Establishment and Validation of an Individualized Cell Cycle Process-Related Gene Signature to Predict Cancer-Specific Survival in Patients with Bladder Cancer
| Autor: | Nina-Sophie Schmidt-Hegemann, Minglun Li, Christian G. Stief, Alexander Buchner, Shun Lu, Claus Belka, Run Shi, Xuanwen Bao, Paul Rogowski, Christian Schäfer, Kristian Unger, Jing Sun |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2020 |
| Předmět: |
0301 basic medicine
Oncology therapeutic resistance Cancer Research medicine.medical_specialty gene signature lcsh:RC254-282 Cancer specific survival Article 03 medical and health sciences 0302 clinical medicine cancer-specific survival Internal medicine medicine Adjuvant therapy Risk factor skin and connective tissue diseases Bladder cancer Framingham Risk Score business.industry Cell cycle process Nomogram Gene signature medicine.disease lcsh:Neoplasms. Tumors. Oncology. Including cancer and carcinogens 030104 developmental biology 030220 oncology & carcinogenesis bladder cancer Bladder Cancer Cell Cycle Process Gene Signature Cancer-specific Survival Therapeutic Resistance business cell cycle process |
| Zdroj: | Cancers, Vol 12, Iss 1146, p 1146 (2020) Cancers Cancers 12:1146 (2020) Volume 12 Issue 5 |
| ISSN: | 2072-6694 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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