ArticlePDF Available

Benzene induces rapid leukemic transformation after prolonged hematotoxicity in a murine model

Authors:
  • Beijing institute of genomic, CAS

Figures

Benzene induces rapid leukemic transformation after prolonged hematotoxicity in transplant Mll–Af9 murine model a Outline of experiments. Transplant Mll–Af9 mice were obtained by transplanting bone marrow (BM) and spleen cells from an 8-weeks-old Mll–Af9 knock-in mouse (preleukemia state, CD45.2⁺) and equal BM cells from an 8-weeks-old B6.SJL mouse (normal, CD45.1⁺) into B6.SJL recipient mice. After 3 weeks of reconstitution, these mice were randomly divided into benzene exposure group (Target concentration: 1000 mg/m³ or 308 ppm. Conversion factor: 20 °C, 101 kPa 1 ppm = 3.25 mg/m³). (n = 25) and air control group (0 mg/m³, n = 25) for lifetime exposure. The actual concentration in the chambers is 972 mg/m³ or 299 ppm. See methods. Peripheral blood (PB) parameters and the number of preleukemic (CD45.2⁺) cells in PB were analyzed once a week. b Growth pattern of white blood cells (WBCs) and preleukemic cells during the whole 28 weeks of exposure. Preleukemic cells in PB were identified by flow cytometry analysis (FACS). The count of WBCs or preleukemic cells was significantly lower during the first 20 weeks in benzene-exposed mice than in air control mice (P < 0.05). c Growth pattern of preleukemic cells prior to the time of death. The fold-change of preleukemic cells number in benzene-exposed mice (63-fold) and air control mice (16-fold) during the last 4 weeks before death are marked on the graph. Fold-change = Y/X−1. The Y represents the number of preleukemic cells in mice at 4 weeks prior to death and the X represents the number of preleukemic cells in mice at the stage of impending death. d, e Red blood cell (RBC) counts and Platelet (PLT) counts in the PB of Mll–Af9 mice during the whole 28 weeks of exposure. Data are presented as the median with interquartile range (b, c) or the mean with SEM (d, e). P-values in b and c were obtained using the Wilcoxon rank-sum test. P-values in d and e were obtained using the unpaired Student’s t-test. Asterisk Means that the difference between benzene group and air control group was significant (P < 0.05).
… 
Transcriptome and genome analysis of AML cells among benzene group and air control group a Heatmap showing changes of all expressed genes across benzene group (AML, n = 4), air control group (AML, n = 4), and preleukemia group (n = 2). The colors reflect scaled values representing the degree of expression from low to high as blue to red, respectively. b GSEA analysis was performed for benzene group (vs preleukemia) and air control group (vs preleukemia), respectively. Presentative upregulated terms that specifically enriched in one of two groups are listed (P < 0.01; FDR < 0.05; Molecular Signatures Database, C2). c Ingenuity Pathway Analysis (IPA) was performed to identify the affected upstream regulators in both groups with differential expressed genes (threshold for differentially expressed genes: P < 0.01, FDR < 0.05, |Fold-change | > 2; threshold for affected upstream regulators: |z-score | > 2, P < 0.01). Top five regulators that affected in benzene group but not in control group were selected to build network with their differentially expressed target genes using Cytoscape (purple and blue ellipses represent differential expressed targets associated with DNA damage response and other pathways, respectively; red and green rectangles represent activated and inhibited regulators specifically affected by benzene exposure, respectively). d Contribution of known COSMIC signatures to somatic SNVs identified in each mouse. Given the mutational profiles and 30 reference COSMIC signatures, the weighted contributions of each reference signature for each mouse were iteratively inferred by deconstructSigs. Among contributing signatures found in four mice, signature 3 is associated with abnormal DSB repair and signature 9 is thought to result from error-prone polymerase η-associated mutagenesis. The underlying mechanisms behind other signatures are detailed at https://cancer.sanger.ac.uk/cosmic/signatures/SBS/. e Circos plots showing the distribution of structural variations within each mouse. The middle circle: deletions (blue) and insertions (red). The inner circle: interchromosomal (seagreen) or intrachromosomal (darkmagenta) translocations. f Clonal structure of each AML mouse analyzed by sciClone with all neutral copy SNVs and small indels. For the clonal structure graphics of each mouse, the upper and lower graph represent the kernel density plots of VAFs and the distribution of tumor coverage(depth) along the VAFs, respectively. Mutation clusters of different colors determined by model fit represent distinct clones. Six and nine clones were found in Benzene AML_1 mouse and Benzene AML_2 mouse. Two and Three clones were found in Air control AML_1 and Air control AML_2.
… 
This content is subject to copyright. Terms and conditions apply.
Leukemia (2021) 35:595600
https://doi.org/10.1038/s41375-020-0894-x
LETTER
Acute myeloid leukemia
Benzene induces rapid leukemic transformation after prolonged
hematotoxicity in a murine model
Jianxin Zhao1Pinpin Sui2,3,4 Bo Wu1,5 Aili Chen 2,3 Yedan Lu1Fenxia Hou1Xiurong Cheng1Shiwei Cui1
Jiayang Song1Gang Huang 6Caihong Xing 1Qian-fei Wang 2,3,4
Received: 6 March 2020 / Revised: 22 May 2020 / Accepted: 26 May 2020 / Published online: 5 June 2020
© Springer Nature Limited 2020
To the Editor:
Benzene is an important industrial chemical and ubiquitous
environmental mutagen known to induce hematological
malignancies particularly leukemia [1]. The development of
benzene-induced leukemia takes an average of 11.4 years to
occurs in workers chronically exposed to high levels of
benzene [2]. Before the onset of the malignancy, benzene
workers experience a strong and prolonged hematotoxicity
characterized by signicantly reduced white blood cell
counts, and in severe forms, pancytopenia or anemia, and
the later has been referred to as benzene poisoning (BP) [3].
These observations are consistent with in vitro ndings that
benzene inhibit hematopoietic growth and self-renewal
through induction of DNA double strand breaks and
adducts of bone marrow DNA [4]. Benzene-induced
hematotoxicity is associated with future risk of developing
haematological malignancy. While benzene exposure has an
overall 7-fold risk for development of leukemia, BP is
associated with a 71-fold risk for development of the acute
myeloid leukemia (AML) or myelodysplastic syndromes
(MDS) in human [2,5]. Malignant transformation in these
benzene-exposed workers can take place in a very short
time, as evident by rapid 10-fold expansion of white blood
cell (WBC) within 6-month in reported long-term exposure
BP cases [3].
While these population-based cohort studies characterize
key aspects of this unique entity of AML in humans, models
are needed to recapitulate this distinct evolutionary trajec-
tory of benzene-induced leukemia. Such model will be a
powerful tool to explore the pathobiology and the under-
lying molecular mechanisms of benzene-induced carcino-
genesis. The inhibitory effects of benzene on hematopoietic
cells have been extensively characterized in vitro and
in vivo [1]. However, hematotoxicity does not lead to leu-
kemic transformation in these systems. In the efforts to
develop cancer models, benzene treatment induced mostly
lymphoma [6], a different type of blood cancer from what
have been commonly observed in benzene-exposed human
population. Benzene also has been shown to promote tumor
development in transgenic mice carrying Trp53 or Ras
mutation [6,7]. The toxic effect on hematopoiesis, how-
ever, was not observed in these mice. Therefore, the con-
tinum of hematotoxicity and malignant transformation in
the development of benzene-induced human leukemia has
been difcult to model.
