ArticleCancer immunology, immunotherapy : CII2025
Machine learning-derived prognostic signature integrating programmed cell death and mitochondrial function in renal clear cell carcinoma: identification of PIF1 as a novel target.
Article in Cancer immunology, immunotherapy : CII, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed.
- Machine learning-based prognostic signature integrating mitochondrial function and programmed cell death patterns in pancreatic adenocarcinoma.Scientific reports · 2026Article
- In-silico study of machine learning discovers de novo lipogenesis for predicting prognosis and immunotherapy responses in kidney renal clear cell carcinoma.Biology direct · 2026Article
- Mitochondrial Dysfunction in Renal Cell Carcinoma: A Comprehensive Review of Pathogenic Mechanisms and Emerging Therapeutic Opportunities.Oncology research · 2026Review
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Authors and funding
6 authors.
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Abstract
backgroundThe pathogenesis and progression of renal cell carcinoma (RCC) involve complex programmed cell death (PCD) processes. As the powerhouse of the cell, mitochondria can influence cell death mechanisms. However, the prognostic significance of the interplay between mitochondrial function (MF) and PCD remains unclear.
methodsWe collected sets of genes related to PCD and MF. Using a powerful machine learning algorithm framework, we investigated the relationship between MF and PCD in different cohorts of patients and developed a machine learning-derived prognostic signature (mpMLDPS) related to MF and PCD. Finally, the most appropriate prognostic markers for RCC were screened by survival analysis and clinical correlation analysis, and the effects on renal cancer cells were analysed in vitro.
resultsmpMLDPS was significantly correlated with the prognosis of RCC patients, and the prognosis was worse in the high mpMLDPS group, and this result was also validated in external independent cohorts. There were associations between mpMLDPS and immune checkpoints, tumour microenvironment, somatic mutations, and drug sensitivity. Finally, a novel RCC prognostic marker PIF1 was identified in model genes. The knockdown of PIF1 in vitro inhibited the progression of renal carcinoma cells.
conclusionmpMLDPS has great potential to serve as a reliable clinical signature to improve the accuracy and reliability of prognostic assessment in RCC patients, thereby choosing the appropriate therapeutic regimen in clinical practice. PIF1 is also expected to be a novel target for the clinical treatment of RCC.
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