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　in　vitro　and　in　vivo　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.