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Renal cell carcinoma.

BMJ (Clinical research ed.) | 2014

The treatment of renal cell carcinoma (RCC) has changed greatly over the past 15 years. Progress in the surgical management of the primary tumor and increased understanding of the molecular biology and genomics of the disease have led to the development of new therapeutic agents. The management of the primary tumor has changed owing to the realization that clean margins around the primary lesion are sufficient to prevent local recurrence, as well as the development of more sophisticated tools and techniques that increase the safety of partial nephrectomy. The management of advanced disease has altered even more dramatically as a result of new agents that target the tumor vasculature or that attenuate the activation of intracellular oncogenic pathways. This review summarizes data from prospective randomized phase III studies on the surgical management and systemic treatment of RCC, and provides an up to date summary of the histology, genomics, staging, and prognosis of RCC. It describes the management of the primary tumor and offers an overview of systemic agents that form the mainstay of treatment for advanced disease. The review concludes with an introduction to the exciting new class of immunomodulatory agents that are currently in clinical trials and may form the basis of a new therapeutic approach for patients with advanced RCC.

Pubmed ID: 25385470 RIS Download

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Associated grants

  • Agency: NCI NIH HHS, United States
    Id: P30 CA016672

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Gene Expression Omnibus (GEO) (tool)

RRID:SCR_005012

Functional genomics data repository supporting MIAME-compliant data submissions. Includes microarray-based experiments measuring the abundance of mRNA, genomic DNA, and protein molecules, as well as non-array-based technologies such as serial analysis of gene expression (SAGE) and mass spectrometry proteomic technology. Array- and sequence-based data are accepted. Collection of curated gene expression DataSets, as well as original Series and Platform records. The database can be searched using keywords, organism, DataSet type and authors. DataSet records contain additional resources including cluster tools and differential expression queries.

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