemed to

be the most important, and they were not selected to somehow

imply (based on current information) that they are endanger-

ing us. Rather, we simply wanted to illustrate that many non-

carcinogenic chemicals (that are ubiquitous in the environment)

have also been shown to exert effects at low doses, which are

highly relevant to the process of carcinogenesis. We also wanted

W.H.Goodson et al. | S277

Table5. Aggregated evidence of cross-hallmark effects for selected chemical disruptors

Chemicals Originating review Procarcinogenic Anticarcinogenic Mixed

12-O-Tetradecanoylphorbol-13-acetate SPS 5 1 0

HPTE ANG 4 0 0

Acetaminophen RI 0 4 2

Acrolein DM 3 3 3

Acrylamide GI 3 1 1

Atrazine ISE 3 0 1

EAS 4 0 1

TPI 3 0 1

Azamethiphos ISE 1 0 0

Benomyl GI 0 3 1

Benzo(a)pyrene SPS 8 1 0

Biorhythms TIM 3 2 0

Biphenyl ANG 2 2 1

BPA EAS 6 0 1

GI 6 0 1

ISE 7 0 1

RCD 7 0 0

SPS 6 0 1

TIM 7 0 1

TM 7 0 1

TPI 6 0 1

Bisphenol AF ANG 5 1 0

Butyltins (such as tributyltin) TM 4 2 0

C.I.solvent yellow 14 ANG 4 0 0

Carbendazim GI 0 2 1

Carbon black GI 5 1 0

Chlorothalonil ANG 5 1 0

RCD 5 0 0

Cobalt GI 5 2 0

Copper DM 6 0 3

Cotinine RI 4 1 0

Cypermethrin DM 5 0 0

DDT EAS 6 0 0

Diazinon DM 2 3 0

Dibutyl phthalate RCD 4 0 0

Dichlorvos RCD 4 0 0

DEHP ISE 4 0 1

RCD 4 0 0

Diniconazole ANG 2 0 0

Fluoxastrobin ISE 2 1 0

Folpet EAS 2 1 0

Hexachlorobenzene TIM 5 2 0

Hexythiazox DM 0 0 0

Imazalil SPS 3 1 0

Iron DM 5 1 3

TIM 5 1 2

Lactofen SPS 2 0 0

Lead GI 3 1 0

RI 3 1 0

Lindane RCD 5 0 0

Linuron RCD 2 0 0

Malathion DM 5 0 0

Maneb ISE 4 2 0

Mercury GI 3 2 1

MXC RCD 3 0 0

Methylene bis(thiocyanate) ANG 2 1 0

MeHg TM 5 2 0

Na-selenite RI 0 4 2

Nickel GI 6 1 1

TM 6 1 1

Nickel chloride RI 6 0 2

Nitric oxide RI 5 2 2

4-NP TPI 2 1 0

Oxyuorfen RCD 4 0 0

S278 | Carcinogenesis, 2015, Vol. 36, Supplement 1

to lay out a heuristic framework that would be helpful for other

researchers who are interested in considering these and other

chemicals as potential constituents for low-dose mixtures

research.

LDE, chemical mixtures and carcinogenicity

Although we did not specically ask the teams to focus on

disruptive chemicals that were known to exert LDE, the sum-

mary of dose-response characterizations for the chemicals

that were selected by these teams is dominated by chemi-

cals (i.e. 50/85) that have been shown to produce LDE, and

15 of the 50 showed evidence of a non-linear dose-response.

Surprisingly, only 15% of the chemicals reviewed (i.e. 13/85)

showed evidence of a threshold. We believe that this helps to

validate the idea that chemicals can act disruptively on key

cancer-related mechanisms at environmentally relevant lev-

els of exposure.

Historically, the axiom ‘the dose makes the poison’ has had

some merit, so many people remain skeptical about the idea

that adverse outcomes can result from minute exposures to

commonly encountered chemicals. But we are now at a point in

time where our knowledge of the biology of cancer has advanced

considerably, and we know that carcinogenesis can begin when

key events have occurred in a single cell, between cells or in

the surrounding microenvironment. So the idea that LDE from

many environmental chemicals (acting together) might serve

to instigate, support or fully enable carcinogenesis, no longer

appears to be an unreasonable assertion.

At this stage, we are not making any assumptions about

whether or not future empirical research will nd support for

this hypothesis, nor are we assuming that this a signicant

problem. We are simply impressed by the fact that we are now

starting to see evidence of a wide range of LDE (that are directly

related to carcinogenesis) that can be exerted by chemicals that

are ubiquitous and unavoidable in the environment. As a result,

we are compelled to explore and consider this possibility.

In-utero exposures and transgenerational effects

Additionally, a number of the teams cited in-utero exposure

studies in their reviews and presented evidence on transgen-

erational effects. Although this detail is not fully captured in

the team summaries offered in this capstone paper (please see

the individual reviews in this special issue for complete details),

these effects are important to acknowledge. For example, the

inammation team noted that transient early life exposures in

utero to vinclozolin have been linked to both adult-onset dis-

ease and transgenerational disease that involves inamma-

tion. Similarly, the immune system evasion team reported that

there is increasing evidence from animal studies that in-utero

or neonatal exposures to BPA are associated with higher risk of

immune system dysregulation that may develop later inlife.

Taken together, these and other similar types of examples

raise intriguing possibilities about vulnerabilities at the popu-

lation level, and the contributions that in utero and early life

exposures to mixtures of those chemicals might make towards

cancer susceptibility. Single-generation experimental models

are inadequate to detect this sort of disruptive activity (for expo-

sures to a given chemical or to mixtures of chemicals), but these

sorts of effects may increase cancer risks by promoting and/or

enabling tumorigenesis.

The interplay between genetic factors and

environmental factors

Given the number of key cancer-related mechanisms that can

apparently be disrupted by chemicals that are commonly found

in the environment, and the possibility that in-utero and/or early

life exposures may also contribute to population vulnerabil-

ity, the interplay between genetic factors and environmental

Chemicals Originating review Procarcinogenic Anticarcinogenic Mixed

Paraquat GI 4 2 0

TM 4 2 0

PFOS ANG 4 1 0

SPS 4 1 0

Phosalone SPS 1 1 0

Phthalates TIM 6 0 1

TPI 6 0 1

PBDEs TPI 2 0 2

Pyraclostrobin ISE 2 1 0

Pyridaben ISE 1 3 1

Quinones GI 1 6 1

Rotenone DM 2 5 1

Sulfur dioxide TIM 5 1 0

Titanium dioxide NPs GI 3 1 1

Tributyltin chloride ANG 3 1 0

Triclosan GI 2 2 1

ISE 3 2 1

Tungsten GI 2 1 1

Vinclozolin TPI 2 1 0

Ziram ANG 3 1 1

Aggregated number of procarcinogenic actions, anticarcinogenic actions and mixed actions (i.e. procarciniogenic and anticarcinogenic) where cross-hallmark effects

have been reported (for each chemical across the full range of hallmark domains—i.e. from all of the areas covered by the reviews in this special issue)—see samples

of this how this data were reported in Table3. Note: fully referenced data for these cross-hallmark effects can be found in each of the reviews in this special issue.

ANG, angiogenesis; DM, dysregulated metabolism; EAS, evasion of antigrowth signaling; GI, genetic instability; ISE, immune system evasion; RCD, resistance to cell

death; RI, replicative immortality; SPS, sustained proliferative signaling; TIM, tissue invasion and metastasis; TM, tumor microenvironment; TPI, tumor-promoting

inammation.

Table5. Continued

W.H.Goodson et al. | S279

factors should also be mentioned. For example, a hereditary

genetic vulnerability (such as mutations to BRCA1/2 genes

which greatly increase the lifetime risk of breast and ovarian

cancer (482)) can predispose someone to a higher risk of cancer.

But many hereditary genetic mutations and somatic mutations

do not result in cancer, presumably because additional actions

(e.g. sustained proliferative signaling) are needed or additional

biological safeguards still need to be suppressed or defeated

(e.g. apoptosis, senescence, immuno-surveillance and so on)

before a fully immortalized cellular phenotype can emerge. In

these instances, cancer may not be assured, but it is easy to

see how the disruptive effects of low-dose exposures to certain

chemicals might act on key pathways/mechanisms and play a

supporting role in the steps involved in carcinogenesis and/or

increase the overall risk of getting cancer.

