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Association of a novel seven-gene expression signature with the disease prognosis in colon cancer patients

机译:新型七基因表达特征与结肠癌患者疾病预后的关系

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摘要

Older patients who are diagnosed with colon cancer face unique challenges, specifically regarding to cancer treatment. The aim of this study was to identify prognostic signatures to predicting prognosis in colon cancer patients through a detailed transcriptomic analysis. RNA-seq expression profile, miRNA expression profile, and clinical phenotype information of all the samples of TCGA colon adenocarcinoma were downloaded and differentially expressed mRNAs (DEMs), differentially expressed lncRNAs (DELs) and differentially expressed miRNAs (DEMis) were identified. A competing endogenous RNA (ceRNA) network was constructed further and DEMs related with prognosis in the ceRNA network was screened using Cox regression analysis. Risk score models for predicting the prognosis of colon cancer patients were built using these DEMs. A total of 1476 DEMs, 9 DELs, and 243 DEMis between the tumor and normal samples were identified and functional enrichment analyses showed that the DEMs were significantly enriched in the nervous system development, ribosome biogenesis pathways in eukaryotes, and drug metabolism cytochrome P450. Twelve DEMs related with prognosis were screened from the ceRNA network. Thereafter, the risk score models of prognostic DEMs were obtained, involving seven DEMs (SGCG, CLDN23, SLC4A4, CCDC78, SLC17A7, OTOP3, and SMPDL3A). Additionally, cancer stage was identified as a prognostic clinical factor. This prognostic signature was further validated in two independent datasets. Our study developed a seven-mRNA and one-clinical factor signature that are associated with prognosis in colon cancer patients, which may serve as possible biomarkers and therapeutic targets in the future.
机译:被诊断患有结肠癌的老年患者面临独特的挑战,特别是在癌症治疗方面。这项研究的目的是通过详细的转录组分析来鉴定预测结肠癌患者预后的预后特征。下载了所有TCGA结肠腺癌样品的RNA-seq表达谱,miRNA表达谱和临床表型信息,并鉴定了差异表达的mRNA(DEM),差异表达的lncRNA(DEL)和差异表达的miRNA(DEMis)。进一步构建了竞争性内源RNA(ceRNA)网络,并使用Cox回归分析筛选了与ceRNA网络中预后相关的DEM。使用这些DEM建立了可预测结肠癌患者预后的风险评分模型。在肿瘤与正常样品之间共鉴定出1476个DEM,9个DEL和243个DEMis,功能富集分析表明,DEM在神经系统发育,真核生物中的核糖体生物发生途径以及药物代谢细胞色素P450中显着富集。从ceRNA网络中筛选了十二个与预后相关的DEM。此后,获得了涉及七个DEM(SGCG,CLDN23,SLC4A4,CCDC78,SLC17A7,OTOP3和SMPDL3A)的预后DEM风险评分模型。另外,癌症阶段被鉴定为预后的临床因素。在两个独立的数据集中进一步验证了该预后签名。我们的研究开发了与结肠癌患者预后相关的7-mRNA和1临床因子信号,它们可能在将来成为生物标志物和治疗靶标。

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