ArticleInternational journal of molecular sciences2024
Prognostic Significance of Glycolysis-Related Genes in Lung Squamous Cell Carcinoma.
Article in International journal of molecular sciences, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed, 5 citations in OpenAlex.
- Integrating machine learning and single-cell sequencing to reveal the role of kinase-related genes in subtype classification and prognostic significance of lung squamous cell carcinoma.Discover oncology · 2026Article
- Unique Clinical Features of Imaging-Stage I Peripheral Lung Squamous Cell Carcinoma: A Retrospective Study.Current oncology (Toronto, Ont.) · 2026Article
- Impact of piR_004530 reactivation in lung cancer: implications for recurrence and survival of lung squamous cell carcinoma patients.BMC medicine · 2025Article
- An efficient epithelial-mesenchymal transition-related gene signature for predicting the survival of patients with lung adenocarcinoma.Translational cancer research · 2025Article
- Selective inhibition of TGF-β-induced epithelial-mesenchymal transition overcomes chemotherapy resistance in high-risk lung squamous cell carcinoma.Communications biology · 2025Article
- Unlocking the secrets of glucose metabolism reprogramming: the role in pulmonary diseases.Frontiers in pharmacology · 2025Review
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Authors and funding
1 author at 1 institution in 1 country.
Funding
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Abstract
Lung squamous cell carcinoma (LUSC) is one of the most common malignancies. There is growing evidence that glycolysis-related genes play a critical role in tumor development, maintenance, and therapeutic response by altering tumor metabolism and thereby influencing the tumor immune microenvironment. However, the overall impact of glycolysis-related genes on the prognostic significance, tumor microenvironment characteristics, and treatment outcome of patients with LUSC has not been fully elucidated. We used The Cancer Genome Atlas (TCGA) dataset to screen glycolysis-related genes with prognostic effects in LUSC and constructed signature and nomogram models using Lasso and Cox regression, respectively. In addition, we analyzed the immune infiltration and tumor mutation load of the genes in the models. We finally obtained a total of glycolysis-associated DEGs. The signature model and nomogram model had good prognostic power for LUSC. Gene expression in the models was highly correlated with multiple immune cells in LUSC. Through this analysis, we have identified and validated for the first time that glycolysis-related genes are highly associated with the development of LUSC. In addition, we constructed the signature model and nomogram model for clinical decision-making.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.