This same issue applies to other sensitive subpopulations

who might be predisposed to higher levels of cancer risk. In some

instances, vulnerabilities that exist are genetic in nature (e.g.

cancer patients in remission), due to endogenous factors (e.g.

due to obesity) or due to external inuences (i.e. smoking). But

in all cases, the enhanced risks in these subpopulations leave

the affected individuals vulnerable to carcinogenesis. Although

a detailed investigation of this type of interaction is beyond the

scope of this project, it is important to consider that low dose,

disruptive chemical effects on key pathways and mechanisms

in these subpopulations may serve to further enhance cancer

susceptibility, or even fully enable carcinogenesis.

The low-dose carcinogenesis hypothesis

It is important to reiterate that this group has no interest in

implicating any of the chemicals that were reviewed in this

project as individual carcinogens per se. We fully realized

at the outset that much of the evidence in the toxicological

literature that documented the disruptive actions of these

chemicals had been produced under a wide range of differing

experimental circumstances. So it was agreed at the beginning

that we would not make leaps between different lines of evi-

dence nor draw any specic conclusions about chemical mix-

tures that might prove to be carcinogenic. Nonetheless, we are

intrigued by the number of chemicals that we reviewed that

were found to be capable of disruptive LDE on key pathways/

mechanisms across all of the areas that were reviewed. Many

of the environmental chemicals that we chose are well known

as environmental contaminants, but they represent only a

small fraction of the thousands of chemicals that are now

ubiquitous and unavoidable in the environment. So although

we cannot draw any rm conclusions at this stage, we emerge

from this effort with a better understanding of the evidence

that is available to support the merits of our initial hypothesis

(i.e. that low-dose exposures to disruptive chemicals that are

not individually carcinogenic may be capable of instigating

and/or enabling carcinogenesis).

Although the breadth and scope of this review effort was

daunting, we now believe that we have enough supporting evi-

dence to offer a holistic overview of this issue. At a minimum,

we hope that the studies cited in this review, the gaps that we

have identied and the framework that we have proposed for

future research will be useful to researchers who are encour-

aged to explore this hypothesis in greater detail.

The implications for risk assessment

Thirty-ve years ago, the work of Ames and others who fol-

lowed set in motion a quest for individual chemicals as (com-

plete) ‘carcinogens’ that became a dominant paradigm that has

shaped our thinking for decades (226). So dominant has the

focus been on single chemicals, that combinations of chemi-

cals are rarely tested or even considered. For example, although

IARC has focused on extensive monographs of the carcinogenic

nature of individual chemicals, little has been done to evaluate

the possibility of carcinogenic effects attributable to chemical

mixtures except in a few instances where mixtures of concern

are encountered during occupational exposures (e.g. polychlo-

rinated dibenzo-p-dioxins and polychlorinated dibenzofurans)

or as a result of personal and cultural habits (e.g. cigarette

smoke, diesel and gasoline engine exhausts).

But the search for mutagenic carcinogens was never

matched with a corresponding search for chemicals that might

contribute to the promotion of carcinogenesis along with other

chemicals. We now know that individual chemicals can produce

unique disruptions of cellular biology and specic combinations

of non-carcinogenic chemicals have been able to demonstrate

potent carcinogenic effects. Yet, we have only scratched the sur-

face of the biology of mixtures, and we need to look carefully at

the synergistic effects.

In risk assessments, the risks associated with exposures to

mixtures of chemicals are often estimated using relatively sim-

ple, component-based approaches (476). Risk analysts evalu-

ate information regarding the mode of action associated with

individual mixture components and then use either ‘dose addi-

tion’ or ‘response addition’ to predict effects. Dose addition is

an appropriate approach to assess mixtures risks, when the

chemicals of interest act through a common mode of action.

Although response addition assumes that constituent agents

act independently of each other (cause the same outcome via

different modes of action). In general, a dose addition approach

would be appropriate for mixtures risk assessment if we wanted

to consider a series of chemicals that were carcinogenic in their

own right, and if they all produced the cancer by the same mode

of action. The Hallmarks of Cancer framework suggests that

we should be equally, if not more, concerned about mixtures of

chemicals that are not individually carcinogenic but disruptive

in a manner that is collectively procarcinogenic (i.e. potentially

capable of producing carcinogenic synergies when combined

with other chemicals that are acting on the diverse series of

mechanisms involved in carcinogenesis).

With this in mind, there should be concern that the World

Health Organization International Programme on Chemical

Safety (WHO IPCS) has spent the past decade developing a

risk analysis agenda predicated mainly on a ‘Mode of Action’

framework (477–480), where ‘mode of action’ is dened as a

sequence of key events and processes, starting with interaction

of an agent with a cell, proceeding through operational and ana-

tomical changes and resulting in an adverse outcome, in this

case, cancer formation. The OECD guidance on the conduct and

design of chronic toxicity and carcinogenicity (which is followed

by many nations) now also reects this approach (480). This

analysis of risks from cumulative effects of chemical exposures

is restrictive because it suggests that regulators should only

focus on groupings of individual chemicals that are as follows:

(a) known to act via a common sequence of key events and

processes;

(b) known to act on a common target/tissue and

cancer).

So, for example, in the USA, the Food Quality Protection Act pro-

vides legislated guidance on testing for cumulative effects by

using the term ‘common mechanism of toxicity’ (481), which is

interpreted to mean ‘mode of action’ or ‘the major steps leading

to an adverse health effect following interaction of a pesticide

S280 | Carcinogenesis, 2015, Vol. 36, Supplement 1

with biological targets’. Similarly, in Canada, the Pest Control

Products Act requires the government to assess the cumulative

effects of pest control products that have a ‘common mecha-

nism of toxicity’. In the USA, there has also been a tradition of

employing an additional restriction requiring chemical struc-

tural similarity when selecting groups of chemicals to be sub-

jected to mixtures risk assessment (other than a few instances

where whole mixtures have been assessed, e.g. diesel exhaust,

combinations of chemicals that are not similar structurally have

been largely ignored (489)). In light of current knowledge of can-

cer biology, these criteria appear to be inappropriately restric-

tive, and thus demand a number of considerations—as follows:

Cumulative risk assessment should anticipate synergies of chemicals

acting via dissimilar sequences/processes. From the Hallmarks of

Cancer framework, it becomes evident that chemicals that act

via dissimilar pathways/targets or that produce different sorts

of key events and/or employ different processes could very

well produce synergies within carcinogenesis that would be

relevant for cumulative risk assessment purposes. For example,

ethylenediaminetetraacetic acid (EDTA) is a ubiquitous,

presumably non-carcinogenic chemical that disrupts DNA

repair (483,484), and it is well established that it inuences

chromosome breakage by mutagenic agents. In particular,

when applied in combination with chemical mutagens, EDTA

enhances mutagen-induced aberration frequencies and

contributes to genetic instability (485). But within the mode of

action framework, a chemical that is a mutagenic carcinogen,

would not be assessed for the cumulative risks associated with

an additional exposure to a chemical that disrupts DNA repair (a

key layer of cancer defense) because it is not known to produce

a common sequence of key events and processes.

A 2008 report on phthalates and cumulative risk assess-

ment emphasized that the chemicals considered for cumula-

tive risk assessment should be ones that cause the same health

outcomes or the same types of health outcomes, not ones that

cause the health outcomes only by a specic pathway (486).

Similarly, The European Food Safety Authority Panel on Plant

Protection Products and their Residues (PPR Panel) produced a

scientic opinion on the relevance of dissimilar modes of action

and their relevance for cumulative risk assessment of pesticides

residues in food (482). The PPR Panel found good evidence that

combination effects can arise from co-exposure to chemicals

that produce common (adverse) outcomes through entirely

different modes of action and recommended cumulative risk

assessment methods to evaluate mixtures of pesticides in foods

that have dissimilar modes of action (396).

Cumulative risk assessment should anticipate synergies of chemicals

acting on different targets/tissues. The Hallmarks of Cancer

framework suggest that spatiotemporal aspects of chemical

exposures are likely important as well. For example, the many

constituent parts of the immune system and its distributed

nature (e.g. lymph vessels, thymus, bone marrow and so on), the

hypothalamic–pituitary–adrenal axis and cortisol in circulation,

which are used to suppress macrophage migration inhibitory

factor and control inammation (487–489) and the surrounding

tissues of the tumor microenvironment, are all relevant targets

that could be chemically disrupted to produce procarcinogenic

contributions to carcinogenesis.

For example, as noted previously, maneb is a fungicide with

a potentially disrupting effect on cortisol (446), which could

impact the body’s response to inammation suppression,

whereas atrazine affects the host immune response by directly

targeting maturation of DCs and decreasing the levels of major

histocompatibility complex class I molecules (243,453). Both

are highly relevant forms of disruption for carcinogenesis, but

within the mode of action framework, the cumulative effects

of these chemicals (and other chemicals acting on these and

similarly distributed targets) would never be assessed together

because they do not act on a common biological target.

