Abstract
Background
Early-onset colorectal cancer (EOCRC), defined as CRC diagnosed before age 50, is rising globally. The genomic landscape of EOCRC has been characterized in several prior studies, but the reproducibility of findings across independent cohorts, the impact of adjustment for tumor stage and sample type, and the specificity of prognostic biomarkers to the EOCRC subgroup remain incompletely defined. Furthermore, BRAF mutation frequency is strongly modified by tumor location, which is often not considered in prior analyses.
Methods
We performed a dual-cohort analysis using two independent, publicly available genomic databases: The Cancer Genome Atlas (TCGA) PanCancer Atlas (discovery cohort) and the MSK-IMPACT 50K Clinical Sequencing Cohort (validation cohort). Patients with any somatic mutation in the four canonical MMR genes (MLH1, MSH2, MSH6, PMS2) were excluded to reduce the influence of MMR-deficient tumors on comparisons. After exclusion, the discovery cohort comprised 536 CRC patients (EOCRC n = 67, LOCRC n = 469) and the validation cohort comprised 4,254 CRC patients (EOCRC n = 1,470, LOCRC n = 2,784). Somatic mutation frequencies for 11 genes and MSI status were compared between EOCRC and LOCRC, with BRAF analyses further stratified by BRAF V600E specifically and by tumor location. Kaplan-Meier overall survival (OS) analyses were performed with number-at-risk tables. Multivariate Cox regression was adjusted for tumor stage (TCGA) or sample type (Primary vs. Metastasis; MSK-IMPACT). An EOCRC-specific multivariate model was also constructed to test whether prognostic effects were specific to the young-onset subgroup.
Results
BRAF total mutations were significantly less frequent in EOCRC in the validation cohort (6.5% vs 10.1%, p
Conclusions
After exclusion of MMR-deficient tumors, tumor location adjustment, and sample type adjustment, BRAF mutation depletion in EOCRC is confirmed but is at least partially explained by tumor location distribution differences. KRAS/NRAS/BRAF and MSI-H are validated as CRC prognostic biomarkers, but these effects are driven by the overall cohort and are not specific to the EOCRC subgroup. These findings support comprehensive NGS profiling in EOCRC while cautioning against interpreting general CRC prognostic biomarkers as EOCRC-specific.