Nathanael R. Fillmore
Publications / 2023
paper
Cold Spring Harbor Molecular Case Studies2023doi:10.1101/mcs.a006298

Prostate cancer patient stratification by molecular signatures in the Veterans Precision Oncology Data Commons.

Kyle M. Hernandez†, Aarti Venkat†, Danne C. Elbers†, John R. Bihn, Mary T. Brophy, Nhan V. Do, Jennifer La, Qiong Liu, Andrew Prokhorenkov, Noah Metoki-Shlubsky, Feng-Chi Sung, Channing J. Paller‡, Nathanael R. Fillmore‡, Robert L. Grossman‡

† Equal first authorship · ‡ Equal senior authorship

Summary

Analysis of genomic data from veterans with advanced prostate cancer identified two distinct molecular subgroups with unique mutational signatures. These findings suggest that clustering patients by their specific genetic profiles can help clinicians identify targetable mutations and personalize precision oncology treatments.

Key result

Hierarchical clustering of 45 veterans with advanced prostate cancer identified two distinct subgroups containing therapeutically targetable molecular features and novel mutational signatures.

Abstract

Veterans are at an increased risk for prostate cancer, a disease with extraordinary clinical and molecular heterogeneity, compared with the general population. However, little is known about the underlying molecular heterogeneity within the veteran population and its impact on patient management and treatment. Using clinical and targeted tumor sequencing data from the National Veterans Affairs health system, we conducted a retrospective cohort study on 45 patients with advanced prostate cancer in the Veterans Precision Oncology Data Commons (VPODC), most of whom were metastatic castration-resistant. We characterized the mutational burden in this cohort and conducted unsupervised clustering analysis to stratify patients by molecular alterations. Veterans with prostate cancer exhibited a mutational landscape broadly similar to prior studies, including KMT2A and NOTCH1 mutations associated with neuroendocrine prostate cancer phenotype, previously reported to be enriched in veterans. We also identified several potential novel mutations in PTEN, MSH6, VHL, SMO, and ABL1 Hierarchical clustering analysis revealed two subgroups containing therapeutically targetable molecular features with novel mutational signatures distinct from those reported in the Catalogue of Somatic Mutations in Cancer database. The clustering approach presented in this study can potentially be used to clinically stratify patients based on their distinct mutational profiles and identify actionable somatic mutations for precision oncology.

Key figure

Key figure from Prostate cancer patient stratification by molecular signatures in the Veterans Precision Oncology Data Commons.