The PPR Panel recently pointed out that there is no empiri-

cal evidence for the validity of independent action as a predic-

tive concept for multicomponent mixtures in the mammalian

toxicological literature. Further, they argued that although over-

lapping toxic effects in different organs/systems may exist, it is

difcult to identify a combination effect. Thus, the panel speci-

cally restricted their focus to chemicals that ultimately produce

a common adverse outcome (e.g. cancer) in the same target

organ/system (482). Although it may be difcult to identify this

sort of an effect, that does not mean, however, that we should

ignore this possibility (i.e. now that our understanding of the

biology of cancer has improved).

Cumulative risk assessment should anticipate synergies of non-

carcinogens. The WHO IPCS mode of action framework accepts

the notion of a common toxic endpoint and therefore that

chemicals need to rst be carcinogens themselves before they

can be considered as possible constituents of carcinogenic

mixtures. However, it is now evident that not every

procarcinogenic action resulting from a chemical exposure

must be the result of a chemical that is a carcinogen itself.

Continued focus on individual carcinogens reects a lingering

paradigm that overlooks the examples of synergies such as

those highlighted in this project. Low-dose mechanistic

effects may be very important so approaches are needed

that take this into account. In chronic and complex diseases,

establishing dose thresholds using the whole disease as the

endpoint (e.g. cancer) may be inappropriate, especially when

exposures to individual chemicals can produce relevant (but

not disease causing) mechanistic effects at much lower dose

levels.

Cumulative risk assessment should anticipate synergies of

structurally dissimilar chemicals. The EPA’s emphasis on

structurally similar classes of chemicals for mixtures risk

assessments is unnecessarily restrictive. The dissimilar

chemicals reviewed within this special issue are testament to

the fact that similar disruptive effects can be produced by a wide

range of chemical structures and failure to adapt testing to this

fact is no longer acceptable (486).

In sum, it is concerning that the WHO IPCS approach is so

highly restrictive when it comes to the assessment of cumu-

lative effects. The OECD guidelines acknowledge that cancers

originating from at least some cell types may arise by a vari-

ety of independent pathways, but the guidance is fundamen-

tally focused on the identication of individual carcinogens and

cumulative effects of carcinogens, specically noting that the

approach is intended to ‘avoid misidentication of non-tumorigenic

compounds as possible human carcinogens’ (480). But in practice, as

in-vitro and in-vivo evidence for many chemicals is frequently

not available (i.e. to prove that they individually act via a com-

mon sequence of key events or process a common target/tissue

to produce cancer), it means that risk assessments of the cumu-

lative effects of exposures to mixtures of chemicals on carcino-

genesis are rarely conducted.

W.H.Goodson et al. | S281

The International Life Sciences Institute, which is a non-

prot organization with members comprised largely of major

corporate interests from the food and beverage, agricultural,

chemical and pharmaceutical industries, has worked closely

with the WHO IPCS to support this approach. But while it may

serve to ensure the avoidance of the misidentication of (non-

tumorigenic) chemicals/compounds as possible human car-

cinogens, it simultaneously discourages regulatory agencies

from exploring the sorts of synergies that might plausibly be

expected to occur. Indeed, the biology of cancer suggests that

the cumulative effects of non-carcinogenic chemicals acting on

different pathways that are relevant to cancer, and on a variety

of cancer-relevant systems, organs, tissues and cells may very

well conspire to produce carcinogenic synergies that will be

overlooked entirely as long as the mode of action framework

(and the restrictions that it imposes) remains inuse.

As mentioned briey previously, a considerable effort has

been made by toxicologists to advance a new approach called

the Adverse Outcome Pathway framework. This is an extension

of the Mode of Action framework and is primarily being devel-

oped as an alternative solution to in-vivo toxicity testing. The

framework is based on the idea that any adverse human health

effect caused by exposure to an exogenous substance can be

described by a series of causally linked biochemical or biologi-

cal key events with measurable parameters (28,490). Although

the Adverse Outcome Pathway framework anticipates the pos-

sibility that multiple pathways may need to be dened (i.e. dif-

ferent pathways that can produce the same adverse human

health effect), the concept is currently aligned with the mode

of action approach and focuses mainly on individual chemi-

cal effects that follow a well-described pathway to produce an

adverse health outcome. So as it is currently conceived, it has

some of the same limitations that apply to the mode of action

framework.

Nonetheless, this focus at a mechanistic level is progressive

in nature and some researchers in this area are starting to call

for the adoption of practices within the framework that can

account for epigenetic effects, transgenerational effects and

chronic toxicity (detrimental effects arising in individual or at

the population level following long-term continuous or uctu-

ating exposure to chemicals at sublethal concentrations—i.e.

concentrations not high enough to cause mortality or directly

observable impairment following acute, short-term exposure,

but able to induce specic effects potentially leading to adverse

outcomes occurring at a later point in time) (28).

So this framework may be suitable for research that is

focused on mixtures of chemicals and the pathways involved

in carcinogenesis, so long as the adherents to this approach

are open to the possibility that all relevant pathways need not

have adverse health outcomes as endpoints, and that synergies

between pathways may need to be anticipated. In other words,

a series of seemingly benign actions on different pathways may

be needed to conspire to produce the adverse health outcome

that is of interest. This is the case in cancer. There are so many

layers of redundancy and safeguards in place that individual

disruptions of certain pathways may never cause disease on

their own. Yet, when a number of these pathways are enabled,

they can produce a discernable adverse health outcome (i.e.

cancer). If this approach is robust enough to anticipate this type

of complexity, it may be a model that will allow us to move past

the limitations imposed by the mode of actionmodel.

Many regulatory agencies that conduct chemical risk assess-

ments also have a mandate to ensure that adequate safety

margins are in place to protect sensitive subpopulations. So

they will need to place an increasing emphasis on the inter-

play between environmental factors and genetic factors and

also consider in-utero exposures and the potential for transgen-

erational effects. Some progress has been made in tackling the

gene-environment interaction problem using pathway analysis

to demonstrate the role of genetic variants in exposure-related

cancer susceptibility (c.f. Malhotra et al. (498)), but very little

research has been done on in-utero exposures to mixtures of

chemicals that act on cancer-related mechanisms. An approach

that focuses on dening mixtures of constituents that act dis-

ruptively on key mechanisms that are related to individual hall-

marks may serve as a useful starting point to nd evidence of

relevant transgenerational effects (c.f. Singh et al. (499)). This

is denitely an area where additional research and regulatory

input is needed.

Research needs: cancer versus carcinogenesis

One of the main challenges in this project has been the need

to better understand carcinogenesis as a process characterized

by a long latency—and the corollary possibility of both direct

and indirect effects—rather than cancer as a disease endpoint

that must occur rapidly and in the majority of exposed persons

to be relevant. This was also accompanied the recognition that

the Hallmarks of Cancer are frequently neither xed nor spe-

cic for cancer (349–351). Numerous experimental models have

been used in cancer research over the years, and Vineis etal.

(493) summarized them into at least ve separate classes of

models—seebelow:

(a) Mutational models

(b) Genome instability

expansion and epigenetics

(d) ‘Darwinian’ or ‘somatic cellular selection’, and

(e) ‘Tissue organization’.

All of these models have had signicant support in the scientic

literature (based upon empirical evidence) and there is consid-

erable overlap between them. But our collective understanding

of carcinogenesis is still largely constrained by a historically

monolithic toxicology-based approach that has been focused on

the effects of mutagens and the disease itself. So although the

Hallmarks of Cancer framework helps us to better conceptualize

the many acquired capabilities of the disease, it leaves much to

the imagination when it comes to advancing our understanding

of carcinogenesis per se. This lacuna was recently highlighted by

Brash etal. (494,495) in an article on what they called ‘the mys-

terious steps in carcinogenesis’.

Carcinogenesis appears to be an evolution of factors that

ultimately conspire towards various acquired capabilities (i.e.

those delineated within the Hallmarks of Cancer framework),

but how much does the sequencing of these acquired capabili-

ties matter and in what order are these capabilities acquired?

Figure 1 implies a rough sequencing of these capabilities, but

do we know for certain that all hallmarks for established cancer

are important for carcinogenesis as well (i.e. which hallmarks

are necessary for all tumors, and of those, which are sufcient

or perhaps distinct for certain cancers?). Other important ques-

tions to ask relate to whether or not the individual hallmarks

are a cause or a consequence of cancer development? Do the

individual hallmarks need to be expressed simultaneously or

sequentially along the continuum of carcinogenesis (from expo-

sure to unambiguous cancer phenotype development)? More

S282 | Carcinogenesis, 2015, Vol. 36, Supplement 1

importantly, how does our understanding of this framework

inform our general approach to the study of carcinogenesis?

