Mechanistic insights into FEN1-mediated drug sensitivity and risk signature in colon cancer: An integrative bioinformatics study.

Abstract

The overexpression of Flap endonuclease 1 (FEN1) has been implicated in drug resistance and prognosis across various cancer types. However, the precise role of FEN1 in colon cancer remains to be fully elucidated. In this study, we employed comprehensive datasets from The Cancer Genome Atlas, Gene Expression Omnibus, and Human Protein Atlas to examine FEN1 expression and assess its correlation with clinical pathology and prognosis in colon cancer. We utilized the pRRophetic algorithm to evaluate drug sensitivity and performed differential expression analysis to identify genes associated with FEN1-mediated drug sensitivity. Gene set enrichment analysis was conducted to further investigate these genes. Additionally, single-cell sequencing analysis was employed to explore the relationship between FEN1 expression and functional states. Cox regression analysis was implemented to construct a prognostic model, and a nomogram for prognosis was developed. Our analysis of The Cancer Genome Atlas and Gene Expression Omnibus datasets revealed a significant upregulation of FEN1 in colon cancer. However, while FEN1 expression showed no notable correlation with prognosis, it displayed associations with metastasis. Single-cell sequencing analysis further confirmed a positive correlation between FEN1 expression and colon cancer metastasis. Furthermore, we detected marked discrepancies in drug responsiveness between the High_FEN1 and Low_FEN1 groups, identifying 342 differentially expressed genes. Enrichment analysis showed significant suppression in processes related to DNA replication, spliceosome, and cell cycle pathways in the Low_FEN1 group, while the calcium signaling pathway, cAMP signaling pathway, and other pathways were activated. Of the 197 genes differentially expressed and strongly linked to FEN1 expression, 39 were significantly implicated in colon cancer prognosis. Finally, we constructed a risk signature consisting of 5 genes, which, when combined with drug treatment and pathological staging, significantly improved the prediction of colon cancer prognosis. This study offers novel insights into the interplay among FEN1 expression levels, colon cancer metastatic potential, and sensitivity to therapeutic agents. Furthermore, we successfully developed a multi-gene prognostic risk signature derived from FEN1.