Colorectal cancer remains a formidable global health challenge, characterized by high recurrence rates and poor prognosis. This study introduces a novel Recurrence Related Gene Signature (RRGS), designed to predict therapy response and enhance prognostic accuracy in colorectal cancer. Through analysis of the GSE17536 cohort, we identified 79 differentially expressed genes (DEGs) between recurrent and non-recurrent cases, comprising 54 upregulated and 25 downregulated genes. Pathway analysis revealed that upregulated genes were enriched in cancer progression-related pathways, while downregulated genes were associated with immune-related processes. Leveraging these findings, we developed the RRGS using LASSO regression, resulting in an innovative 11-gene model with robust diagnostic and prognostic capabilities. Notably, the RRGS demonstrated significant predictive value for both overall survival and disease-free survival across multiple datasets, with higher RRGS scores correlating with advanced tumor stages and poorer outcomes, particularly in post-chemotherapy patients. This predictive power highlights the RRGS's potential in guiding personalized treatment strategies. Furthermore, we identified STC1 as a critical component of the RRGS, playing a significant role in tumor progression and immune evasion. Through rigorous and experiments we confirmed that STC1 knockdown substantially reduced cell proliferation and metastasis, emphasizing its potential as a therapeutic target. This comprehensive study not only elucidates the molecular mechanisms driving colorectal cancer recurrence but also introduces a powerful tool for enhancing prognostic accuracy and personalizing therapeutic interventions.