| Autor: |
Minsi Li, Yi Wei, Wenhua Huang, Cen Wang, Shixi He, Shuwen Bi, Shuangyu Hu, Ling You, Xuanping Huang |
| Jazyk: |
angličtina |
| Rok vydání: |
2024 |
| Předmět: |
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| Zdroj: |
Scientific Reports, Vol 14, Iss 1, Pp 1-14 (2024) |
| Druh dokumentu: |
article |
| ISSN: |
2045-2322 |
| DOI: |
10.1038/s41598-024-70498-0 |
| Popis: |
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. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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