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pmid:33364813
A Novel Prognostic Score Based on ZG16 for Predicting CRC Survival.
Wei Wang · Jian-Fang Sun · Xiao-Zhong Wang · Hou-Qun Ying · Xia-Hong You · Fan Sun
Pharmacogenomics and personalized medicine · 2020 doi:10.2147/PGPM.S275941
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Experiment
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Complete file
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The aim of this study was to identify the key genes associated with CRC and to further explore their prognostic significance.\nMETHODS: Four expression profile datasets (GSE41657, GSE74602, GSE113513, and GSE40967) downloaded from Gene Expression Omnibus (GEO) and one RNAseq dataset of CRC from The Cancer Genome Atlas (TCGA) database were included in our study. The Cox model was utilized for univariate or multivariate survival analysis. GEPIA and HAP database were adopted for verification of DEGs (ZG16). The decision curve analysis (DCA) and time-dependent ROC were chosen for evaluating the prognostic effectiveness of biomarkers.\nRESULTS: In total, 88 differentially expressed genes (DEGs) were identified, and the GO and KEGG enrichment analyses of DEGs were processed. After, the protein-protein interaction (PPI) network was constructed and 15 hub genes including ZG16 were identified. The differential expression of ZG16 between tumor and normal colorectal tissues were further verified in GEPIA and HAP database. Subsequent survival indicated that expression of ZG16 is negatively correlated with overall survival of OS and is an independent prognostic factor for CRC patients. Furthermore, the construction of a prognostic score containing ZG16, TNM stage and age exhibited superior effectiveness for predicting long-term survival of CRC patients. Additionally, our results were verified using the GSE40967 dataset, which indicated an improved performance of combined risk score based on ZG16 for predicting OS of CRC patients.\nCONCLUSION: ZG16 is a potential parameter for predicting prognosis in CRC. 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{"pmcid": "PMC7751443", "section_index": 11, "section_title": "Enrichment of DEGs", "row_count": 14, "column_count": 7}, "table": {"label": "Table 1", "caption": "Significantly Enriched GO Terms and KEGG Pathways of DEGs", "rows": [["GOID", "GOTerm", "P-value", "FDR", "-Log10(FDR)", "% Associated Genes", "Nr. Genes"], ["KEGG:04978", "Mineral absorption", "2.000E-07", "6.500E-07", "6.187", "10.34", "6.00"], ["GO:0008237", "Metallopeptidase activity", "6.024E-07", "1.566E-06", "5.805", "4.02", "9.00"], ["GO:0004222", "Metalloendopeptidase activity", "2.067E-04", "2.067E-04", "3.685", "4.07", "5.00"], ["GO:0005903", "Brush border", "4.896E-06", "9.093E-06", "5.041", "4.58", "7.00"], ["GO:0031526", "Brush border membrane", "1.480E-06", "3.206E-06", "5.494", "7.41", "6.00"], ["KEGG:04972", "Pancreatic secretion", "8.563E-05", "9.276E-05", "4.033", "4.90", "5.00"], ["KEGG:04976", "Bile secretion", "1.594E-05", "2.073E-05", "4.683", "6.94", "5.00"], ["GO:0055067", "Monovalent inorganic cation homeostasis", "9.778E-06", "1.412E-05", "4.850", "4.12", "7.00"], ["KEGG:00910", "Nitrogen metabolism", "8.520E-09", "5.538E-08", "7.257", "29.41", "5.00"], ["GO:0016835", "Carbon-oxygen lyase activity", "4.462E-05", "5.273E-05", "4.278", "5.62", "5.00"], ["GO:0016836", "Hydro-lyase activity", "8.930E-06", 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