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Grant Details

Grant Number: 5R01CA201358-03 Interpret this number
Primary Investigator: Witte, John
Organization: University Of California, San Francisco
Project Title: Genome-Wide Pleiotropy Scan Across Multiple Cancers
Fiscal Year: 2018
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Abstract

Project Summary Cancer is a common but complex disease with a number of unresolved issues surrounding its underlying genetic basis. Recent work suggests that some phenotypically distinct cancers may arise due to similar genetic factors. We propose to evaluate this potential pleiotropy using existing genetic measures in the large, well-characterized Kaiser Permanente Research Program in Genes, Environment and Health cohort. This cohort includes over 110,266 individuals with a genome-wide array data, and 22,575 of these individuals will have been diagnosed with cancer by the start of this project. We will leverage this information to undertake a comprehensive evaluation of the shared genetic basis underlying cancers. In particular, our initial aim will evaluate the heritability and overall shared genetic basis of different cancers sites. Then we will investigate whether specific genetic variants impact risk of different cancers, incorporating into our analyses information about cancer organ systems and exposures that may modify the genetic associations (e.g., smoking). Our third aim will decipher the genetic basis of multiple cancers occurring in the same individual, including exome sequencing of the approximately 1,800 individuals diagnosed with multiple cancers in the cohort and their family members as available. Based on our findings from these aims, we will evaluate the potential biological and functional relevance of genetic variants exhibiting carcinogenic pleiotropy. Taken together, this project provides a unique, innovative, and efficient opportunity to detect pleotropic associations across a range of cancer sites in a single, large cohort. he individual-level data from an essentially population-based study allows us to evaluate novel hypotheses about the shared genetic basis of multiple cancers, and nicely complements existing meta-analyses efforts across different GWAS of the most common cancer sites. Understanding such potential carcinogenic pleiotropy may help clarify the biological basis of this disease, explain and predict the occurrence of multiple cancers, and insights into possible treatment strategies among patients with seemingly distinct cancers.

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Publications

Orchid: a novel management, annotation and machine learning framework for analyzing cancer mutations.
Authors: Cario C.L. , Witte J.S. .
Source: Bioinformatics (oxford, England), 2018-03-15 00:00:00.0; 34(6), p. 936-942.
PMID: 29106441
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Identification of Pleiotropic Cancer Susceptibility Variants from Genome-Wide Association Studies Reveals Functional Characteristics.
Authors: Wu Y.H. , Graff R.E. , Passarelli M.N. , Hoffman J.D. , Ziv E. , Hoffmann T.J. , Witte J.S. .
Source: Cancer Epidemiology, Biomarkers & Prevention : A Publication Of The American Association For Cancer Research, Cosponsored By The American Society Of Preventive Oncology, 2018 Jan; 27(1), p. 75-85.
EPub date: 2017-11-17 00:00:00.0.
PMID: 29150481
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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 00:00:00.0; 186(7), p. 762-770.
PMID: 28978192
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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 00:00:00.0; 186(7), p. 753-761.
PMID: 28978193
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Familial Risk and Heritability of Colorectal Cancer in the Nordic Twin Study of Cancer.
Authors: Graff R.E. , Möller S. , Passarelli M.N. , Witte J.S. , Skytthe A. , Christensen K. , Tan Q. , Adami H.O. , Czene K. , Harris J.R. , et al. .
Source: Clinical Gastroenterology And Hepatology : The Official Clinical Practice Journal Of The American Gastroenterological Association, 2017 Aug; 15(8), p. 1256-1264.
EPub date: 2017-01-24 00:00:00.0.
PMID: 28130150
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Cis-eQTL-based trans-ethnic meta-analysis reveals novel genes associated with breast cancer risk.
Authors: Hoffman J.D. , Graff R.E. , Emami N.C. , Tai C.G. , Passarelli M.N. , Hu D. , Huntsman S. , Hadley D. , Leong L. , Majumdar A. , et al. .
Source: Plos Genetics, 2017 Mar; 13(3), p. e1006690.
EPub date: 2017-03-31 00:00:00.0.
PMID: 28362817
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Genome-wide Association Study Of Prostate-specific Antigen Levels Identifies Novel Loci Independent Of Prostate Cancer
Authors: Hoffmann T.J. , Passarelli M.N. , Graff R.E. , Emami N.C. , Sakoda L.C. , Jorgenson E. , Habel L.A. , Shan J. , Ranatunga D.K. , Quesenberry C.P. , et al. .
Source: Nature Communications, 2017-01-31 00:00:00.0; 8, p. 14248.
PMID: 28139693
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Determining Which Phenotypes Underlie A Pleiotropic Signal
Authors: Majumdar A. , Haldar T. , Witte J.S. .
Source: Genetic Epidemiology, 2016 Jul; 40(5), p. 366-81.
PMID: 27238845
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An efficient Bayesian meta-analysis approach for studying cross-phenotype genetic associations.
Authors: Majumdar A. , Haldar T. , Bhattacharya S. , Witte J.S. .
Source: Plos Genetics, 2018 02; 14(2), p. e1007139.
EPub date: 2018-02-12 00:00:00.0.
PMID: 29432419
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