ArticleScientific reports2025
Bioinformatic analysis of glycolysis and lactate metabolism genes in head and neck squamous cell carcinoma.
Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
2 citing papers in PubMed.
- Single-Cell Transcriptomics Identifies Novel Prognostic Signatures in HNSCC Immunotherapy Response.Cancer science · 2025Article
- Developments in the study of the role of lactate metabolism in the genesis and progression of thyroid cancer.Frontiers in cell and developmental biology · 2025Review
Corrections and comments
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Head and neck squamous cell carcinoma (HNSCC) is a heterogeneous cancer with significant global incidence. This study investigates glycolysis- and lactate metabolism-related genes (GALMRGs) in HNSCC, focusing on their impact on prognosis, the tumor immune microenvironment, and their potential as therapeutic biomarkers. Analysis of data from the Cancer Genome Atlas and Gene Expression Omnibus identified 16 GALMRGs that were differentially expressed in HNSCC compared to normal tissues. Functional analysis revealed the involvement of lactate and pyruvate metabolism and HIF-1 signaling pathways. Weighted gene co-expression network analysis identified two module genes, CDKN3 and SLC2A1. Five key genes (CAV1, CDKN3, LDHA, MB, and PER2) were identified through univariate, multivariate, and LASSO regression analyses and used to construct a prognostic model. This model demonstrated strong predictive accuracy for overall survival, stratifying patients into high- and low-risk groups. Immune cell infiltration analysis showed a negative correlation between resting and activated mast cells, and low-risk patients had higher tumor mutational burden, suggesting a better response to immunotherapy. Consensus clustering classified HNSCC into two distinct molecular subtypes with differing expression of the key genes. This GALMRG-based prognostic model is a promising biomarker for predicting HNSCC outcomes and immunotherapy responses, providing valuable insights for personalized treatment strategies.
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Registered trials
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