Colon cancer is one of the most common cancers in digestive system, and its prognosis remains unsatisfactory. Therefore, this study aimed to identify gene signatures that could effectively predict the prognosis of colon cancer patients by examining the data from the Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) database. LASSO-Cox regression analysis generated a five-gene signature (DCBLD2, RAB11FIP1, CTLA4, HOXC6 and KRT6A) that was associated with patient survival in the TCGA cohort. The prognostic value of this gene signature was further validated in two independent GEO datasets. GO enrichment revealed that the function of this gene signature was mainly associated with extracellular matrix organization, collagen-containing extracellular matrix, and extracellular matrix structural constituent. Moreover, a nomogram was established to facilitate the clinical application of this signature. The relationships among the gene signature, mutational landscape and immune infiltration cells were also investigated. Importantly, this gene signature also reliably predicted the overall survival in IMvigor210 anti-PD-L1 cohort. In addition to the bioinformatics study, we also conducted a series of in vitro experiments to demonstrate the effect of the signature genes on the proliferation, migration, and invasion of colon cancer cells. Collectively, our data demonstrated that this five-gene signature might serve as a promising prognostic biomarker and shed light on the development of personalized treatment in colon cancer patients.
Keywords: Colon cancer; gene signature; prediction; prognosis; risk model.
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