Individualizing Systemic Therapies in First Line Treatment and beyond for Advanced Renal Cell Carcinoma.

Simple Summary In recent years, a number of new, effective treatments have become available for advanced renal (kidney) cancer. However, with more drugs available it has become more difficult to decide which drugs to choose for particular patients, and in which order to use them. In addition, the new treatments do not work for all patients and they can have troublesome side effects. At the moment, these choices are made according to factors including the type of renal carcinoma from a biopsy, the extent of cancer for that patient, their previous health and their current fitness. The options are summarized in guidelines although these do not make recommendations for individual patients. It is hoped that ongoing research will uncover new tests that allow these decisions to be made more accurately in a "personalized" manner. This article describes how the process is undertaken at present and how it may change in the future. Therapeutic options for treating advanced renal cell cancer (RCC) are rapidly evolving. Vascular endothelial growth factor (VEGF)-directed therapy, predominantly VEGF receptor (VEGFr) tyrosine kinase inhibitors (TKIs) had been the most effective first line treatment since 2005 irrespective of International Metastatic RCC Database Consortium (IMDC) risk stratification. However, immune checkpoint inhibitors (ICI) have recently changed the treatment paradigm for advanced RCC particularly as the first-line systemic treatment modality. The combination of Ipilimumab and Nivolumab provides better disease control and long-term outcomes compared with the anti-VEGFr TKI Sunitinib for IMDC intermediate- to poor-risk patients and we now have the option of using ICI with TKI upfront for all IMDC risk groups. This poses a challenge for physicians, both to select the most suitable first line regimen and the most suitable subsequent therapy given the lack of data about sequencing in this setting. This treatment landscape is expected to become more complex with the emerging treatment options. Moreover, these therapeutic options cannot be generalized as significant variability exists between individual's disease biologies and their physiologies for handling treatment adverse effects. Notable efforts are being made to identify promising predictive biomarkers ranging from neo-antigen load to gene expression profiling. These biomarkers need prospective validation to justify their utility in clinical practice and in treatment decision making. This review article discusses various clinicopathological characteristics that should be carefully evaluated to help select appropriate treatment and discusses the current status of biomarker-based selection.