Utilizing a novel model of PANoptosis-related genes for enhanced prognosis and immune status prediction in kidney renal clear cell carcinoma

• Published in: Apoptosis (London) 2024-06, Vol.29 (5-6), p.681-692
• Main Authors: Jiang, Zhansheng, Wang, Jiahe, Dao, Chenghuan, Zhu, Mingyu, Li, Yuan, Liu, Fangchao, Zhao, Yangyang, Li, Jiayue, Yang, Yinli, Pan, Zhanyu
• Format: Article
• Language: English
• Subjects: Apoptosis; Biochemistry; Biomedical and Life Sciences; Biomedicine; Cancer; Cancer Research; CD4 antigen; Cell Biology; Cell death; Clustering; Drug efficacy; Gene expression; Gene sequencing; Genes; Genomes; Immune checkpoint inhibitors; Immune status; Immunoregulation; Kidneys; Lymphocytes; Lymphocytes T; Macrophages; Microenvironments; Multivariate analysis; Natural killer cells; Necroptosis; Oncology; Paclitaxel; Prognosis; Pyroptosis; Renal cell carcinoma; Risk; Risk groups; Therapeutic targets; Virology
• ISSN: 1360-8185; 1573-675X; 1573-675X
• DOI: 10.1007/s10495-023-01932-3

Kidney renal clear cell carcinoma (KIRC) is the most common histopathologic type of renal cell carcinoma. PANoptosis, a cell death pathway that involves an interplay between pyroptosis, apoptosis and necroptosis, is associated with cancer immunity and development. However, the prognostic significance of PANoptosis in KIRC remains unclear. RNA-sequencing expression and mutational profiles from 532 KIRC samples and 72 normal samples with sufficient clinical data were retrieved from the Cancer Genome Atlas (TCGA) database. A prognostic model was constructed using differentially expressed genes (DEGs) related to PANoptosis in the TCGA cohort and was validated in a Gene Expression Omnibus (GEO) cohorts. Incorporating various clinical features, the risk model remained an independent prognostic factor in multivariate analysis, and it demonstrated superior performance compared to unsupervised clustering of the 21 PANoptosis-related genes alone. Further mutational analysis showed fewer VHL and more BAP1 alterations in the high-risk group, with alterations in both genes also associated with patient prognosis. The high-risk group was characterized by an unfavorable immune microenvironment, marked by reduced levels of CD4 + T cells and natural killer cells, but increased M2 macrophages and regulatory T cells. Finally, the risk model was predictive of response to immune checkpoint blockade, as well as sensitivity to sunitinib and paclitaxel. The PANoptosis-related risk model developed in this study enables accurate prognostic prediction in KIRC patients. Its associations with the tumor immune microenvironment and drug efficacy may offer potential therapeutic targets and inform clinical decisions.