In this study, we aimed to develop a mouse model to
recapitulate the two-stage (hematotoxicity and malignant
transformation) process of benzene-induced AML. To
observe leukemia development under benzene exposure,
preleukemic bone marrow (BM) cells and spleen cells
(CD45.2+) harboring MllAf9 oncogenic fusion gene were
transplanted into recipient mice (CD45.1+) (Fig. 1a). After
These authors contributed equally: Jianxin Zhao, Pinpin Sui, Bo Wu
*Caihong Xing
xingch@niohp.chinacdc.cn
*Qian-fei Wang
wangqf@big.ac.cn
1Key Laboratory of Chemical Safety and Health, National Institute
for Occupational Health and Poison Control, Chinese Center for
Disease Control and Prevention, Beijing, China
2CAS Key Laboratory of Genomic and Precision Medicine,
Collaborative Innovation Center of Genetics and Development,
Beijing Institute of Genomics, Chinese Academy of Sciences,
Beijing, China
3China National Center for Bioinformation, Beijing, China
4University of Chinese Academy of Sciences, Beijing, China
5Chinese Academy of Inspection and Quarantine, Beijing, China
6Division of Pathology and Experimental Hematology and Cancer
Biology, Cincinnati Childrens Hospital, Cincinnati, Ohio, USA
Supplementary information The online version of this article (https://
doi.org/10.1038/s41375-020-0894-x) contains supplementary
material, which is available to authorized users.
1234567890();,:
1234567890();,:
allowing for engraftment and reconstitution of BM, MllAf9
mice were exposed to benzene at 299 ppm (972 mg/m3)
(n=25) or air (n=25) by inhalation for a lifetime exposure
(8 h/d for 5 d/w). This level of benzene exposure con-
centration is sufcient to induce myeloid leukemia both in
wild-type and transgenic mice [1,6,8]. (See methods). The
8 weeks-old
Mll-Af9 mice
8 weeks-old
B6.SJL mice
BM & spleen cells
BM cells
MIX 1:1
3w post
irradiated
Benzene exposure
(1000 mg/m3, n=25)
Air Control
(0 mg/m , n=25)
28 weeks
Collect PB, weekly
Complete blood count
Flow cytometry analysis
CD45.2
CD45.1
Recipients mice
7.5 Gy
C
A
0246810121416182022242628
20
21
22
23
24
25
26
27
28
29
Weeks after benzene exposure
Cells number (×103l)
Control
Benzene
Control
Benzene
WBC
(N=25/group)
Pre-leukemic cell
(N=25/group)
B
Week 0 of exposure
8wpriortode
ath
4w prior to death
Death
Week 0 of exposure
8w prior to death
4w prior to death
Death
20
21
22
23
24
25
26
27
28
29
Pre-leukemic cells number (×103/µl)
63-fold 16-fold
Benzene
(N=25)
Control
(N=25)
**
0 2 4 6 8 10 12 14 16 18 20 22 24 26 28
0
2
4
6
8
10
Weeks after benzene exposure
Control (N=25)
Benzene (N=25)
Cells number (×106/µl)
RBC
**********
****
*****
*******
**
D
0 2 4 6 8 10121416182022242628
0
200
400
600
Weeks after benzene exposure
Control (N=25)
Benzene (N=25)
Cells number(
×103l)
PLT
*
*
**
**
*
***
3
E
596 J. Zhao et al.
effect of benzene on hematopoiesis was assessed by mea-
suring the complete blood cell counts and preleukemic cells
counts (CD45.2+WBC). After maintaining a preleukemic
condition for a period of 15 weeks (leukemia development
stage), mice from both groups started to develop leukemia
and all died of the disease within 28 weeks (Leukemic death
stage) (Supplementary Fig. 1a). Although the survival rate
was similar among the groups, benzene-exposed mice and
air control mice exhibited a drastic difference in the growth
trajectory of CD45.2+preleukemic cells. CD45.2+cells in
the air control group experienced a steady 2.6-fold increases
(2.4-fold increases for WBC) over an extended time of
15 weeks (Fig. 1b). Subsequently, mice underwent a 16-
fold expansion (12-fold expansion for WBC) in the last
4 weeks towards impending death (Fig. 1c, Supplementary
Fig. 1b). In sharp comparison, benzene exposure induced a
3665% inhibition on the growth of CD45.2+cells (36%-
67% inhibition for WBC) over the 15-week leukemic
development stage. Consistently, red blood cell (RBC)
counts, hemoglobin (HGB), and Platelet (PLT) levels were
signicantly decreased in benzene-exposed mice compared
to air control (Fig. 1d,e, Supplementary Fig. 1c). Remark-
ably, a 63-fold drastic expansion of CD45.2+cells (57-fold
expansion for WBC) were observed during the last 4 weeks
towards impending death in the benzene group (n=25)
(Fig. 1c, Supplementary Fig. 1b). This rapid leukemic
transformation following prolonged growth inhibition
recapitulate the distinct evolutionary trajectory of benzene-
induced leukemia in human.
We went on to use this model to explore the pathobiology
of benzene-induced AML. We carried out RNA-sequencing
on sorted CD45.2+bone marrow cells from AML mice to
examine potential functional difference between the benzene
group (n=4) and air control group (n=4). Although AML-
associated pathways were signicantly upregulated in both
two groups (Supplementary Fig. 2a), we found a signicant
difference in the transcriptome prole between benzene-
exposed mice and control mice (Fig. 2a). Transcriptome of
benzene group preferentially enriched for stem or pro-
genitor cell,metastasis/invasion,mixed-lineage leuke-
mia (MLL)and proliferation, as shown by Gene Set
Enrichment Analysis (GSEA) (P< 0.01, FDR < 0.05)
(Fig. 2b). Consistent with the notion that benzene and its
metabolites induces DNA double strand breaks and DNA
repair, ve top upstream regulators (P<1×10
3) predicted
by Ingenuity Pathway Analysis (IPA) were all related to
DNA damage and mutagenesis in benzene group, including
activation of Trp53,Crebbp, and Dnase2a, as well as inhi-
bition of Cgas and Ifna (Fig. 2c, Supplementary Table 1).
Interestingly, Trp53 and Crebbp were previously found to
positively regulate DNA damage response [9]. Dnase2a is
key to degrade damaged double-stranded DNA [10], and
Cgas is an inhibitor of DNA repair [11]. Together, these data
suggested that AML cells from benzene-exposed mice
exhibited increased activity of DNA damage response, as
well as an enhanced function in stem cell activity, malignant
proliferation, and invasion.
To further determine the genomic basis for the observed
transcriptomic changes, we carried out whole-genome
sequencing (WGS) at a median depth of 36.88 ×
(35.96~37.07×) on benzene-exposed mice (AML stage,
n=2) and air control mice (AML stage, n=2). Using
MllAf9 preleukemic cells as baseline control, we identied
point mutations as well as structural changes in benzene-
exposed and air control mice, respectively. Although the
total number of genomic alterations had no signicant dif-
ference between the two groups (Supplementary Fig. 2b),
functional related changes including nonsynonymous, spli-
cing, stopgain, stoploss, frameshift SNVs, and indels were
signicantly higher in benzene-exposed mice than air con-
trol mice (Supplementary Fig. 2c). Furthermore, we iden-
tied more AML-associated mutations in benzene-exposed
mice including those known to be essential for the self-
renewal potential of leukemic stem cells (e.g., Kmt2c,Bcor,
and Nras. Supplementary Table 2). These data were sup-
portive of the transcriptional changes for an enhanced stem
cell function and proliferative capability of benzene AMLs.
