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
Related Citations
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
Related Citations
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
Related Citations
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
Related Citations
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
Related Citations
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
Related Citations
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
Related Citations
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
Related Citations
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
Related Citations