Skip to main content
Grant Details

Grant Number: 2R01CA189532-05 Interpret this number
Primary Investigator: Hsu, Li
Organization: Fred Hutchinson Cancer Research Center
Project Title: Statistical Methods for Analysis of Tumor Heterogeneity in Genetic Epidemiology
Fiscal Year: 2019
Back to top


Abstract

PROJECT SUMMARY/ABSTRACT Cancer is a major morbidity and mortality burden throughout the world. While much progress has been made, the elimination of cancer has not yet been achieved. In the currently funded grant, we have developed statistical methods for genome-wide association analysis of cancer and studied cancer by the site of origin. However, even within a site, cancer can have distinct mutational profiles across patients. Pooling all cancer cases occurring at one site as one disease may miss important clinical and etiological insights. Recently technology advances have made it possible to characterize somatic mutations at great detail in large numbers of tumors, providing a unique opportunity to study tumor heterogeneity. The objective of this competitive renewal is to continue our statistical methods development for association analyses of tumor heterogeneity with clinical outcomes, and for studying the underlying genetic and environmental etiology. There are challenges in analyzing the somatic mutation data. First, somatic mutation may only exist in a subset of tumor cells of a patient, so called intra-tumor heterogeneity. While our application is focused on tumor heterogeneity across patients, because intra-tumor heterogeneity can also impact clinical outcomes, important insight could be missed if it were not accounted for. The goal of Aim 1 is to develop statistical methods to account for intra-tumor heterogeneity when assessing the association of somatic mutations with clinical outcomes. Second, it is of great interest to discover germline-somatic mutation link; however, despite that tumor studies are considerably larger than before due to technology advances, the power for discovering such links remains limited because of moderate genetic effects and the burden of accounting for multiple comparison from testing millions of variants. The goal of Aim 2 is to develop novel screening strategies for prioritizing genetic variants in testing genome-wide association with tumor heterogeneity. We will achieve optimal power by using the weighted hypothesis testing framework, allowing for correlated genetic variants and continuous screening statistics. Third, it is common that tumor blocks can usually only be retrieved from a subset of cases and tumor sequencing data are thus only available for this subset. Meanwhile, extensive risk factor information has already been collected for the larger study. The goal of Aim 3 is to develop a robust and efficient approach to incorporate the summary statistics information from the larger study for characterizing the effects of genetic and environmental risk factors on risk of developing cancer with specific tumor feature. The methods will be applied to the Genetics and Epidemiology of Colorectal Cancer Consortium (GECCO, PI: Ulrike Peters; Lead Biostatistician: Li Hsu), which includes over 125,000 colorectal cancer cases and controls all with GWAS data and additionally 7,000 tumors sequencing data. As our methods are also applicable to other cancer studies, we will implement them in computationally efficient and user-friendly software packages and disseminate them to the community through R/CRAN, R/Bioconductor, or Github.

Back to top


Publications

Diagnostics for Pleiotropy in Mendelian Randomization Studies: Global and Individual Tests for Direct Effects.
Authors: Dai J.Y. , Peters U. , Wang X. , Kocarnik J. , Chang-Claude J. , Slattery M.L. , Chan A. , Lemire M. , Berndt S.I. , Casey G. , et al. .
Source: American journal of epidemiology, 2018-12-01; 187(12), p. 2672-2680.
PMID: 30188971
Related Citations

Joint skeleton estimation of multiple directed acyclic graphs for heterogeneous population.
Authors: Liu J. , Sun W. , Liu Y. .
Source: Biometrics, 2019 03; 75(1), p. 36-47.
EPub date: 2018-08-06.
PMID: 30081434
Related Citations

Characterizing functional consequences of DNA copy number alterations in breast and ovarian tumors by spaceMap.
Authors: Conley C.J. , Ozbek U. , Wang P. , Peng J. .
Source: Journal of genetics and genomics = Yi chuan xue bao, 2018-07-20; 45(7), p. 361-371.
EPub date: 2018-07-26.
PMID: 30057342
Related Citations

A new method for constructing tumor specific gene co-expression networks based on samples with tumor purity heterogeneity.
Authors: Petralia F. , Wang L. , Peng J. , Yan A. , Zhu J. , Wang P. .
Source: Bioinformatics (Oxford, England), 2018-07-01; 34(13), p. i528-i536.
PMID: 29949994
Related Citations

Mendelian randomisation study of age at menarche and age at menopause and the risk of colorectal cancer.
Authors: Neumeyer S. , Banbury B.L. , Arndt V. , Berndt S.I. , Bezieau S. , Bien S.A. , Buchanan D.D. , Butterbach K. , Caan B.J. , Campbell P.T. , et al. .
Source: British journal of cancer, 2018 06; 118(12), p. 1639-1647.
EPub date: 2018-05-24.
PMID: 29795306
Related Citations

A Mixed-Effects Model for Powerful Association Tests in Integrative Functional Genomics.
Authors: Su Y.R. , Di C. , Bien S. , Huang L. , Dong X. , Abecasis G. , Berndt S. , Bezieau S. , Brenner H. , Caan B. , et al. .
Source: American journal of human genetics, 2018-05-03; 102(5), p. 904-919.
PMID: 29727690
Related Citations

The association between copy number aberration, DNA methylation and gene expression in tumor samples.
Authors: Sun W. , Bunn P. , Jin C. , Little P. , Zhabotynsky V. , Perou C.M. , Hayes D.N. , Chen M. , Lin D.Y. .
Source: Nucleic acids research, 2018-04-06; 46(6), p. 3009-3018.
PMID: 29529299
Related Citations

