Principal Investigator: Kara Maxwell PhD MD, Danielle Mowery PhD
Co-Investigators: Chris Stoeckert PhD, Peter Gabriel MD
Department: Medicine and Genetics
Services Provided: Data Wrangling, Data Analysis
Description:
According to the Center for Disease Control, in the United States, lung cancer is ranked 3rd in among rates of new cancers and 1st among cancer mortality. The estimated 5-year survival from 2009-2015 is only 19.4%. Genome wide association studies (GWAS) have identified a number of common inherited single nucleotide polymorphisms (SNPs) associated with lung cancer risk, and, in some cases, survival in many common cancer types. However, most of these SNPs are associated with small effect sizes and the clinical utility of individual SNPs is low. Polygenic risk scores (PRS) combining the effects of multiple SNPs have been shown to be predictive of cancer risk; however, the effect on lung cancer outcomes i.e., recurrence and mortality is unknown. To study this hypothesis, robust and high throughput methods of determining a patient’s course with regards to diagnosis, recurrence, and survival from electronic health record (EHR) data are needed.
