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A non-synonymous polymorphism in IRS1 modifies risk of
developing breast and ovarian cancers in BRCA1 and ovarian
cancer in BRCA2 mutation carriers
Yuan C. Ding1, Lesley McGuffog2, Sue Healey3, Eitan Friedman4, Yael Laitman4, Shani-
Shimon–Paluch4, Bella Kaufman4, SWE-BRCA5, Annelie Liljegren6, Annika Lindblom7,
Håkan Olsson8, Ulf Kristoffersson9, Marie Stenmark-Askmalm10, Beatrice Melin11, Susan
M. Domchek12, Katherine L. Nathanson12, Timothy R. Rebbeck12, Anna Jakubowska13, Jan
Lubinski13, Katarzyna Jaworska13, Katarzyna Durda13, Jacek Gronwald13, Tomasz
Huzarski13, Cezary Cybulski13, Tomasz Byrski13, Ana Osorio14,15, Teresa Ramóny Cajal16,
Alexandra V Stavropoulou17, Javier Benítez18, Ute Hamann19, HEBON120, Matti Rookus20,
Cora M. Aalfs121, Judith L. de Lange122, Hanne E.J. Meijers-Heijboer123, Jan C.
Oosterwijk124, Christi J. van Asperen125, Encarna B. Gómez García126, Nicoline
Hoogerbrugge127, Agnes Jager128, Rob B. van der Luijt129, EMBRACE21, Douglas F.
Easton21, Susan Peock21, Debra Frost21, Steve D. Ellis21, Radka Platte21, Elena Fineberg21,
D. Gareth Evans22, Fiona Lalloo22, Louise Izatt23, Ros Eeles24, Julian Adlard25, Rosemarie
Davidson26, Diana Eccles27, Trevor Cole28, Jackie Cook29, Carole Brewer30, Marc
Tischkowitz31, Andrew K. Godwin32, Harsh Pathak32, GEMO Study Collaborators36,
Dominique Stoppa-Lyonnet33,34,35, Olga M. Sinilnikova38,39, Sylvie Mazoyer38, Laure
Barjhoux38, Mélanie Léoné39, Marion Gauthier-Villars33, Virginie Caux-Moncoutier33,
Antoine de Pauw33, Agnès Hardouin42, Pascaline Berthet42, Hélène Dreyfus37,58, Sandra
Fert Ferrer60, Marie-Agnès Collonge-Rame40, Johanna Sokolowska41, Saundra Buys46,
Mary Daly47, Alex Miron48, Mary Beth Terry49, Wendy Chung49, Esther M John50, Melissa
Southey51, David Goldgar52, Christian F Singer53, Muy-Kheng Tea Maria53, Daphne
Gschwantler-Kaulich53, Anneliese Fink-Retter53, Thomas v. O. Hansen54, Bent Ejlertsen55,
Oskar Th. Johannsson56, Kenneth Offit57, Kara Sarrel57, Mia M. Gaudet59, Joseph Vijai57,
Mark Robson61, Marion R Piedmonte62, Lesley Andrews63, David Cohn64, Leslie R.
DeMars65, Paul DiSilvestro66, Gustavo Rodriguez67, Amanda Ewart Toland68, Marco
Montagna69, Simona Agata69, Evgeny Imyanitov70, Claudine Isaacs71, Ramunas
Janavicius72,73, Conxi Lazaro74, Ignacio Blanco43, Susan J Ramus75, Lara Sucheston76,
Beth Y. Karlan77, Jenny Gross77, Patricia A. Ganz78, Mary S. Beattie79, Rita K.
Schmutzler80, Barbara Wappenschmidt80, Alfons Meindl81, Norbert Arnold82, Dieter
Niederacher83, Sabine Preisler-Adams84, Dorotehea Gadzicki85, Raymonda Varon-
Mateeva86, Helmut Deissler87, Andrea Gehrig88, Christian Sutter89, Karin Kast90, Heli
Nevanlinna91, Kristiina Aittomäki92, Jacques Simard93, KConFab Investigators94, Amanda
B. Spurdle3, Jonathan Beesley3, Xiaoqing Chen3, Gail E. Tomlinson95, Jeffrey Weitzel1,
Judy E. Garber96, Olufunmilayo I. Olopade97, Wendy S. Rubinstein98, Nadine Tung99,
Joanne L. Blum100, Steven A. Narod101, Sean Brummel102, Daniel L. Gillen103, Noralane
Lindor105, Zachary Fredericksen106, Vernon S. Pankratz106, Fergus J. Couch107, Paolo
Radice108,109, Paolo Peterlongo108,109, Mark H. Greene110, Jennifer T. Loud110, Phuong L.
Mai110, Irene L. Andrulis111,112, Gord Glendon111, Hilmi Ozcelik111,113, OCGN114, Anne-
Marie Gerdes115, Mads Thomassen116, Uffe Birk Jensen117, Anne-Bine Skytte118, Maria A.
*To whom correspondence should be addressed: Susan L. Neuhausen, Ph.D. The Morris and Horowitz Families Professor in Cancer
Etiology and Outcomes Research Department of Population Sciences Beckman Research Institute of the City of Hope 1500 East
Duarte Road Duarte, CA 91010, USA Phone: 626-471-9261 FAX: 626-471-9269 sneuhausen@coh.org.
Disclosure of Potential Conflicts of Interest The authors declare that they have no competing interests
NIH Public Access
Author Manuscript
Cancer Epidemiol Biomarkers Prev
. Author manuscript; available in PMC 2013 February 01.
Published in final edited form as:
Cancer Epidemiol Biomarkers Prev
. 2012 August ; 21(8): 1362–1370. doi:
10.1158/1055-9965.EPI-12-0229.
NIH-PA Author Manuscript NIH-PA Author Manuscript NIH-PA Author Manuscript
Caligo119, Andrew Lee2, Georgia Chenevix-Trench3, Antonis C Antoniou2, Susan L.
Neuhausen1,*, and on behalf of Consortium of Investigators of Modifiers of BRCA1/2
(CIMBA)
1Department of Population Sciences, Beckman Research Institute of City of Hope, Duarte, CA.
USA 2Department of Public Health and Primary Care, Strangeways Research Laboratory,
University of Cambridge Worts Causeway,Cambridge CB1 8RN, UK 3Genetics and Population
Health Division, Queensland Institute of Medical Research, Locked Bag 2000, Royal Brisbane
Hospital, Brisbane, Australia 4the Oncogenetics unit and the Institute of Oncology, The Chaim
Sheba Medical Center, Tel-Hashomer and the Sackler School of Medicine, Tel-Aviv University,
Tel-Aviv Israel 5Swedish Breast Cancer Study, Sweden 6Department of Oncology, Karolinska
University Hospital, Stockholm, Sweden 7Department of Clinical Genetics, Karolinska University
Hospital, Stockholm, Sweden 8Department of Oncology, Lund University Hospital, Lund, Sweden
9Department of Clinical Genetics, Lund University Hospital, Lund, Sweden 10Division of Clinical
Genetics, Department of Clinical and Experimental Medicine, Linköping University, Linköping,
Sweden 11Department of Radiation Sciences, Oncology, Umeå University, Umea, Sweden
12Abramson Cancer Center, University of Pennsylvania, 3400 Civic Center Boulevard,
Philadelphia, PA 19104, USA 13Department of Genetics and Pathology, Pomeranian Medical
University, Szczecin, Poland 14Human Genetics Group, Human Cancer Genetics Programme,
Spanish National Cancer Research Centre, Madrid, Spain 15Spanish Network on Rare Diseases
(CIBERER) 16Oncology Service, Hospital de la Santa Creu i Sant Pau, Barcelona, Spain
17Molecular Diagnostics Laboratory, IRRP, National Centre for Scientific Research “Demokritos”,
Aghia Paraskevi Attikis, 15310 Athens Greece 18Human Genetics Group and Genotyping Unit,
Human Cancer Genetics Programme, Spanish National Cancer Research Centre, Madrid, Spain
and Spanish Network on Rare Diseases (CIBERER) 19Molecular Genetics of Breast Cancer,
Deutsches Krebsforschungszentrum (DKFZ), Heidelberg, Germany 20Department of
Epidemiology, Netherlands Cancer Institute, Amsterdam, The Netherlands 21Centre for Cancer
Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge,
UK 22Genetic Medicine, Manchester Academic Health Sciences Centre, Central Manchester
University Hospitals NHS Foundation Trust, Manchester, UK 23Clinical Genetics, Guy's and St.
