A Novel Prognostic Signature for Survival Prediction and Immune Implication Based on SARS-CoV-2-Related Genes in Kidney Renal Clear Cell Carcinoma.

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COVID-19, a highly infectious and severe disease caused by SARS-CoV-2, has become a significant challenge for global public health. Cancer patients have been reported to be more vulnerable to SARS-CoV-2 infection and have a higher risk for serious complications than the general population. However, the correlation between KIRC and COVID-19 remains incompletely elucidated. In this study, we comprehensively investigated the expression and prognostic significance of 333 SARS-CoV-2 infection-related genes in KIRC using the TCGA dataset and identified 31 SARS-CoV-2-related differently expressed genes between KIRC and normal renal tissues. Based on these genes, we constructed and validated a 5-gene prognostic signature (including ACADM, CENPF, KDELC1, PLOD2, and TRMT1) to distinguish low- and high-risk KIRC patients of poor survival in TCGA and E-MTAB-1980 cohorts. Gene set enrichment analysis (GSEA) showed that some inflammatory/immune-related pathways were significantly enriched in the high-risk group. The ESTIMATE analysis indicated that patients in the high-risk group had higher stromal and immune cell scores, therefore lower tumor purity. Moreover, they presented higher proportions of macrophages M0, regulatory T cells (Tregs), and T follicular helper cells and higher expression of immune checkpoints CTLA-4, LAG-3, TIGIT, and PDCD1 than low-risk patients. Besides, we also developed a nomogram to expand clinical applicability, which exhibits excellent predictive accuracy for survival. In conclusion, we identified a novel prognostic signature and nomogram based on SARS-CoV-2-related genes as reliable prognostic predictors for KIRC patients and provided potential therapeutic targets for KIRC and COVID-19.", "claims": [{"id": "claim-method", "statement": "The survival comparisons were carried out through the Kaplan–Meier method with the log-rank test.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:35141213", "locator": "sections[10] \"Statistical Analysis\" paragraph 2", "quote": "The survival comparisons were carried out through the Kaplan–Meier method with the log-rank test."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The original contributions presented in the study are included in the article/Supplementary Material; further inquiries can be directed to the corresponding author.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:35141213", "locator": "sections[23] \"Data Availability Statement\" paragraph 2", "quote": "The original contributions presented in the study are included in the article/Supplementary Material; further inquiries can be directed to the corresponding author."}], "state": "complete"}, {"id": "claim-target-result", "statement": "The study identified and validated a 5-gene prognostic signature and nomogram based on SARS-CoV-2–related genes for predicting survival in KIRC patients.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:35141213", "locator": "sections[0] \"Abstract\" paragraph 1", "quote": "In conclusion, we identified a novel prognostic signature and nomogram based on SARS-CoV-2–related genes as reliable prognostic predictors for KIRC patients and provided potential therapeutic targets for KIRC and COVID-19."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "The study identified and validated a 5-gene prognostic signature and nomogram based on SARS-CoV-2–related genes for predicting survival in KIRC patients.", "steps": [{"id": "read_published_estimate", "order": 1, "name": "Read the published estimate from the source", "kind": "other", "state": "complete", "blocked_on": null, "description": "The claim, method and evidence span published with the source article.", "duration_hours": null, "parameters": {}, "inputs": ["source:pmid:35141213"], "outputs": ["the published estimate and its evidence"], "instruments": [], "reagents": []}, {"id": "obtain_source_data", "order": 2, "name": "Obtain the source data from the named repository", "kind": "data-preparation", "state": "complete", "blocked_on": null, "description": "The GEO series accession resolves and its sample accessions are listed. 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