ArticleFrontiers in molecular biosciences2021
Development and Validation of a Prognostic Gene Signature in Clear Cell Renal Cell Carcinoma.
Article in Frontiers in molecular biosciences, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed.
- Machine learning and multi-omics clustering to map cellular rewiring and immune evasion in ccRCC.Human genomics · 2026Article
- The role of MELK in cancer: mechanisms and therapeutic options.Frontiers in oncology · 2026Review
- Targeting MELK in tumor cells and tumor microenvironment: from function and mechanism to therapeutic application.Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico · 2025Review
- AURKB affects the proliferation of clear cell renal cell carcinoma by regulating fatty acid metabolism.Discover oncology · 2025Article
- Kidney Cancer Prediction Empowered with Blockchain Security Using Transfer Learning.Sensors (Basel, Switzerland) · 2022Article
- Oncogenic role and potential regulatory mechanism of topoisomerase IIα in a pan-cancer analysis.Scientific reports · 2022Article
- Comprehensive analysis of a homeobox family gene signature in clear cell renal cell carcinoma with regard to prognosis and immune significance.Frontiers in oncology · 2022Article
- The Predictive Competing Endogenous RNA Regulatory Networks and Potential Prognostic and Immunological Roles of Cyclin A2 in Pan-Cancer Analysis.Frontiers in molecular biosciences · 2022Article
- Using a Machine Learning Approach to Identify Key Biomarkers for Renal Clear Cell Carcinoma.International journal of general medicine · 2022Article
- Identification of Prognostic Gene Signatures for Survival of Patients With Phaeochromocytoma, Paraganglioma, and Other Tumor Types.Cancer diagnosis & prognosisArticle
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Authors and funding
9 authors.
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Abstract
Clear cell renal cell carcinoma (ccRCC), one of the most common urologic cancer types, has a relatively good prognosis. However, clinical diagnoses are mostly done during the medium or late stages, when mortality and recurrence rates are quite high. Therefore, it is important to perform real-time information tracking and dynamic prognosis analysis for these patients. We downloaded the RNA-seq data and corresponding clinical information of ccRCC from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. A total of 3,238 differentially expressed genes were identified between normal and ccRCC tissues. Through a series of Weighted Gene Co-expression Network, overall survival, immunohistochemical and the least absolute shrinkage selection operator (LASSO) analyses, seven prognosis-associated genes (AURKB, FOXM1, PTTG1, TOP2A, TACC3, CCNA2, and MELK) were screened. Their risk score signature was then constructed. Survival analysis showed that high-risk scores exhibited significantly worse overall survival outcomes than low-risk patients. Accuracy of this prognostic signature was confirmed by the receiver operating characteristic curve and was further validated using another cohort. Gene set enrichment analysis showed that some cancer-associated phenotypes were significantly prevalent in the high-risk group. Overall, these findings prove that this risk model can potentially improve individualized diagnostic and therapeutic strategies.
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