Thomas' NHS Foundation Trust, London, UK 24Oncogenetics Team, The Institute of Cancer
Research and Royal Marsden NHS Foundation Trust, UK 25Yorkshire Regional Genetics Service,
Leeds, UK 26Ferguson-Smith Centre for Clinical Genetics, Yorkhill Hospitals, Glasgow, UK
27Wessex Clinical Genetics Service, University Hospital Southampton NHS Foundation Trust,
Southampton, UK 28West Midlands Regional Genetics Service, Birmingham Women's Hospital
Healthcare NHS Trust, Edgbaston, Birmingham, UK 29Sheffield Clinical Genetics Service,
Sheffield Children's Hospital, Sheffield, UK 30Department of Clinical Genetics, Royal Devon &
Exeter Hospital, Exeter, UK 31Department of Medical Genetics, University of Cambridge, UK
32Department of Pathology and Laboratory Medicine, University of Kansas Medical Center,
Kansas City, Kansas, 66160 33Institut Curie, Department of Tumour Biology, Paris, France
34Unité INSERM U830, Institut Curie, Paris, France 35Université Paris Descartes, Faculté de
Médecine, Paris, France 36GEMO: National Cancer Genetics Network «UNICANCER Genetic
Group», France 37Department of Genetics, Centre Hospitalier Universitaire de Grenoble,
Grenoble, France 38INSERM U1052, CNRS UMR5286, Université Lyon 1, Centre de Recherche
en Cancérologie de Lyon, Lyon, France 39Unité Mixte de Génétique Constitutionnelle des
Cancers Fréquents, Centre Hospitalier Universitaire de Lyon / Centre Léon Bérard, Lyon, France
40Service de Génétique Biologique-Histologie-Biologie du Développement et de la Reproduction,
Centre Hospitalier Universitaire de Besançon, Besançon, France 41Laboratoire de Génétique
Médicale, Nancy Université, Centre Hospitalier Régional et Universitaire, Vandoeuvre-les-Nancy,
France 42Centre François Baclesse, Caen, France 43Genetic Counseling Unit, Hereditari Cancer
Program, IDIBELL-Catalan Institute of Oncology, Spain 46Department of Oncological Sciences,
Huntsman Cancer Institute, University of Utah, Salt Lake City, USA 47Fox Chase Cancer Center,
Ding et al. Page 2
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Philadelphia, Pennsylvania, USA 48Department of Cancer Biology, Dana-Farber Cancer Institute,
Boston, MA, USA 49Department of Epidemiology, Columbia University, New York, NY, USA
50Cancer Prevention Institute of California, Fremont, California, USA, and Stanford University
School of Medicine and Stanford Cancer Institute, Palo Alto, CA, USA 51Genetic Epidemiology
Laboratory, Department of Pathology, University of Melbourne, Australia 52Department of
Dermatology, University of Utah School of Medicine, Salt Lake City, Utah, USA 53Dept of OB/
GYN, Medical University of Vienna, Vienna, Austria 54Center for Genomic Medicine,
Rigshospitalet, Copenhagen University Hospital, Copenhagen, Denmark 55Department of
Oncology, Rigshospitalet, Copenhagen University Hospital, Copenhagen, Denmark 56Department
of Oncology, Landspitali University Hospital, Reykjavik, Iceland, Faculty of Medicine, University of
Iceland, Reykjavik Iceland 57Clinical Cancer Genetics Laboratory, Memorial Sloane Kettering
Cancer Center, New York, NY 58Institut Albert Bonniot, Université de Grenoble, Grenoble, France
59Epidemiology Research Program, American Cancer Society, Atlanta, GA, USA 60Laboratoire de
Génétique Chromosomique, Hôtel Dieu Centre Hospitalier, Chambéry, France 61Memorial Sloan-
Kettering Cancer Center, New York, NY 62Gynecologic Oncology Group Statistical and Data
Center, Roswell Park Cancer Institute, Buffalo, NY,USA 63Australia New Zealand Gynaecological
Oncology Group 64Ohio State University/Columbus Cancer Council; Columbus, OH 43026
65Dartmouth-Hitchcock Medical Center, Gynecologic Oncology, Lebanon, NH 03756 66Women
and Infants Hospital, Providence, RI 02905 67NorthShore University Health System, Evanston, IL
60201 68Division of Human Cancer Genetics, Departments of Internal Medicine and Molecular
Virology, Immunology and Medical Genetics, OSU Comprehensive Cancer Center, The Ohio
State University, Columbus, OH, USA 69Immunology and Molecular Oncology Unit, Istituto
Oncologico Veneto IOV - IRCCS, Padua, Italy 70N.N. Petrov Institute of Oncology, St.-Petersburg,
Russia 71Lombardi Comprehensive Cancer Center, Georgetown University, Washington DC, USA
72Dept. of Molecular and Regenerative medicine, Hematology, Oncology and Transfusion
Medicine Center, Vilnius University Hospital Santariskiu Clinics, Santariskiu st 2, LT-08661
Vilnius 73State Research Institute Innovative Medicine Center, Zygimantu st. 9, LT-01102 Vilnius,
Lithuania 74Molecular Diagnostic Unit, Hereditary Cancer Program, Laboratori de Recerca
Translacional, Institut Català d'Oncologia, Barcelona, Spain 75Department of Preventive
Medicine, Keck School of Medicine, University of Southern California, California, USA
76Department of Cancer Prevention and Control, Roswell Park Cancer Institute, Buffalo, NY, USA
77Women's Cancer Program at the Samuel Oschin Comprehensive Cancer Institute, Cedars-
Sinai Medical Center, Los Angeles, CA, USA 78UCLA Schools of Medicine and Public Health,
Division of Cancer Prevention & Control Research, Jonsson Comprehensive Cancer Center,Los
Angeles, CA, USA 79University of California, San Francisco, Departments of Medicine,
Epidemiology, and Biostatistics, USA 80Centre of Familial Breast and Ovarian Cancer,
Department of Gynaecology and Obstetrics and Centre for Integrated Oncology (CIO), University
hospital of Cologne, Germany 81Department of Gynaecology and Obstetrics, Division of Tumor
Genetics, Klinikum rechts der Isar, Technical University Munich, Germany 82Department of
Gynaecology and Obstetrics, University Hospital of Schleswig-Holstein, Campus Kiel, Christian-
Albrechts University Kiel, Germany 83Department of Gynaecology and Obstetrics, University
Hospital Düsseldorf, Heinrich-Heine University Düsseldorf, Germany 84Institute of Human
Genetics, University of Münster, Münster, Germany 85Institute of Cell and Molecular Pathology,
Hannover Medical School, Hannover, Germany 86Institute of Human Genetics, Campus Virchov
Klinikum, Charite Berlin, Germany 87Department of Gynaecology and Obstetrics, University
Hospital Ulm, Germany 88Centre of Familial Breast and Ovarian Cancer, Department of Medical
Genetics, Institute of Human Genetics, University Würzburg, Germany 89Institute of Human
Genetics, Department of Human Genetics, University Hospital Heidelberg, Germany
90Department of Gynaecology and Obstetrics, University Hospital Carl Gustav Carus, Technical
University Dresden, Germany 91Department of Obstetrics and Gynecology, University of Helsinki
and Helsinki University Central Hospital, Helsinki, Finland 92Department of Clinical Genetics,
Ding et al. Page 3
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University of Helsinki and Helsinki University Central Hospital, Helsinki, Finland 93Canada
Research Chair in Oncogenetics, Cancer Genomics Laboratory, Centre Hospitalier Universitaire
de Québec and Laval University, Canada 94Kathleen Cuningham Consortium for Research into
Familial Breast Cancer – Peter MacCallum Cancer Center, Melbourne, Australia (kConFab)
95Division of Pediatric Hematology Oncology, University of Texas Health Science Center at San
Antonio 96Department of Medicine, Harvard Medical School and Dana Farber Cancer Institute,
Boston, MA 97Departments of Medicine and Human Genetics, University of Chicago, Chicago, IL
98NorthShore University HealthSystem, Evanston, IL; University of Chicago Pritzker, School of
Medicine,Chicago, IL 99Beth Israel Deaconess Medical Center, Boston, MA 100Baylor-Charles A.
