Abstract
PurposeThe present study aimed to establish a hypoxia related genes model to predict the prognosis of kidney clear cell carcinoma (KIRC) patients using data accessed from The Cancer Genome Atlas (TCGA) database and International Cancer Genome Consortium (ICGC) database.MethodsPatients’ data were downloaded from the TCGA and ICGC databases, and hypoxia related genes were accessed from the Molecular Signatures Database. The differentially expressed genes were evaluated and then the differential expressions hypoxia genes were screened. The TCGA cohort was randomly divided into a discovery TCGA cohort and a validation TCGA cohort. The discovery TCGA cohort was used for constructing the hypoxia genes risk model through Lasso regression, univariate and multivariate Cox regression analysis. Receiver operating characteristic (ROC) curves were used to assess the reliability and sensitivity of our model. Then, we established a nomogram to predict the probable one-, three-, and five-year overall survival rates. Lastly, the Tumor Immune Dysfunction and Exclusion (TIDE) score of patients was calculated.ResultsWe established a six hypoxia-related gene prognostic model of KIRC patients in the TCGA database and validated in the ICGC database. The patients with high riskscore present poorer prognosis than those with low riskscore in the three TCGA cohorts and ICGC cohort. ROC curves show our six-gene model with a robust predictive capability in these four cohorts. In addition, we constructed a nomogram for KIRC patients in the TCGA database. Finally, the high risk-group had a high TIDE score than the patients with low riskscore.ConclusionsWe established a six hypoxia-related gene risk model for independent prediction of the prognosis of KIRC patients was established and constructed a robust nomogram. The different riskscores might be a biomarker for immunotherapy strategy.
Highlights
Renal cell carcinoma is one of the most common malignant tumors in the urinary system [1]
We investigate the role of our prognosis model in the immunotherapy strategy
Two hundred hypoxia-related genes were acquired from the Molecular Signatures Database
Summary
Renal cell carcinoma is one of the most common malignant tumors in the urinary system [1]. Clear cell renal cell carcinoma (ccRCC) is the most common type of RCC, and accounts for approximately 80% of cases, with a 10-year cancer specificsurvival rate of 62% [2]. Radical nephrectomy is the standard surgical treatment for localized and locally advanced ccRCC. There is a lack of sufficient effective treatment for metastatic ccRCC and its 5-year survival rate of 12% [1]. The immune checkpoint inhibition agents have been recommended as the first line agents for metastatic RCC instead of targeted therapy [3]. Constructing a prognostic model that can accurately predict the prognosis has become a key issue in the diagnosis and formulation of treatment strategies for renal cancer
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