Grant Details
Grant Number: |
1R01CA158473-01A1 Interpret this number |
Primary Investigator: |
Zheng, Wei |
Organization: |
Vanderbilt University |
Project Title: |
Genome Sequencing to Identify Novel Genetic Factors for Breast Cancer Risk |
Fiscal Year: |
2012 |
Abstract
DESCRIPTION (provided by applicant): Genetic factors play an important role in the etiology of both sporadic and familial breast cancer, a complex, multifactorial disease. Known genetic risk factors identified to date, including both rare high- penetrance genes and common low-penetrance variants, explain only about 28% of heritability for breast cancer. Recently emerged evidence strongly suggests that most of the heritable risk for breast cancer and other complex diseases may be due to a large number of low-frequency moderate-penetrance genes that are difficult to identify using conventional family-based linkage analyses and genome-wide association studies (GWAS). In this application, we propose a novel study to systematically search for the entire coding region in the human genome to identify new genetic susceptibility factors for breast cancer. This study will be built upon the resources we established in three NCI-funded large epidemiologic studies conducted among women in Shanghai, in which genomic DNA samples and comprehensive clinical and epidemiological data were collected from nearly 8,000 breast cancer cases and a large number of community controls. Specifically, we propose to sequence the whole exome for 600 genetically-enriched breast cancer cases and 600 controls (Stage 1). Using data from Stage 1 and those from the 1000 Genomes Project, we will select approximately 350 promising genes for replication through variant genotyping (Stage 2) in an independent set of cases and controls. Approximately 20 genes will be selected for Stage 3 replication from those that show promising association in Stage 2 but require additional evaluation to either confirm or reject the hypotheses. To our knowledge, this is the first large association study for breast cancer using whole exome sequencing. With strong methodology and the use of novel technology and study design, the proposed study will identify novel genes and pathways that will significantly improve our understanding of breast cancer genetics and biology. Newly identified genes, particularly those with a substantial effect size, could serve as targets for novel cancer treatment and be used for cancer screening and risk assessment.
PUBLIC HEALTH RELEVANCE: Genetic factors play a major role in the etiology of breast cancers, yet only a small number of cases are explained by genetic factors identified thus far. Using novel research designs and sequencing technologies, this proposed study will systematically search the human genomes for genes that contribute to breast cancer susceptibility. Results from this study will significantly improve the understanding of breast cancer biology and genetics, which will be valuable in designing new therapies and cost-efficient prevention strategies for this common malignancy.
Publications
Deciphering colorectal cancer genetics through multi-omic analysis of 100,204 cases and 154,587 controls of European and east Asian ancestries.
Authors: Fernandez-Rozadilla C.
, Timofeeva M.
, Chen Z.
, Law P.
, Thomas M.
, Schmit S.
, Díez-Obrero V.
, Hsu L.
, Fernandez-Tajes J.
, Palles C.
, et al.
.
Source: Nature Genetics, 2023 Jan; 55(1), p. 89-99.
EPub date: 2022-12-20 00:00:00.0.
PMID: 36539618
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Genome- and transcriptome-wide association studies of 386,000 Asian and European-ancestry women provide new insights into breast cancer genetics.
Authors: Jia G.
, Ping J.
, Shu X.
, Yang Y.
, Cai Q.
, Kweon S.S.
, Choi J.Y.
, Kubo M.
, Park S.K.
, Bolla M.K.
, et al.
.
Source: American Journal Of Human Genetics, 2022-11-03 00:00:00.0; , .
EPub date: 2022-11-03 00:00:00.0.
PMID: 36356581
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Developing and validating polygenic risk scores for colorectal cancer risk prediction in East Asians.
Authors: Ping J.
, Yang Y.
, Wen W.
, Kweon S.S.
, Matsuda K.
, Jia W.H.
, Shin A.
, Gao Y.T.
, Matsuo K.
, Kim J.
, et al.
.