Considering benzene can directly cause DNA adducts
and double strand breaks (DSBs), as well as to induce
Fig. 1 Benzene induces rapid leukemic transformation after pro-
longed hematotoxicity in transplant MllAf9 murine model. a Outline
of experiments. Transplant MllAf9 mice were obtained by transplanting
bone marrow (BM) and spleen cells from an 8-weeks-old MllAf9
knock-in mouse (preleukemia state, CD45.2+) and equal BM cells from
an 8-weeks-old B6.SJL mouse (normal, CD45.1+) into B6.SJL recipient
mice. After 3 weeks of reconstitution, these mice were randomly divided
into benzene exposure group (Target concentration: 1000 mg/m3or
308 ppm. Conversion factor: 20 °C, 101 kPa 1 ppm =3.25 mg/m3). (n=
25) and air control group (0 mg/m3,n=25) for lifetime exposure. The
actual concentration in the chambers is 972 mg/m3or 299 ppm. See
methods. Peripheral blood (PB) parameters and the number of pre-
leukemic (CD45.2+) cells in PB were analyzed once a week. bGrowth
pattern of white blood cells (WBCs) and preleukemic cells during the
whole 28 weeks of exposure. Preleukemic cells in PB were identied by
ow cytometry analysis (FACS). The count of WBCs or preleukemic
cells was signicantly lower during the rst 20 weeks in benzene-
exposedmicethaninaircontrolmice(P< 0.05). cGrowth pattern of
preleukemic cells prior to the time of death. The fold-change of pre-
leukemic cells number in benzene-exposed mice (63-fold) and air control
mice (16-fold) during the last 4 weeks before death are marked on the
graph. Fold-change =Y/X1. The Y represents the number of pre-
leukemic cells in mice at 4 weeks prior to death and the X represents the
number of preleukemic cells in mice at the stage of impending death.
d,eRed blood cell (RBC) counts and Platelet (PLT) counts in the PB of
MllAf9 mice during the whole 28 weeks of exposure. Data are presented
as the median with interquartile range (b,c)orthemeanwithSEM(d,e).
P-values in band cwere obtained using the Wilcoxon rank-sum test.
P-values in dand ewere obtained using the unpaired Studentst-test.
Asterisk Means that the difference between benzene group and air
control group was signicant (P< 0.05).
Benzene induces rapid leukemic transformation after prolonged hematotoxicity in a murine model 597
chromosomal aberrations in cultured cell lines [4], we fur-
ther looked for potential genomic features that may speci-
cally derived from benzene exposure in AML mice. As
base substitution pattern of point mutations, termed
mutational signatures, are often indicative of mutational
processes (e.g., cellular defects or mutagen exposures), we
2 Copies
Model Fit
Component Fits
−2
−1
0
1
2
1 2 3 4 1 2 3 4 1 2
Benzene AML
Air control AML
Pre-leukemia
HARRIS_BRAIN_CANCER_PROGENITORS
ENGELMANN_CANCER_PROGENITORS_UP
YAMASHITA_LIVER_CANCER_STEM_CELL_UP
BOQUEST_STEM_CELL_UP
ENGELMANN_CANCER_PROGENITORS_DN
VALK_AML_CLUSTER_1
VALK_AML_CLUSTER_2
CASORELLI_ACUTE_PROMYELOCYTIC_LEUKEMIA_UP
BRUNO_HEMATOPOIESIS
HALMOS_CEBPA_TARGETS_UP
ALONSO_METASTASIS_EMT_UP
PEDERSEN_METASTASIS_BY_ERBB2_ISOFORM_6
GILDEA_METASTASIS(Down regulated)
NAKAMURA_METASTASIS_MODEL_UP
ANASTASSIOU_MULTICANCER_INVASIVENESS_SIGNATURE
PID_HIF1_TFPATHWAY
SEMENZA_HIF1_TARGETS
WU_CELL_MIGRATION
MULLIGHAN_MLL_SIGNATURE_1_UP
MULLIGHAN_MLL_SIGNATURE_2_UP
GAUSSMANN_MLL_AF4_FUSION_TARGETS_E_UP
SCHRAETS_MLL_TARGETS_UP
VALK_AML_WITH_11Q23_REARRANGED
PID_RAS_PATHWAY
KEGG_MAPK_SIGNALING_PATHWAY
BIOCARTA_MAPK_PATHWAY
RASHI_NFKB1_TARGETS
HINATA_NFKB_TARGETS_FIBROBLAST_UP
HINATA_NFKB_TARGETS_KERATINOCYTE_UP
No Significance
Upregulation
Stem or
Progenitor cell
Metastasis or
Invasion
MLL
Proliferation
A
poe
Pfn1
Plod2
Cox5b
Ppard
Chst12
Scn3B
Prdx6
Ptp4a3
Lgals3 Capns1
Ncor2
F8a
Tlr6
Ddx39
Igfbp4
Pla2g16
Cdc42bpa
Cnot11
Hsp90ab1
A
tp5k
Pg
r
Fkbp5
Rgs12
P4ha1
A
tf3
Laptm4a
Myh10
Nck2
Sesn2
Trim28 Tyms Inhba
Ifi30
Fn1
Id2
Ubc
Socs1
Eif2ak2
A
xl
Oas2
Ifna
Ifit2
Tnfsf13b
Ifit3
Oas1
Oas1a
A
ckr4
Cgas
Dnase2a
Ifit1b
Ifi44
Slfn3
Ccl2
Isg15
A
nk
Fkbp1a
Spp1
Sod1
Irf7
Mx1
Mmp23
Nos2
Bmp1
Stard4
Gpnmb
Psmd3
Gpx3
Tnfsf10
Card11
Stau1
Usp9x
Ifit1
Rtp4
Usp18
Tnfaip8l2 Oas3
Rsad2
p3m2
A
rhgef10l
Ntn1
Mga
Spsb1
Scn4b
Crebbp
Eya2
Cdc6
Edaradd
Jund Socs3
Slc43a1
Epn1
Wfs1
Trim26
Dcx
Nr4a1
Ddx3y
Dusp22
Neurod1
Egr3
Trpm1
A
hi1
Fosb
Hmgcs2
Egr2
Hist3h2a
Gng2
Bank1
A
ngpt1
Slamf1
Rasa3
Grin2d
Zfp36l2
Egr1
Tap2
Gm2a
Lsp1
Gata1
Glul
Tacc2
Mcam
Eif4e2
Il27ra
Bcl2l1
Gadd45a
A
tg10
Itgb5
Fuca1
Bub1
A
ce
Pou5f1
Brca1 Tpm4
Ier5
Cpox
A
sl Cstb
Eif4g3
Ptk2
Sphk1
Irf8
Fosl1
A
drb2
Hbegf
Cep170b
Hist1h1b
Csnk1d
Tgfbi
Zmat3
Rhob
Nptx1 Vim
Klhl21
Dnase1
Ephx1
Il1b Rnase4
Lasp1 Hadhb
Gstp1
Tex15 Vcan
Mafb
Rap2b
Htt
Bcap31
Tsc22d3
A
nxa8
Pura Rps6ka2
Hsph1
Stat1
A
paf1
Ptgds
Gapdh
Cyb5r3
Nudt5 Gadd45g
