| Literature DB >> 30231375 |
Jeffrey Graham1, Daniel Y C Heng1, James Brugarolas1, Ulka Vaishampayan1.
Abstract
The treatment of renal cell carcinoma represents one of the great success stories in translational cancer research, with the development of novel therapies targeting key oncogenic pathways. These include drugs that target the VEGF and mTOR pathways, as well as novel immuno-oncology agents. Despite the therapeutic advancements, there is a paucity of well-validated prognostic and predictive biomarkers in advanced kidney cancer. With a number of highly effective therapies available across multiple lines, it will become increasingly important to develop a more tailored approach to treatment selection. Prognostic clinical models, such the International Metastatic Renal Cell Carcinoma Database Consortium (IMDC) model, are routinely used for prognostication in clinical practice. The IMDC model has demonstrated a predictive capability in the context of these treatments including immune checkpoint inhibition. A number of promising molecular markers and gene expression signatures are being explored as prognostic and predictive biomarkers, but none are ready to be widely used for treatment selection. In this review, we will explore the current landscape of personalized care in metastatic renal cell carcinoma. This will include a focus on both prognostic and predictive factors as well as clinical applications of biology in kidney cancer.Entities:
Mesh:
Year: 2018 PMID: 30231375 PMCID: PMC6865066 DOI: 10.1200/EDBK_201215
Source DB: PubMed Journal: Am Soc Clin Oncol Educ Book ISSN: 1548-8748