254
Views
2
CrossRef citations to date
0
Altmetric
Original Article

Identification of a novel glycolysis-related gene signature for predicting the survival of patients with colon adenocarcinoma

, , , , &
Pages 214-221 | Received 18 Jun 2021, Accepted 24 Sep 2021, Published online: 13 Oct 2021
 

Abstract

Background

The most frequent histologic subtype of colon cancer is colon adenocarcinoma (COAD). A major problem in the diagnosis and treatment of COAD is that there is lack of new biomarkers to indicate the early stage of COAD. Compared with normally differentiated cells, the glycolytic pathways of tumor cells are more active, thus making them more adaptable to the hypoxic environment of solid tumors, which is known as the Warburg effect. Therefore, establishing a diagnostic and prognostic model based on glycolysis-related genes may provide guidance for the precise treatment of colon cancer.

Methods

The Cancer Genome Atlas (TCGA) mRNA data were used to identify differentially expressed genes (DEGs). The glycolysis-related DEGs were identified using Gene Set Enrichment Analysis (GSEA) with HALLMARK gene sets. Combined with clinical data, we identified prognostic genes in glycolysis-related DEGs based on Cox regression analysis. Four glycolysis-related genes were identified and a predictive model was developed using univariate and multivariate Cox regression analysis. cBioPortal investigated the chromosomal variations of these genes. Following that, survival analysis and receiver operating characteristic (ROC) curve validation were carried out. The correlations between glycolysis-related gene signatures and molecular features and cancer subtypes were analyzed.

Results

We discovered five genes (SPAG4, P4HA1, STC2, ENO3, and GPC1) that are associated with COAD patients' prognosis. The risk score was more accurate in predicting prognosis when based on this gene signature in COAD patients. Furthermore, multivariate Cox regression analysis demonstrated that the glycolysis-related gene signature's predictive value was independent of clinical variables.

Conclusion

We identified a glycolysis-related five-gene signature and developed a risk staging model potentially valuable for the clinical management of COAD patients. Our results suggest that prognostic markers based on glycolysis-related genes may be a reliable predictive tool for the prognosis of COAD patients.

Disclosure statement

No competing financial interests exist.

Additional information

Funding

This work was supported by the Improvement Project for Theranostic ability on Difficulty Miscellaneous disease (Tumor) and the Science & Technology Innovation Fostering Foundation of Zhongnan Hospital of Wuhan University [ZLYNXM202008, No. znpy2019050, znpy2019004, znpy2018027]. This work was also funded by Medical Top-talented youth development project of Hubei Province, and by Medical talented youth development project in Health Commission of Hubei Province [No. WJ2019Q049].

Log in via your institution

Log in to Taylor & Francis Online

PDF download + Online access

  • 48 hours access to article PDF & online version
  • Article PDF can be downloaded
  • Article PDF can be printed
USD 65.00 Add to cart

Issue Purchase

  • 30 days online access to complete issue
  • Article PDFs can be downloaded
  • Article PDFs can be printed
USD 336.00 Add to cart

* Local tax will be added as applicable

Related Research

People also read lists articles that other readers of this article have read.

Recommended articles lists articles that we recommend and is powered by our AI driven recommendation engine.

Cited by lists all citing articles based on Crossref citations.
Articles with the Crossref icon will open in a new tab.