Flap核酸内切酶1(FEN1)的过表达与各种癌症类型的耐药性和预后有关。然而,FEN1在结肠癌中的确切作用仍有待完全阐明.在这项研究中,我们采用了来自癌症基因组图谱的全面数据集,基因表达综合,和人蛋白质图谱检查FEN1的表达并评估其与结肠癌临床病理和预后的相关性。我们利用pRRophetic算法评估药物敏感性,并进行差异表达分析以鉴定与FEN1介导的药物敏感性相关的基因。进行基因集富集分析以进一步研究这些基因。此外,采用单细胞测序分析探讨FEN1表达与功能状态的关系.实施Cox回归分析以构建预后模型,并绘制了预后的列线图。我们对癌症基因组图谱和基因表达综合数据集的分析揭示了FEN1在结肠癌中的显著上调。然而,而FEN1的表达与预后无显著相关性,它显示与转移有关。单细胞测序分析进一步证实FEN1表达与结肠癌转移之间呈正相关。此外,我们检测到High_FEN1和Low_FEN1组之间的药物反应性明显差异,鉴定342个差异表达基因。富集分析显示在与DNA复制相关的过程中显著抑制,剪接体,和Low_FEN1组的细胞周期通路,而钙信号通路,cAMP信号通路,和其他途径被激活。在197个差异表达并与FEN1表达密切相关的基因中,39例与结肠癌预后密切相关。最后,我们构建了由5个基因组成的风险标记,which,当与药物治疗和病理分期相结合时,显著改善结肠癌预后的预测。这项研究为FEN1表达水平之间的相互作用提供了新的见解,结肠癌转移潜能,和对治疗剂的敏感性。此外,我们成功开发了一种源自FEN1的多基因预后风险标志.
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.