We have partial answers to some of these questions, but

some of these questions remain unanswered, and given the

prolonged latency of many cancers, these are important ques-

tions. Our lack of knowledge in this regard makes it difcult to

draw immediate conclusions about the effects that exposures to

mixtures of disruptive chemicals might cause and the synergies

they might produce. Public health protection is challenged by

the combinatorial complexity posed, not only by multiple expo-

sures to chemicals at environmentally relevant doses (either

simultaneously or sequentially) but also through the different

mechanisms played out in temporospatial manners (includ-

ing life stages of development, which are different from those

applied in traditional toxicologic and carcinogenic screening).

We, therefore, need to consider an expanded research agenda

to include the origins, determinants and temporospatial evolu-

tion of the various cancer hallmarks and their interrelatedness.

The key questions of reversibility and of cause versus conse-

quence must also be rigorously addressed at every step from ini-

tiating carcinogenic exposure to established cancer, recognizing

that not all hallmarks are either xed or specic for any given

cancer type.

Research needs: the Hallmarks ofCancer

Current approaches to the study of chemical exposures and car-

cinogenesis have not been designed to address effects at low

concentrations or in complex mixtures. Procarcinogenic agents

may be directly genotoxic, indirectly genotoxic or non-genotoxic.

In principle, not every disruptive effect resulting in a change

that mimics a cancer hallmark is necessarily carcinogenic. Such

associations, when observed, still require rigorous validation to

ensure that exposures are unequivocally linked to the develop-

ment of both cancer and accompanying phenotypic hallmarks.

These complex interactional possibilities, coupled with the fact

that low-dose combinatorial effects on cancer development

and progression have not been rigorously or comprehensively

addressed, speak to major gaps in our understanding of envi-

ronmental cancer risk and the specic role that mixtures of

environmental chemical exposures might play in the incidence

of cancer at the populationlevel.

Unfortunately, the known effects for chemicals examined in

isolation and at higher concentrations cannot be readily extrap-

olated to effects at lower concentrations. Interactions within

complex mixtures will also occur against the backdrop of com-

plex interactions with other environmental, genetic and epige-

netic factors, so there is a need for expanded or complementary

conceptual and experimental frameworks to better understand

the determinants and specic functional contributions of envi-

ronmental exposures in cancer.

A considerable amount of energy is now being placed on the

development of research and technologies that can support the

‘exposome’ (496), an emerging concept aimed at representing

the totality of chemical exposures received by a person during

a lifetime. This approach encompasses all sources of toxicants

and is intended to help researchers discern some of the contrib-

uting factors that are driving chronic diseases such as cancer.

Related projects are expected to involve extensive biomoni-

toring (e.g. blood and urine sampling) and other techniques to

assess biomarkers that might be relevant, and this information

should be extremely helpful. Longitudinal studies should also

be carried out in animal models to assess the tissue distribution

of mixtures of chemical metabolites. To truly make good use

of this information, we are going to need a better mechanistic

understanding of the process of carcinogenesis itself and better

early markers of cancer development.

It therefore makes sense to pursue empirical research based

on our current understandings of the disease to test the effects

of real-world environmental mixtures at relevant dose levels.

Basic studies should be designed to test joint toxic action (of

carefully designed combinations of chemicals) to assess both

dose additivity (via common mode of action) and response addi-

tivity (via disparate modes of action). Research designs should

anticipate the many layers of inherent defense and incorporate

chemical constituents specically intended to demonstrate pre-

dictable synergies and mechanistic relevance. It would also be

useful to know whether or not the chemical induction of certain

numbers/combinations of hallmarks is sufcient to consistently

produce in-vivo carcinogenesis.

Mixtures research that focuses on the carcinogenic synergies

of non-carcinogenic constituents would be particularly useful.

In addition, compounds or classes of chemicals already consid-

ered to be (complete) carcinogens in the classical sense may also

contribute to carcinogenesis in complex mixtures at concentra-

tions not traditionally deemed carcinogenic. For this reason

and for completeness, ‘classic’ carcinogens with an established

environmental presence at levels that are presumed to be incon-

sequential may still have pathogenic relevance and should be

routinely included in the analysis.

Target sites that are being manipulated and disruptive chem-

icals that are being selected to produce carcinogenic effects

should be scrutinized for confounding effects. Table4 contains

aggregated evidence of cross-hallmark effects for selected path-

ways/mechanisms, and although some target sites for disrup-

tion may be compelling starting points for researchers focused

on a given phenotype (e.g. genetic instability), cross-hallmark

relationships should be explored. So, for example, telomere loss

is seen as a disruptive (procarcinogenic) effect from the per-

spective of the the genetic instability team (i.e. the group in this

project who selected this target) and it has also been shown to

exert procarcinogenic effects in four other hallmark areas. But

evidence also exists that suggests that telomere loss can have

anticarcinogenic effects in four other hallmark areas. The exact

circumstances of the various studies that support these cross-

hallmark relationships would need to be reviewed to better

understand the implications/relevance of these reported effects.

But checking planned disruptions of each target across all of

the other hallmark areas is a way to ensure that confounding

(i.e. anticarcinogenic) effects are not inadvertantly introduced

into experiments that are aimed at producing carcinogenesis,

or phenotypes that can support/contribute to carcinogenesis.

Similarly, Table 5 contains aggregated evidence of cross-hall-

mark effects for the chemical disruptors in this review, so this

table can be used for the same purpose.

It may also be productive to identify ‘reference compounds’

(ideal and prototypical disruptors) for each hallmark path-

way as a guide to predict different combinations of chemicals

that might act in a procarcinogenic manner on any one of

the hallmarks. This may involve different systems and organs

that have relevance to cancer and this sort of research could

also be combined with similar sorts of research on other refer-

ence compounds or mixtures that are shown to enable other

hallmarks. In doing so, researchers should evaluate epigenetic

changes in multiple samples/organs/tissues from exposed ani-

mals/other experimental models using gene array technology,

‘omics’ approaches, real-time imaging of tumors in 3D both in-

vitro (primary cells) and in-vivo models combined with molecu-

lar biomarkers of disease progression, and cellular immune

W.H.Goodson et al. | S283

parameters. The combination of use of computational chemical

genomics virtual screening (497), system biology/pharmacology

and high-quality imaging techniques should help us nd quan-

titative-structure-activity-relationship correlations between the

chemical structure of dissimilar disruptors and experimental

data on biological activity, physiological changes, in-vivo toxicity

and 3D cellular protein dynamics.

It is also conceivable that the combined effects of hundreds of

chemicals in the environment may be involved in the process of

enabling carcinogenesis at the population level, so basic empiri-

cal research that can demonstrate carcinogenic effects with min-

imalistic combinations may initially be needed to reveal the more

granular aspects of carcinogenesis. For example, initial research

might test our assumptions of the step-wise progression of car-

cinogenesis using targeted mixtures of chemicals that exert LDE

to test combinations of 2, 3, 4 chemicals etc. against specic

hallmarks and then adding additional targets to move through

the various steps that are believed to be needed to fully enable

the process. Experiments of this nature may reveal increases

as well as decreases in cancer risk when different mechanisms

are disrupted and corresponding hallmark phenotypes are ena-

bled (depending on the timing of various disruptive exposures).

Batteries of tests may ultimately be needed to evaluate whole

mixtures and key components individually and in various com-

binations. HTS approaches will be particularly helpful here, and

a tiered approach may make sense to look for disruptive combi-

nations, which can then be applied in vivo. Exposure sequenc-

ing and dosage may also be important and should be evaluated

based on our current understandings of the biology of cancer.

In terms of setting research priorities, tissue fate is also a

matter for consideration. It has been known for many years that

certain chemicals have afnities for certain tissues, and radi-

otracer labeling studies that have been conducted on chemicals

for regulatory purposes illustrate how certain chemicals tend

to accumulate in certain tissues. Additionally, it is well known

that some tissue types give rise to human cancers millions of

times more often than other tissue types (498). So, researchers

may want to focus their work on mixtures of disruptive chemi-

cals that prove to be complementary at a mechanistic level and

individually known to accumulate in the same types of tissues,

while at the same time choosing tissue types that are known to

produce cancers more rapidly.

The work that has been done by the WHO IPCS on mode of

action has been very useful. Understanding when chemicals

operate through the same mode of action is denitely good

information for analytical purposes, but given that we now rec-

ognize that non-carcinogens acting at very low-dose levels on

different targets and mechanisms can still activate carcinogen-

esis-related pathways, the combined (carcinogenic) potential of

the many commonly encountered chemicals within the envi-

ronment still needs to be evaluated.

