Details

Autor(en) / Beteiligte

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

Titel

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

Ist Teil von

• Cold Spring Harbor molecular case studies, 2023-12, Vol.9 (4), p.a006298

Ort / Verlag

United States: Cold Spring Harbor Laboratory Press

Erscheinungsjahr

2023

Quelle

MEDLINE

Beschreibungen/Notizen

• 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 and mutations associated with neuroendocrine prostate cancer phenotype, previously reported to be enriched in veterans. We also identified several potential novel mutations in , , , , and 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.