ArticleCancer medicine2021
Identification of a glycolysis-related gene signature associated with clinical outcome for patients with lung squamous cell carcinoma.
Article in Cancer medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Who cites it
11 citing papers in PubMed.
- Effects of Camrelizumab Combined with First-Line Chemotherapy on Serum SCC, VEGF Levels, and Adverse Reactions in Patients with Advanced Squamous Cell Carcinoma of the Lung.Computational intelligence and neuroscience · 2022Trial
- SLC16A3 links tumor metabolism to therapeutic opportunities in hepatocellular carcinoma.Translational cancer research · 2026Review
- Article
- Article
- Myo-Inositol Oxygenase (MIOX): A Pivotal Regulator and Therapeutic Target in Multiple Diseases.Current issues in molecular biology · 2025Review
- ComprehensiveOncology reports · 2025Review
- Comprehensive pan-cancer analysis identified SLC16A3 as a potential prognostic and diagnostic biomarker.Cancer cell international · 2025Article
- HKDC1 in Cancer: Mechanisms, Clinical Applications, and Future.Journal of Cancer · 2025Review
- Energy metabolism as the hub of advanced non-small cell lung cancer management: a comprehensive view in the framework of predictive, preventive, and personalized medicine.The EPMA journal · 2024Review
- The hexokinase "HKDC1" interaction with the mitochondria is essential for liver cancer progression.Cell death & disease · 2022Article
- Development and Validation of a 7-Gene Inflammatory Signature Forecasts Prognosis and Diverse Immune Landscape in Lung Adenocarcinoma.Frontiers in molecular biosciences · 2022Article
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Authors and funding
4 authors.
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No grant is acknowledged in the PubMed record.
Abstract
backgroundLung squamous cell carcinoma (LUSC), one of the main types of lung cancer, has caused a huge social burden. There has been no significant progress in its therapy in recent years, Resulting in a poor prognosis. This study aims to develop a glycolysis-related gene signature to predict patients' survival with LUSC and explore new therapeutic targets.
methodsWe obtained the mRNA expression and clinical information of 550 patients with LUSC from the Cancer Genome Atlas (TCGA) database. Glycolysis genes were identified by Gene Set Enrichment Analysis (GSEA). The glycolysis-related gene signature was established using the Cox regression analysis.
resultsWe developed five glycolysis-related genes signature (HKDC1, AGL, ALDH7A1, SLC16A3, and MIOX) to calculate each patient's risk score. According to the risk score, patients were divided into high- and low-risk groups and exhibited significant differences in overall survival (OS) between the two groups. The ROC curves showed that the AUC was 0.707 for the training cohort and 0.651 for the validation cohort. Additionally, the risk score was confirmed as an independent risk factor for LUSC patients by Cox regression analysis.
conclusionWe built a gene signature to clarify the connection between glycolysis and LUSC. This model performs well in evaluating patients' survival with LUSC and provides new biomarkers for targeted therapy.
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