Identification and validation of a novel signature as a diagnostic and prognostic biomarker in colorectal cancer

作者：Di Wang, Junye Liufu, Qiyuan Yang, Shengqun Dai, Jiaqi Wang, Biao Xie · 发表于：Biology Direct · 年份：2022 · DOI：10.1186/s13062-022-00342-w · 被引用次数：22 · 研究领域：Ferroptosis and cancer prognosis、Cancer Immunotherapy and Biomarkers、Colorectal Cancer Surgical Treatments

BACKGROUND: Colorectal cancer (CRC) is one of the most common malignant neoplasms worldwide. Although marker genes associated with CRC have been identified previously, only a few have fulfilled the therapeutic demand. Therefore, based on differentially expressed genes (DEGs), this study aimed to establish a promising and valuable signature model to diagnose CRC and predict patient's prognosis. METHODS: The key genes were screened from DEGs to establish a multiscale embedded gene co-expression network, protein-protein interaction network, and survival analysis. A support vector machine (SVM) diagnostic model was constructed by a supervised classification algorithm. Univariate Cox analysis was performed to construct two prognostic signatures for overall survival and disease-free survival by Kaplan-Meier analysis, respectively. Independent clinical prognostic indicators were identified, followed by univariable and multivariable Cox analysis. GSEA was used to evaluate the gene enrichment analysis and CIBERSORT was used to estimate the immune cell infiltration. Finally, key genes were validated by qPCR and IHC. RESULTS: In this study, four key genes (DKC1, FLNA, CSE1L and NSUN5) were screened. The SVM diagnostic model, consisting of 4-gene signature, showed a good performance for the diagnostic (AUC = 0.9956). Meanwhile, the four-gene signature was also used to construct a risk score prognostic model for disease-free survival (DFS) and overall survival (OS), and the results indica...