Increasingly, our information is improving and there are

several tools that researchers can use to improve their research

designs. For example, ToxCast™ is an approach launched by

the EPA in 2007 to develop ways to predict potential toxicity of

chemicals and to develop a cost-effective approach for prior-

itizing the thousands of chemicals that need toxicity testing.

The ToxCast™ database was used in this project by a number

of the teams and an incredible amount of data are available on

in-vitro tests (produced using HTS) for a wide range of chemi-

cals. For example, there are many results that are direct meas-

ures of actions related to important mechanisms found within

the Hallmarks of Cancer framework, which would be useful for

research focused along theselines.

Although the hallmark phenotypes in this project repre-

sent areas of cancer research for which there is considerable

agreement, one critique of this framework is that it ignores the

‘missing hallmark’ of dedifferentiation (351). As well, the com-

plexity encompassed by each of these areas of research is hum-

bling. Moreover, cancer is not a singular or xed entity, which

frequently limits the ability to generalize about cancer biology

(349–351). In a recent reection on his career, Weinberg et al.

(499) noted not only widespread acceptance of the ‘Hallmarks of

Cancer’ heuristic but also that this attempt to simplify the dis-

ease is rapidly being eclipsed by calls from the next generation

of researchers who are now focused on assembling and analyz-

ing enormous data sets to gain an increasingly sophisticated

understanding of cancer (e.g. genomes, transcriptomes, pro-

teomes—including isoforms, post-translational modications

and proteoforms, epigenomes, kinomes, methylomes, glycomes

and matrisomes—each one of which encompasses staggering

amounts of accumulated information) (499).

Many researchers have called for an analytical use of sys-

tems biology to transcend the study of individual genes/proteins

and to integrate this complexity into higher order phenotypes

(500,501). Systems biology enables researchers to identify prop-

erties that emerge from complex chemical–biological systems

by probing how changes in one part affect the others and the

behavior of the whole system. The combined effects of tens,

if not hundreds, of simultaneous exposures may need to be

accounted for. The fundamental challenge is that such models

require parameters that are driven by data, but there are very

few good examples of research on mixtures at environmentally

relevant dose levels (502) (c.f. Porter etal. (510)), and there are

fewer still that are focused on cancer.

Nonetheless, in the near term, this basic framework should

serve as a useful starting point for foundational research and

government funding agencies should consider new ways to

support large-scale, team-based holistic approaches to this

problem.

Regulatory priorities (in the face of combinatorial

complexity)

It will take time before we fully understand the carcinogenic

potential of low-dose exposures to chemical mixtures in the

environment. Nonetheless, we cannot afford to lose sight of

the fact that the incidence of cancer remains unacceptably

high, and that the unavoidable (i.e. not lifestyle related) causa-

tive factors that are, in part, underpinning this trend are still

not fully understood (9–11,504,505). Populations worldwide are

continually exposed to a wide range of chemicals, so keeping

the precautionary principle in mind (506), there is a need to take

the risks related to the cumulative effects of these chemicals

seriously (422). Of primary concern is the fact that WHO IPCS

mode of action framework (477) and the OECD guidelines for

risk assessment (480) are restrictive to the point that regulators

could be underestimating the risks posed by exposures to low

doses of mixtures of chemicals.

National regulatory agencies and cancer research founda-

tions must proactively pursue empirical research programs to

assess any basic relationships that can be discerned between

exposures to mixtures of commonly encountered chemicals and

carcinogenicity. For example, systematic exploratory research in

appropriate rodent models exposed to ‘whole-mixtures’ that

consist of multiple chemical constituents at environmentally

relevant dose levels could demonstrate the carcinogenic poten-

tial of complex mixtures that are relevant to the population.

S284 | Carcinogenesis, 2015, Vol. 36, Supplement 1

There is also a compelling need for complementary basic

research to address specic causal relationships between envi-

ronmental exposures and the associated development of cancer

and its characteristic hallmarks.

Hypothetically speaking, such a ‘whole mixture’ should be

composed of non-carcinogens and potential carcinogens given

that individual chemicals that are not carcinogenic could act on a

range of different systems, tissues and/or cells and act synergisti-

cally with other chemicals to instigate carcinogenesis. The goal of

such investigations would not be to single out any given chemical

as a carcinogen, but rather to determine whether or not unantici-

pated (procarcinogenic) synergies of many commonly encoun-

tered chemicals when combined are endangering public health.

In line with the 3Rs (Reduction, Replacement and Renement)

guiding principles for more ethical use of animals in scientic

experiments, there has been a signicant push for research-

ers and regulatory agencies to move away from in-vivo testing

(e.g. European Union REACH legislation and in the USA, the NRC

Toxicology for the 21st Century vision (507)) to take advantage

of HTS and other new technologies. The EPA’s effort to search

for environmental chemicals that are most active in relevant

assays across the various cancer hallmarks, and then to com-

pare those results with in-vivo rodent carcinogenicity data for

the same chemicals, was a denite step in this direction (29).

However, HTS models of carcinogenicity will require validation,

and signicant hurdles remain before this sort of testing will

be ready to replace in-vivo research (508). Therefore, in the near

term, in-vivo testing still remains an important avenue for devel-

oping data sets to address cancer risks of complex mixtures.

Summary/Conclusions

For several decades, there has been a concerted effort to iden-

tify individual chemicals and other agents that are carcinogenic.

At the same time, however, little has been done to determine

whether or not chronic lifetime exposures to mixtures of non-

carcinogenic chemicals in the environment (at low-dose lev-

els) have carcinogenic potential. Many chemicals are known to

accumulate in bodily tissues over time, but little is known about

their combined effects at a mechanistic level and their impact

on cancer-related mechanisms and carcinogenesis. In this pro-

ject, teams of cancer biologists worked with researchers in the

eld of environmental health for the very rst time to explore

this possibility.

Teams that reviewed these cancer-related phenotypes (i.e.

genetic instability, tumor-promoting inammation, sustained

proliferative signaling, insensitivity to antigrowth signals, resist-

ance to cell death, angiogenesis, tissue invasion and metastasis,

the tumor microenvironment and avoiding immune destruc-

tion) readily identied individual (non-carcinogenic) chemicals

that are ubiquitous in the environment that have some poten-

tial to act on key/priority functional targets in each of these

domains. In contrast, the teams focused on replicative immortality

and dysregulated metabolism found examples of chemicals to con-

sider but noted a signicant lack of useful toxicological research

in theseareas.

In total, 85 examples of environmental chemicals were

reviewed as prototypical disruptors (for specic actions on key

pathways/mechanisms that are important for carcinogenesis)

and 59% of them (i.e. 50/85) were found to exert LDE (at levels that

are deemed relevant given the background levels of exposure that

exist in the environment) with 15 of the 50 demonstrating their

LDE in a non-linear dose-response pattern. Only 15% of the chem-

icals reviewed (i.e. 13/85) were found to have a dose-response

threshold and the remaining 26% (i.e. 22/85) were categorized as

‘unknown’ due to a lack of dose-response information.

Cross-hallmark effects for all target sites for disruption and

for all chemicals were found, but the evidence supporting these

results varied considerably in strength and in context.

A number of the teams also cited relevant in-utero expo-

sure studies in their reviews and presented data on transgen-

erational effects related to different aspects of the disease (e.g.

inammation, immune evasion and so on). These examples

raise intriguing possibilities about vulnerabilities at the popu-

lation level, and the contributions that in-utero and early life

exposures to mixtures of those chemicals might make towards

cancer susceptibility.

Therefore, current regulations in many countries (that con-

sider only the cumulative effects of exposures to individual

carcinogens that act via a common sequence of key events and

processes on a common target/tissue to produce cancer) should

be revisited. Our current understanding of the biology of can-

cer suggests that the cumulative effects of (non-carcinogenic)

chemicals acting on different pathways that are relevant to

cancer, and on a variety of cancer-relevant systems, organs, tis-

sues and cells could conspire to produce carcinogenic synergies

that will be overlooked using current risk assessment methods.

Cumulative risk assessment methods that are based on ‘com-

mon mechanisms of toxicity’ or common ‘modes of action’ may

therefore be underestimating cancer-related risks. In-utero and

early life exposures, transgenerational effects and the interplay

between the low-dose mechanistic effects of chemical mixtures

in the environment and the vulnerabilities of subpopulations

who are predisposed to cancer (i.e. via genetics or other inu-

ences) must also be considered. Current policies and practices

do not adequately address these issues and should therefore be

revisited if regulatory agencies hope to better understand and

assess theserisks.