Sammons Cancer Center, Dallas, Texas 101Women's College Hospital, Toronto, Ontario
102Center for Biostatistics in AIDS Research, Harvard School of Public Health, Boston, MA;
103Department of Statistics and Department of Epidemiology, University of California- Irvine,
Irvine, CA; 105Department of Medical Genetics, Mayo Clinic, USA 106Department of Health
Sciences Research, Mayo Clinic, USA 107Department of Laboratory Medicine and Pathology, and
Health Sciences Research, Mayo Clinic, USA 108Unit of Genetic Susceptibility to Cancer,
Department of Experimental Oncology and Molecular Medicine, Fondazione IRCCS Istituto
Nazionale Tumori (INT), Milan, Italy 109IFOM, Fondazione Istituto FIRC di Oncologia Molecolare,
Milan, Italy 110Clinical Genetics Branch, Division of Cancer Epidemiology and Genetics, National
Cancer Institute, Rockville, MD 20852 111Samuel Lunenfeld Research Institute, Mount Sinai
Hospital, Toronto, Ontario M5G 1×5 112Departments of Molecular Genetics and Laboratory
Medicine and Pathobiology, University of Toronto, Ontario 113Department of Laboratory Medicine
and Pathobiology, University of Toronto, Ontario 114Ontario Cancer Genetics Network, Samuel
Lunenfeld Research Institute, Mount Sinai Hospital, Toronto, Ontario M5G 1×5 115Clinical
Genetics, Rigshospitalet, Copenhagen, Denmark 116Department of Clinical Genetics, Odense
University Hospital, Denmark 117Department of Clinical Genetics, Skejby Hospital, Aarhus,
Denmark 118Department of Clinical Genetics, Vejle Hospital; Denmark 119Section of Genetic
Oncology, Dept. of Laboratory Medicine, University and University Hospital of Pisa, Pisa, Italy
120The Hereditary Breast and Ovarian Cancer Research Group Netherlands 121Department of
Clinical Genetics, Academic Medical Center, Amsterdam, The Netherlands 122Department of
Epidemiology, Netherlands Cancer Institute, Amsterdam, The Netherlands 123Department of
Clinical Genetics, VU Medical Center, Amsterdam, The Netherlands 124Department of Genetics,
University Medical Center, Groningen University, Groningen, The Netherlands 125Department of
Clinical Genetics Leiden University Medical Center Leiden, The Netherlands 126Department of
Clinical Genetics and GROW, School for Oncology and Developmental Biology, MUMC,
Maastricht, The Netherlands 127Hereditary Cancer Clinic, Radboud University Nijmegen Medical
Center, The Netherlands 128Department of Medical Oncology, Family Cancer Clinic, Erasmus
University Medical Center, Rotterdam, The Netherlands 129Department of Medical Genetics,
University Medical Center Utrecht, The Netherlands
Abstract
Background—We previously reported significant associations between genetic variants in
insulin receptor substrate 1 (
IRS1)
and breast cancer risk in women carrying
BRCA1
mutations.
The objectives of this study were to investigate whether the
IRS1
variants modified ovarian cancer
risk and were associated with breast cancer risk in a larger cohort of
BRCA1
and
BRCA2
mutation carriers.
Methods—
IRS1
rs1801123, rs1330645, and rs1801278 were genotyped in samples from 36
centers in the Consortium of Investigators of Modifiers of
BRCA1/2
(CIMBA). Data were
analyzed by a retrospective cohort approach modeling the associations with breast and ovarian
cancer risks simultaneously. Analyses were stratified by
BRCA1
and
BRCA2
status and mutation
class in
BRCA1
carriers.
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Results—Rs1801278 (Gly972Arg) was associated with ovarian cancer risk for both
BRCA1
[Hazard ratio (HR) = 1.43; 95% CI: 1.06–1.92; p = 0.019] and
BRCA2
mutation carriers
(HR=2.21; 95% CI: 1.39–3.52, p=0.0008). For
BRCA1
mutation carriers, the breast cancer risk
was higher in carriers with class 2 mutations than class 1 (mutations (class 2 HR=1.86, 95% CI:
1.28–2.70; class 1 HR=0.86, 95%CI:0.69–1.09; p-for difference=0.0006). Rs13306465 was
associated with ovarian cancer risk in
BRCA1
class 2 mutation carriers (HR = 2.42; p = 0.03).
Conclusion—The
IRS1
Gly972Arg SNP, which affects insulin-like growth factor and insulin
signaling, modifies ovarian cancer risk in
BRCA1
and
BRCA2
mutation carriers and breast cancer
risk in
BRCA1
class 2 mutation carriers.
Impact—These findings may prove useful for risk prediction for breast and ovarian cancers in
BRCA1
and
BRCA2
mutation carriers.
Keywords
Breast cancer; Ovarian cancer;
BRCA1
and
BRCA2
mutation carriers; insulin receptor substrate
1; Insulin-like growth factor /insulin (IGF/INS) signaling
Introduction
Women who carry mutations in
BRCA1
or
BRCA2
are at a substantially increased risk of
developing breast and/or ovarian cancers. Lifetime risks for breast cancer range from 40–
87% and for ovarian cancer from 11–68% (1, 2). In addition to variability in the incidence of
breast and ovarian cancers, there is also variability in age at diagnosis and type of cancer in
the index case (proband) (1), even among women who carry the same
BRCA
mutation (3)
and among women in the same family (4). These observations suggest that cancer risk in
mutation carriers is modified by other genetic and/or environmental factors.
IRS1 is a docking protein for both the insulin-like growth factor receptor 1 (IGF1R) and the
insulin receptor (IR), and as such is central to a network of intracellular signaling molecules
(5). The IGF pathway plays crucial roles in regulating cell proliferation, differentiation, and
apoptosis through downstream signaling in the phosphoinositol-3-kinase pathway (PI3K)
and mitogen-activated protein kinase (MAPK) pathways (6). It is a key factor in the
development and progression of breast cancer [reviewed in (7–9)] and in ovarian cancer
(10). The insulin signaling pathway is primarily involved in regulation of metabolism, and a
growing body of data supports its significant roles in cancer initiation and progression (5,
11).
We previously reported significant associations between a haplotype and genetic variants
rs1801123 and rs1330645 in
IRS1
and risk of breast cancer in women carrying
BRCA1
with
a similar, but non-significant haplotype HR observed in women carrying
BRCA2
mutations
(12). The risk of developing ovarian cancer was not investigated. The objective of this study
was to investigate whether these three SNPs modify risk of developing ovarian cancer and
breast cancer in a large set of
BRCA1
and
BRCA2
mutation carriers within the Consortium
of Investigators of Modifiers of BRCA1/2 (CIMBA).
Methods
Subjects: BRCA1 and BRCA2 mutation carriers
Carriers of pathogenic mutations in
BRCA1
and
BRCA2
are from one of 36 centers from
North America, Europe, the Mediterranean, and Australia participating in CIMBA (13). The
participants were all enrolled under IRB-approved protocols at the respective institutions,
and all signed informed consent. Inclusion criteria for this analysis were female carriers of
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pathogenic
BRCA1
or
BRCA2
mutations who were 18 years or older at recruitment and
were of self-reported non-Hispanic white Caucasian ancestry. Information collected
included year of birth, mutation type including nucleotide position and base change, age at
last follow-up, age at breast and/or ovarian cancer diagnosis, and age or date at bilateral
prophylactic mastectomy or oophorectomy. Characteristics of the mutations carriers are
shown in the Supplemental Table.
