Proteomics-Driven Risk Stratification in Stage III Colon Cancer: A Validated Prognostic Signature for Recurrence...

Despite advances in colon cancer management, stage III disease lacks robust, clinically applicable prognostic biomarkers. We aimed to use proteomic profiling to provide a quantitative, tissue-based approach to improve recurrence risk stratification.

We performed data-independent acquisition mass spectrometric proteomic analysis of tumor samples from three independent stage III colon cancer cohorts (n = 759). Differential protein expression between tumor and matched normal adjacent tissue was analyzed in the training cohort (cohort 1) using the limma package, and a univariate Cox model identified candidate biomarker proteins. A risk score based on the levels of six proteins (ITIH1, PPIE, LTBP1, KPNA2, IGFBP7, and CKAP4) was developed using multivariate Cox regression in the training cohort (n = 175) and validated in two external cohorts (cohort 2, n = 386; cohort 3, n = 198). Kaplan-Meier and multivariate Cox regression analyses assessed the prognostic value of the score for recurrence.

The six-protein risk score categorized patients in the training cohort as high- or low-risk for recurrence [hazard ratio (HR) 5.7, P < 0.001], and this was validated in the two separate cohorts (cohort 2: HR 1.8, P < 0.001; cohort 3: HR 1.8, P = 0.02). Integrating the proteomic score with clinical risk factors further enhanced prognostic accuracy (P < 0.001 in all three cohorts). The combined proteomic-clinical risk score consistently identified a subgroup of patients with very low recurrence risk across cohorts.

The validated six-protein risk score improves prognostic stratification beyond standard clinical factors in stage III colon cancer, providing a robust framework for risk-adapted clinical investigation. Prospective, treatment-stratified clinical trials are warranted to determine whether this prognostic information can inform adjuvant therapy decision-making.