A
bcb4
Ipo7
Trp53
Cdc7
Hist2h4
Plk2
Igfbp3
Prelid1
Tlr1
Padi2
Cdkn2a
Gna14
Gstm1
Stmn1
Iffo1
Bax
Cdkn1a
Fos
Ugdh
Adamtsl4
Col14a1
Prkg1
Nlrx1
Hmox1
Slc5a3
Tjp1
Scpep1
Ubl3
Hdac9 Tspan6
A
fp
Dusp2
Ubqln2
Lima1
Pmaip1
Psen1
Top2a
Bbc3
Mvp
Ddit4
Psap
Rrm1
Cav1
dam8
Epha2
Mki67
Ctsb
A
tl3
Sgk1
Mapre3
Il17ra
Serpina3
Ulk1
Rfc1
Prpsap1
Itgb7
Ckb
Il10ra
Ccdc80
Pdlim4
Mef2c
Btg1
Runx2
Ndrg1
Klf2
Irf6
Evl
Jun
Gfi1b
Camk2b
Plekha1
Ccnd1
A
dam12
Pde10a
Cd160
Dusp1
Xist
Fabp4
A
nxa6
Il12rb1
Lgals3bp
Car2
Jup
Utrn Hvcn1
Mpo Uty
Dhrs3
Benzene AML
Air control AML
0MB
80MB
160MB
1
0MB
80MB
160MB
2
0MB
80MB
160MB
3
0MB
80MB
4
0MB
80MB
5
0MB
80MB
6
0MB
80MB
7
0MB
80MB
8
0MB
80MB
9
0MB
80MB
10
0MB
80MB
11
0MB
80MB
12
0MB
80MB
13
0MB
80MB
14
0MB
80MB
15
0MB
80MB
16
0MB
80MB
17
0MB
80MB
18
0MB
19
0MB
80MB
160MB
X
0MB
80MB
Y
0MB
80MB
160MB
1
0MB
80MB
160MB
2
0MB
80MB
160MB
3
0MB
80MB
4
0MB
80MB
5
0MB
80MB
6
0MB
80MB
7
0MB
80MB
8
0MB
80MB
9
0MB
80MB
10
0MB
80MB
11
0MB
80MB
12
0MB
80MB
13
0MB
80MB
14
0MB
80MB
15
0MB
80MB
16
0MB
80MB
17
0MB
80MB
18
0MB
19
0MB
80MB
160MB
X
0MB
B
M
0
8
Y
BM0
80MB
160MB
1
0MB
80MB
160MB
2
0MB
80MB
160MB
3
0MB
80MB
4
0MB
80MB
5
0MB
80MB
6
0MB
80MB
7
0MB
80MB
8
0MB
80MB
9
0MB
80MB
10
0MB
80MB
11
0MB
80MB
12
0MB
80MB
13
0MB
80MB
14
0MB
80MB
15
0MB
80MB
16
0MB
80MB
17
0MB
80MB
18
0MB
19
0MB
80MB
160MB
X
0MB
80MB
Y
B
M
0
80MB
160MB
1
0MB
80MB
160MB
2
0MB
80MB
160MB
3
0MB
80MB
4
0MB
80MB
5
0MB
80MB
6
0MB
80MB
7
0MB
80MB
8
0MB
80MB
9
0MB
80MB
10
0MB
80MB
11
0MB
80MB
12
0MB
80MB
13
0MB
80MB
14
0MB
80MB
15
0MB
80MB
16
0MB
80MB
17
0MB
80MB
18
0MB
19
0MB
80MB
160MB
X
0MB
80MB
Y
Benzene AML_1 Benzene AML_2
Air control AML_1 Air control AML_2
2 Copies
Model Fit
Component Fits
020406080100
Variant Allele Frequency
Density (a.u.)
5
10
20
50
100
200
T
umor Coverage
020406080100
020406080100
Variant Allele Frequency
Density (a.u.)
5
10
20
50
100
200
500
1000
Tumo r C overage
020406080100
2 Copies
Model Fit
Component Fits
020406080100
Variant Allele Frequency
Density (a.u.)
5
10
20
50
100
200
2
Tumor Coverage
020406080100
2 Copies
Model Fit
Component Fits
020406080100
Variant Allele Frequency
Density (a.u.)
5
10
20
50
100
200
500
2
T
umor Coverage
020406080100
Benzene AML_1 Benzene AML_2
Air control AML_1 Air control AML_2
AB
CD
EF
1212
0.0
0.2
0.4
0.6
0.8
1.0
Benzene AML Air control AML
Signature 17
Signature 16
Signature 15
Signature 14
Signature 12
Signature 9
Signature 8
Signature 5
Signature 3
Signature 1
Unknown
RelativeContribution
2
2
598 J. Zhao et al.
examined the genomes for the presence of 30 COSMIC
mutational signatures. This analysis showed that, comparing
to air control, benzene-exposed mice had a signicant
higher proportion of signature 3 (Fig. 2d), which is known
to be associated with abnormal DSB repair [12]. Notably, in
line with the notion that genomes with DSBs are prone for
structural alterations [13], benzene-exposed mice were
characterized with extensive inter- or intrachromosomal
translocations, and deletions (Fig. 2e). The analyses of base
substitution signature and structural alterations suggested
that benzene may impact on the AML genome through
induction of DSBs and subsequent abnormal repair. As the
AMLs in benzene and control group were developed
through very distinct growth pattern of CD45.2+pre-
leukemic cells, we further carried out clonal structure ana-
lysis to infer the evolutionary process of the observed
genomic alterations. The genome of each of air control
AML mice was represented by a simple clonal structure
with one to two subclones consisting of multiple mutations,
suggesting that a subset of MllAf9 preleukemic cells
acquired additional mutations and proceeded to malignant
transformation. Notably, each of the benzene-induced AML
genomes consisted multiple (58) subclones (Fig. 2f). This
increased complexity of clonal structure suggested that
benzene-induced-genomic mutations provided the basis for
a genetically diversied pool of MllAf9 cells, and multiple
subsets of preleukemic cells with unique mutations may be
further selected by persistent benzene exposure to even-
tually transformed into AML. Together, these data indicated
that benzene AML genomes bear mutational imprints
associated with DSBs, a characteristic of benzene-induced
DNA damage. Benzene exposure may reshape the genomic
landscape and clonal structure during the development of
leukemia.
In summary, our study employed a preleukemia mouse
transplantation system to model benzene-induced AML.
Benzene exposure resulted in a drastic difference in cellular
dynamics and genome evolution of the disease. This model
recapitulate the prolonged inhibitory phase followed by
rapid onset of AML observed in benzene-exposed workers.
