Artificial Intelligence-Guided Molecular Determinants of PI3K Pathway Alterations in Early-Onset Colorectal Cancer Among High-Risk Groups Receiving FOLFOX

Authors:
Open Access
Publisher website
Google Scholar
Abstract
Background: Early-onset colorectal cancer (EOCRC), defined as diagnosis before the age of 50, is rising rapidly and disproportionately affects high-risk populations, particularly Hispanic/Latino (H/L) individuals, who experience the steepest increases in incidence and mortality. While prevention and screening strategies have curbed late-onset CRC rates, EOCRC remains outside standard screening guidelines and is projected to become the leading cause of cancer-related death in individuals aged 20–49 by 2030. FOLFOX (folinic acid, fluorouracil, and oxaliplatin) is a standard first-line therapy for microsatellite stable (MSS) CRC lacking actionable driver mutations; however, its efficacy and genomic impact in EOCRC, particularly in underrepresented groups, remain poorly understood. The phosphatidylinositol 3-kinase (PI3K) pathway regulates cell growth, survival, and metabolism, and its alterations have been implicated in therapeutic resistance and adverse outcomes. Yet, the prevalence, clinical relevance, and treatment-specific associations of PI3K pathway alterations in EOCRC remain underexplored. Methods: We analyzed somatic mutation and clinical data from 2515 CRC patients (266 H/L and 2249 Non-Hispanic White [NHW]) across publicly available genomic datasets. Patients were stratified by age at diagnosis (EOCRC < 50 vs. LOCRC ≥ 50), ancestry (H/L vs. NHW), and FOLFOX treatment status. PI3K pathway alterations—including mutations in PIK3CA, PTEN, AKT isoforms, and regulatory genes—were identified using curated pathway definitions. Mutation prevalence was compared across groups using Fisher’s exact or chi-squared tests. AI-HOPE-PI3K, a conversational AI platform, was deployed to automate cohort construction, stratify subgroups, and perform post hoc survival analysis. Results: PI3K pathway alterations were observed across all demographic groups. In EO NHW patients treated with FOLFOX, Kaplan–Meier analysis revealed significantly reduced overall survival among those with PI3K pathway alterations (n = 124) compared with their unaltered counterparts (n = 251; p = 0.0008), identifying alterations as a candidate prognostic biomarker in this subgroup. AI-guided subgroup interrogation further highlighted mutation-specific signals: INPP4B and RPTOR emerged as exploratory candidates in EO H/L patients but did not show significant treatment- or ancestry-specific enrichment upon confirmatory testing. Similarly, ancestry-stratified analysis of PIK3R2 mutations revealed comparable rates in EO H/L (1.37%) and EO NHW (1.6%) FOLFOX-treated patients (p = 1.0). Across ancestry and age groups, mutational landscape analysis revealed diverse molecular events—including missense, nonsense, splice-site, frameshift, and in-frame deletions—underscoring the heterogeneity of PI3K pathway dysregulation. Conclusions: This study identifies PI3K pathway alterations as a potential prognostic marker of poor survival in EO NHW patients receiving FOLFOX and uncovers ancestry- and treatment-specific mutational differences in high-risk CRC populations. By integrating clinical, molecular, and treatment variables, the AI-HOPE and AI-HOPE-PI3K platforms enabled rapid, reproducible, and fine-grained analysis of complex datasets. These findings underscore the need for ancestry-informed molecular profiling to optimize therapeutic strategies and highlight AI-guided interrogation as a powerful tool for advancing precision oncology in underrepresented and disproportionately affected CRC populations.
Funding Information
  • National Cancer Institute (U2CCA252971)
  • City of Hope Cancer Control and Population Sciences program by the National Institutes of Health, NIH, National Cancer Institute, NCI (P30CA033572)
  • Drug Development and Capacity Building: A UCR/CoH-CCC Partnership project by the National Institutes of Health, NIH, National Cancer Institute, NCI (U54 CA285116)

This publication has 39 references indexed in Scilit: