Novel Genomic Risk Stratification Model for Primary Gastrointestinal Stromal Tumors (GIST) in the Adjuvant Therapy Era.
Academic Article
Overview
abstract
PURPOSE: Traditional risk stratification schemes in gastrointestinal stromal tumors (GIST) were defined in the pre-imatinib era and rely solely on clinicopathologic metrics. We hypothesize that genomic-based risk stratification is prognostically relevant in the current era of tyrosine kinase inhibitor (TKI) therapeutics. EXPERIMENTAL DESIGN: Comprehensive mutational and copy-number profiling using MSK-IMPACT was performed. We integrated clinicopathologic and genomic parameters and utilized an elastic-net penalized Cox proportional hazards machine learning model for outcome risk stratification. RESULTS: A 3-tier genomic risk stratification model for recurrence-free survival (RFS) in 152 primary localized gastric and 80 small bowel GISTs was proposed. Gastric GISTs were classified as high risk if chr1p deletion or SDHB loss was present, and intermediate risk if chr14q deletion was present or KIT exon 11 mutation was absent. Small bowel GISTs were classified as high risk if MAX/MGA/MYC, CDKN2A, or RB1 alterations were present, and intermediate risk if chr1p deletion or chr5q amplification was present. Compared with conventional risk stratification, genomic risk stratification both upgrades and downgrades, suggesting that conventional risk stratification may underestimate or overtreat some high-risk and low-risk patients, respectively. Longitudinal sequencing detected most KIT-independent genomic alterations at baseline. Subanalysis in 26 SDH-deficient GISTs revealed that presence of TP53 mutations or chr1q amplifications portends worse RFS and disease-free survival. CONCLUSIONS: We developed a novel, next-generation genomic risk stratification model for primary gastric and small bowel GISTs, complementing traditional clinicopathologic models. Future independent validation of our model in external cohorts is essential.