Genotyping—The three SNPs, rs1801123, rs1801278, and rs1330645, were genotyped
either by 5' exonuclease Taqman assays (Applied Biosystems) run on an ABI9700 detection
system or single-base primer extension as part of a Sequenom iPLEX Gold assay run on a
Sequenom MassARRAY system (Table 1). To ensure consistency in genotyping,
genotyping centers were required to adhere to strict genotyping quality control criteria. We
included a minimum of 2% of the samples in duplicate, no template controls in every plate,
and a random mixture of affected and unaffected carriers. Samples that failed for two or
more of the SNPs genotyped (among those analysed in that genotyping round) were
excluded from the analysis. The genotype data for a given SNP and a given study were
included in the analysis only if the call rate was >95% after samples that failed at multiple
SNPs had been excluded. The concordance between duplicates had to be at least 98%. To
assess the accuracy of genotyping across genotyping centers, all centers genotyped 95 DNA
samples from a standard test plate (Coriell Institute) for all SNPs. If the genotyping was
inconsistent for more than one sample in the test plate, the study was excluded from the
analysis of that SNP. As an additional genotyping quality-control check, we also evaluated
the deviation from Hardy-Weinberg equilibrium (HWE) for unrelated subjects separately for
each SNP and study. Studies with a HWE p-value of less than 0.005 were excluded from the
analysis. If HWE p-values were in the range 0.005–0.05 we examined the genotyping cluster
plots; none revealed any unusual patterns and these studies were therefore included in all the
analyses. Within CIMBA, SNPs were selected to be genotyped in the full panel of carriers at
the time, or in a smaller set of carriers that were genotyped at the Queensland Institute of
Medical Research (QIMR). Thus, based on our previous result, SNP rs1801123 was selected
to be genotyped in all available
BRCA1
and
BRCA2
mutation carriers, whereas rs13306465
and rs1801278 were genotyped only in DNA stored at QIMR (Table 1).
Statistical analysis—Mutation carriers in CIMBA are mainly ascertained through
ongoing genetic testing programs primarily aimed at screening young affected individuals
for
BRCA1
and
BRCA2
mutations. Therefore, mutation carriers in our sample are not
randomly sampled with respect to their disease phenotype. To account for sampling, data
were analysed within a retrospective cohort framework, by modeling the retrospective
likelihood of the observed genotypes conditional on the disease phenotypes (14). To obtain
estimates of the risk ratios for both breast and ovarian cancers, and given the prior evidence
of variants in
IRS1
and association with breast cancer risk, analyses were performed within
a competing risk model in which breast and ovarian cancer risks were modelled
simultaneously (15). This has been shown to yield valid tests of association for both diseases
and to provide unbiased estimates of the risk ratios (15). In this model, each individual was
assumed to be at risk of developing either breast or ovarian cancer, and the probabilities of
developing each disease were assumed to be independent conditional on the underlying
genotype. Individuals were followed up to the age of the first breast or ovarian cancer
diagnosis and were considered to have developed the corresponding disease. No follow-up
was considered after the first cancer diagnosis. Individuals were censored for breast cancer
at the age of bilateral prophylactic mastectomy and for ovarian cancer at the age of bilateral
oophorectomy and in such circumstances were assumed to be unaffected for the
corresponding disease. The remaining individuals were censored at the age at last
observation and were assumed to be unaffected for both diseases. Individuals who were
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diagnosed with both breast and ovarian cancer at the same age were treated as ovarian
cancer cases. Models were implemented in the pedigree analysis software MENDEL (16).
Each woman was considered to be at risk of developing either breast or ovarian cancer by
assuming that the probabilities of developing each disease were independent, conditional on
the underlying genotype. Women with cancer were followed up to the age of the first breast
or ovarian cancer diagnosis and were considered affected with that cancer. No follow-up
was considered after the first cancer diagnosis. Individuals were censored for breast cancer
at the age of bilateral prophylactic mastectomy and for ovarian cancer at the age of bilateral
oophorectomy, and were assumed to be unaffected for the corresponding cancer. The
remaining individuals were censored at the age at last observation and were assumed to be
unaffected for both cancers. Breast and ovarian cancer incidences were assumed to depend
on the underlying SNP genotype through a Cox-proportional hazards model. The models
were parameterized in terms of the per-allele HR for effect of the minor allele at each SNP.
All analyses used calendar period- and cohort-specific incidences for
BRCA1
and
BRCA2
mutation carriers and were stratified by study-center and country of residence. A robust
variance-estimation approach was used to allow for non-independence among related
carriers (17, 18). Tests for difference in the log-HR estimates for class1 and class2 mutations
were based on a test statistic for the equality of two normally distributed random variables.
Results
The centers, number of samples from each center, and genotyping platforms used are shown
in Table 1. The number of mutation carriers by censoring event is shown in Table 2. SNP
rs1801278 (Gly972Arg) was significantly associated with ovarian cancer risk in both
BRCA1
and
BRCA2
mutation carriers (
BRCA1
: HR=1.43, 95% CI: 1.06–1.92, p = 0.019;
BRCA2
: HR 2.21, 95% CI: 1.39–3.52, p = 0.0008). There was no association of this SNP
with breast cancer risk within the overall unstratified sets of
BRCA1
and
BRCA2
mutation
carriers. SNPs rs13306465 and rs1801123 were not associated with breast or ovarian cancers
for either
BRCA1
or
BRCA2
mutation carriers.
For
BRCA1
, we also evaluated the SNP associations by mutation type based on the
predicted functional consequence (described in detail previously (19)). There were too few
BRCA2 carriers to stratify by mutation type. Class 1 mutations are predicted to result in a
reduced transcript or protein level due to nonsense mediated RNA decay, whereas class 2
mutations are likely to generate stable protein with potential residual or dominant negative
function. None of the SNPs were significantly associated with risk of developing breast or
ovarian cancers among
BRCA1
class 1 mutation carriers. However, among class 2 mutation
carriers, there was a significant association of rs1801278 with both risk of developing
ovarian cancer (HR = 2.17; 95% CI: 1.21–3.90; p = 0.009) and breast cancer (HR = 1.86;
95% CI: 1.28–2.70; p = 0.001). The HR estimates for class 2 mutations were significantly
higher than those for class 1 mutations, for breast cancer (breast cancer class 2 HR=1.86,
95% CI: 1.28–2.70; class 1 HR=0.86, 95%CI:0.69–1.09; p- for difference between class1
and class 2 mutations =0.0006). The difference was not significant by mutation class for risk
of ovarian cancer (ovarian cancer class 2 HR = 2.17, 95%CI: 1.21–3.90; class 1 HR=1.33,
95%CI:0.95–1.86; p-for difference between class 1 and class 2 mutations=0.15). There was
also evidence of an association between rs13306465 and risk of developing ovarian cancer
for
BRCA1
class 2 mutation carriers (HR=2.42; 95% CI: 1.06–5.56; p = 0.037).
Discussion
Previously, we identified a significant association of risk of breast cancer in
BRCA1
mutation carriers and a rare haplotype comprised of the three SNPs studied here (HR = 1.43;
95% CI: 1.06–1.95; p = 0.021) (12). A similar, but non-significant HR of 1.52 (95% CI: .
Ding et al. Page 7
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99–2.32; p = 0.055) was observed in
BRCA2
carriers. For rs13306465 and rs1801123,
individuals carrying at least one variant allele experienced a 44% (HR=1.44; 95% CI: 1.07–
1.94) and 37% (HR=1.37; 95% CI: 1.11–1.69) higher risk of breast cancer relative to wild-
type carriers, respectively. There was no individual association of the rs1801278
(Gly972Arg) variant and breast cancer risk. In this current study, we expanded these
analyses and investigated, for the first time, whether these three
IRS1
SNPs were associated
with ovarian cancer risk, as well as with breast cancer risk in this larger cohort of
BRCA1
and
BRCA2
mutation carriers.
We found that rs1801278 (Gly972Arg) in
IRS1
was significantly associated with ovarian
cancer risk for both
BRCA1
and
BRCA2
mutation carriers. In analyses stratified by
mutation function, the ovarian cancer risk for
BRCA1
mutation carriers was especially
pronounced in women who carried mutations predicted to retain residual BRCA1 function
(class 2 mutations) (HR = 2.2; 95% CI: 1.2–3.9; p= 0.009). There was also a significant
association of this SNP with breast cancer risk (HR = 1.86), but limited to women who
carried class 2 mutations, with no discernable effect on breast cancer risk in women who
carried class 1 mutations. There was marginal evidence of association between rs13306465
and ovarian cancer risk for
BRCA1
class 2 mutation carriers. The previous statistically
significant associations of rs13306465 and rs1801123 and breast cancer risk in
BRCA1
mutation carriers were not observed in this larger set of mutation carriers. Additional
carriers within CIMBA should be tested to further refine the estimates of risk for the
IRS1
Gly972Arg mutation.
