An integrated approach to implement precision oncology in renal cell carcinoma (RCC): identification and validation of clinical, tissue-based, and circulating factors to refine prognosis, response prediction, and therapeutic choices.

The first-line treatment scenario of advanced Renal Cell Carcinoma (aRCC) witnessed a significant paradigm shift from vascular growth factor receptor tyrosine kinase inhibitors (VEGFR-TKIs) monotherapy to immune checkpoint inhibitors (ICIs) doublet or in combination with VEGFR-TKIs. Prognostic stratification and first-line treatment choices still rely on clinical risk scores as the IMDC, whose prognostic rather than predictive value is widely recognized. However, a substantial proportion of patients experience remarkably different clinical outcomes from those predicted by their risk class. The lack of reproducible, affordable, and biology-based predictive biomarkers represents a significant unmet need for therapeutic tailoring. The topic of this thesis is focused on the first interim analysis of the multicentre multicohort SIGNS-RCC trial. This study aims to identify novel prognostic/predictive biomarkers through the analysis of clinical, tissue-based, and circulating factors. Their impact will be evaluated by correlation with clinical outcomes. The tissue-based analysis is based on reproducible techniques, including immunohistochemistry (IHC), fluorescence in situ hybridization (FISH), a custom next-generation sequencing (NGS) panel, and RNA in situ hybridization (RNA-ISH). Serum cytokine levels and mononuclear cell subpopulations are assessed as potential circulating prognostic/predictive biomarkers. The interim analysis of the retrospective cohort underlined a substantial selection bias, requiring further refinement before completing the accrual. Selected cases were analyzed as a pilot cohort, confirming the feasibility of the project. However, the assessment of specific variables as interleukin-8 (IL-8) and BRCA-associated protein 1 (BAP1), revealed the need for additional optimization before conducting the final analysis of the full cohort. The second part of the thesis is focused on two historical cohorts of first-line treated aRCC patients. The first group included good-risk patients according to IMDC criteria. The results converge on available evidence in identifying a subgroup of “very good” risk patients exhibiting extremely long survival with VEGFR-TKIs monotherapy. Therefore, this population requires further effort for its proper identification and the exploration of specific therapeutic strategies. The second cohort included aRCC patients regardless of their IMDC risk group (“all comers”). As result, additional clinical variables demonstrated a slightly better performance in OS prediction when compared to IMDC. These results confirm that biology-based factors are required for an optimal and tailored clinical assessment of each patient. In addition, wedemonstrated the feasibility of the tissue-based analysis while maintaining an approach informed by widely used and cost-effective techniques. Taken together, these data reinforce the importance and feasibility of the objectives of the SIGNS-RCC study, which is awaiting completion of enrolment for final results.