Based on previous studies [1,6,8], a high level of
approximate 300 ppm of benzene exposure is required to
induce myeloid leukemia in mice (C3H/He: 8.7%; CBA/Ca:
19.3%; Trp53-decient C3H/He: 37.5%). In order to explore
the potential tumorigenic responses, an exposure con-
centration at the aforementioned level was selected in this
mouse model study, although such level of exposure do not
occur in industrial workers anymore [1]. MLL translocations
are frequently occurred in pediatric, particular infant leuke-
mia, as well as therapy-related leukemia induced by topoi-
somerase II inhibitors [14]. Considering children with low
concentration of outdoor benzene exposure have been
shown to have a signicantly increased risk of AML [15],
this MllAf9 mouse model may have relevance to specic
subgroup of pediatric or therapy-related MLL-rearranged
AML who had previous benzene exposure. Through com-
bined transcriptome and genome analysis, we also showed
that benzene AMLs had increased capability of malignant
proliferation and self-renewal, which may be resulted from
benzene-induced DSBs and genomic reconguration char-
acterized by prevalence of leukemia-associated point muta-
tions, structural alterations, as well as increased levels of
clonal complexity. It is worthy to note that the current model
used a preleukemia system involving a common AML
oncogenic fusion gene MllAf9. Such preleukemic condition
is present in general population. Hematological cancer
associated chromosomal abnomalities have been found in
roughly 23% of elderly individuals without a history of
blood-related disorders [16]. Around 10% of healthy elderly
people (older than 65 years) have clonal hematopoiesis with
somatic mutations in known leukemia driver genes
DNMT3A,TET2, and ASXL1 [17]. Furthermore, around 5%
Fig. 2 Transcriptome and genome analysis of AML cells among
benzene group and air control group. a Heatmap showing changes
of all expressed genes across benzene group (AML, n=4), air control
group (AML, n=4), and preleukemia group (n=2). The colors reect
scaled values representing the degree of expression from low to high
as blue to red, respectively. bGSEA analysis was performed for
benzene group (vs preleukemia) and air control group (vs pre-
leukemia), respectively. Presentative upregulated terms that speci-
cally enriched in one of two groups are listed (P< 0.01; FDR < 0.05;
Molecular Signatures Database, C2). cIngenuity Pathway Analysis
(IPA) was performed to identify the affected upstream regulators in
both groups with differential expressed genes (threshold for differen-
tially expressed genes: P< 0.01, FDR < 0.05, |Fold-change | > 2;
threshold for affected upstream regulators: |z-score | > 2, P< 0.01).
Top ve regulators that affected in benzene group but not in control
group were selected to build network with their differentially expres-
sed target genes using Cytoscape (purple and blue ellipses represent
differential expressed targets associated with DNA damage response
and other pathways, respectively; red and green rectangles represent
activated and inhibited regulators specically affected by benzene
exposure, respectively). dContribution of known COSMIC signatures
to somatic SNVs identied in each mouse. Given the mutational
proles and 30 reference COSMIC signatures, the weighted con-
tributions of each reference signature for each mouse were iteratively
inferred by deconstructSigs. Among contributing signatures found in
four mice, signature 3 is associated with abnormal DSB repair and
signature 9 is thought to result from error-prone polymerase η-
associated mutagenesis. The underlying mechanisms behind other
signatures are detailed at https://cancer.sanger.ac.uk/cosmic/signa
tures/SBS/.eCircos plots showing the distribution of structural var-
iations within each mouse. The middle circle: deletions (blue) and
insertions (red). The inner circle: interchromosomal (seagreen) or
intrachromosomal (darkmagenta) translocations. fClonal structure of
each AML mouse analyzed by sciClone with all neutral copy SNVs
and small indels. For the clonal structure graphics of each mouse, the
upper and lower graph represent the kernel density plots of VAFs and
the distribution of tumor coverage(depth) along the VAFs, respec-
tively. Mutation clusters of different colors determined by model t
represent distinct clones. Six and nine clones were found in Benzene
AML_1 mouse and Benzene AML_2 mouse. Two and Three clones
were found in Air control AML_1 and Air control AML_2.
Benzene induces rapid leukemic transformation after prolonged hematotoxicity in a murine model 599
of children are born with the common leukemia fusion gene,
such as TEL-AML1 and AML1-ETO [18]. Benzene poison-
ing workers are likely to harbor oncogenic alterations. Our
study may serve as a model to explore the pathobiology and
to test therapeutic agent for benzene-induced AML derived
from those preleukemic conditions.
Acknowledgements This work was supported by the Beijing Natural
Science Foundation (No. 7182118), the National Natural Science
Foundation of China (No. 81641009), the Social Development Project
of Jiangsu Province (No. BE2017659), and the Youth Innovation
Promotion Association of the Chinese Academy of Sciences (to
C.A.L.). We acknowledge Bing Liu at Academy of Military Medical
Sciences for kindly providing the male B6.SJL mouse strain. We are
grateful to Nan Lian at West China School of Public Health for
technical assistance.
Author contributions JZ and BW performed experiments; CX, QW,
HG, and AC designed experiments; JZ, PS, and JS analyzed data; YL,
FH, and XC established techniques of ow cytometry; SC helped to
monitor the concentration of benzene; QWang, CX, JZ, and PS wrote
the manuscript. All authors approved and take shared responsibility for
the nal submitted version of the manuscript.
Compliance with ethical standards
Conict of interest The authors declare that they have no conict of
interest.
Publishers note Springer Nature remains neutral with regard to
jurisdictional claims in published maps and institutional afliations.
References
1. IARC. IARC Monographs on the Evaluation of Carcinogenic
Risks to Humans Volume 120. IARC publications; 2018.
2. Yin SN, Li GL, Tain FD, Fu ZI, Jin C, Chen YJ, et al. Leukaemia
in benzene workers: a retrospective cohort study. Br J Ind Med.
1987;44:1248.
3. Upton, Arthur C., Myron A. Mehlman. The identication and
control of environmental and occupational diseases. In: Hazards
and risks of chemicals in the oil rening industry. Princeton:
Princeton Scientic Publishing Co; 1994. pp 2912.
4. McHale CM, Zhang L, Smith MT. Current understanding of the
mechanism of benzene-induced leukemia in humans: implications
for risk assessment. Carcinogenesis. 2012;33:24052.
5. Rothman N, Smith MT, Hayes RB, Traver RD, Hoener B,
Campleman S, et al. Benzene poisoning, a risk factor for hema-
tological malignancy, is associated with the NQO1 609C->T
mutation and rapid fractional excretion of chlorzoxazone. Cancer
Res. 1997;57:283942.
6. Kawasaki Y, Hirabayashi Y, Kaneko T, Kanno J, Kodama Y,
Matsushima Y, et al. Benzene-induced hematopoietic neoplasms
including myeloid leukemia in Trp53-decient C57BL/6 and
C3H/He mice. Toxicol Sci. 2009;110:293306.
7. French JE, Saulnier M. Benzene leukemogenesis: an environ-
mental carcinogen-induced tissue-specic model of neoplasia
using genetically altered mouse models. J Toxicol Environ health
Part A. 2000;61:3779.
8. Cronkite EP, Drew RT, Inoue T, Hirabayashi Y, Bullis JE.
Hematotoxicity and carcinogenicity of inhaled benzene. Environ
health Perspect. 1989;82:97108.
9. Dutto I, Scalera C, Prosperi E. CREBBP and p300 lysine acetyl
transferases in the DNA damage response. Cell Mol Life Sci.
2018;75:132538.
10. Lan YY, Londoño D, Bouley R, Rooney MS, Hacohen N. Dna-
se2a deciency uncovers lysosomal clearance of damaged nuclear
DNA via autophagy. Cell Rep. 2014;9:18092.