Finally, given the long latency period in most cancers, early

detection to cancer is key so an improved understanding of the

biology within originating tissues (during the latency period)

would be very helpful. If we can use the heuristic presented in

this review to better assess the combined effects of common

exposures to chemical mixtures in the environment, it will help

us improve our understanding of carcinogenesis and identify

exogenous triggers and enabling factors (in utero and during

this important latency period), all of which will be key for the

development of effective strategies for prevention and early

detection.

Contributions

The rst draft of this manuscript (prepared by W.H.G.) was distrib-

uted to all of the contributors within the task force for feedback

and additional inputs. The many responses that followed were

managed by W.H.G. (with the assistance of L.Lo., M.G.and D.O.C.).

Then, multiple rounds of inputs were solicited from the entire task

force with several subsequent rounds of revisions and renements

prior to submission. In addition to the contributions mentioned

previously, The Halifax Project also beneted from the involve-

ment of D.J.C. (who provided details, at the workshop in Halifax,

Nova Scotia, Canada, of National Institute of Environmental

Health Sciences priorities and the agency’s interest in unravel-

ling the health effects of environmental mixtures) and from Glenn

Rice (who gave a Halifax workshop presentation on the chemical

mixtures as a consideration in cancer risk assessment). Both of

these presenters were included in the iterative rounds of manu-

script revisions mentioned previously, and both offered inputs that

W.H.Goodson et al. | S285

resulted in renements to the manuscript. Finally, the journal’s

peer-review process was important, and resulted in the collection

of additional evidence from the teams that related to thresholds,

LDE and of non-monotonic dose-response relationships. The

reviewer’s critical analysis on these topics resulted in a substantial

improvement to the data presented in this capstone document,

which ultimately served to highlight the extent to which low-dose

exposures to individual chemical constituents (within mixtures of

environmental chemicals) might have relevance for the process of

carcinogenesis. Dose-response characterization data and inputs

were then submitted by all teams and subsequently reviewed and

compiled by N.K., A.Co. and R.M.

The Halifax Project Task Force that worked on this manuscript

involved nearly 200 people, many of whom contributed to, and

signed on to this capstone article. The design of the Halifax Project

was conceived by L.Lo. with scientic advice from M.G. Funding

provided by the National Institute for Environmental Health

Sciences was arranged by D.O.C., and this manuscript was rst

drafted by W.H.G. Starting with the Hallmarks of Cancer frame-

work (Hanahan etal. (21)), 11 teams of international cancer biolo-

gists and toxicologists were established to review the literature

on key cancer-related mechanisms/pathways in their respective

domains and to also look at the disruptive potential of low-dose

exposures to chemicals commonly encountered in the environ-

ment (i.e. as it relates to those same mechanisms/pathways).

Each team had a leader and each team was responsible for con-

tributing a section of related content within the capstone manu-

script. The contributing authors from these teams are as follows:

(1) Angiogenesis (Z.H., C-W.H., H-Y.H., L-T.L., M.X., N.K., S.A.B.,

T.M., V.D., W.K.R.); (2) Dysregulated metabolism (R.B.R., A.C.S.,

A.B., E.Ry., D.B., F.C., F.L.M., G.Wi., J.We., N.B.K., R.P.); (3) Evasion of

antigrowth signaling (R.N., A.L., C.C.N., D.W.L., D.R., G.S.G., G.M.C.,

H.Kr., J.V., K.A.C-S., M.W., N.C., P.A.M., P.De., R.A-V., R.V., R.D.F., R.P-

C., R.C.C., S.N.B.), (4) Genetic instability (S.A.S.L., A.L.d.C.S., A.Az.,

A.K.C., A.R.C., A-K.O., E.Ro., F.D., F.J.V.S., G.K., G.B., L.Go., L.Le., L.Z.,

M.Val., M.K-V., N.v L., P.O-W., S.Pav., T.C.); (5) Immune system eva-

sion (H.K.L., E.C., J.K., M.A.W., M.H.M., T.O., W.K.D.), (6) Replicative

immortality (A.Ca., C.B-A., H.Y., H.Ko., J.P.W., J.F.M-L., M.L., S.S.W.);

(7) Resistance to cell death (H.H.P., A.M.A., B.J.B., C.Y., E.R., K.B.N.,

L.S.D’A., L.Li., M.F.R., M.J.G., P.M.G., P.S.L., Q.(S.) C., R.K.S., R.D., S.Ro.,

S.L., T-J.L., Y.R.); (8) Sustained proliferative signaling (W.E., A.W.,

G.Wa., H.S., J.E.K., J.R., K.M., L.Gu., M.V.K., P.V., P.Da., R.M., S.Er.,

T.S., T.H.); (9) Tissue invasion and metastasis (J.O., B.P.Z., C.D., G.N.,

G.T.W., I.K., I.R.M., L.J.M., N.A., O.O., P.N-M., S.El., S.Pap., V.O-M., Y.L.,

Z.C.); (10) Tumor microenvironment (D.W.F., C.S.C., D.C.K., E.L.,

F.M., J.Ro., J.C., J.R.W., L.S., L.V., M.C., P.K.K., P.H., S.Ry., S.C.C., V.M-

S.) and (11) Tumor-promoting inammation (P.T., C.B., E-Y. M., J.S.,

L.J., M.K., S.H., T.G., V.S.).** Additionally, a special cross-functional

team was established to investigate whether or not the chemi-

cals that were identied by the teams as having disruptive poten-

tial for key mechanisms/pathways in a particular domain might

also have been shown in other research to exert relevant effects

on mechanisms/pathways in other domains. The results of the

efforts from this team have been compiled and summarized in

this article and can be found within Table4. This team was com-

prised as follows: W.H.B., A.Am., I.S., A.Co., C.M., D.B., E.Ry., F.A-

M., H.A.H., H.K.S., J.Ra., J.Wo., K.R.P., L.M., M.Vac., N.S., R.A-T., R.R.,

R.A.H.and S.F.** **Note that team leaders are denoted by the rst

set of initials in each team list.

Funding/Acknowledgements

We gratefully acknowledge the support of the National Institute

of Health-National Institute of Environmental Health Sciences

(NIEHS) conference grant travel support (R13ES023276); Glenn

Rice, Ofce of Research and Development, United States

Environmental Protection Agency, Cincinnati, OH, USA also

deserves thanks for his thoughtful feedback and inputs on the

manuscript; William H.Goodson III was supported by the

California Breast Cancer Research Program, Clarence Heller

Foundation and California Pacic Medical Center Foundation;

Abdul M.Ali would like to acknowledge the nancial support of

the University of Sultan Zainal Abidin, Malaysia; Ahmed Lasfar

was supported by an award from the Rutgers Cancer Institute of

New Jersey; Ann-Karin Olsen and Gunnar Brunborg were sup-

ported by the Research Council of Norway (RCN) through its

Centres of Excellence funding scheme (223268/F50), Amancio

Carnero’s lab was supported by grants from the Spanish Ministry

of Economy and Competitivity, ISCIII (Fis: PI12/00137, RTICC:

RD12/0036/0028) co-funded by FEDER from Regional Development

European Funds (European Union), Consejeria de Ciencia e

Innovacion (CTS-1848) and Consejeria de Salud of the Junta de

Andalucia (PI-0306-2012); Matilde E. Lleonart was supported by a

trienal project grant PI12/01104 and by project CP03/00101 for per-

sonal support. Amaya Azqueta would like to thank the Ministerio

de Educacion y Ciencia (‘Juande la Cierva’ programme, 2009) of

the Spanish Government for personal support; Amedeo Amedei

was supported by the Italian Ministry of University and Research

(2009FZZ4XM_002), and the University of Florence (ex60%2012);

Andrew R.Collins was supported by the University of Oslo;

Annamaria Colacci was supported by the Emilia-Romagna Region

- Project ‘Supersite’ in Italy; Carolyn Baglole was supported by a

salary award from the Fonds de recherche du Quebec-Sante (FRQ-

S); Chiara Mondello’s laboratory is supported by Fondazione

Cariplo in Milan, Italy (grant n.2011-0370); Christian C.Naus holds

a Canada Research Chair; Clement Yedjou was supported by a

grant from the National Institutes of Health (NIH-NIMHD grant

no. G12MD007581); Daniel C.Koch is supported by the Burroughs

Wellcome Fund Postdoctoral Enrichment Award and the Tumor

Biology Training grant: NIH T32CA09151; Dean W.Felsher would

like to acknowledge the support of United States Department of

Health and Human Services, NIH grants (R01 CA170378 PQ22, R01

CA184384, U54 CA149145, U54 CA151459, P50 CA114747 and

R21 CA169964); Emilio Rojas would like to thank CONACyT sup-

port 152473; Ezio Laconi was supported by AIRC (Italian

Association for Cancer Research, grant no. IG 14640) and by the

Sardinian Regional Government (RAS); Eun-Yi Moon was sup-

ported by grants from the Public Problem-Solving Program

(NRF-015M3C8A6A06014500) and Nuclear R&D Program

(#2013M2B2A9A03051296 and 2010-0018545) through the National

Research Foundation of Korea (NRF) and funded by the Ministry

of Education, Science and Technology (MEST) in Korea;