Joint Analysis of Strain and Parent-of-Origin Effects for Recombinant Inbred Intercrosses Generated from Multiparent Populations with the Collaborative Cross as an Example.
Authors: Liu Y. , Xiong S. , Sun W. , Zou F. .
Source: G3 (Bethesda, Md.), 2018-02-02; 8(2), p. 599-605.
EPub date: 2018-02-02.
PMID: 29255115
Related Citations

On Estimation of the Hazard Function from Population-based Case-Control Studies.
Authors: Hsu L. , Gorfine M. , Zucker D.M. .
Source: Journal of the American Statistical Association, 2018; 113(522), p. 560-570.
EPub date: 2018-06-12.
PMID: 30906082
Related Citations

Current Challenges and New Opportunities for Gene-Environment Interaction Studies of Complex Diseases.
Authors: McAllister K. , Mechanic L.E. , Amos C. , Aschard H. , Blair I.A. , Chatterjee N. , Conti D. , Gauderman W.J. , Hsu L. , Hutter C.M. , et al. .
Source: American journal of epidemiology, 2017-10-01; 186(7), p. 753-761.
PMID: 28978193
Related Citations

Update on the State of the Science for Analytical Methods for Gene-Environment Interactions.
Authors: Gauderman W.J. , Mukherjee B. , Aschard H. , Hsu L. , Lewinger J.P. , Patel C.J. , Witte J.S. , Amos C. , Tai C.G. , Conti D. , et al. .
Source: American journal of epidemiology, 2017-10-01; 186(7), p. 762-770.
PMID: 28978192
Related Citations

Incorporation of Biological Knowledge Into the Study of Gene-Environment Interactions.
Authors: Ritchie M.D. , Davis J.R. , Aschard H. , Battle A. , Conti D. , Du M. , Eskin E. , Fallin M.D. , Hsu L. , Kraft P. , et al. .
Source: American journal of epidemiology, 2017-10-01; 186(7), p. 771-777.
PMID: 28978191
Related Citations

A new method to study the change of miRNA-mRNA interactions due to environmental exposures.
Authors: Petralia F. , Aushev V.N. , Gopalakrishnan K. , Kappil M. , W Khin N. , Chen J. , Teitelbaum S.L. , Wang P. .
Source: Bioinformatics (Oxford, England), 2017-07-15; 33(14), p. i199-i207.
PMID: 28881990
Related Citations

Enrichment of colorectal cancer associations in functional regions: Insight for using epigenomics data in the analysis of whole genome sequence-imputed GWAS data.
Authors: Bien S.A. , Auer P.L. , Harrison T.A. , Qu C. , Connolly C.M. , Greenside P.G. , Chen S. , Berndt S.I. , Bézieau S. , Kang H.M. , et al. .
Source: PloS one, 2017; 12(11), p. e0186518.
EPub date: 2017-11-21.
PMID: 29161273
Related Citations

Heritability Estimation using a Regularized Regression Approach (HERRA): Applicable to continuous, dichotomous or age-at-onset outcome.
Authors: Gorfine M. , Berndt S.I. , Chang-Claude J. , Hoffmeister M. , Le Marchand L. , Potter J. , Slattery M.L. , Keret N. , Peters U. , Hsu L. .
Source: PloS one, 2017; 12(8), p. e0181269.
EPub date: 2017-08-16.
PMID: 28813438
Related Citations

Multivariate association analysis with somatic mutation data.
Authors: He Q. , Liu Y. , Peters U. , Hsu L. .
Source: Biometrics, 2018 03; 74(1), p. 176-184.
EPub date: 2017-07-19.
PMID: 28722765
Related Citations

Quantifying the Genetic Correlation between Multiple Cancer Types.
Authors: Lindström S. , Finucane H. , Bulik-Sullivan B. , Schumacher F.R. , Amos C.I. , Hung R.J. , Rand K. , Gruber S.B. , Conti D. , Permuth J.B. , et al. .
Source: Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology, 2017 09; 26(9), p. 1427-1435.
EPub date: 2017-06-21.
PMID: 28637796
Related Citations

Hypothesis testing in functional linear models.
Authors: Su Y.R. , Di C.Z. , Hsu L. .
Source: Biometrics, 2017 06; 73(2), p. 551-561.
EPub date: 2017-03-10.
PMID: 28295175
Related Citations

On estimation of time-dependent attributable fraction from population-based case-control studies.
Authors: Zhao W. , Chen Y.Q. , Hsu L. .
Source: Biometrics, 2017 09; 73(3), p. 866-875.
EPub date: 2017-01-18.
PMID: 28099992
Related Citations

A unified powerful set-based test for sequencing data analysis of GxE interactions.
Authors: Su Y.R. , Di C.Z. , Hsu L. , Genetics and Epidemiology of Colorectal Cancer Consortium .
Source: Biostatistics (Oxford, England), 2017 01; 18(1), p. 119-131.
EPub date: 2016-07-28.
PMID: 27474101
Related Citations

A fully nonparametric estimator of the marginal survival function based on case-control clustered age-at-onset data.
Authors: Gorfine M. , Bordo N. , Hsu L. .
Source: Biostatistics (Oxford, England), 2017 01; 18(1), p. 76-90.
EPub date: 2016-07-19.
PMID: 27436674
Related Citations




Back to Top