My long-term goal is to become an independent scientific leader in the genetic epidemiology of cancer. My background includes an MD, a PhD in epidemiology, and post- doctoral training in statistical genetics. My immediate career goals are to obtain the necessary training in computational genomics and bioinformatics that would allow me to expand my methodological focus to encompass the integrative analysis of multiple types of genomic data to enhance the detection of cancer-associated genes. The application of these methods to two distinct diseases will considerably broaden my training as a cancer genetic epidemiologist. To this end, I have chosen highly qualified and experienced mentors: Drs. Alice Whittemore (cancer genetic epidemiology), Robert Tibshirani (statistical analysis of genomic data), James Brooks (cancer genomics), and Patrick Brown (genomic analysis of cancer);and developed a training plan that includes coursework in computational genomics and bioinformatics. The overall goal of this proposal is to better understand the genetic bases of ovarian and prostate cancer.
The specific aims are to: (1) identify genetic risk factors for ovarian cancer by re-sequencing one of the most promising regions implicated by genome-wide association studies in order to help find the most likely causal variants;(2) identify genetic risk factors for prostate cancer by mining genome-wide association studies and expression data repositories;and (3) define genomic signatures of aggressive prostate tumors based upon a new method for the combined analysis of genome-wide expression level, copy number, and genotype data. The elucidation of the genetic underpinnings of ovarian and prostate cancer may ultimately lead to improvements in risk stratification and prognostication, and better management of these important diseases. The proposed methodology is also applicable to other cancers with available genomic data. This multidisciplinary research and training will form an invaluable experience that will become increasingly important in cancer research as '-omics'technology rapidly advances.
Cancers of the ovary and prostate are significant public health concerns in the aging U.S. population. This project addresses genetic factors that are associated with the development or progression of these diseases. A better understanding of the underlying genetics will help improve efforts to prevent, diagnose, and reduce morbidity and mortality from these important cancers.
|Block, Matthew S; Vierkant, Robert A; Rambau, Peter F et al. (2018) MyD88 and TLR4 Expression in Epithelial Ovarian Cancer. Mayo Clin Proc 93:307-320|
|Earp, Madalene; Tyrer, Jonathan P; Winham, Stacey J et al. (2018) Variants in genes encoding small GTPases and association with epithelial ovarian cancer susceptibility. PLoS One 13:e0197561|
|Peres, Lauren C; Risch, Harvey; Terry, Kathryn L et al. (2018) Racial/ethnic differences in the epidemiology of ovarian cancer: a pooled analysis of 12 case-control studies. Int J Epidemiol 47:460-472|
|Ong, Jue-Sheng; Hwang, Liang-Dar; Cuellar-Partida, Gabriel et al. (2018) Assessment of moderate coffee consumption and risk of epithelial ovarian cancer: a Mendelian randomization study. Int J Epidemiol 47:450-459|
|Praestegaard, Camilla; Jensen, Allan; Jensen, Signe M et al. (2017) Cigarette smoking is associated with adverse survival among women with ovarian cancer: Results from a pooled analysis of 19 studies. Int J Cancer 140:2422-2435|
|Reid, Brett M; Permuth, Jennifer B; Chen, Y Ann et al. (2017) Integration of Population-Level Genotype Data with Functional Annotation Reveals Over-Representation of Long Noncoding RNAs at Ovarian Cancer Susceptibility Loci. Cancer Epidemiol Biomarkers Prev 26:116-125|
|Alexeeff, Stacey E; Odo, Nnaemeka U; Lipson, Jafi A et al. (2017) Age at Menarche and Late Adolescent Adiposity Associated with Mammographic Density on Processed Digital Mammograms in 24,840 Women. Cancer Epidemiol Biomarkers Prev 26:1450-1458|
|Kar, Siddhartha P; Adler, Emily; Tyrer, Jonathan et al. (2017) Enrichment of putative PAX8 target genes at serous epithelial ovarian cancer susceptibility loci. Br J Cancer 116:524-535|
|Ovarian Tumor Tissue Analysis (OTTA) Consortium; Goode, Ellen L; Block, Matthew S et al. (2017) Dose-Response Association of CD8+ Tumor-Infiltrating Lymphocytes and Survival Time in High-Grade Serous Ovarian Cancer. JAMA Oncol 3:e173290|
|Usset, Joseph L; Raghavan, Rama; Tyrer, Jonathan P et al. (2016) Assessment of Multifactor Gene-Environment Interactions and Ovarian Cancer Risk: Candidate Genes, Obesity, and Hormone-Related Risk Factors. Cancer Epidemiol Biomarkers Prev 25:780-90|
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