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pmid:31929144
Development and validation of an immune prognostic classifier for clear cell renal cell carcinoma.
Yong-Yao Gu · Gang Chen · Peng Lin · Ji-Wen Cheng · Zhi-Guang Huang · Jie Luo · Gao-Qiang Zhai · Ying-Lun Wang · Hai-Biao Yan · Sheng-Hua Li
Cancer biomarkers : section A of Disease markers · 2020 doi:10.3233/CBM-191017
Paper
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Experiment
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Data
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Analysis
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Execution
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Complete file
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Twenty-four types of immune cells were evaluated using single-sample gene set enrichment analysis. Cox regression analyses were conducted to develop an immune risk score.\nRESULTS: Survival analyses revealed that 13 genes significantly associated with the overall survival (OS). Furthermore, multivariate Cox analysis identified an immune risk score on the basis of mast cells, natural killer CD56bright cells, T helper 17 (Th17) cells, and Th2 cells. The immune risk score was associated with OS, with hazard ratios of 2.72 (95% CI 2.17-3.40) and 3.24 (95% CI 1.64-6.44) in TCGA and E-MTAB-1980 datasets, respectively. This immune risk score was significantly correlated with some immunotherapy-related biomarkers.\nCONCLUSIONS: We profiled a prognostic signature and established an immune risk score model for ccRCC, which could provide novel predictive markers for patients with ccRCC and an indicator for immunotherapy response measurement.", "claims": [{"id": "claim-method", "statement": "Twenty-four types of immune cells were evaluated using single-sample gene set enrichment analysis. Cox regression analyses were conducted to develop an immune risk score.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:31929144", "locator": "sections[0] \"Abstract\" paragraph 3", "quote": "Twenty-four types of immune cells were evaluated using single-sample gene set enrichment analysis. 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