11. Jiang H, Xue X, Panda S, Kawale A, Hooy RM, Liang F, et al.
Chromatin-bound cGAS is an inhibitor of DNA repair and hence
accelerates genome destabilization and cell death. EMBO J.
2019;38:e102718.
12. Alexandrov LB, Nik-Zainal S, Wedge DC, Aparicio SA, Behjati
S, Biankin AV, et al. Signatures of mutational processes in human
cancer. Nature. 2013;500:41521.
13. Ballinger TJ, Bouwman BAM, Mirzazadeh R, Garnerone S,
Crosetto N, Semple CA. Modeling double strand break suscept-
ibility to interrogate structural variation in cancer. Genome Biol.
2019;20:28.
14. Muntean AG, Hess JL. The pathogenesis of mixed-lineage leu-
kemia. Annu Rev Pathol. 2012;7:283301.
15. Margueritte G, Perel Y, Mechinaud F, Bordigoni P, Hémon D,
Clavel J. Acute childhood leukaemia and residence next to petrol
stations and automotive repair garages: the ESCALE study
(SFCE). Occup Environ Med. 2009;66:598606.
16. Laurie CC, Laurie CA, Rice K, Doheny KF, Zelnick LR, McHugh
CP, et al. Detectable clonal mosaicism from birth to old age and its
relationship to cancer. Nat Genet. 2012;44:64250.
17. Genovese G, Kähler AK, Handsaker RE, Lindberg J, Rose SA,
Bakhoum SF, et al. Clonal hematopoiesis and blood-cancer risk
inferred from blood DNA sequence. N. Engl J Med.
2014;371:247787.
18. Mori H, Colman SM, Xiao Z, Ford AM, Healy LE, Donaldson C,
et al. Chromosome translocations and covert leukemic clones are
generated during normal fetal development. Proc Natl Acad Sci
USA. 2002;99:82427.
600 J. Zhao et al.
... Gaseous benzene is an environmental mutagen and highly toxic compound that induces hematological malignancies [1] including multiple myeloma and leukemia. [2] Frequently, accidents with Table 1. ...
Article
Full-text available
More than 1 million workers are exposed routinely to carcinogenic benzene, contained in various consumer products (e.g., gasoline, rubbers, and dyes) and released from combustion of organics (e.g., tobacco). Despite strict limits (e.g., 50 parts per billion (ppb) in the European Union), routine monitoring of benzene is rarely done since low-cost sensors lack accuracy. This work presents a compact, battery-driven device that detects benzene in gas mixtures with unprecedented selectivity (>200) over inorganics, ketones, aldehydes, alcohols, and even challenging toluene and xylene. This can be attributed to strong Lewis acid sites on a packed bed of catalytic WO 3 nanoparticles that prescreen a chemoresistive Pd/SnO 2 sensor. That way, benzene is detected down to 13 ppb with superior robustness to relative humidity (RH, 10-80%), fulfilling the strictest legal limits. As proof of concept, benzene is quantified in indoor air in good agreement (R 2 ≥ 0.94) with mass spectrometry. This device is readily applicable for personal exposure assessment and can assist the implementation of low-emission zones for sustainable environments.
... Before the development of hematological malignancies, benzene-exposed populations experienced long-term hematologic toxicity characterized by decreased blood cells (14). To explore the molecular mechanism and screen biomarkers of benzene-induced hematotoxicity, the variation of endogenous metabolites in urinary, BM cells, and plasma of male C3H/He mice exposed to benzene was detected using untargeted metabolomics (15,16). ...
Article
Full-text available
Metabolomics has been used to explore the molecular mechanism and screen biomarkers. However, the critical metabolic signatures associated with benzene-induced hematotoxicity remain elusive. Here, we performed a plasma metabolomics study in 86 benzene-exposed workers and 76 healthy controls, followed by a validation analysis in mice, to investigate the dynamical change of the metabolic profile. We found that 8 fatty acids were significantly altered in both benzene-exposed worker and benzene-exposed animal models. These metabolites were significantly associated with S-phenylmercapturic acid and WBC, and they mediated the benzene-induced WBC decline. Furthermore, in vivo results confirm that fatty acid levels were dynamically altered, characterized by a decrease at 15 days and then sharp increases at 30 and 45 days. Following these identified fatty acids, the potential metabolic pathways were investigated. Fatty acids, as precursors for fatty acid oxidation, may disturb the balance of fatty acid biosynthesis and degradation. Our results reveal that fatty acid metabolism was strongly reprogrammed after benzene exposure. This abnormal change of fatty acids might be the key metabolic signature associated with benzene-induced hematotoxicity.
... Numerous genetic and environmental factors are reported to be involved in the predisposing or prevention of hematologic malignancies. Exposure to radiation, chemicals, tobacco, oxidizing agents, socioeconomic status, and some viral infections (i.e., Epstein-Barr virus) are among environmental risk factors for blood cancers (Erdmann et al., 2021;Chunxia et al., 2019;Parkhideh et al., 2021;Kazemi et al., 2021;Abalo et al., 2021;Chabay, 2021;Zhao et al., 2021;Ardakani et al., 2020). Multitude genes are listed as risk factors for hematologic cancers in the Iranian population, including genes involved in the epigenetic process (micro RNAs), apoptosis, genome stability, signaling pathways, transcription factors (WNT genes), drug resistance, growth factors, and finally those involved in the immune responses (Izadifard et al., 2018;Hajifathali et al., 2020;Amini et al., 2021;Jahangiri et al., 2020;Tavakoli et al., 2021;Roshandel et al., 2021;Amini et al., 2020;Jahangiri et al., 2018). ...
Article
Several genetic and environmental factors are reported to be involved in the predisposing or prevention of hematologic malignancies. Due to their high polymorphisms, human leukocytes antigen (HLA) molecules are critical factors in disease predisposition. In this study, we investigated the frequencies of HLA-I and -II alleles in 476 blood cancer patients having acute myeloid leukemia (AML), acute lymphoblastic leukemia (ALL), Hodgkin's disease (HD), non-Hodgkin lymphoma (NHL), and multiple myeloma (MM) as well as 500 healthy individuals to find the possible links between HLA alleles and hematologic malignancy incidence in the Iranian population. HLA-A*03, −A*11, −A*31, −A*66, and -C*17 in ALL, HLA-A*25 and -A*30 in HD, HLA-A*26, -B*45, and -B*73 in NHL, and HLA-B*45, -B*53 and -DQB1*03 in MM were found to be associated with high risks of malignancies. On the other hand, HLA-DQB1*02 in AML, HLA-DQB1*05 in HD, and HLA-A*03 in NHL were found to have negative associations with the disease. Interestingly, HLA-DQB1*04 is associated with the risk of all studied blood cancers. Besides, HLA-B*45 is associated with the risk of both NHL and MM. Intriguingly, HLA-A*03 is found to be associated with a higher risk of ALL, while it might serve as a protective allele for NHL. Future multicenter studies and meta-analyses could find the universal and regional risky HLA alleles for each hematologic malignancy.
