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Establishment and Validation of an Individualized Cell Cycle Process-Related Gene Signature to Predict Cancer-Specific Survival in Patients with Bladder Cancer

More accurate models are essential to identify high-risk bladder cancer (BCa) patients who will benefit from adjuvant therapies and thus helpful to facilitate personalized management of BCa. Among various cancer-related hallmarks and pathways, cell cycle process (CCP) was identified as a dominant ri...

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Detalles Bibliográficos
Autores principales: Shi, Run, Bao, Xuanwen, Rogowski, Paul, Schäfer, Christian, Schmidt-Hegemann, Nina-Sophie, Unger, Kristian, Lu, Shun, Sun, Jing, Buchner, Alexander, Stief, Christian, Belka, Claus, Li, Minglun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7281226/
https://www.ncbi.nlm.nih.gov/pubmed/32370292
http://dx.doi.org/10.3390/cancers12051146
Descripción
Sumario:More accurate models are essential to identify high-risk bladder cancer (BCa) patients who will benefit from adjuvant therapies and thus helpful to facilitate personalized management of BCa. Among various cancer-related hallmarks and pathways, cell cycle process (CCP) was identified as a dominant risk factor for cancer-specific survival (CSS) in BCa. Using a series of bioinformatic and statistical approaches, a CCP-related gene signature was established, and the prognostic value was validated in other independent BCa cohorts. In addition, the risk score derived from the gene signature serves as a promising marker for therapeutic resistance. In combination with clinicopathological features, a nomogram was constructed to provide more accurate prediction for CSS, and a decision tree was built to identify high-risk subgroup of muscle invasive BCa patients. Overall, the gene signature could be a useful tool to predict CSS and help to identify high-risk subgroup of BCa patients, which may benefit from intensified adjuvant therapy.