Renal cell carcinoma (RCC) represents 2 to 3% of cancers worldwide, and is among the top ten most diagnosed, with a higher incidence in Western Countries. Among these, clear cell renal carcinoma (CCRcc) is the predominant histology seen, corresponding to 85% of cases. Treatment is with targeted therapy against vascular endothelial growth factor (VEGF) and with new immunotherapeutic agents. Among the new approaches, immune checkpoint inhibitors (ICIs) are the first-line therapeutic option for the treatment of CCRcc, showing improvement in clinical outcomes. These drugs include ipilimumab and nivolumab, monoclonal antibodies that bind to CTLA-4 and PD-1, respectively. However, despite the significant impact on the treatment of kidney cancer, there are many challenges to be overcome. It is estimated that 44% of cancer patients in the US may be eligible for therapy with ICIs, but with a response of only 12%, acquiring mechanisms of resistance not yet fully understood. Additionally, some patients show total tumor regression and, others, hyper-progression. Thus, demands elucidation of the mechanisms involved in resistance based on the identification of new molecular targets involved in the process. The CLARA study, which will recruit 100 patients with metastatic kidney cancer and treat them with immunotherapy, aims to identify somatic and germline mechanisms of response and resistance to treatment. In the present project, we aim to integrate large-scale proteogenomic analyzes for these patients. In the study, patients are treated with anti-CTLA4 in combination with anti-PD1, as per the Phase III Check-Mate-214 study, with collection and genomic material for exome, transcriptome, methylome, microbiome and cellular evaluation. For the clinical response of patients treated with immunotherapy, it is necessary that protein alterations are recognized by the immune system. These changes may result from somatic mutations in the tumor, but, as the proteins still undergo post-translational modifications (PTMs), these may also contribute to the recognition of the tumor by the immune system and, thus, trigger a therapeutic response. Thus, in the present study, we will integrate genomic data with proteomics and phosphoproteomics for the same set of patients. For this, initially biopsy tissues from 40 to 100 patients will be used for analysis by mass spectrometry. Furthermore, a proteomic analysis of immunodepleted plasma pools for high-abundance proteins will be performed, separated into groups arising from specific sub-classifications generated by the response to treatment (responders vs non-responders), using the quantitative strategy of isobaric labeling with TMT of 6 or 10 channels. Therefore, the present project has the potential to provide a better understanding of the mechanisms related to the response to immunotherapy and the identification of candidate biomarkers for prognosis in tissue samples from patients with kidney cancer. Thus, we intend to directly impact the renal cancer care line through the characterization of molecular signatures that indicate response to treatment.
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