Biomarkers in renal-cell carcinoma: building on clinical paradigms
Menée à partir d'échantillons tumoraux fixés au formaldéhyde et inclus en paraffine après prélèvement sur 357 patients atteints d'un carcinome métastatique à cellules rénales puis validée sur 258 patients complémentaires, cette étude évalue l'intérêt d'inclure le statut mutationnel de six gènes (BAP1, PBRM1, TP53, TERT, KDM5C et SETD2) dans le modèle prédictif du "Memorial Sloan Kettering Cancer Center" pour améliorer la performance de ce dernier
Several models for prognostic stratification of patients with metastatic renal-cell carcinoma have been reported. The two most widely used models are the Memorial Sloan Kettering Cancer Center (MSKCC) and the International Metastatic Renal Cell Carcinoma Database Consortium (IMDC) models.The MSKCC model, which was developed in 1999, when cytokine therapy was standard of care, stratifies treatment-naive patients on the basis of five clinical and laboratory factors. Meanwhile, the IMDC model was developed in the context of VEGF-targeted therapy and stratifies patients on the basis of six factors, four of which are shared with the MSKCC model. These models have a valuable role in prognostication and counselling of patients with metastatic renal-cell carcinoma and in designing clinical trials by providing estimates for expected overall survival. In the past few years, the utility of risk categorisation of patients with advanced renal-cell carcinoma has expanded into treatment algorithms. Two examples are cabozantinib and the combination regimen of nivolumab plus ipilimumab, both of which were approved on the basis of their improved activity over sunitinib in treatment-naive patients with metastatic renal-cell carcinoma who are in intermediate and poor IMDC risk categories. However, both models use only clinical and laboratory parameters and do not incorporate genomic data, despite comprehensive genomic profiling of tumour tissue being increasingly available in clinics and with decreasing costs. Hence, now is an opportune time to integrate tumour mutational status into these prognostic models.
The Lancet Oncology , résumé, 2017