ArticleCancer cell international2024
Assessing the role of programmed cell death signatures and related gene TOP2A in progression and prognostic prediction of clear cell renal cell carcinoma.
Article in Cancer cell international, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
What it found
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Who cites it
10 citing papers in PubMed.
- Glycosylation-Related Gene Signature Identifies MFNG as a Key Driver of Proliferation and Metastasis in Colorectal Cancer.OncoTargets and therapy · 2026Article
- A SWI/SNF complex-related genes signature predicts prognosis and immune infiltration in ccRCC with KCNK5 as a novel biomarker.Scientific reports · 2025Article
- Unraveling the Role of Programmed Cell Death Gene Signature and THBS1 in Gastric Cancer Progression and Therapy Response.Journal of gastroenterology and hepatology · 2025Article
- Identification of key biomarker genes in liver hepatocellular carcinoma and kidney renal clear cell carcinoma progression: A shared high-throughput screening and molecular docking method with potentials for targeted therapeutic interventions.Journal, genetic engineering & biotechnology · 2025Article
- Advances in research on malignant tumors and targeted agents for TOP2A (Review).Molecular medicine reports · 2025Review
- TOP2A inhibition and its cellular effects related to cell cycle checkpoint adaptation pathway.Scientific reports · 2025Article
- A Chemotherapy Response-Related Gene Signature and DNAJC8 as Key Mediators of Hepatocellular Carcinoma Progression and Drug Resistance.Journal of hepatocellular carcinoma · 2025Article
- Harnessing Natural Products to Surmount Drug Resistance in Gastric Cancer: Mechanisms and Therapeutic Perspectives.International journal of biological sciences · 2025Review
- Review
- Assessing TGF-β Prognostic Model Predictions for Chemotherapy Response and Oncogenic Role of FKBP1A in Liver Cancer.Current pharmaceutical design · 2024Article
Corrections and comments
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Authors and funding
12 authors.
Funding
Abstract
Kidney Clear Cell Carcinoma (KIRC), the predominant form of kidney cancer, exhibits a diverse therapeutic response to Immune Checkpoint Inhibitors (ICIs), highlighting the need for predictive models of ICI efficacy. Our study has constructed a prognostic model based on 13 types of Programmed Cell Death (PCD), which are intertwined with tumor progression and the immune microenvironment. Validated by analyses of comprehensive datasets, this model identifies seven key PCD genes that delineate two subtypes with distinct immune profiles and sensitivities to anti-PD-1 therapy. The high-PCD group demonstrates a more immune-suppressive environment, while the low-PCD group shows better responses to PD-1 treatment. In particular, TOP2A emerged as crucial, with its inhibition markedly reducing KIRC cell growth and mobility. These findings underscore the relevance of PCDs in predicting KIRC outcomes and immunotherapy response, with implications for enhancing clinical decision-making.
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Registered trials
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