Abstract
Simple SummaryThe identification of biomarkers in response to therapeutic treatment is one of the main objectives of personalized oncology. Predictive biomarkers are particularly relevant for oncologists challenged by the busy scenario of possible therapeutic options in mRCC patients, including immunotherapy and TKIs. In fact the activation of the immune system can determine the outcome and success of the different therapeutic strategies. In this study we evaluated changes in the immune system of TKI mRCC-treated patients defining immunological profiles related to response characterized by specific biomarkers. The validation of the proposed immune portrait to an extended number of patients could allow characterization and selection of responsive and non-responsive patients from the beginning of the therapeutic process.With the introduction of immune checkpoint inhibitors (ICIs) and next-generation vascular endothelial growth factor receptor–tyrosine kinase inhibitors (VEGFR–TKIs), the survival of patients with advanced renal cell carcinoma (RCC) has improved remarkably. However, not all patients have benefited from treatments, and to date, there are still no validated biomarkers that can be included in the therapeutic algorithm. Thus, the identification of predictive biomarkers is necessary to increase the number of responsive patients and to understand the underlying immunity. The clinical outcome of RCC patients is, in fact, associated with immune response. In this exploratory pilot study, we assessed the immune effect of TKI therapy in order to evaluate the immune status of metastatic renal cell carcinoma (mRCC) patients so that we could define a combination of immunological biomarkers relevant to improving patient outcomes. We profiled the circulating levels in 20 mRCC patients of exhausted/activated/regulatory T cell subsets through flow cytometry and of 14 immune checkpoint-related proteins and 20 inflammation cytokines/chemokines using multiplex Luminex assay, both at baseline and during TKI therapy. We identified the CD3+CD8+CD137+ and CD3+CD137+PD1+ T cell populations, as well as seven soluble immune molecules (i.e., IFNγ, sPDL2, sHVEM, sPD1, sGITR, sPDL1, and sCTLA4) associated with the clinical responses of mRCC patients, either modulated by TKI therapy or not. These results suggest an immunological profile of mRCC patients, which will help to improve clinical decision-making for RCC patients in terms of the best combination of strategies, as well as the optimal timing and therapeutic sequence.
Highlights
Renal cell carcinoma (RCC) represents 2–3% of cancer diagnoses in adults [1]
0.27% ± 0.18% in non-responsive, p = 0.28; at >T0: 0.87% ± 0.28% in responsive vs. 0.23% ± 0.08% in non-responsive, p = 0.18). These results show that CD137+ T cells could represent a possible biomarker that is able to identify patients that could clinically benefit from tyrosine kinase inhibitor (TKI) treatment
The results obtained in our study are in line with that observed in a previous study conducted on a limited number of metastatic renal carcinoma (mRCC) patients, where we identified modulations occurring in the immune T cell repertoire of mRCC during TKI
Summary
Renal cell carcinoma (RCC) represents 2–3% of cancer diagnoses in adults [1]. The prognosis of metastatic renal carcinoma (mRCC). Has considerably improved due to the recent introduction of the vascular endothelial growth factor receptor–tyrosine kinase inhibitors (VEGFR–TKIs) and immune checkpoint inhibitors (ICIs). New synergistic combinations between TKIs and ICIs could increase the first line of therapeutic strategies in RCC. The recent improvements and advances in genomic sequencing and molecular characterizations have allowed an accurate definition of prognosis, predictive biomarkers are still needed to select the patients beneficiaries of the different therapeutic approaches. Diagnostic tools that pool biomarker data could help to tailor treatment strategies based on the biological and immunological parameters of the patient [2]
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