Come hear David Qian, MD/PhD Candidate, Geisel School of Medicine talk on Wednesday, April 29 on his research in the application of statistics to characterizing lung cancer risk in Kemeny 006 at 6:00 PM.

PIZZA WILL BE SERVED.



TITLE:
Statistical Genetics of Lung Cancer Risk: a Pathway-Based Approach

ABSTRACT:
For most diseases, strong single-gene effects are the exception, not the rule. Genome-wide association studies (GWAS) have identified hundreds of risk-conferring germline mutations for common cancers, such as lung cancer, breast cancer, and prostate cancer. However, each individual mutation explains only a small fraction of phenotypic variation and is therefore a poor predictor of cancer development. The mutations' biomolecular mechanisms of augmenting cancer risk are also usually poorly understood. I conduct "pathway analysis" to evaluate the joint effects of many mutations in the context of cellular pathway disturbances. In contrast to the conventional study of single mutation-gene-protein influences, this approach captures how overall intracellular functions may be affected by groups of mutations without particular emphasis on any individual mutation. By coupling GWAS results with datasets of tissue-specific protein interactions and pathways, I identify pathways that are statistically enriched with the protein products of genes whose sequence or expression levels are altered by cancer-associated mutations. These derived pathways offer not only greater biologic insights into cancer development, but also a more meaningful way to characterize patient risk in the clinic compared to existing gene panels. The two most common subtypes of lung cancer will be used for pathway analysis demonstrations.