There have been a limited number of epidemiologic studies of the association of sporadic
breast cancer risk and genetic variation in
IRS1
(20, 21). Rs1801278 was associated with
postmenopausal breast cancer in Hispanic, but not non-Hispanic whites in the Southwest US
(21). Two other
IRS1
SNPs investigated in the Cancer Prevention II study were not
associated with risk in postmenopausal breast cancer (20). There have been no reports of
studies investigating the association of SNPs in
IRS1
and ovarian cancer. From a meta-
analysis of 11 studies, rs1801278 has been associated with an increased risk of developing
polycystic ovary syndrome (22).
Gly972 (rs1801278) in the IRS1 protein is located between two tyrosine phosphorylation
sites involved in binding downstream effectors including the regulatory p85 subunit of PI3K
and Grb2 (23). The Arg972 variant results in altered function of the IRS1 protein, leading to
a decreased ability of IRS1 to bind the p85 subunit of PI3K
in vitro
. In two studies of 32D
mouse myeloid progenitor cells lacking IRS-1 (32D-IR cells), the Gly972Arg variant
resulted in decreased binding to the p85 subunit of PI3K by 25% and 42% and decreased
PI3K activity by 36% and 39%, respectively (24, 25). Studies of the insulin signaling
pathway in both cultured cells and in transgenic mice have shown that this variant is
associated with impaired insulin-stimulated signaling, likely contributing to insulin
resistance (24, 26, 27). Interestingly, epidemiologic data have long suggested that insulin
resistance might be a breast cancer risk factor, but study results have been inconsistent. In a
2007 review of all the available epidemiology studies, Xue and Michael concluded that
having type 2 diabetes was modestly associated with the risk of breast cancer (28).
IRS1 is partially regulated through a negative feedback loop in the downstream PI3K
signaling pathway. Insulin activates jun nuclear kinase (JNK), extraceullar signal-regulated
kinase (ERK), protein kinase C (PKC), and mammalian target of rapamycin (mTOR) which
then can induce the phosphorylation of IRS1 at specific sites inhibiting its ability for
downstream signaling (29). In experiments in MCF-7 breast cancer cells, IGF-1 was shown
to induce IRS-1 degradation which could be blocked by PI3K inhibitors, suggesting a direct
negative-feedback mechanism of PI3K that degrades IRS-1 and thus blocks further IGF
Ding et al. Page 8
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signaling (29). It is possible that with decreased PI3K binding, less IRS-1 is degraded
resulting in longer signaling through both PI3K and RAS-ERK pathways. Alternatively,
decreased binding of IRS-1 to PI3K may allow for activation of the pathway by other
ligands that are not regulated through a negative feedback mechanism, thereby increasing
downstream signaling (30).
BRCA1 interacts directly with the IRS-1 promoter to inhibit its activity (31), and with
induction of BRCA1, there was a 2- to 3-fold decrease of IRS-1 mRNA and protein levels,
as well as a decrease in the phosphorylation level of AKT, a downstream target of IRS-1
(31). In the current study, we found that Gly972Arg conferred a higher risk of ovarian
cancer for
BRCA1
mutation carriers with class 2 mutations (predicted to produce a stable
aberrant protein) compared to class1 mutations (predicted to undergo nonsense-mediated
decay), and modified breast cancer risk only in class 2
BRCA1
carriers. As class 1
BRCA1
mutations result in loss of the BRCA1 protein, this would result in failure to inhibit IRS-1
levels such that levels of IRS1 may be elevated in women carrying class 1 mutations. From
this, it follows that the effects of the Gly972Arg may be attenuated in class 1 mutation
carriers because of the increased levels of IRS1, and that, the reduction in signaling from the
Arg972 variant in IRS1 only plays a role in
BRCA1
class 2 and
BRCA2
carriers for whom
stable BRCA1 protein is still suppressing IRS1 expression. To test this hypothesis, future
experiments can be performed to evaluate the effects of the IRS1 Gly972Arg on PI3K
signaling in carriers of both class 1 and 2
BRCA1
mutations. It is not known whether the
effect we are observing is due to signaling through insulin, or through IGF or through both.
In summary, the
IRS1
Gly972Arg SNP, known to affect both IGF and INS signaling,
significantly modifies risk of developing ovarian cancer in both
BRCA1
and
BRCA2
mutation carriers with more than a two-fold increased risk, and of developing breast cancer
in
BRCA1
class 2 mutation carriers with an almost two-fold increased risk. These findings
may prove useful for risk prediction for breast and ovarian cancers in
BRCA1
and
BRCA2
mutation carriers. Given the known interactions between IRS1 and BRCA1, studies to
investigate response to therapies targeted to the PI3K-AKT downstream signaling pathways
in
BRCA
-related breast and ovarian cancers may have merit.
Supplementary Material
Refer to Web version on PubMed Central for supplementary material.
Acknowledgments
Epidemiological study of BRCA1 & BRCA2 mutation carriers (EMBRACE): Douglas F. Easton is the PI of the
study. EMBRACE Collaborating Centres are: Coordinating Centre, Cambridge: Susan Peock, Debra Frost, Steve D.
Ellis, Elena Fineberg, Radka Platte. North of Scotland Regional Genetics Service, Aberdeen: Zosia Miedzybrodzka,
Helen Gregory. Northern Ireland Regional Genetics Service, Belfast: Patrick Morrison, Lisa Jeffers. West Midlands
Regional Clinical Genetics Service, Birmingham: Trevor Cole, Kai-ren Ong, Jonathan Hoffman. South West
Regional Genetics Service, Bristol: Alan Donaldson, Margaret James. East Anglian Regional Genetics Service,
Cambridge: Marc Tischkowitz, Joan Paterson, Sarah Downing, Amy Taylor. Medical Genetics Services for Wales,
Cardiff: Alexandra Murray, Mark T. Rogers, Emma McCann. St James's Hospital, Dublin & National Centre for
Medical Genetics, Dublin: M. John Kennedy, David Barton. South East of Scotland Regional Genetics Service,
Edinburgh: Mary Porteous, Sarah Drummond. Peninsula Clinical Genetics Service, Exeter: Carole Brewer, Emma
Kivuva, Anne Searle, Selina Goodman, Kathryn Hill. West of Scotland Regional Genetics Service, Glasgow:
Rosemarie Davidson, Victoria Murday, Nicola Bradshaw, Lesley Snadden, Mark Longmuir, Catherine Watt, Sarah
Gibson, Eshika Haque, Ed Tobias, Alexis Duncan. South East Thames Regional Genetics Service, Guy's Hospital
London: Louise Izatt, Chris Jacobs, Caroline Langman. North West Thames Regional Genetics Service, Harrow:
Huw Dorkins. Leicestershire Clinical Genetics Service, Leicester: Julian Barwell. Yorkshire Regional Genetics
Service, Leeds: Julian Adlard, Gemma Serra-Feliu. Cheshire & Merseyside Clinical Genetics Service, Liverpool:
Ian Ellis, Catherine Houghton. Manchester Regional Genetics Service, Manchester: D Gareth Evans, Fiona Lalloo,
Jane Taylor. North East Thames Regional Genetics Service, NE Thames, London: Lucy Side, Alison Male, Cheryl
Berlin. Nottingham Centre for Medical Genetics, Nottingham: Jacqueline Eason, Rebecca Collier. Northern
Ding et al. Page 9
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NIH-PA Author Manuscript NIH-PA Author Manuscript NIH-PA Author Manuscript
Clinical Genetics Service, Newcastle: Fiona Douglas, Oonagh Claber, Irene Jobson. Oxford Regional Genetics
Service, Oxford: Lisa Walker, Diane McLeod, Dorothy Halliday, Sarah Durell, Barbara Stayner. The Institute of
Cancer Research and Royal Marsden NHS Foundation Trust: Ros Eeles, Susan Shanley, Nazneen Rahman, Richard
Houlston, Elizabeth Bancroft, Elizabeth Page, Audrey Ardern-Jones, Kelly Kohut, Jennifer Wiggins, Elena Castro,
Emma Killick, Sue Martin, Gillian Rea, Anjana Kulkarni. North Trent Clinical Genetics Service, Sheffield: Jackie
Cook, Oliver Quarrell, Cathryn Bardsley. South West Thames Regional Genetics Service, London: Shirley
Hodgson, Sheila Goff, Glen Brice, Lizzie Winchester, Charlotte Eddy, Vishakha Tripathi, Virginia Attard, Anna
Lehmann. Wessex Clinical Genetics Service, Princess Anne Hospital, Southampton: Diana Eccles, Anneke
Lucassen, Gillian Crawford, Donna McBride, Sarah Smalley. Fox Chase Cancer Center (FCCC): we thank Ms.
