ArticleScientific reports2024
Identifying prognostic biomarkers in oral squamous cell carcinoma: an integrated single-cell and bulk RNA sequencing study on mitophagy-related genes.
Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed.
- Analysis of tumor stem cell recruitment and integration in microvascular architectural heterogeneity during oral mucosal carcinogenesis: an in vivo experimental study.Journal of translational medicine · 2026Article
- Mitophagy-driven immune evasion in skin cancer: multidimensional regulatory networks and context-dependent therapeutic strategies-a narrative review.Frontiers in immunology · 2026Review
- spVelo: RNA velocity inference for multi-batch spatial transcriptomics data.Genome biology · 2025Article
- Mitophagy's impacts on cancer and neurodegenerative diseases: implications for future therapies.Journal of hematology & oncology · 2025Review
- Mitophagy-Related Gene CHDH Predicts Prognosis and Immune Response and Inhibits Proliferation and Migration in vitro and in vivo of Oral Squamous Cell Carcinoma.Journal of inflammation research · 2025Article
- Unravelling molecular mechanism of oral squamous cell carcinoma and genetic landscape: an insight into disease complexity, available therapies, and future considerations.Frontiers in immunology · 2025Review
- Molecular Targets of Plant-Derived Bioactive Compounds in Oral Squamous Cell Carcinoma.Cancers · 2024Review
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9 authors.
Funding
Abstract
Oral squamous cell carcinoma (OSCC) has an extremely poor prognosis. Recent studies have suggested that mitophagy-related genes (MRGs) are closely correlated with the development and occurrence of cancer, but the role they play in oral cancer has not yet been explained.We conducted a comprehensive analysis of integrated single-cell and bulk RNA sequencing (RNA-seq) data retrieved from Gene Expression Omnibus (GEO) datasets and The Cancer Genome Atlas (TCGA) database. Multiple methods were combined to provide a comprehensive understanding of the genetic expression patterns and biology of OSCC, such as analysis of pseudotime series, CellChat cell communication, immune infiltration, Gene Ontology (GO), LASSO Cox regression, gene set variation analysis (GSVA), Kyoto Encyclopedia of Genes and Genomes (KEGG), gene set enrichment analysis (GSEA), Tumor Mutation Burden (TMB) and drug sensitivity assessments. The findings of this study demonstrated significantly greater activity of MRGs in NK cells than in other cells in OSCC. A reliable prognostic model was developed using 12 candidate genes strongly associated with mitochondrial autophagy. T stage, N stage and risk score were revealed as independent prognostic factors. Distinctively enriched pathways and immune cells were observed in different risk groups. Notably, low-risk patients were more responsive to chemotherapy. In addition, a nomogram model with excellent predictive ability was established by combining the risk scores and clinical features. The activity of MRGs suggest the potential for the development of new targeted therapies. The construction of a robust prognostic model also provides reference value for individualized prediction and clinical decision-making in patients with OSCC.
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