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

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Abstract

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.

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Data availability

The data that support the findings of this study are openly available in TCGA database at https://portal.gdc.cancer.gov/, GEO database at https://www.ncbi.nlm.nih.gov/geo/, or are available from the corresponding author upon reasonable request.

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Acknowledgements

We are grateful to Sangerbox (http://vip.sangerbox.com) and Nanjing Geneseeq Technology Inc. for providing technical support of this manuscript.

Funding

This research is supported by the National Natural Science Foundation of China (82274607), the Tianjin Health and Family Planning Commission program (No. 2017166) and Beijing Xisike Clinical Oncology Research Foundation (Y-HS202102-0120, Y-HS202202-0005).

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  1. Zhansheng Jiang and Jiahe Wang have authors contributed equally to this work.

Authors and Affiliations

  1. Department of Integrative Oncology, Key Laboratory of Cancer Prevention and Therapy, Tianjin’s Clinical Research Center for Cancer, Key Laboratory of Cancer Immunology and Biotherapy, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, 1 Huanhu West Road, Tianjin, 300060, China

    Zhansheng Jiang, Mingyu Zhu, Fangchao Liu, Yangyang Zhao, Jiayue Li, Yinli Yang & Zhanyu Pan

  2. Tianjin University of Traditional Chinese Medicine, Tianjin, China

    Jiahe Wang, Chenghuan Dao & Yuan Li

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ZJ and JW made substantial contributions to the conception or design of the work; JW and CD made substantial contributions to the acquisition of the work; MZ,Y L,FL,YZ and JL made substantial contributions to the creation of new software used in the work; ZJ, ZP and YY drafted the work or revised it critically for important intellectual content; ZP and YY approved the version to be published; ZP and YY agree to be accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved.

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Jiang, Z., Wang, J., Dao, C. et al. Utilizing a novel model of PANoptosis-related genes for enhanced prognosis and immune status prediction in kidney renal clear cell carcinoma. Apoptosis 29, 681–692 (2024). https://doi.org/10.1007/s10495-023-01932-3

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