Health systems are stewards of patient electronic health record (EHR) data with extraordinarily rich depth and breadth, reflecting thousands of diagnoses and exposures. Measures of genomic variation integrated with EHRs offer a potential strategy to accurately stratify patients for risk profiling and discover new relationships between diagnoses and genomes. The objective of this study was to evaluate whether Polygenic Risk Scores (PRS) for common cancers are associated with multiple phenotypes in a Phenome-wide Association Study (PheWAS) conducted in 28,260 unrelated, genotyped patients of recent European ancestry who consented to participate in the Michigan Genomics Initiative, a longitudinal biorepository effort within Michigan Medicine. PRS for 12 cancer traits were calculated using summary statistics from the NHGRI-EBI GWAS catalog. A total of 1,711 synthetic case-control studies was used for PheWAS analyses. Patients with at least one cancer diagnosis constituted 13,490 patients. PRSs exhibited strong association for several cancer traits they were designed for including female breast cancer, prostate cancer and melanomas of skin. Phenome-wide significant associations were observed between PRS and many non-cancer diagnoses. To differentiate primary trait-mediated PRS associations from associations that arise through shared genetic risk profiles, the idea of “exclusion PRS PheWAS” was introduced and uncovered phenome-wide significant associations between a lower risk for hypothyroidism in patients with high thyroid cancer PRS and a higher risk for actinic keratosis in patients with high squamous cell carcinoma PRS after removing all cases of the primary cancer trait. This is the first PheWAS study using PRS instead of single variant.