Genomic profiling of colorectal liver metastasis and insight into their prognostic value.

e15536 Background: Colorectal liver metastases (CRLM) pose a significant clinical challenge, characterized by high recurrence rate even after surgical resection. Current prognostic strategies, which rely on clinicopathologic features, have demonstrated limited accuracy. As a result, there is an urgent need to identify more reliable prognostic markers. Genomic profiling of CRLM offers a promising approach to uncover molecular drivers and identify biomarkers that can improved risk stratification and guide treatment selection. Methods: In this study, we performed whole exome sequencing on 57 CRLM patients, and conducted a comprehensive analysis of primary tumor lesions. Prognostic factors associated with overall survival (OS) were systematically identified in the univariate and multivariate Cox regression analysis, and a nomogram was constructed to predict OS for CRLM patients. The nomogram further underwent external validation in an independent validation cohort of 21 CRLM patients from published data. Results: The most frequently mutated genes in our cohort were APC (64.91%) and TP53 (64.91%), followed by KRAS (50.88%), PIK3CA (24.56%) and SMAD4 (24.56%). Altered genes were primarily enriched in TP53, IGF, and Ras signaling pathway. Mutation concordance between primary and metastatic lesions was high. In the univariate analysis, a significant decrease in OS was linked with mutations in ZNF717 (HR 4.4, P = 0.00069), POTEE (HR 2.8, P = 0.015), MUC2 (HR 2.6, P = 0.017) and Amp_Chr9p13.3 (HR 1.9, P = 0.034), whereas a significant increase in OS was associated with mutations in APC (HR 0.5, P = 0.028). Multivariable analysis identified five independent prognostic factors for OS: the number of metastasis-positive lymph node stations in primary surgically removed tumor tissue, and the status of ZNF717, MUC2, APC, and Chr9p13.3 amplification. The nomogram incorporating these five factors achieved a C-index of 0.789 in this cohort, and C-index of 0.643 on an external validation cohort. Conclusions: Integration genomic profiling into routine clinical practice enables innovative prognostic strategies and improved treatment stratification for CRLM patients.