Dataset Information

Prognostic value of a novel glycolysis-related gene expression signature for gastrointestinal cancer in the Asian population.

ABSTRACT:

Background

Globally, gastrointestinal (GI) cancer is one of the most prevalent malignant tumors. 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.

Methods

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.

Results

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?-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.

Conclusions

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.

SUBMITTER: Xia R

PROVIDER: S-EPMC7934443 | biostudies-literature | 2021 Mar

REPOSITORIES: biostudies-literature

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Publications

Prognostic value of a novel glycolysis-related gene expression signature for gastrointestinal cancer in the Asian population.

Xia Rong R Tang Hua H Shen Jiemiao J Xu Shuyu S Liang Yinyin Y Zhang Yuxin Y Gong Xing X Min Yue Y Zhang Di D Tao Chenzhe C Wang Shoulin S Zhang Yi Y Yang Jinyou J Wang Chao C

Cancer cell international 20210304 1

<h4>Background</h4>Globally, gastrointestinal (GI) cancer is one of the most prevalent malignant tumors. 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.<h4>Methods</h4>First, we evaluated the mRNA expression profiles and the corresponding clinical data ...[more]

PMID: 33663535

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Dataset Information

Prognostic value of a novel glycolysis-related gene expression signature for gastrointestinal cancer in the Asian population.

Background

Methods

Results

Conclusions

Publications

Prognostic value of a novel glycolysis-related gene expression signature for gastrointestinal cancer in the Asian population.

Similar Datasets

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