Shoji S, Nakano M, Sato H, Tang XY, Osamura YR, Terachi T, Uchida T, Takeya K. The current status of tailor-made medicine with molecular biomarkers for patients with clear cell renal cell carcinoma.
Clin Exp Metastasis 2014;
31:111-34. [PMID:
23959576 DOI:
10.1007/s10585-013-9612-7]
[Citation(s) in RCA: 14] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2013] [Accepted: 08/12/2013] [Indexed: 01/05/2023]
Abstract
Appropriate use of multiple reliable molecular biomarkers in the right context will play a role in tailormade medicine of clear cell renal cell carcinoma (RCC) patients in the future. A total of 11,056 patients from 53 studies were included in this review. The article numbers of the each evidence levels, using the grading system defined by the Oxford Centre for Evidence-based Medicine, in 1b, 2a, 2b, and 3b were 5 (9%), 18 (34%), 29 (55%), and 1 (2%), respectively. The main goal of using biomarkers is to refine predictions of tumor progression, pharmacotherapy responsiveness, and cancer-specific and/or overall survival. Currently, carbonic anhydrase (CA9) and vascular endothelial growth factor (VEGF) in peripheral blood and p53 in tumor tissues are measured to predict metastasis, while VEGF-related proteins in peripheral blood are used to assess pharmacotherapy responsiveness with sunitinib. Furthermore, interleukin 8, osteopontin, hepatocyte growth factor, and tissue inhibitors of metalloproteinases-1 in peripheral blood enable assessment of responsiveness to pazopanib treatment. Other reliable molecular biomarkers include von Hippel–Lindau gene alteration, hypoxia-inducible factor-1a, CA9, and survivin in tumor tissues and VEGF in peripheral blood for predicting cancer-specific survival. In the future, studies should undergo external validation for developing tailored management of clear cell RCC with molecular biomarkers, since individual institutional studies lack the generalization and consistency required to maintain accuracy among different patient series.
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