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Systematic Review: ClearCode 34 – A Validated Prognostic Signature in Clear Cell Renal Cell Carcinoma (ccRCC)
BACKGROUND: ccA/ccB classification was developed to classify clear cell renal carcinoma (ccRCC) patients into high and low risk based on gene expression patterns. ClearCode34 is a genetic signature that was developed from the ccA/ccB classification to predict recurrence in localized ccRCC patients....
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
IOS Press
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6176730/ https://www.ncbi.nlm.nih.gov/pubmed/30320241 http://dx.doi.org/10.3233/KCA-170021 |
Sumario: | BACKGROUND: ccA/ccB classification was developed to classify clear cell renal carcinoma (ccRCC) patients into high and low risk based on gene expression patterns. ClearCode34 is a genetic signature that was developed from the ccA/ccB classification to predict recurrence in localized ccRCC patients. OBJECTIVE: This review will evaluate the molecular signature ClearCode34, discuss its role in predicting recurrence and consider the rational application of the tool as a strategy to guide future applications of adjunctive therapy in ccRCC. METHODS: A review of all the relevant papers in PubMed with the terms “ccA/ccB” or “ClearCode34” in ccRCC were reviewed. RESULTS: Gene expression data was used to model dominant molecular subtypes of ccRCC tumors using consensus clustering methods. The most stable model implied two dominant subgroups – subsequently named ccA and ccB. A 34-gene panel was developed for clinical application, with 10 genes highly expressed corresponding to ccB subtype and 24 from ccA subtype. ClearCode34 independently correlated with cancer-specific survival, overall survival and recurrence in localized ccRCC patients in multiple validations. CONCLUSIONS: ClearCode34 is a robust and well validated molecular signature that can identify aggressive ccRCC in primary tumors. Along with basic clinical and pathologic variables like stage, necrosis and grade, robust molecular based prognostic markers are needed that could help better predict groups of patients who will most benefit from risk-adapted treatment approaches. |
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