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BMC Cancer

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Open Access 01-12-2021 | Lung Cancer | Research article

A glycolysis-based three-gene signature predicts survival in patients with lung squamous cell carcinoma

Authors: Guichuan Huang, Jing Zhang, Ling Gong, Yi Huang, Daishun Liu

Published in: BMC Cancer | Issue 1/2021

Abstract

Background

Lung cancer is one of the most lethal and most prevalent malignant tumors worldwide, and lung squamous cell carcinoma (LUSC) is one of the major histological subtypes. Although numerous biomarkers have been found to be associated with prognosis in LUSC, the prediction effect of a single gene biomarker is insufficient, especially for glycolysis-related genes. Therefore, we aimed to develop a novel glycolysis-related gene signature to predict survival in patients with LUSC.

Methods

The mRNA expression files and LUSC clinical information were obtained from The Cancer Genome Atlas (TCGA) dataset.

Results

Based on Gene Set Enrichment Analysis (GSEA), we found 5 glycolysis-related gene sets that were significantly enriched in LUSC tissues. Univariate and multivariate Cox proportional regression models were performed to choose prognostic-related gene signatures. Based on a Cox proportional regression model, a risk score for a three-gene signature (HKDC1, ALDH7A1, and MDH1) was established to divide patients into high-risk and low-risk subgroups. Multivariate Cox regression analysis indicated that the risk score for this three-gene signature can be used as an independent prognostic indicator in LUSC. Additionally, based on the cBioPortal database, the rate of genomic alterations in the HKDC1, ALDH7A1, and MDH1 genes were 1.9, 1.1, and 5% in LUSC patients, respectively.

Conclusion

A glycolysis-based three-gene signature could serve as a novel biomarker in predicting the prognosis of patients with LUSC and it also provides additional gene targets that can be used to cure LUSC patients.

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Title: A glycolysis-based three-gene signature predicts survival in patients with lung squamous cell carcinoma
Authors: Guichuan Huang
Jing Zhang
Ling Gong
Yi Huang
Daishun Liu
Publication date: 01-12-2021
Publisher: BioMed Central
Keywords: Lung Cancer
Lung Cancer
Lung Cancer
Published in: BMC Cancer / Issue 1/2021
Electronic ISSN: 1471-2407
DOI: https://doi.org/10.1186/s12885-021-08360-z

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Abstract

Background

Methods

Results

Conclusion

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