ArticleJournal of dental sciences2022
Prognostic significance of a 4-lncRNA glycolysis-related signature in oral squamous cell carcinoma.
Article in Journal of dental sciences, 2022. 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, 7 citations in OpenAlex.
- Identification of glycolysis-related genes and analysis of potential prognostic clinical application in oral squamous cell carcinoma.Translational cancer research · 2025Article
- A Narrative Review of Prognostic Gene Signatures in Oral Squamous Cell Carcinoma Using LASSO Cox Regression.Biomedicines · 2025Review
- Development and validation of a novel disulfidptosis-related lncRNAs signature in patients with HPV-negative oral squamous cell carcinoma.Scientific reports · 2024Article
- Construction of lncRNA/Pseudogene-miRNA Network Based on In Silico Approaches for Glycolysis Pathway to Identify Prostate Adenocarcinoma-Related Potential Biomarkers.Applied biochemistry and biotechnology · 2024Article
- Glycolysis-associated lncRNAs in cancer energy metabolism and immune microenvironment: a magic key.Frontiers in immunology · 2024Review
- The role of long noncoding RNAs as regulators of the epithelial-Mesenchymal transition process in oral squamous cell carcinoma cells.Frontiers in molecular biosciences · 2022Review
Corrections and comments
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Authors and funding
3 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background/purpose: Oral squamous cell carcinoma (OSCC) is a highly malignant tumor, and the overall survival (OS) time of patients with OSCC varies considerably. This study aimed to identify reliable biomarkers for OSCC and construct a new prognostic signature, which may guide personalized precision treatment. Materials and methods: Transcriptome array data of 317 patients with OSCC from The Cancer Genome Atlas Project (TCGA) cohort were retrospectively analyzed. Single-sample gene set enrichment analysis (ssGSEA) and univariate Cox regression were performed to identify the prognostic significance of the hallmarks of each tumor in OSCC. Subsequently, lncRNAs related to glycolysis were identified through co-expression analysis. A glycolysis-related prognostic signature was constructed by combining univariate Cox regression, least absolute shrinkage and selection operator (Lasso) regression, and multivariate Cox regression analyses. Additionally, the infiltration of immune cells in OSCC was evaluated based on data from ssGSEA and TIMER databases. Results: Glycolysis was identified as the main risk factor for OS in a variety of cancer hallmarks. The 4-lncRNA glycolysis prognostic signature could distinguish high and low-risk patients. This risk signature was found to be an independent prognostic risk factor for OSCC, showing good predictive power compared with other clinicopathological indicators. Immune correlation analysis showed that patients in the low-risk group exhibited higher levels of immune cell infiltration. Conclusion: The novel 4-lncRNA prognostic signature can predict the clinical outcome of patients with OSCC well, and it is expected to become a promising prognostic biomarker as well as a potential therapeutic target in the future.
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