ArticleFrontiers in oncology2023
Mitochondrial metabolic reprogramming-mediated immunogenic cell death reveals immune and prognostic features of clear cell renal cell carcinoma.
Article in Frontiers in oncology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed, 4 citations in OpenAlex.
- Neutrophil extracellular traps and metabolic reprogramming in renal cell carcinoma: implications for tumor progression and immune-based therapeutics.Cancer biology & medicine · 2025Review
- Natural Compounds in Cancer Therapy: Revealing the Role of Flavonoids in Renal Cell Carcinoma Treatment.Biomolecules · 2025Review
- MZB1 regulates the immune microenvironment and inhibits ovarian cancer cell migration.Open medicine (Warsaw, Poland) · 2025Article
- Identification of immunogenic cell death-related genes involved in Alzheimer's disease.Scientific reports · 2024Article
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Authors and funding
7 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Mitochondrial metabolic reprogramming (MMR)-mediated immunogenic cell death (ICD) is closely related to the tumor microenvironment (TME). Our purpose was to reveal the TME characteristics of clear cell renal cell carcinoma (ccRCC) by using them. Methods: Target genes were obtained by intersecting ccRCC differentially expressed genes (DEGs, tumor VS normal) with MMR and ICD-related genes. For the risk model, univariate COX regression and K-M survival analysis were used to identify genes most associated with overall survival (OS). Differences in the TME, function, tumor mutational load (TMB), and microsatellite instability (MSI) between high and low-risk groups were subsequently compared. Using risk scores and clinical variables, a nomogram was constructed. Predictive performance was evaluated by calibration plots and receiver operating characteristics (ROC). Results: We screened 140 DEGs, including 12 prognostic genes for the construction of risk models. We found that the immune score, immune cell infiltration abundance, and TMB and MSI scores were higher in the high-risk group. Thus, high-risk populations would benefit more from immunotherapy. We also identified the three genes ( Conclusions: Our model and nomogram allow accurate prediction of patients' prognoses and immunotherapy responses.
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