Article
Long-term exposure to fine particles (PM2.5), ultrafine particles (UFPs), and volatile organic compounds (VOCs) emissions from cooking has been linked to adverse human health effects. Here, we measured the real-time number size distribution of particles emitted when cooking two served food in Chinese restaurants and estimated the emission rate of UFPs and PM2.5. Experiments were conducted under a control hood, and both online measurement and offline analysis of PM2.5 were carried out. The measured emission rates of PM2.5 generated from deep-frying and grilling were 0.68 ± 0.11 mg/min and 1.58 ± 0.25 mg/min, respectively. Moreover, the UFPs emission rate of deep-frying (4.3 × 10⁹ #/min) is three times higher than that of grilling (1.4 × 10⁹ #/min). Additionally, the PM2.5 emission of deep-frying was comprised of a considerable amount of α−Fe2O3 (5.7% of PM2.5 total mass), which is more toxic than other iron oxide species. A total of six carcinogenic HAPs were detected, among which formaldehyde, acrolein, and acetaldehyde were found to exceed the inhalation reference concentration (RfC) for both cooking methods. These findings can contribute to future evaluation of single particle and HAPs emission from cooking to better support toxicity assessment.
Article
Benzene exposure leads to hematopoietic dysfunction and is characterized clinically by a decrease in blood cells, but the underlying mechanisms remain elusive. Disturbed gut microbiota may induce host metabolic, immune disorders and the onset of disease. However, the characterization of gut microbiota, metabolism, cytokines and their association with benzene-induced hematopoietic toxicity lacks systematic evidence. Here, the microbiomics, metabolomics and cytokine network were applied to find out the critical characteristics of gut microbiota, metabolism and cytokines in mice involved in the benzene-induced hematopoietic toxicity. We found that the decline in hematopoietic stem cells was earlier than the hematological changes in the 5 mg/kg and 25 mg/kg benzene exposure groups. While 125 mg/kg benzene exposure resulted in a significant decline in whole blood cells. High-throughput sequencing results showed that benzene exposure disrupted homeostasis of gut microbiota, metabolism and cytokine in mice. 6 bacteria, 12 plasma metabolites and 6 cytokines were associated with benzene-induced hematopoietic damage. Notably, IL-5 was significantly increased in benzene exposure group in a dose-dependent manner, and a significant negative correlation was found between IL-5 and hematopoietic damage. We further found that increased Family_XIII_AD3011_group at the genus level and decreased Anaerotruncus_sp at the species level in benzene-exposed group were strongly associated with hematopoietic toxicity and IL-5. Furthermore, the abundance of Family_XIII_AD3011_group and Anaerotruncus_sp were negatively correlated with Adipic acid and 4-Hydroxyproline, respectively. Our findings indicated that altered flora structure of gut microbiota affects the metabolic phenotype which acts as messengers for the gut microbes, affecting host inflammation. This preliminary study provides new insight into the potential mechanisms of benzene-induced hematopoietic toxicity, further exploration by functional studies is required in the future.
Article
Full-text available
Background Structural variants (SVs) are known to play important roles in a variety of cancers, but their origins and functional consequences are still poorly understood. Many SVs are thought to emerge from errors in the repair processes following DNA double strand breaks (DSBs). Results We used experimentally quantified DSB frequencies in cell lines with matched chromatin and sequence features to derive the first quantitative genome-wide models of DSB susceptibility. These models are accurate and provide novel insights into the mutational mechanisms generating DSBs. Models trained in one cell type can be successfully applied to others, but a substantial proportion of DSBs appear to reflect cell type-specific processes. Using model predictions as a proxy for susceptibility to DSBs in tumors, many SV-enriched regions appear to be poorly explained by selectively neutral mutational bias alone. A substantial number of these regions show unexpectedly high SV breakpoint frequencies given their predicted susceptibility to mutation and are therefore credible targets of positive selection in tumors. These putatively positively selected SV hotspots are enriched for genes previously shown to be oncogenic. In contrast, several hundred regions across the genome show unexpectedly low levels of SVs, given their relatively high susceptibility to mutation. These novel coldspot regions appear to be subject to purifying selection in tumors and are enriched for active promoters and enhancers. Conclusions We conclude that models of DSB susceptibility offer a rigorous approach to the inference of SVs putatively subject to selection in tumors. Electronic supplementary material The online version of this article (10.1186/s13059-019-1635-1) contains supplementary material, which is available to authorized users.
Article
Full-text available
The CREB-binding protein (CREBBP, or in short CBP) and p300 are lysine (K) acetyl transferases (KAT) belonging to the KAT3 family of proteins known to modify histones, as well as non-histone proteins, thereby regulating chromatin accessibility and transcription. Previous studies have indicated a tumor suppressor function for these enzymes. Recently, they have been found to acetylate key factors involved in DNA replication, and in different DNA repair processes, such as base excision repair, nucleotide excision repair, and non-homologous end joining. The growing list of CBP/p300 substrates now includes factors involved in DNA damage signaling, and in other pathways of the DNA damage response (DDR). This review will focus on the role of CBP and p300 in the acetylation of DDR proteins, and will discuss how this post-translational modification influences their functions at different levels, including catalytic activity, DNA binding, nuclear localization, and protein turnover. In addition, we will exemplify how these functions may be necessary to efficiently coordinate the spatio-temporal response to DNA damage. CBP and p300 may contribute to genome stability by fine-tuning the functions of DNA damage signaling and DNA repair factors, thereby expanding their role as tumor suppressors.
Article
Full-text available
Background Cancers arise from multiple acquired mutations, which presumably occur over many years. Early stages in cancer development might be present years before cancers become clinically apparent. Methods We analyzed data from whole-exome sequencing of DNA in peripheral-blood cells from 12,380 persons, unselected for cancer or hematologic phenotypes. We identified somatic mutations on the basis of unusual allelic fractions. We used data from Swedish national patient registers to follow health outcomes for 2 to 7 years after DNA sampling. Results Clonal hematopoiesis with somatic mutations was observed in 10% of persons older than 65 years of age but in only 1% of those younger than 50 years of age. Detectable clonal expansions most frequently involved somatic mutations in three genes (DNMT3A, ASXL1, and TET2) that have previously been implicated in hematologic cancers. Clonal hematopoiesis was a strong risk factor for subsequent hematologic cancer (hazard ratio, 12.9; 95% confidence interval, 5.8 to 28.7). Approximately 42% of hematologic cancers in this cohort arose in persons who had clonality at the time of DNA sampling, more than 6 months before a first diagnosis of cancer. Analysis of bone marrow–biopsy specimens obtained from two patients at the time of diagnosis of acute myeloid leukemia revealed that their cancers arose from the earlier clones. Conclusions Clonal hematopoiesis with somatic mutations is readily detected by means of DNA sequencing, is increasingly common as people age, and is associated with increased risks of hematologic cancer and death. A subset of the genes that are mutated in patients with myeloid cancers is frequently mutated in apparently healthy persons; these mutations may represent characteristic early events in the development of hematologic cancers. (Funded by the National Human Genome Research Institute and others.)
