ArticleInternational dental journal2024
Prognostic Analysis of Lactic Acid Metabolism Genes in Oral Squamous Cell Carcinoma.
Article in International dental journal, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.
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Who cites it
6 citing papers in PubMed, 1 synthesis or guideline pooled it, 6 citations in OpenAlex.
- Biomarkers in oral squamous cell carcinoma: a systematic review.Medicina oral, patologia oral y cirugia bucal · 2026Pooled it
- Experimental Models and Nanotechnology-Based Platforms in Oral Squamous Cell Carcinoma: From Tumor Biology to Translational Applications.Pharmaceutics · 2026Review
- Expression Characteristics of SYPL1 in Oral Squamous Cell Carcinoma and Its Correlation With Prognosis.International dental journal · 2026Article
- Exploring Metabolic and Immunological Biomarkers for Oral Squamous Cell Carcinoma: Potential Targets for Precision Therapy.Biology · 2025Review
- A Narrative Review of Prognostic Gene Signatures in Oral Squamous Cell Carcinoma Using LASSO Cox Regression.Biomedicines · 2025Review
- Promoter Hyper-methylation of ZNF662 Restrains its Tumor Suppressing Function in Triple-Negative Breast Cancer Through Regulating NGF Signaling Axis.International journal of biological sciences · 2025Article
Corrections and comments
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Authors and funding
8 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectivesOral squamous cell carcinoma (OSCC) is the most common malignant tumour in the oral and maxillofacial region. Lactic acid accumulation in the tumour microenvironment (TME) has gained attention for its dual role as an energy source for cancer cells and an activator of signalling pathways crucial to tumour progression. This study aims to reveal the impact of lactate-related genes (LRGs) on the prognosis, TME, and immune characteristics of OSCC, with the ultimate goal of developing a novel prognostic model.
methodsUnsupervised clustering analysis of LRGs in OSCC patients from The Cancer Genome Atlas database was conducted to evaluate and compare TME, immune features, and clinical characteristics across various lactate subtypes. A refined prognostic model was developed through the application of Cox and Least absolute shrinkage and selection operator (LASSO) regression techniques. External validation sets were then utilised to improve model accuracy, along with a detailed correlation analysis of drug sensitivity.
resultsThe Cancer Genome Atlas-OSCC patients were categorised into 4 distinct lactate subtypes based on LRGs. Notably, patients in subtype 1 and subtype 2 exhibited the least and most favourable prognoses, respectively. Subtype 1 patients showed elevated expression levels of immune checkpoint genes. Further analysis identified 1086 genes with significant expression differences between cancer and noncancer tissues, as well as between subtype 1 and subtype 2 patients. Selected genes for the prognostic model included ZNF662, CGNL1, VWCE, and ZFP42. The high-risk group defined by this model had a significantly poorer prognosis (P < .0001) and functioned as an independent prognostic factor (P < .001), accurately predicting 1-, 3-, and 5-year survival rates. Additionally, individuals in the high-risk category exhibited heightened sensitivity to chemotherapy drugs such as AZ6102 and Venetoclax.
conclusionsThe predictive model based on the genes ZNF662, CGNL1, VWCE, and ZFP42 can serve as a reliable biomarker, providing accurate prognostic predictions for OSCC patients and potential opportunities for pharmaceutical interventions.
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