JoEllen Weaver for her help collecting patient data and samples. The Baltic Familial Breast and Ovarian Cancer
Consortium (BFBOCC, Latvia and Lithuania): we acknowledge Laima Tikhomirova (Latvian Biomedical Research
and Study Centre) for providing data and DNA samples. UK and Gilda Radner Familial Ovarian Cancer Registries
(UKGRFOCR): we thank Paul Pharoah, Simon Gayther, Carole Pye, Patricia Harrington and Eva Wozniak for their
contributions towards the UKFOCR. We acknowledge the Roswell Park Alliance Foundation for their continued
support of the Gilda Radner Ovarian Family Cancer Registry. GRFOCR would like to acknowledge Kirsten
Moysich (Department of Cancer Prevention and Control) and Kunle Odunsi (Departments Gynecologic Oncology
and Immunology). Helsinki Breast Cancer Study (HEBCS): we thank Taru A. Muranen, Tuomas Heikkinen and
RN Irja Erkkilä for their help with the HEBCS data and samples. Interdisciplinary Health Research International
Team Breast Cancer Susceptibility (INHERIT BRCAs): we would like to thank Dr Martine Dumont and Martine
Tranchant (Cancer Genomics Laboratory, CRCHUQ) for sample management. Kathleen Cuningham Consortium
for Research into Familial Breast Cancer (KCONFAB): we thank Heather Thorne, Eveline Niedermayr, all the
kConFab research nurses and staff, the heads and staff of the Family Cancer Clinics, and the Clinical Follow Up
Study. The Hereditary Breast and Ovarian Cancer Research Group Netherlands (HEBON): HEBON Collaborating
Centers: Coordinating center: Netherlands Cancer Institute, Amsterdam, NL: F.B.L. Hogervorst, S. Verhoef, F.E.
van Leeuwen, M.A. Rookus, M. Schmidt; Erasmus Medical Center, Rotterdam, NL: M. Collée, A.M.W. van den
Ouweland, M.J. Hooning, C. Seynaeve; Leiden University Medical Center, NL, Leiden: C.J. van Asperen, J.T.
Wijnen, R.A. Tollenaar, P. Devilee, T.C.T.E.F. van Cronenburg; Radboud University Nijmegen Medical Center,
Nijmegen, NL: C.M. Kets, M. Nelen; University Medical Center Utrecht, Utrecht, NL: M.G. Ausems, R.B. van der
Luijt; Amsterdam Medical Center, NL: C.M. Aalfs, T.A. van Os; VU University Medical Center, Amsterdam, NL:
J.J.P. Gille, Q. Waisfisz, E.J. Meijers-Heijboer; University Hospital Maastricht, Maastricht, NL: E.B. Gomez-
Garcia, M.J. Blok; University Medical Center Groningen University, NL: J.C. Oosterwijk, A.H. van der Hout, M.J.
Mourits, G.H. de Bock; The Netherlands Foundation for the detection of hereditary tumours, Leiden, NL: H.F.
Vasen. At OSU, we thank Kevin Sweet, Leigha Senter, Caroline Craven and Michelle O'Connor for patient accrual
and data management, the Human Genetics Sample Bank for sample preparation and the OSU Nucleic Acids
Shared Resource for genotyping plate reads.
Grant Support Beckman Research Institute of the City of Hope (BRICOH) study was supported by NIH
RO1CA74415 (S.L.N.) and P30 CA033752. S.L.N. is the Morris and Horowitz Families Endowed Professor. Sheba
Medical Center Study (SMC) was in part sponsored by a grant from the Israel cancer association to E.F. on behalf
of the Israeli consortium of inherited breast cancer. University of Pennsylvania (UPENN) study was supported by
R01-CA083855 and R01-CA102776 (T.R.R.) Spanish National Cancer Center (CNIO) study has been partially
funded by Mutua Madrileña Foundation, “Red de Investigación en Cáncer RD06/0020/1160” and Spanish Ministry
of Science and Innovation (FIS PI08 1120 and SAF2010-20493). Epidemiological study of BRCA1 & BRCA2
mutation carriers (EMBRACE) is supported by Cancer Research UK Grants C1287/A10118 and C1287/A11990.
D.G.E. and F.L. are supported by an NIHR grant to the Biomedical Research Centre, Manchester. The Investigators
at The Institute of Cancer Research and The Royal Marsden NHS Foundation Trust are supported by an NIHR
grant to the Biomedical Research Centre at The Institute of Cancer Research and The Royal Marsden NHS
Foundation Trust. R. E. and E. B. are supported by Cancer Research UK Grant C5047/A8385.Fox Chase Cancer
Center (FCCC) study was supported by R01CA140323, U01CA69631, and 5U01CA113916 (A.K.G.) .Copenhagen
Breast Cancer Study (CBCS) was supported by the NEYE Foundation.Gynecologic Oncology Group (GOG) was
supported through funding provided by both intramural (Clinical Genetics Branch, DCEG) and extramural
(Community Oncology and Prevention Trials Program – COPTRG) NCI programs, and was based in GOG's
Cancer Prevention and Control Committee. N.N. Petrov Institute of Oncology (NNPIO) study is supported by the
Russian Foundation for Basic Research (grants 10-04-92110, 10-04-92601 and 11-04-00227), the Federal Agency
for Science and Innovations (contract 02.740.11.0780) and through a Royal Society International Joint Grant
(JP090615).The Baltic Familial Breast and Ovarian Cancer Consortium (BFBOCC, Latvia and Lithuania) study is
supported by the Research Council of Lithuania grant LIG-19/2010 to R.J..Institut Català d'Oncologia(ICO):
Asociación Española Contra el Cáncer, Spanish Health Research Fund; Carlos III Health Institute; Catalan Health
Institute and Autonomous Government of Catalonia. Contract grant numbers: ISCIIIRETIC RD06/0020/1051,
PI10/01422, PI10/31488 and 2009SGR290.UK and Gilda Radner Familial Ovarian Cancer Registries
(UKGRFOCR) study was supported by a project grant from CRUK (P.P.). Women's Cancer Program at the Samuel
Oschin Comprehensive Cancer Institute (WCP) is supported by American Cancer Society (120950-
SIOP-06-258-06-COUN).The German Consortium of Hereditary Breast and Ovarian Cancer (GC-HBOC) was
supported by a grant of the German Cancer Aid (DKH 109076). Helsinki Breast Cancer Study (HEBCS) was
supported by the Helsinki University Central Hospital Research Fund, Academy of Finland (132473), the Finnish
Cancer Society, and the Sigrid Juselius Foundation. Interdisciplinary Health Research International Team Breast
Ding et al. Page 10
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NIH-PA Author Manuscript NIH-PA Author Manuscript NIH-PA Author Manuscript
Cancer Susceptibility (INHERIT BRCAs) was supported by the Canadian Institutes of Health Research for the
“CIHR Team in Familial Risks of Breast Cancer” program and by the Canadian Breast Cancer Research Alliance-
grant #019511. J.S. is Chairholder of the Canada Research Chair in Oncogenetics. The Breast Cancer Family
Registry (BCFR) was supported by the National Cancer Institute, National Institutes of Health under RFA #
CA-06-503 and through cooperative agreements with members of the BCFR and Principal Investigators, including
Cancer Care Ontario (U01 CA69467), Cancer Prevention Institute of California (U01 CA69417), Columbia
University (U01 CA69398), Fox Chase Cancer Center (U01 CA69631), Huntsman Cancer Institute (U01
CA69446), and University of Melbourne (U01 CA69638). The content of this manuscript does not necessarily
reflect the views or policies of the National Cancer Institute or any of the collaborating centers in the BCFR, nor
does mention of trade names, commercial products, or organizations imply endorsement by the US Government or
the BCFR. The Australian BCFR was also supported by the National Health and Medical Research Council of
Australia, the New South Wales Cancer Council, the Victorian Health Promotion Foundation (Australia) and the
Victorian Breast Cancer Research Consortium. M.C.S. is a NHMRC Senior Research Fellow and a Victorian Breast
Cancer Research Consortium Group Leader. J.L.H. is an Australia Fellow of the NHMRC and a Victorian Breast
Cancer Research Consortium Group Leader. Carriers at FCCC were also identified with support from National
Institutes of Health grants P01 CA16094 and R01 CA22435. The New York BCFR was also supported by National
Institutes of Health grants P30 CA13696 and P30 ES009089. The Utah BCFR was also supported by the National
Center for Research Resources and the National Center for Advancing Translational Sciences, NIH Grant UL1
RR025764, and by Award Number P30 CA042014 from the National Cancer Institute. Kathleen Cuningham
Consortium for Research into Familial Breast Cancer (KCONFAB) is funded by NHMRC grants 145684, 288704
and 454508. A.B.S. is supported by an NHMRC Senior Research Fellowship, and G-CT by an NHMRC Senior
Principal Research Fellowship. National Cancer Institute (NCI): P.L.M., J.T.L. and M.H.G. were funded by the
Intramural Research Program of the US National Cancer Institute at the National Institutes of Health, with
infrastructure support from contracts NO2-CP-11019-50 and N02-CP-65504 with Westat, Inc, Rockville, MD.
