Background/Objectives: Early-onset colorectal cancer (EOCRC; diagnosed before age 50) is rising at an accelerated rate, with a disproportionate impact on underserved populations. While alterations in the receptor tyrosine kinase–RAS (RTK–RAS) signaling pathway play a fundamental role in colorectal cancer (CRC) biology, their prognostic significance in the setting of FOLFOX chemotherapy—particularly across different age groups and ancestral backgrounds—remains insufficiently characterized. We sought to characterize age-, ancestry-, and treatment-specific associations between RTK–RAS alterations and clinical outcomes using an AI-enabled precision oncology framework. Methods: We analyzed 2515 CRC cases, including 266 Hispanic/Latino (H/L) and 2249 non-Hispanic White (NHW) patients, stratified by age at onset, ancestry, and FOLFOX treatment status. Mutation frequencies were assessed using Fisher’s exact and chi-square tests, while overall survival was analyzed with Kaplan–Meier methods. The AI-HOPE and AI-HOPE–RTK–RAS conversational artificial intelligence platforms were used to integrate clinical, genomic, and treatment data via multi-parameter, natural language–based queries. Results: In early-onset Hispanic/Latino patients, ERBB2 and NF1 mutations occurred at significantly lower frequencies in FOLFOX-treated cases compared with untreated cases (p = 0.01 for both). In late-onset H/L patients, NTRK2 mutations were depleted in FOLFOX-treated tumors (p = 0.04). In untreated early-onset H/L patients, MAPK3 and NF1 mutations were enriched relative to NHW counterparts. Among early-onset NHW patients, IGF1R and ERRFI1 mutations were less frequent with FOLFOX exposure, while multiple RTK–RAS genes were reduced in FOLFOX-treated late-onset NHW patients. Survival analyses revealed worse overall survival in FOLFOX-untreated early-onset NHW patients with RTK–RAS alterations (p = 0.029), but improved survival in FOLFOX-treated late-onset NHW patients (p = 0.048). Conclusions: RTK–RAS pathway alterations demonstrate strong age-, ancestry-, and treatment-specific prognostic effects and may serve as precision biomarkers of differential chemotherapy response. AI-enabled analytics substantially accelerated integrative biomarker discovery, supporting their utility for advancing precision oncology in EOCRC.
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Fernando C. Diaz
Brigette Waldrup
Francisco G. Carranza
Cancers
University of North Carolina at Chapel Hill
City of Hope
UNC Lineberger Comprehensive Cancer Center
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Diaz et al. (Tue,) studied this question.
www.synapsesocial.com/papers/696719be0042a3ed5427d7f8 — DOI: https://doi.org/10.3390/cancers18020239