Source: International Journal Of Cancer, 2022-06-29 00:00:00.0; , .
EPub date: 2022-06-29 00:00:00.0.
PMID: 35765848
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Evaluation of pathogenetic mutations in breast cancer predisposition genes in population-based studies conducted among Chinese women.
Authors: Zeng C.
, Guo X.
, Wen W.
, Shi J.
, Long J.
, Cai Q.
, Shu X.O.
, Xiang Y.
, Zheng W.
.
Source: Breast Cancer Research And Treatment, 2020-04-21 00:00:00.0; , .
EPub date: 2020-04-21 00:00:00.0.
PMID: 32318955
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Identification of novel breast cancer susceptibility loci in meta-analyses conducted among Asian and European descendants.
Authors: Shu X.
, Long J.
, Cai Q.
, Kweon S.S.
, Choi J.Y.
, Kubo M.
, Park S.K.
, Bolla M.K.
, Dennis J.
, Wang Q.
, et al.
.
Source: Nature Communications, 2020-03-05 00:00:00.0; 11(1), p. 1217.
EPub date: 2020-03-05 00:00:00.0.
PMID: 32139696
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Genetically Predicted Levels of DNA Methylation Biomarkers and Breast Cancer Risk: Data From 228 951 Women of European Descent.
Authors: Yang Y.
, Wu L.
, Shu X.O.
, Cai Q.
, Shu X.
, Li B.
, Guo X.
, Ye F.
, Michailidou K.
, Bolla M.K.
, et al.
.
Source: Journal Of The National Cancer Institute, 2020-03-01 00:00:00.0; 112(3), p. 295-304.
PMID: 31143935
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Identification of Novel Loci and New Risk Variant in Known Loci for Colorectal Cancer Risk in East Asians.
Authors: Lu Y.
, Kweon S.S.
, Cai Q.
, Tanikawa C.
, Shu X.O.
, Jia W.H.
, Xiang Y.B.
, Huyghe J.R.
, Harrison T.A.
, Kim J.
, et al.
.
Source: Cancer Epidemiology, Biomarkers & Prevention : A Publication Of The American Association For Cancer Research, Cosponsored By The American Society Of Preventive Oncology, 2020 02; 29(2), p. 477-486.
EPub date: 2019-12-11 00:00:00.0.
PMID: 31826910
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Discovery of rare coding variants in OGDHL and BRCA2 in relation to breast cancer risk in Chinese women.
Authors: Guo X.
, Long J.
, Chen Z.
, Shu X.O.
, Xiang Y.B.
, Wen W.
, Zeng C.
, Gao Y.T.
, Cai Q.
, Zheng W.
.
Source: International Journal Of Cancer, 2019-12-13 00:00:00.0; , .
EPub date: 2019-12-13 00:00:00.0.
PMID: 31837001
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Discovery of a pathogenic variant rs139379666 (p. P2974L) in ATM for breast cancer risk in Chinese populations.
Authors: Guo X.
, Lin W.
, Bai M.
, Li H.
, Wen W.
, Zeng C.
, Chen Z.
, He J.
, Chen J.
, Cai Q.
, et al.
.
Source: Cancer Epidemiology, Biomarkers & Prevention : A Publication Of The American Association For Cancer Research, Cosponsored By The American Society Of Preventive Oncology, 2019-06-03 00:00:00.0; , .
EPub date: 2019-06-03 00:00:00.0.
PMID: 31160347
Related Citations
Large-Scale Genome-Wide Association Study of East Asians Identifies Loci Associated With Risk for Colorectal Cancer.
Authors: Lu Y.
, Kweon S.S.
, Tanikawa C.
, Jia W.H.
, Xiang Y.B.
, Cai Q.
, Zeng C.
, Schmit S.L.
, Shin A.
, Matsuo K.
, et al.
.
Source: Gastroenterology, 2019 Apr; 156(5), p. 1455-1466.