Mayo Clinic Study (MAYO) was supported by NIH R01278978 and grants from the Breast cancer Research
Foundation and the Komen Foundation for the Cure.The Hereditary Breast and Ovarian Cancer Research Group
Netherlands (HEBON) study is supported by the Dutch Cancer Society grants NKI1998-1854, NKI2004-3088,
NKI2007-3756 and the ZonMW grant 91109024. OSU CCG: This work was funded by the OSU Comprehensive
Cancer Center.
References
1. Antoniou A, Pharoah PD, Narod S, Risch HA, Eyfjord JE, Hopper JL, et al. Average risks of breast
and ovarian cancer associated with BRCA1 or BRCA2 mutations detected in case Series unselected
for family history: a combined analysis of 22 studies. Am J Hum Genet. 2003; 72:1117–30.
[PubMed: 12677558]
2. Ford D, Easton DF, Stratton M, Narod S, Goldgar D, Devilee P, et al. Genetic heterogeneity and
penetrance analysis of the BRCA1 and BRCA2 genes in breast cancer families. The Breast Cancer
Linkage Consortium. Am J Hum Genet. 1998; 62:676–89. [PubMed: 9497246]
3. Thorlacius S, Sigurdsson S, Bjarnadottir H, Olafsdottir G, Jonasson JG, Tryggvadottir L, et al.
Study of a single BRCA2 mutation with high carrier frequency in a small population. Am J Hum
Genet. 1997; 60:1079–84. [PubMed: 9150155]
4. Vogl FD, Badzioch MD, Steele L, Neuhausen SL, Goldgar DE. Risks of cancer due to a single
BRCA1 mutation in an extended Utah kindred. Fam Cancer. 2007; 6:63–71. [PubMed: 17051349]
5. Pollak M. Insulin and insulin-like growth factor signalling in neoplasia. Nat Rev Cancer. 2008;
8:915–28. [PubMed: 19029956]
6. Yu H, Rohan T. Role of the insulin-like growth factor family in cancer development and
progression. J Natl Cancer Inst. 2000; 92:1472–89. [PubMed: 10995803]
7. Sachdev D, Yee D. The IGF system and breast cancer. Endocr Relat Cancer. 2001; 8:197–209.
[PubMed: 11566611]
8. Jerome L, Shiry L, Leyland-Jones B. Deregulation of the IGF axis in cancer: epidemiological
evidence and potential therapeutic interventions. Endocr Relat Cancer. 2003; 10:561–78. [PubMed:
14713267]
9. Pollak MN, Schernhammer ES, Hankinson SE. Insulin-like growth factors and neoplasia. Nat Rev
Cancer. 2004; 4:505–18. [PubMed: 15229476]
10. Yee D, Morales FR, Hamilton TC, Von Hoff DD. Expression of insulin-like growth factor I, its
binding proteins, and its receptor in ovarian cancer. Cancer Res. 1991; 51:5107–12. [PubMed:
1717138]
Ding et al. Page 11
Cancer Epidemiol Biomarkers Prev
. Author manuscript; available in PMC 2013 February 01.
NIH-PA Author Manuscript NIH-PA Author Manuscript NIH-PA Author Manuscript
11. Gallagher EJ, LeRoith D. Minireview: IGF, Insulin, and Cancer. Endocrinology. 152:2546–51.
[PubMed: 21540285]
12. Neuhausen SL, Brummel S, Ding YC, Singer CF, Pfeiler G, Lynch HT, et al. Genetic variation in
insulin-like growth factor signaling genes and breast cancer risk among BRCA1 and BRCA2
carriers. Breast Cancer Res. 2009; 11:R76. [PubMed: 19843326]
13. Chenevix-Trench G, Milne RL, Antoniou AC, Couch FJ, Easton DF, Goldgar DE. An international
initiative to identify genetic modifiers of cancer risk in BRCA1 and BRCA2 mutation carriers: the
Consortium of Investigators of Modifiers of BRCA1 and BRCA2 (CIMBA). Breast Cancer Res.
2007; 9:104. [PubMed: 17466083]
14. Antoniou AC, Sinilnikova OM, Simard J, Leone M, Dumont M, Neuhausen SL, et al. RAD51
135G-->C modifies breast cancer risk among BRCA2 mutation carriers: results from a combined
analysis of 19 studies. Am J Hum Genet. 2007; 81:1186–200. [PubMed: 17999359]
15. Barnes DR, Lee A, Investigators E, Investigators k, Easton DF, Anoniou AC. Evaluation of
Association Methods for Analysing Modifiers of Disease Risk in Carriers of High-Risk Mutations.
Genetic Epidemiology. 2012 In Press.
16. Lange K, Weeks D, Boehnke M. Programs for Pedigree Analysis: MENDEL, FISHER, and
dGENE. Genet Epidemiol. 1988; 5:471–2. [PubMed: 3061869]
17. Huber PJ. The behavior of maximum likelihood estimates under non-standard conditions.
Proceedings of the Fifth Berkley Symposium in Mathematical Statistics and Probability. 1967;
1:221–233.
18. Boos DD. On generalized score tests. American Statistician. 1992; 46:327–333.
19. Antoniou AC, Spurdle AB, Sinilnikova OM, Healey S, Pooley KA, Schmutzler RK, et al.
Common breast cancer-predisposition alleles are associated with breast cancer risk in BRCA1 and
BRCA2 mutation carriers. Am J Hum Genet. 2008; 82:937–48. [PubMed: 18355772]
20. Feigelson HS, Teras LR, Diver WR, Tang W, Patel AV, Stevens VL, et al. Genetic variation in
candidate obesity genes ADRB2, ADRB3, GHRL, HSD11B1, IRS1, IRS2, and SHC1 and risk for
breast cancer in the Cancer Prevention Study II. Breast Cancer Res. 2008; 10:R57. [PubMed:
18611262]
21. Slattery ML, Sweeney C, Wolff R, Herrick J, Baumgartner K, Giuliano A, et al. Genetic variation
in IGF1, IGFBP3, IRS1, IRS2 and risk of breast cancer in women living in Southwestern United
States. Breast Cancer Res Treat. 2007; 104:197–209. [PubMed: 17051426]
22. Ioannidis A, Ikonomi E, Dimou NL, Douma L, Bagos PG. Polymorphisms of the insulin receptor
and the insulin receptor substrates genes in polycystic ovary syndrome: a Mendelian
randomization meta-analysis. Mol Genet Metab. 99:174–83. [PubMed: 19926323]
23. Mardilovich K, Pankratz SL, Shaw LM. Expression and function of the insulin receptor substrate
proteins in cancer. Cell Commun Signal. 2009; 7:14. [PubMed: 19534786]
24. Almind K, Inoue G, Pedersen O, Kahn CR. A common amino acid polymorphism in insulin
receptor substrate-1 causes impaired insulin signaling. Evidence from transfection studies. J Clin
Invest. 1996; 97:2569–75. [PubMed: 8647950]
25. Yoshimura R, Araki E, Ura S, Todaka M, Tsuruzoe K, Furukawa N, et al. Impact of natural IRS-1
mutations on insulin signals: mutations of IRS-1 in the PTB domain and near SH2 protein binding
sites result in impaired function at different steps of IRS-1 signaling. Diabetes. 1997; 46:929–36.
