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Grant Details

Grant Number: 5R01CA235553-06 Interpret this number
Primary Investigator: Zheng, Wei
Organization: Vanderbilt University Medical Center
Project Title: Integrating Genomic and Transcriptomic Data to Identify Breast Cancer Susceptibility Genes
Fiscal Year: 2024


Abstract

Project Summary Genetic factors play an important role in the etiology of both sporadic and familial breast cancer. Since 2007, common genetic variants in ~200 loci have been identified in genome-wide association studies (GWAS) in relation to breast cancer risk. However, it is often difficult to translate GWAS findings to disease prevention and treatment since causal genes in the large majority of GWAS-identified loci are unknown. Furthermore, a large fraction of breast cancer heritability remains unexplained. Recent studies suggest that nearly 80% of disease heritability can be explained by genetic variants regulating gene expression. Herein, we propose three well-powered transcriptome-wide association studies (TWAS) to systematically investigate the association of breast cancer risk with gene expression across the transcriptome of African, Asian and European descendants. In Aim 1, we will perform RNA sequencing and high-density genotyping assays using normal breast tissue samples and build race-specific gene expression prediction models using data from 1000 women of African, Asian and European descent. These models will be applied to the GWAS data generated from approximately 320,000 breast cancer patients and controls to impute gene expression for association analyses of predicted gene expression with risk of breast cancer overall and by estrogen receptor and HER2 status. In Aim 2, we will select the top 50 genes identified in Aim 1 for in vitro functional assays to assess their influence on major cell functions related to cancer biology. In Aim 3, we will evaluate whether TWAS-identified genes may express differently in normal breast tissues and breast cancer tissues collected from African, Asian, and European descendants to assess whether these genes may contribute to racial differences in breast cancer risk by molecular subtypes. With strong methodology and a large sample size, we believe that this proposed study should be able to identify and characterize a large number of novel genes related to breast cancer risk. Uncovering breast cancer susceptibility genes will greatly improve the understanding of the genetic and biological basis for breast cancer and accelerate the translation of genetic findings to disease prevention and patient care.



Publications

Case-Case Genome-Wide Analyses Identify Subtype-Informative Variants that Confer Risk for Breast Cancer.
Authors: Sun X. , Verma S.P. , Jia G. , Wang X. , Ping J. , Guo X. , Shu X.O. , Chen J. , Derkach A. , Cai Q. , et al. .
Source: Cancer Research, 2024-06-04 00:00:00.0; , .
EPub date: 2024-06-04 00:00:00.0.
PMID: 38832928
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Large-scale alternative polyadenylation-wide association studies to identify putative cancer susceptibility genes.
Authors: Guo X. , Ping J. , Yang Y. , Su X. , Shu X.O. , Wen W. , Chen Z. , Zhang Y. , Tao R. , Jia G. , et al. .
Source: Cancer Research, 2024-05-17 00:00:00.0; , .
EPub date: 2024-05-17 00:00:00.0.
PMID: 38759092
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Using genome and transcriptome data from African-ancestry female participants to identify putative breast cancer susceptibility genes.
Authors: Ping J. , Jia G. , Cai Q. , Guo X. , Tao R. , Ambrosone C. , Huo D. , Ambs S. , Barnard M.E. , Chen Y. , et al. .
Source: Nature Communications, 2024-05-02 00:00:00.0; 15(1), p. 3718.
EPub date: 2024-05-02 00:00:00.0.
PMID: 38697998
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Genome-wide association analyses of breast cancer in women of African ancestry identify new susceptibility loci and improve risk prediction.
Authors: Jia G. , Ping J. , Guo X. , Yang Y. , Tao R. , Li B. , Ambs S. , Barnard M.E. , Chen Y. , Garcia-Closas M. , et al. .
Source: Nature Genetics, 2024 May; 56(5), p. 819-826.
EPub date: 2024-05-13 00:00:00.0.
PMID: 38741014
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Identification of target proteins for breast cancer genetic risk loci and blood risk biomarkers in a large study by integrating genomic and proteomic data.
Authors: Jia G. , Yang Y. , Ping J. , Xu S. , Liu L. , Guo X. , Tao R. , Long J. , Zheng W. .
Source: International Journal Of Cancer, 2023-02-13 00:00:00.0; , .
EPub date: 2023-02-13 00:00:00.0.
PMID: 36779764
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Integrating transcription factor occupancy with transcriptome-wide association analysis identifies susceptibility genes in human cancers.
Authors: He J. , Wen W. , Beeghly A. , Chen Z. , Cao C. , Shu X.O. , Zheng W. , Long Q. , Guo X. .
Source: Nature Communications, 2022-11-19 00:00:00.0; 13(1), p. 7118.
EPub date: 2022-11-19 00:00:00.0.
PMID: 36402776
Related Citations