EPub date: 2018-12-06 00:00:00.0.
PMID: 30529582
Related Citations
Associations of obesity and circulating insulin and glucose with breast cancer risk: a Mendelian randomization analysis.
Authors: Shu X.
, Wu L.
, Khankari N.K.
, Shu X.O.
, Wang T.J.
, Michailidou K.
, Bolla M.K.
, Wang Q.
, Dennis J.
, Milne R.L.
, et al.
.
Source: International Journal Of Epidemiology, 2018-10-01 00:00:00.0; , .
EPub date: 2018-10-01 00:00:00.0.
PMID: 30277539
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A transcriptome-wide association study of 229,000 women identifies new candidate susceptibility genes for breast cancer.
Authors: Wu L.
, Shi W.
, Long J.
, Guo X.
, Michailidou K.
, Beesley J.
, Bolla M.K.
, Shu X.O.
, Lu Y.
, Cai Q.
, et al.
.
Source: Nature Genetics, 2018 Jul; 50(7), p. 968-978.
EPub date: 2018-06-18 00:00:00.0.
PMID: 29915430
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Use of deep whole-genome sequencing data to identify structure risk variants in breast cancer susceptibility genes.
Authors: Guo X.
, Shi J.
, Cai Q.
, Shu X.O.
, He J.
, Wen W.
, Allen J.
, Pharoah P.
, Dunning A.
, Hunter D.J.
, et al.
.
Source: Human Molecular Genetics, 2018-03-01 00:00:00.0; 27(5), p. 853-859.
PMID: 29325031
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Whole-Exome Sequencing Identifies Novel Somatic Mutations in Chinese Breast Cancer Patients.
Authors: Zhang Y.
, Cai Q.
, Shu X.O.
, Gao Y.T.
, Li C.
, Zheng W.
, Long J.
.
Source: Journal Of Molecular And Genetic Medicine : An International Journal Of Biomedical Research, 2015 Dec; 9(4), .
PMID: 26870154
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Genome measures used for quality control are dependent on gene function and ancestry.
Authors: Wang J.
, Raskin L.
, Samuels D.C.
, Shyr Y.
, Guo Y.
.
Source: Bioinformatics (oxford, England), 2015-02-01 00:00:00.0; 31(3), p. 318-23.
EPub date: 2015-02-01 00:00:00.0.
PMID: 25297068
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Illumina human exome genotyping array clustering and quality control.
Authors: Guo Y.
, He J.
, Zhao S.
, Wu H.
, Zhong X.
, Sheng Q.
, Samuels D.C.
, Shyr Y.
, Long J.
.
Source: Nature Protocols, 2014 Nov; 9(11), p. 2643-62.
PMID: 25321409
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Rare coding variants and breast cancer risk: evaluation of susceptibility Loci identified in genome-wide association studies.
Authors: Zhang Y.
, Long J.
, Lu W.
, Shu X.O.
, Cai Q.
, Zheng Y.
, Li C.
, Li B.
, Gao Y.T.
, Zheng W.
.
Source: Cancer Epidemiology, Biomarkers & Prevention : A Publication Of The American Association For Cancer Research, Cosponsored By The American Society Of Preventive Oncology, 2014 Apr; 23(4), p. 622-8.
PMID: 24470074
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Improved variant calling accuracy by merging replicates in whole-exome sequencing studies.
Authors: Zhang Y.
, Li B.
, Li C.
, Cai Q.
, Zheng W.
, Long J.
.
Source: Biomed Research International, 2014; 2014, p. 319534.
PMID: 25162009
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An evaluation of allele frequency estimation accuracy using pooled sequencing data.
Authors: Guo Y.
, Cai Q.
, Li C.
, Li J.
, Courtney R.
, Zheng W.
, Long J.
.
Source: International Journal Of Computational Biology And Drug Design, 2013; 6(4), p. 279-93.
PMID: 24088264
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