Metastatic Burden and TP53 Mutation Overshadow the Independent Prognostic Value of KRAS in Colorectal Cancer

Background The independent prognostic value of KRAS mutation in colorectal cancer (CRC) remains controversial, often yielding inconsistent results across studies. We hypothesized that its impact might be overestimated when confounding clinical factors, such as metastatic burden, are rigorously controlled. Methods In this single-center retrospective study, we enrolled 253 CRC patients treated at West China Hospital. We integrated clinical data with next-generation sequencing (NGS) profiles to re-evaluate the prognostic significance of KRAS . Kaplan-Meier survival analysis and multivariate Cox regression models were employed to assess the impact of KRAS status, metastatic burden, and co-occurring mutations on overall survival. Results While Kaplan-Meier analysis showed a trend toward poorer survival in KRAS -mutated patients (P = 0.088), this difference did not reach statistical significance. Crucially, multivariate Cox regression revealed that KRAS mutation was not an independent prognostic factor (HR = 0.723, P = 0.497) after adjusting for confounders. Instead, outcomes were dominated by metastatic burden (M stage: HR = 7.2, P < 0.001) and TP53 mutation (HR = 2.53, P = 0.032). Subgroup analyses confirmed the lack of independent KRAS prognostic value across age, tumor location, and treatment strata. Notably, TP53 mutation emerged as a significant independent risk factor specifically in patients receiving neoadjuvant therapy (HR = 3.12, P = 0.044). Conclusions The prognostic weight of KRAS mutation in CRC is largely overshadowed by dominant clinical determinants (metastatic burden) and concurrent molecular drivers (TP53). Our findings suggest that for high-risk patients, particularly those undergoing neoadjuvant therapy, TP53 status may serve as a superior prognostic biomarker compared to KRAS . We propose moving beyond a " KRAS -centric" assessment toward a multi-parameter model integrating TNM staging with comprehensive genomic profiling.