Fahd Al-Mulla was supported by the Kuwait Foundation for

the Advancement of Sciences (2011-1302-06); Ferdinando

Chiaradonna is supported by SysBioNet, a grant for the Italian

Roadmap of European Strategy Forum on Research Infrastructures

(ESFRI) and by AIRC (Associazione Italiana Ricerca sul Cancro; IG

15364); Francis L.Martin acknowledges funding from Rosemere

Cancer Foundation; he also thanks Lancashire Teaching Hospitals

NHS trust and the patients who have facilitated the studies he

has undertaken over the course of the last 10 years; Gary

S.Goldberg would like to acknowledge the support of the New

Jersey Health Foundation; Gloria M.Calaf was supported by Fondo

Nacional de Ciencia y Tecnología (FONDECYT), Ministerio de

Educación de Chile (MINEDUC), Universidad de Tarapacá (UTA);

Gudrun Koppen was supported by the Flemish Institute for

Technological Research (VITO), Belgium; Hemad Yasaei was sup-

ported from a triennial project grant (Strategic Award) from the

S286 | Carcinogenesis, 2015, Vol. 36, Supplement 1

National Centre for the Replacement, Renement and Reduction

(NC3Rs) of animals in research (NC.K500045.1 and G0800697);

Hiroshi Kondoh was supported in part by grants from the Ministry

of Education, Culture, Sports, Science, and Technology of Japan,

Japan Science and Technology Agency and by JST, CREST; Hsue-

Yin Hsu was supported by the Ministry of Science and Technology

of Taiwan (NSC93-2314-B-320-006 and NSC94-2314-B-320-002);

Hyun Ho Park was supported by the Basic Science Research

Program through the National Research Foundation of Korea

(NRF) of the Ministry of Education, Science and Technology

(2012R1A2A2A01010870) and a grant from the Korea Healthcare

Technology R&D project, Ministry of Health and Welfare, Republic

of Korea (HI13C1449); Igor Koturbash is supported by the UAMS/

NIH Clinical and Translational Science Award (UL1TR000039 and

KL2TR000063) and the Arkansas Biosciences Institute, the major

research component of the Arkansas Tobacco Settlement

Proceeds Act of 2000; Jan Vondráček acknowledges funding from

the Czech Science Foundation (13-07711S); Jesse Roman thanks

the NIH for their support (CA116812); John Pierce Wise Sr. and

Sandra S.Wise were supported by National Institute of

Environmental Health Sciences (ES016893 to J.P.W.) and the Maine

Center for Toxicology and Environmental Health; Jonathan

Whiteld acknowledges support from the FERO Foundation in

Barcelona, Spain; Joseph Christopher is funded by Cancer

Research UK and the International Journal of Experimental

Pathology; Julia Kravchenko is supported by a philanthropic

donation by Fred and Alice Stanback; Jun Sun is supported by a

Swim Across America Cancer Research Award; Karine A.Cohen-

Solal is supported by a research scholar grant from the American

Cancer Society (116683-RSG-09-087-01-TBE); Laetitia Gonzalez

received a postdoctoral fellowship from the Fund for Scientic

Research–Flanders (FWO-Vlaanderen) and support by an

InterUniversity Attraction Pole grant (IAP-P7-07); Laura Soucek is

supported by grant #CP10/00656 from the Miguel Servet Research

Contract Program and acknowledges support from the FERO

Foundation in Barcelona, Spain; Liang-Tzung Lin was supported

by funding from the Taipei Medical University (TMU101-AE3-Y19);

Linda Gulliver is supported by a Genesis Oncology Trust (NZ)

Professional Development Grant, and the Faculty of Medicine,

University of Otago, Dunedin, New Zealand; Louis Vermeulen is

supported by a Fellowship of the Dutch Cancer Society (KWF,

UVA2011-4969) and a grant from the AICR (14–1164); Mahara

Valverde would like to thank CONACyT support 153781; Masoud

H. Manjili was supported by the ofce of the Assistant Secretary

of Defense for Health Affairs (USA) through the Breast Cancer

Research Program under Award No. W81XWH-14-1-0087 Neetu

Singh was supported by grant #SR/FT/LS-063/2008 from the

Department of Science and Technology, Government of India;

Nicole Kleinstreuer is supported by NIEHS contracts (N01-ES

35504 and HHSN27320140003C); P.K. Krishnakumar is supported

by the Funding (No. T.K. 11-0629) of King Abdulaziz City for

Science and Technology, Riyadh, Saudi Arabia; Paola A.Marignani

is supported by the Dalhousie Medical Research Foundation, The

Beatrice Hunter Cancer Institute and CIHR and the Nova Scotia

Lung Association; Paul Dent is the holder of the Universal Inc.

Chair in Signal Transduction Research and is supported with

funds from PHS grants from the NIH (R01-CA141704,

R01-CA150214, R01-DK52825 and R01-CA61774); Petr Heneberg

was supported by the Charles University in Prague projects UNCE

204015 and PRVOUK P31/2012, and by the Czech Science

Foundation projects P301/12/1686 and 15-03834Y; Po Sing Leung

was supported by the Health and Medical Research Fund of Food

and Health Bureau, Hong Kong Special Administrative Region,

Ref. No: 10110021; Qiang Cheng was supported in part by grant

NSF IIS-1218712; R. Brooks Robey is supported by the United

States Department of Veterans Affairs; Rabindra Roy was sup-

ported by United States Public Health Service Grants (RO1

CA92306, RO1 CA92306-S1 and RO1 CA113447); Rafaela Andrade-

Vieira is supported by the Beatrice Hunter Cancer Research

Institute and the Nova Scotia Health Research Foundation; Renza

Vento was partially funded by European Regional Development

Fund, European Territorial Cooperation 2007–13 (CCI 2007 CB 163

PO 037, OP Italia-Malta 2007–13) and grants from the Italian

Ministry of Education, University and Research (MIUR) ex-60%,

2007; Riccardo Di Fiore was a recipient of fellowship granted by

European Regional Development Fund, European Territorial

Cooperation 2007–2013 (CCI 2007 CB 163 PO 037, OP Italia-Malta

2007–2013); Rita Dornetshuber-Fleiss was supported by the

Austrian Science Fund (FWF, project number T 451-B18) and the

Johanna Mahlke, geb.-Obermann-Stiftung; Roberta Palorini is

supported by a SysBioNet fellowship; Roslida Abd Hamid is sup-

ported by the Ministry of Education, Malaysia-Exploratory

Research Grant Scheme-Project no: ERGS/1-2013/5527165; Sabine

A.S.Langie is the beneciary of a postdoctoral grant from the AXA

Research Fund and the Cec-LRI Innovative Science Award 2013;

Sakina Eltom is supported by NIH grant SC1CA153326; Samira

A.Brooks was supported by National Research Service Award (T32

ES007126) from the National Institute of Environmental Health

Sciences and the HHMI Translational Medicine Fellowship;

Sandra Ryeom was supported by The Garrett B.Smith Foundation

and the TedDriven Foundation; Thierry Massfelder was supported

by the Institut National de la Santé et de la Recherche Médicale

INSERM and Université de Strasbourg; Thomas Sanderson is sup-

ported by the Canadian Institutes of Health Research (CIHR; MOP-

115019), the Natural Sciences and Engineering Council of Canada

(NSERC; 313313) and the California Breast Cancer Research

Program (CBCRP; 17UB-8703); Tiziana Guarnieri is supported by a

grant from Fundamental Oriented Research (RFO) to the Alma

Mater Studiorum University of Bologna, Bologna, Italy and thanks

the Fondazione Cassa di Risparmio di Bologna and the Fondazione

Banca del Monte di Bologna e Ravenna for supporting the Center

for Applied Biomedical Research, S.Orsola-Malpighi University

Hospital, Bologna, Italy; W.Kimryn Rathmell is supported by the V

Foundation for Cancer Research and the American Cancer

Society; William K.Decker was supported in part by grant

RP110545 from the Cancer Prevention Research Institute of Texas;

William H.Bisson was supported with funding from the NIH P30

ES000210; Yon Rojanasakul was supported with NIH grant

R01-ES022968; Zhenbang Chen is supported by NIH grants

(MD004038, CA163069 and MD007593); Zhiwei Hu is grateful for

the grant support from an institutional start-up fund from The

Ohio State University College of Medicine and The OSU James

Comprehensive Cancer Center (OSUCCC) and a Seed Award from

the OSUCCC Translational Therapeutics Program.

