Development of a prognostic risk model for clear cell renal cell carcinoma by systematic evaluation of DNA methylation markers.

BACKGROUND: Current risk models for renal cell carcinoma (RCC) based on clinicopathological factors are sub-optimal in accurately identifying high-risk patients. Here, we perform a head-to-head comparison of previously published DNA methylation markers and propose a potential prognostic model for clear cell RCC (ccRCC). PATIENTS AND METHODS: Promoter methylation of PCDH8, BNC1, SCUBE3, GREM1, LAD1, NEFH, RASSF1A, GATA5, SFRP1, CDO1, and NEURL was determined by nested methylation-specific PCR. To identify clinically relevant methylated regions, The Cancer Genome Atlas (TCGA) was used to guide primer design. Formalin-fixed paraffin-embedded (FFPE) tissue samples from 336 non-metastatic ccRCC patients from the prospective Netherlands Cohort Study (NLCS) were used to develop a Cox proportional hazards model using stepwise backward elimination and bootstrapping to correct for optimism. For validation purposes, FFPE ccRCC tissue of 64 patients from the University Hospitals Leuven and a series of 232 cases from The Cancer Genome Atlas (TCGA) were used. RESULTS: Methylation of GREM1, GATA5, LAD1, NEFH, NEURL, and SFRP1 was associated with poor ccRCC-specific survival, independent of age, sex, tumor size, TNM stage or tumor grade. Moreover, the association between GREM1, NEFH, and NEURL methylation and outcome was shown to be dependent on the genomic region. A prognostic biomarker model containing GREM1, GATA5, LAD1, NEFH and NEURL methylation in combination with clinicopathological characteristics, performed better compared to the model with clinicopathological characteristics only (clinical model), in both the NLCS and the validation population with a c-statistic of 0.71 versus 0.65 and a c-statistic of 0.95 versus 0.86 consecutively. However, the biomarker model had limited added prognostic value in the TCGA series with a c-statistic of 0.76 versus 0.75 for the clinical model. CONCLUSION: In this study we performed a head-to-head comparison of potential prognostic methylation markers for ccRCC using a novel approach to guide primers design which utilizes the optimal location for measuring DNA methylation. Using this approach, we identified five methylation markers that potentially show prognostic value in addition to currently known clinicopathological factors.

Resistance to sunitinib in renal cell carcinoma: From molecular mechanisms to predictive markers and future perspectives.

The introduction of agents that inhibit tumor angiogenesis by targeting vascular endothelial growth factor (VEGF) signaling has made a significant impact on the survival of patients with metastasized renal cell carcinoma (RCC). Sunitinib, a tyrosine kinase inhibitor of the VEGF receptor, has become the mainstay of treatment for these patients. Although treatment with sunitinib substantially improved patient outcome, the initial success is overshadowed by the occurrence of resistance. The mechanisms of resistance are poorly understood. Insight into the molecular mechanisms of resistance will help to better understand the biology of RCC and can ultimately aid the development of more effective therapies for patients with this infaust disease. In this review we comprehensively discuss molecular mechanisms of resistance to sunitinib and the involved biological processes, summarize potential biomarkers that predict response and resistance to treatment with sunitinib, and elaborate on future perspectives in the treatment of metastasized RCC.