Prediction of interval breast cancer risk using genetic variants

项目总结/文摘

Project Summary/Abstract This is a resubmission of a K08 award application for Dr. Yiwey Shieh, a general internist at the University of California, San Francisco (UCSF). Dr. Shieh’s long-term career goal is to become a leading clinician- investigator working at the intersection of precision medicine and cancer screening/prevention. This K08 award will provide Dr. Shieh with the support necessary to: 1) develop an understanding of breast cancer biology and tumor gene expression profiling, 2) expand his analytical skills in genetics and prediction modeling, 3) obtain the skills needed to conduct late-translational studies on personalized cancer screening, and 4) build an inde- pendent research career. To help him achieve these goals, Dr. Shieh has assembled an exemplary team of mentors with complementary expertise. Dr. Elad Ziv, a leading cancer genetic epidemiologist, will serve as the primary mentor and oversee completion of research aims and training goals. Co-mentors include: Dr. Laura van’t Veer, an expert in gene expression analysis of breast cancer; Dr. Mi-Ok Kim, an expert in biostatistical methods and study design; and Dr. Laura Esserman, a breast surgeon and leading innovator in precision on- cology. The proposed work will benefit from the available expertise and rich institutional environment of UCSF, specifically the Helen Diller Family Comprehensive Cancer Center, one of the top cancer centers in the coun- try. Dr. Shieh will leverage the above resources to address an important problem in cancer control, namely the limited ability of current breast cancer screening strategies to detect biologically aggressive cancers. These cancers tend to present symptomatically following a normal mammogram as “interval cancers”, and often at advanced stages. Dr. Shieh’s past work has focused on predicting overall breast cancer risk using clinical risk models and polygenic risk scores (PRS) representing the combined effects of multiple single nucleotide poly- morphisms (SNPs). Dr. Shieh proposes to adopt this approach to construct a risk model for interval cancers based on preliminary data suggesting that previously discovered SNPs may hold additional prediction for breast cancer phenotype. Given the ability of gene expression profiling to provide detailed tumor phenotypic information, Dr. Shieh proposes to identify gene expression signatures correlated with rapidly-developing (ag- gressive) interval cancers (Aim 1). Dr. Shieh will then use these gene expression signatures to select SNPs associated with aggressiveness (Aim 2). These selected SNPs will be used to construct a PRS for aggressive cancer. Finally, Dr. Shieh will test the ability of this PRS to predict interval cancers, both alone and in combina- tion with breast density and clinical risk factors (Aim 3). The proposed aims will leverage Dr. Shieh’s unique access to data from clinical trials, tumor atlases, and breast cancer screening cohorts. The results will directly lead to subsequent studies on using an interval cancer risk model to prospectively inform screening and pre- vention, as well as studies on the role of novel biomarkers in refining risk stratification among high-risk women.