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pmid:33663535
Prognostic value of a novel glycolysis-related gene expression signature for gastrointestinal cancer in the Asian population.
Rong Xia · Hua Tang · Jiemiao Shen · Shuyu Xu · Yinyin Liang · Yuxin Zhang · Xing Gong · Yue Min · Di Zhang · Chenzhe Tao · Shoulin Wang · Yi Zhang · Jinyou Yang · Chao Wang
Cancer cell international · 2021 doi:10.1186/s12935-021-01857-4
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Complete file
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However, studies have not established glycolysis-related gene signatures that can be used to construct accurate prognostic models for GI cancers in the Asian population. Herein, we aimed at establishing a novel glycolysis-related gene expression signature to predict the prognosis of GI cancers.\nMETHODS: First, we evaluated the mRNA expression profiles and the corresponding clinical data of 296 Asian GI cancer patients in The Cancer Genome Atlas (TCGA) database (TCGA-LIHC, TCGA-STAD, TCGA-ESCA, TCGA-PAAD, TCGA-COAD, TCGA-CHOL and TCGA-READ). Differentially expressed mRNAs between GI tumors and normal tissues were investigated. Gene Set Enrichment Analysis (GSEA) was performed to identify glycolysis-related genes. Then, univariate, LASSO regression and multivariate Cox regression analyses were performed to establish a key prognostic glycolysis-related gene expression signature. The Kaplan-Meier and receiver operating characteristic (ROC) curves were used to evaluate the efficiency and accuracy of survival prediction. Finally, a risk score to predict the prognosis of GI cancers was calculated and validated using the TCGA data sets. Furthermore, this risk score was verified in two Gene Expression Omnibus (GEO) data sets (GSE116174 and GSE84433) and in 28 pairs of tissue samples.\nRESULTS: Prognosis-related genes (NUP85, HAX1, GNPDA1, HDLBP and GPD1) among the differentially expressed glycolysis-related genes were screened and identified. The five-gene expression signature was used to assign patients into high- and low-risk groups (p < 0.05) and it showed a satisfactory prognostic value for overall survival (OS, p = 6.383 × 10-6). The ROC curve analysis revealed that this model has a high sensitivity and specificity (0.757 at 5 years). Besides, stratification analysis showed that the prognostic value of the five-gene signature was independent of other clinical characteristics, and it could markedly discriminate between GI tumor tissues and normal tissues. Finally, the expression levels of the five prognosis-related genes in the clinical tissue samples were consistent with the results from the TCGA data sets.\nCONCLUSIONS: Based on the five glycolysis-related genes (NUP85, HAX1, GNPDA1, HDLBP and GPD1), and in combination with clinical characteristics, this model can independently predict the OS of GI cancers in Asian patients.", "claims": [{"id": "claim-data-access", "statement": "The data sets used and/or analyzed during the current study are publicly available data from The Cancer Genome Atlas (TCGA), Gene Expression Omnibus (GEO), and Human Protein Atlas. 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"table", "format": "jats-table", "media_type": "application/vnd.jats.table+json", "uri": null, "sha256": "sha256:49d2b514908c75a9374c79acd022a6fbd49e0ae50923fcd933175e395339b9e4", "bytes": 978, "access": "open", "state": "verified", "reader": "read_table", "reader_status": "available", "identifier": "section[11]/table-wrap[1]#Tab2", "version": null, "note": "The information of five prognostic mRNAs weighted by its multivariable LASSO regression coefficient, which importantly associated with overall survival in Asian patients with gastrointestinal cancer", "structure": {"pmcid": "PMC7934443", "section_index": 11, "section_title": "Construction of the five-gene signature as an indicator for prognosis", "row_count": 6, "column_count": 6}, "table": {"label": "Table 2", "caption": "The information of five prognostic mRNAs weighted by its multivariable LASSO regression coefficient, which importantly associated with overall survival in Asian patients with gastrointestinal cancer", "rows": 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