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
Related Citations

Associations between circulating proteins and risk of breast cancer by intrinsic subtypes: a Mendelian randomisation analysis.
Authors: Shu X. , Zhou Q. , Sun X. , Flesaker M. , Guo X. , Long J. , Robson M.E. , Shu X.O. , Zheng W. , Bernstein J.L. .
Source: British Journal Of Cancer, 2022-07-26 00:00:00.0; , .
EPub date: 2022-07-26 00:00:00.0.
PMID: 35882941
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Mendelian randomization analyses of 23 known and suspected risk factors and biomarkers for breast cancer overall and by molecular subtypes.
Authors: Chen F. , Wen W. , Long J. , Shu X. , Yang Y. , Shu X.O. , Zheng W. .
Source: International Journal Of Cancer, 2022-04-11 00:00:00.0; , .
EPub date: 2022-04-11 00:00:00.0.
PMID: 35403707
Related Citations

Polygenic risk scores for prediction of breast cancer risk in Asian populations.
Authors: Ho W.K. , Tai M.C. , Dennis J. , Shu X. , Li J. , Ho P.J. , Millwood I.Y. , Lin K. , Jee Y.H. , Lee S.H. , et al. .
Source: Genetics In Medicine : Official Journal Of The American College Of Medical Genetics, 2022 Mar; 24(3), p. 586-600.
EPub date: 2021-12-15 00:00:00.0.
PMID: 34906514
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Incorporating Polygenic Risk Scores and Nongenetic Risk Factors for Breast Cancer Risk Prediction Among Asian Women.
Authors: Yang Y. , Tao R. , Shu X. , Cai Q. , Wen W. , Gu K. , Gao Y.T. , Zheng Y. , Kweon S.S. , Shin M.H. , et al. .
Source: Jama Network Open, 2022-03-01 00:00:00.0; 5(3), p. e2149030.
EPub date: 2022-03-01 00:00:00.0.
PMID: 35311964
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TBX1 functions as a putative oncogene of breast cancer through promoting cell cycle progression.
Authors: Huang S. , Shu X. , Ping J. , Wu J. , Wang J. , Shidal C. , Guo X. , Bauer J.A. , Long J. , Shu X.O. , et al. .
Source: Carcinogenesis, 2022-02-11 00:00:00.0; 43(1), p. 12-20.
PMID: 34919666
Related Citations

Associations of genetic susceptibility to 16 cancers with risk of breast cancer overall and by intrinsic subtypes.
Authors: Choi J. , Jia G. , Wen W. , Tao R. , Long J. , Shu X.O. , Zheng W. .
Source: Hgg Advances, 2022-01-13 00:00:00.0; 3(1), p. 100077.
EPub date: 2021-12-10 00:00:00.0.
PMID: 35047862
Related Citations

Impact of molecular subtype and race on HR+, HER2- breast cancer survival.
Authors: Reid S. , Haddad D. , Tezak A. , Weidner A. , Wang X. , Mautz B. , Moore J. , Cadiz S. , Zhu Y. , Zheng W. , et al. .
Source: Breast Cancer Research And Treatment, 2021-07-31 00:00:00.0; , .
EPub date: 2021-07-31 00:00:00.0.
PMID: 34331630
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