Disclaimer

This manuscript is the work product of a large group of research-

ers collectively representing a diverse array of institutions and a

signicant number of sponsors; however, the statements, opin-

ions and conclusions expressed herein do not necessarily repre-

sent the views or positions of these institutions and sponsors.

Conict of interest statement: None declared

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Anthropogenic particles (AP), which include microplastics and other synthetic, semisynthetic, and anthropogenically modified materials, are pollutants of concern in aquatic ecosystems worldwide. Rivers are important conduits and retention sites for AP, and time series data on the movement of these particles in lotic ecosystems are needed to assess the role of rivers in the global AP cycle. Much research assessing AP pollution extrapolates stream loads based on single time point measurements, but lotic ecosystems are highly variable over time (e.g., seasonality and storm events). The accuracy of models describing AP dynamics in rivers is constrained by the limited studies that examine how frequent changes in discharge drive particle retention and transport. This study addressed this knowledge gap by using automated, high‐resolution sampling to track AP concentrations and fluxes during multiple storm events in an urban river (Milwaukee River) and comparing these measurements to commonly monitored water quality metrics. AP concentrations and fluxes varied significantly across four storm events, highlighting the temporal variability of AP dynamics. When data from the sampling periods were pooled, there were increases in particle concentration and flux during the early phases of the storms, suggesting that floods may flush AP into the river and/or resuspend particles from the benthic zone. AP flux was closely linked to river discharge, suggesting large loads of AP are delivered downstream during storms. Unexpectedly, AP concentrations were not correlated with other simultaneously measured water quality metrics, including total suspended solids, fecal coliforms, chloride, nitrate, and sulfate, indicating that these metrics cannot be used to estimate AP. These data will contribute to more accurate models of particle dynamics in rivers and global plastic export to oceans. Practitioner Points Anthropogenic particle (AP) concentrations and fluxes in an urban river varied across four storm events. AP concentrations and fluxes were the highest during the early phases of the storms. Storms increased AP transport downstream compared with baseflow. AP concentrations did not correlate with other water quality metrics during storms.

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Several risk factors for the development of laryngeal cancer have been identified, such as smoking and alcohol consumption, but the molecular mechanisms related to the carcinogenesis in the larynx remain under investigation. In this context, deregulations of the cell-cycle-controling mechanisms, Rb-pathway in particular, have been suggested to be involved in the pathogenesis of laryngeal carcinoma. Our purpose was to investigate 13q14 LOH and the expression of Rb protein and their possible prognostic value in laryngeal cancer. The group of 67 patients with laryngeal cancer, surgically treated with minimum 5 years observation, was multi-variously analysed. LOH for Rb was investigated by PCR-based techniques using two microsatellite markers, D13S263 and D13S126, flanking the Rb locus. Amplification products from each polymorphism were fractionated by denaturing gel electrophoresis and detected by audioradiography. Immunohistochemical staining of paraffin specimens of laryngeal cancers was supervised by the use of monoclonal mouse antibodies IgG1 (Anti-Human Retinoblastoma Gene Product of Dako) in dilution of 1:50. Inactivation of Rb protein was assumed to represent the expression in < or =10% tumour cells. The results of each examined individual factor were compared with clinicopathologic features and the results were statistically transformed (Chi-square test with Yates' correction, Mann-Whitney test). The Kaplan and Meier model was used for overall and disease free survival curves. Only p value of less than 0,05 was considered significant. 13q14 LOH was detected in 7/67 (10,4%) of informative tumours. No correlations were found between Rb genetic alteration (LOH) and gender, age, TNM staging, histological differentiation, nodal and local recurrences (p>0.05). There was a strong association between the loss of Rb and supraglottic localisation of tumour in the larynx (p<0.01). By univariate analysis 13q14 LOH proved to be significantly related to the overall survival whereas it was not related to the quicker relapse (p=0.01, p>0.05 respectively). The genetic data were correlated with the expression of the Rb protein (p=0.001). All tumours with Rb-LOH were immunohistochemically Rb-negative. Inactivation of Rb protein was observed in 9/67 cases (13.49%) and was significantly correlated with the polymorphism of cancer cells, but not with the histological grading. We also found the correlation between reduction of Rb protein and the size of primary tumour (T) (p=0.03) and local recurrence (p=0.035). There was no significant dependence between the level of Rb protein and other histopathological and clinical features (p>0.05). To conclude, analysis of 13q14 LOH enables the assessment of biology of laryngeal cancer and it can be a prognostic factor in overall survival. Immunohistochemical analysis of Rb protein expression in neoplastic cells made it easier to evaluate the mechanisms of cancerogenesis in laryngeal cancer and is closely related to genetic alteration in Rb locus.

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R Chapin

修建水坝值不值 ?

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Stephanie Joyce

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Feb 1999

The hormonal activity of natural estrogens is influenced by the degree to which they bind to serum proteins. In the pregnant female and in the fetus, greater than 99% of estradiol may be bound by serum binding proteins. Therefore, even though total serum levels of estradiol appear very high in fetuses, we have found that in rodent fetuses, there is a very low free concentration of estradiol (0.2 pg/ml). Naturally occurring variation in fetal serum estradiol predicts differences in numerous postnatal traits, including prostate size. In addition, when this low level of free estradiol was experimentally increased from 0.2 to 0.3 pg/ml during the last third of fetal life, treated male mice showed an increase in adult prostate weight. Fetal exposure to low doses of xenobiotic estrogens by feeding to pregnant females, including the compounds methoxychlor (20 and 2000 μg/kg body weight), DES (0.02 to 2 μg/kg body weight) and bisphenol A (2 and 20 μg/kg body weight), also led to increased prostate weight in adulthood. In contrast, fetal doses of natural estradiol and DES above the physiological range of estrogenic activity, and within a toxicological dose range, led to the opposite outcome, a reduction in subsequent adult prostate weight. This indicates that it may be impossible to assess endocrine-disrupting activities in response to low doses within a physiological range of activity by using high, toxic doses of xenoestrogens in testing procedures. We have developed approaches in vitro to predict the potential estrogenic bioactivity of compounds in the physiologically relevant range in animals and humans. We address the following factors in predicting the final observed endocrine-disrupting effect in the animal: (1) the intrinsic estrogenic activity of a given molecule, (2) the effective free concentration determined by how the molecule is carried in serum, (3) partitioning between aqueous and lipid compartments in body and cell lipids, and (4) absorption and metabolism relative to the route of exposure. The studies and strategies we describe are important in developing criteria for a tiered testing system for the detection of estrogenic chemicals as well as endocrine-disrupting chemicals with different modes of action.

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Dec 2013

EFSA Panel on Plant Protection Products and their Residues (PPR

The European Food Safety Authority (EFSA) asked the Panel on Plant Protection Products and their Residues (PPR Panel) to develop a Scientific Opinion on the relevance of dissimilar mode of action and its appropriate application for cumulative risk assessment of pesticides residues in food. The present opinion was preceded by three previous opinions of the PPR Panel (EFSA, 2008, 2009, 2013). The purpose of the present opinion was to assess the relevance of dissimilar modes of action (MoA) for cumulative risk assessment, to evaluate the existing methods for assessing chemicals acting by dissimilar MoA and to identify which methods need to be considered. The PPR Panel restricted its considerations of pesticide combinations with dissimilar modes of action to substances that produce a common adverse effect on the same organ/system. The PPR Panel noted that there is no case documented in the scientific literature where independent action provided more conservative predictions of combination effects than dose addition, and where at the same time independent action also produced accurate predictions. The use of independent action as an assessment concept for combination effects requires demonstration that modes of action of individual substances in a mixture are strictly independent, a condition that can rarely be met in practice. The PPR Panel also noted that there is no cumulative risk assessment method derived from independent action. The PPR Panel therefore recommends using cumulative risk assessment methods derived from dose addition also for the assessment of mixtures of pesticides with dissimilar modes of action, provided they produce a common adverse outcome. Pesticides that produce common adverse outcomes on the same target organ/system should be grouped together in CAGs, and their combined effects assessed by using the concept of dose addition as a pragmatic and conservative default approach for the purpose of assessing cumulative risk in relation to MRL setting or risk assessment of chemical mixtures in practice.

Studies examine contaminants: Pharmaceuticals, hormones and other organic wastewater contaminants in ground water resources

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