Article
Full-text available
Deficiencies in DNA-degrading nucleases lead to accumulation of self DNA and induction of autoimmunity in mice and in monogenic and polygenic human diseases. However, the sources of DNA and the mechanisms that trigger immunity remain unclear. We analyzed mice deficient for the lysosomal nuclease Dnase2a and observed elevated levels of undegraded DNA in both phagocytic and nonphagocytic cells. In nonphagocytic cells, the excess DNA originated from damaged DNA in the nucleus based on colocalization studies, live-cell imaging, and exacerbation by DNA-damaging agents. Removal of damaged DNA by Dnase2a required nuclear export and autophagy-mediated delivery of the DNA to lysosomes. Finally, DNA was found to accumulate in Dnase2a(-/-) or autophagy-deficient cells and induce inflammation via the Sting cytosolic DNA-sensing pathway. Our results reveal a cell-autonomous process for removal of damaged nuclear DNA with implications for conditions with elevated DNA damage, such as inflammation, cancer, and chemotherapy.
Article
Full-text available
All cancers are caused by somatic mutations; however, understanding of the biological processes generating these mutations is limited. The catalogue of somatic mutations from a cancer genome bears the signatures of the mutational processes that have been operative. Here we analysed 4,938,362 mutations from 7,042 cancers and extracted more than 20 distinct mutational signatures. Some are present in many cancer types, notably a signature attributed to the APOBEC family of cytidine deaminases, whereas others are confined to a single cancer class. Certain signatures are associated with age of the patient at cancer diagnosis, known mutagenic exposures or defects in DNA maintenance, but many are of cryptic origin. In addition to these genome-wide mutational signatures, hypermutation localized to small genomic regions, ‘kataegis’, is found in many cancer types. The results reveal the diversity of mutational processes underlying the development of cancer, with potential implications for understanding of cancer aetiology, prevention and therapy.
Article
Full-text available
We detected clonal mosaicism for large chromosomal anomalies (duplications, deletions and uniparental disomy) using SNP microarray data from over 50,000 subjects recruited for genome-wide association studies. This detection method requires a relatively high frequency of cells with the same abnormal karyotype (>5-10%; presumably of clonal origin) in the presence of normal cells. The frequency of detectable clonal mosaicism in peripheral blood is low (<0.5%) from birth until 50 years of age, after which it rapidly rises to 2-3% in the elderly. Many of the mosaic anomalies are characteristic of those found in hematological cancers and identify common deleted regions with genes previously associated with these cancers. Although only 3% of subjects with detectable clonal mosaicism had any record of hematological cancer before DNA sampling, those without a previous diagnosis have an estimated tenfold higher risk of a subsequent hematological cancer (95% confidence interval = 6-18).
Article
Full-text available
Benzene causes acute myeloid leukemia and probably other hematological malignancies. As benzene also causes hematotoxicity even in workers exposed to levels below the US permissible occupational exposure limit of 1 part per million, further assessment of the health risks associated with its exposure, particularly at low levels, is needed. Here, we describe the probable mechanism by which benzene induces leukemia involving the targeting of critical genes and pathways through the induction of genetic, chromosomal or epigenetic abnormalities and genomic instability, in a hematopoietic stem cell (HSC); stromal cell dysregulation; apoptosis of HSCs and stromal cells and altered proliferation and differentiation of HSCs. These effects modulated by benzene-induced oxidative stress, aryl hydrocarbon receptor dysregulation and reduced immunosurveillance, lead to the generation of leukemic stem cells and subsequent clonal evolution to leukemia. A mode of action (MOA) approach to the risk assessment of benzene was recently proposed. This approach is limited, however, by the challenges of defining a simple stochastic MOA of benzene-induced leukemogenesis and of identifying relevant and quantifiable parameters associated with potential key events. An alternative risk assessment approach is the application of toxicogenomics and systems biology in human populations, animals and in vitro models of the HSC stem cell niche, exposed to a range of levels of benzene. These approaches will inform our understanding of the mechanisms of benzene toxicity and identify additional biomarkers of exposure, early effect and susceptibility useful for risk assessment.
Article
Full-text available
Aggressive leukemias arise in both children and adults as a result of rearrangements to the mixed-lineage leukemia gene (MLL) located on chromosome 11q23. MLL encodes a large histone methyltransferase that directly binds DNA and positively regulates gene transcription, including homeobox (HOX) genes. MLL is involved in chromosomal translocations, partial tandem duplications, and amplifications, all of which result in hematopoietic malignancies due to sustained HOX expression and stalled differentiation. MLL lesions are associated with both acute myeloid leukemia and acute lymphoid leukemia and are usually associated with a relatively poor prognosis despite improved treatment options such as allogeneic hematopoietic stem cell transplantation, which underscores the need for new treatment regimens. Recent advances have begun to reveal the molecular mechanisms that drive MLL-associated leukemias, which, in turn, have provided opportunities for therapeutic development. Here, we discuss the etiology of MLL leukemias and potential directions for future therapy.
Article
DNA repair via homologous recombination (HR) is indispensable for genome integrity and cell survival but if unrestrained can result in undesired chromosomal rearrangements. The regulatory mechanisms of HR are not fully understood. Cyclic GMP-AMP synthase (cGAS) is best known as a cytosolic innate immune sensor critical for the outcome of infections, inflammatory diseases, and cancer. Here, we report that cGAS is primarily a chromatin-bound protein that inhibits DNA repair by HR, thereby accelerating genome destabilization, micronucleus generation, and cell death under conditions of genomic stress. This function is independent of the canonical STING-dependent innate immune activation and is physiologically relevant for irradiation-induced depletion of bone marrow cells in mice. Mechanistically, we demonstrate that inhibition of HR repair by cGAS is linked to its ability to self-oligomerize, causing compaction of bound template dsDNA into a higher-ordered state less amenable to strand invasion by RAD51-coated ssDNA filaments. This previously unknown role of cGAS has implications for understanding its involvement in genome instability-associated disorders including cancer.
Article
This research focused on three major questions regarding benzene-induced hematopoietic neoplasms (HPNs). First, why are HPNs induced equivocally and at only threshold level with low-dose benzene exposure despite the significant genotoxicity of benzene even at low doses both in experiments and in epidemiology? Second, why is there no linear increase in incidence at high-dose exposure despite a lower acute toxicity (LD(50) > 1000 mg/kg body weight; WHO, 2003, Benzene in drinking-water. Background document for development of WHO Guidelines for Drinking-Water Quality)? Third, why are particular acute myeloid leukemias (AMLs) not commonly observed in mice, although AMLs are frequently observed in human cases of occupational exposure to benzene? In this study, we hypothesized that the threshold-like equivocal induction of HPNs at low-dose benzene exposure is based on DNA repair potential in wild-type mice and that the limited increase in HPNs at a high-dose exposure is due to excessive apoptosis in wild-type mice. To determine whether Trp53 deficiency satisfies the above hypotheses by eliminating or reducing DNA repair and by allowing cells to escape apoptosis, we evaluated the incidence of benzene-induced HPNs in Trp53-deficient C57BL/6 mice with specific regard to AMLs. We also used C3H/He mice, AML prone, with Trp53 deficiency to explore whether a higher incidence of AMLs on benzene exposure might explain the above human-murine differences. As a result, heterozygous Trp53-deficient mice of both strains showed a nonthreshold response of the incidence of HPNs at the lower dose, whereas both strains showed an increasing HPN incidence up to 100% with increasing benzene exposure dose, including AMLs, that developed 38% of heterozygous Trp53-deficient C3H/He mice compared to only 9% of wild-type mice exposed to the high dose. The detection of AMLs in heterozygous Trp53-deficient mice, even in the C57BL/6 strain, implies that benzene may be a potent inducer of AMLs also in mice with some strain differences.