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A novel classification based on non-apoptosis cell death predicts clinical outcomes and immunotherapy response of clear renal cell carcinoma

Non-apoptosis cell death could be a secondary consequence of the immune response, which profoundly influences tumor microenvironment (TME), escaping from chemotherapy/immunotherapy-induced apoptosis resistance effects. Whereas, systemic analysis of non-apoptosis regulated cell death associated with...

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Bibliographic Details
Published in:American journal of translational research 2022, Vol.14 (11), p.7792-7805
Main Authors: Chen, Liuxun, Liu, Xvdong, Zeng, Shenjie, Zhu, Huimin, Wang, Jiawu, Jiang, Qing
Format: Article
Language:English
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Summary:Non-apoptosis cell death could be a secondary consequence of the immune response, which profoundly influences tumor microenvironment (TME), escaping from chemotherapy/immunotherapy-induced apoptosis resistance effects. Whereas, systemic analysis of non-apoptosis regulated cell death associated with TME and clinical outcomes remains unveiled. Our kidney clear carcinoma (KIRC) samples from The Cancer Genome Atlas (TCGA) were stratified into three clusters based on the activity of autophagic cell death, ferroptosis, pyroptosis and necroptosis. Clinical prognosis, TME landscape, biological functions and somatic mutation frequency were compared among the clusters. Additionally, to identify a gene signature highly correlated with clinical prognosis, a risk score model was constructed, and the clinical prognosis, immune infiltration, somatic mutation and biological pathways of risk score subgroups were investigated. Our non-apoptosis cell death clusters are robustly predictive of immunotherapy responses. Patients in Cluster B are the most sensitive to immune checkpoint blockades-depended immunotherapy. Our risk score model was also verified as a promising biomarker for clinical prognosis and immunotherapy efficiency. Where, the High-risk score group was more sensitive to immunotherapy. The novel non-apoptosis cell death-based classification and risk score model could predict the outcome of immunotherapy, and highly associate with immune infiltration. These findings may provide a novel strategy to aid in identificatin of biomarkers and selecting personalized therapeutic strategies.
ISSN:1943-8141
1943-8141