79P SETD2 a potential tissue-agnostic predictive biomarker for ICIs in solid tumors

Genomic Profiling and Molecular Characterization of Clear Cell Renal Cell Carcinoma

Clear cell renal cell carcinoma (ccRCC) treatment has undergone three major paradigm shifts in recent years, first with the introduction of molecular targeted therapies, then with immune checkpoint inhibitors, and, more recently, with immune-based combinations. However, to date, molecular predictors of response to targeted agents have not been identified for ccRCC. The WHO 2022 classification of renal neoplasms introduced the molecularly defined RCC class, which is a first step in the direction of a better molecular profiling of RCC. We reviewed the literature data on known genomic alterations of clinical interest in ccRCC, discussing their prognostic and predictive role. In particular, we explored the role of VHL, mTOR, chromatin modulators, DNA repair genes, cyclin-dependent kinases, and tumor mutation burden. RCC is a tumor whose pivotal genomic alterations have pleiotropic effects, and the interplay of these effects determines the tumor phenotype and its clinical behavior. Therefore, it is difficult to find a single genomic predictive factor, but it is more likely to identify a signature of gene alterations that could impact prognosis and response to specific treatment. To accomplish this task, the interpolation of large amounts of clinical and genomic data is needed. Nevertheless, genomic profiling has the potential to change real-world clinical practice settings.

Prognostic and predictive biomarkers for immunotherapy in advanced renal cell carcinoma

The therapeutic algorithm of renal cell carcinoma has been revolutionized by the approval of immunotherapy agents by regulatory agencies. However, objective and durable responses are still not observed in a large number of patients, and prognostic and predictive biomarkers for immunotherapy response are urgently needed. Prognostic models used in clinical practice are based on clinical and laboratory factors (such as hypercalcaemia, neutrophil count or Karnofsky Performance Status), but, with progress in molecular biology and genome sequencing techniques, new renal cell carcinoma molecular features that might improve disease course and outcomes prediction have been highlighted. An implementation of current models is needed to improve the accuracy of prognosis in the immuno-oncology era. Moreover, several potential biomarkers are currently under evaluation, but effective markers to select patients who might benefit from immunotherapy and to guide therapeutic strategies are still far from validation.