[PubMed: 9166661]
26. Hribal ML, Federici M, Porzio O, Lauro D, Borboni P, Accili D, et al. The Gly-->Arg972 amino
acid polymorphism in insulin receptor substrate-1 affects glucose metabolism in skeletal muscle
cells. J Clin Endocrinol Metab. 2000; 85:2004–13. [PubMed: 10843189]
27. Hribal ML, Tornei F, Pujol A, Menghini R, Barcaroli D, Lauro D, et al. Transgenic mice
overexpressing human G972R IRS-1 show impaired insulin action and insulin secretion. J Cell
Mol Med. 2008; 12:2096–106. [PubMed: 18208559]
28. Xue F, Michels KB. Diabetes, metabolic syndrome, and breast cancer: a review of the current
evidence. Am J Clin Nutr. 2007; 86:s823–35. [PubMed: 18265476]
29. Lee AV, Gooch JL, Oesterreich S, Guler RL, Yee D. Insulin-like growth factor I-induced
degradation of insulin receptor substrate 1 is mediated by the 26S proteasome and blocked by
phosphatidylinositol 3'-kinase inhibition. Mol Cell Biol. 2000; 20:1489–96. [PubMed: 10669726]
Ding et al. Page 12
Cancer Epidemiol Biomarkers Prev
. Author manuscript; available in PMC 2013 February 01.
NIH-PA Author Manuscript NIH-PA Author Manuscript NIH-PA Author Manuscript
30. Metz HE, Houghton AM. Insulin receptor substrate regulation of phosphoinositide 3-kinase. Clin
Cancer Res. 17:206–11. [PubMed: 20966354]
31. Shukla V, Coumoul X, Cao L, Wang RH, Xiao C, Xu X, et al. Absence of the full-length breast
cancer-associated gene-1 leads to increased expression of insulin-like growth factor signaling axis
members. Cancer Res. 2006; 66:7151–7. [PubMed: 16849561]
Ding et al. Page 13
Cancer Epidemiol Biomarkers Prev
. Author manuscript; available in PMC 2013 February 01.
NIH-PA Author Manuscript NIH-PA Author Manuscript NIH-PA Author Manuscript
NIH-PA Author Manuscript NIH-PA Author Manuscript NIH-PA Author Manuscript
Ding et al. Page 14
Table 1
Number of eligible
BRCA1
and
BRCA2
mutation carriers by study group, genotyped for at least one of the three SNPs
Study Country SNPs genotyped*BRCA1, N BRCA2, N Genotyping platform
BCFR Australia, Canada, USA rs1801123 504 363 TaqMan
BFBOCC Latvia, Lithuania rs1801123 97 0 TaqMan
CBCS Denmark rs1801123 193 98 TaqMan
CNIO Spain,Greece rs1801123 201 245 TaqMan
CONSIT TEAM Italy rs1801123 738 469 TaqMan
DKFZ Germany rs1801123 67 27 TaqMan
DNA HEBON The Netherlands All 3 SNPs 801 295 iPlex
EMBRACE U.K. and EIRE All 3 SNPs 997 840 iPlex
FCCC USA All 3 SNPs 81 54 iPlex
GC-HBOC Germany rs1801123 801 398 TaqMan
GEMO France, USA rs1801123 1103 560 TaqMan
GEORGETOWN USA All 3 SNPs 30 16 TaqMan, iPlex
GOG USA rs1801123 380 266 TaqMan
HEBCS Finland rs1801123 103 104 TaqMan
ICO Spain rs1801123 113 117 TaqMan
IHCC Poland rs1801123 796 0 TaqMan
ILUH Iceland All 3 SNPs 0 133 iPlex
INHERIT Quebec rs1801123 73 82 TaqMan
IOVHBOCS Italy rs1801123 119 111 TaqMan
KCONFAB Australia All 3 SNPs 593 489 iPlex
MAGIC USA All 3 SNPs 438 278 TaqMan
MAYO USA All 3 SNPs 231 126 iPlex
MSKCC USA rs1801123 293 234 TaqMan
MUV Austria All 3 SNPs 295 125 TaqMan, iPlex
NCI USA rs1801123 260 74 TaqMan
NNPIO Russia rs1801123 88 0 TaqMan
OCGN Canada rs1801123 220 172 TaqMan
OSU CCG USA rs1801123 90 59 TaqMan
Cancer Epidemiol Biomarkers Prev
. Author manuscript; available in PMC 2013 February 01.
NIH-PA Author Manuscript NIH-PA Author Manuscript NIH-PA Author Manuscript
Ding et al. Page 15
Study Country SNPs genotyped*BRCA1, N BRCA2, N Genotyping platform
OUH Denmark rs1801123 264 195 TaqMan
PBCS Italy All 3 SNPs 90 56 iPlex
SMC Israel rs1801123 396 193 TaqMan
SWE-BRCA Sweden All 3 SNPs 533 175 iPlex
UCSF USA rs1801123 46 29 TaqMan
UKGRFOCR UK, USA rs1801123 168 34 TaqMan
UPENN USA All 3 SNPs 313 152 iPlex
WCP USA rs1801123 169 77 TaqMan
*
Where it states all three SNPs, rs1801123, rs13306465, and rs1801278 were genotyped. For the other sites, only rs1801123 was genotyped.
Cancer Epidemiol Biomarkers Prev
. Author manuscript; available in PMC 2013 February 01.
NIH-PA Author Manuscript NIH-PA Author Manuscript NIH-PA Author Manuscript
Ding et al. Page 16
Table 2
Hazard ratios (HR) from analyses under a competing risk model for breast and ovarian cancers.
Ovarian cancer Breast cancer
SNP Unaffected Ovarian cancer Breast cancer Per allele HR 95%CI P-value*Per allele HR 95% CI P-value*
N MAF+ N MAF N MAF
BRCA1
rs1801123 3922 0.1 1436 0.1 5589 0.11 0.94 0.82–1.08 0.36 1.04 0.96–1.13 0.36
rs13306465 1549 0.03 405 0.04 1942 0.04 1.05 0.72–1.53 0.79 1.12 0.92–1.37 0.26
rs1801278 1533 0.05 395 0.08 1905 0.06 1.43 1.06–1.92 0.019 1.01 0.83–1.23 0.91
BRCA1- Class1
rs1801123 2750 0.11 1034 0.1 3551 0.12 0.87 0.74–1.02 0.087 1.04 0.94–1.15 0.42
rs13306465 1171 0.03 331 0.03 1370 0.04 0.83 0.52–1.30 0.41 1.1 0.87–1.38 0.44
rs1801278 1162 0.06 324 0.08 1348 0.05 1.33 0.95–1.86 0.092 0.87 0.69–1.09 0.22
BRCA1- Class2
rs1801123 940 0.1 341 0.11 1605 0.1 1.3 0.99–1.71 0.057 1.04 0.88–1.24 0.62
rs13306465 250 0.04 57 0.06 354 0.03 2.42 1.06–5.56 0.037 0.99 0.54–1.82 0.97
rs1801278 231 0.03 54 0.07 346 0.07 2.17 1.21–3.90 0.009 1.86 1.28–2.70 0.0011
BRCA2
rs1801123 2449 0.1 411 0.11 3457 0.1 1 0.77–1.30 0.97 0.94 0.84–1.06 0.33
rs13306465 961 0.04 126 0.03 1213 0.03 0.98 0.41–2.38 0.97 1 0.72–1.37 0.98
rs1801278 944 0.06 120 0.11 1168 0.07 2.21 1.39–3.52 0.0008 1.16 0.91–1.49 0.23
rs1801123 alleles: A, G (minor)
rs13306465 alleles: A, G (minor)
rs1801278 alleles: G, A (minor)
+
MAF = minor allele frequency
*
Per-allele trend test
Cancer Epidemiol Biomarkers Prev
. Author manuscript; available in PMC 2013 February 01.
