ArticleDisease markers2022
Construction and Validation of a Novel Immune Checkpoint-Related Model in Clear Cell Renal Cell Carcinoma.
Article in Disease markers, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
4 citing papers in PubMed.
- A comprehensive review on plant-derived bioactive saponins as promising antimicrobial agents: from bioavailability challenges, molecular mechanistic insights to therapeutic applications.Naunyn-Schmiedeberg's archives of pharmacology · 2026Review
- A novel glycogene-related signature for prognostic prediction and immune microenvironment assessment in kidney renal clear cell carcinoma.Annals of medicine · 2025Article
- Prognostic Role of SETDB2 in Clear Cell Renal Cell Carcinoma: Linking Immune Infiltration, Cuproptosis, and Tumor Suppression.Cancer management and research · 2025Article
- Review
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Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: With the highest mortality and metastasis rate, kidney renal clear cell carcinoma (KIRC) is one of the most common urological malignant tumors and not sensitive to chemotherapy and radiotherapy. Immunotherapy, which proves to be effective and a big progression, such as PD-1/PD-L1 inhibitors, is not sensitive to all KIRC patients. To predict prognosis and immunotherapy response, a novel immune checkpoint gene- (ICG-) related model is essential in clinics. Methods: From the public database-downloaded dataset, a novel ICG-related model for predicting prognosis and immunotherapy response in KIRC patients was built up and verified with R packages and Cox regression analysis. The Kaplan-Meier curve was plotted. Results: 39 ICGs were identified to have different expression in KIRC patients and enriched in immune-related biological pathways and activities. Three ICGs (CTLA4, TNFSF14, and HHLA2) were screened to generate KIRC-ICG model. The KIRC-ICG model was verified to be effective. With conducting KIRC-SYS model, KIRC-ICGscore was verified to be an independent factor regardless of age, gender, stage, grade, and TNM stage. Compared to the ICG-low subgroup, the ICG-high subgroup had more immune activities. KIRC-ICGscore was significantly positively correlated with the expression of Treg markers. KIRC-ICG model could also be reliable to predict immunotherapy response. Conclusion: The KIRC-ICG model was reliable to predict prognosis and immunotherapy response for KIRC patients and could be an independent factor regardless of clinical characteristics.
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