ArticleFrontiers in genetics2025
PANoptosis-related gene clusters and prognostic risk model in clear cell renal cell carcinoma.
Article in Frontiers in genetics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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1 citing paper in PubMed.
- Recent advances in PANoptosis research in kidney disease: mechanistic networks, pathological roles, and potential intervention strategies.Frontiers in immunology · 2026Review
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8 authors.
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Abstract
Background: Despite advancements in targeted therapies, the prognosis for clear cell renal cell carcinoma (ccRCC) remains poor, particularly for metastatic cases. PANoptosis, a newly discovered programmed cell death pathway involving crosstalk among pyroptosis, apoptosis, and necroptosis, has an undefined role in ccRCC pathogenesis and prognosis, representing a critical knowledge gap. Methods: We conducted a bioinformatics analysis of the expression PANoptosis-related genes (PRGs) in 524 ccRCC patients from the TCGA and GEO databases. Three ccRCC clusters were identified based on PRG expression. Innovatively, we developed a prognostic risk model using LASSO and Cox regression on three hub genes (WDR72, ANLN, SLC16A12), integrating multi-omics data for immune microenvironment, tumor mutation burden (TMB), cancer stem cell (CSC) index, and drug sensitivity assessment. Expression of these hub genes was further validated by RT-qPCR. Results: We found that most of the PRGs were upregulated in ccRCC tumors with low mutation rates, and 18 PRGs exhibited a significant correlation with ccRCC patient survival. Patients were stratified into three PRG clusters and two gene clusters, which were significantly associated with ccRCC prognosis. We constructed a prognostic risk model based on three genes, dividing ccRCC patients into high- and low-risk groups. The predictive value of this risk model was confirmed by ROC curves. High-risk scores were associated with an increased stromal score, immune score, and tumor mutation burden (TMB), but they were associated with a decrease in the cancer stem cell (CSC) index. RT-qPCR confirmed the expression of Conclusion: This novel PANoptosis-based model addresses the knowledge gap by providing enhanced prognostic accuracy and clinical utility for personalized ccRCC management, potentially guiding targeted and immunotherapeutic strategies.
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