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Simple Summary: The extracellular matrix has a complex structure, and the glycans within are difficult to study, but are able to elicit multiple effects on resident and immune cells, with a crucial role being exerted by hyaluronan. The presence of the glycosaminoglycan hyaluronan in the extracellular matrix of tissues is the result of the cooperative synthesis of several resident cells, that is, macrophages and tumor and stromal cells. Any change in hyaluronan concentration or dimension leads to a modification in stiffness and cellular response through receptors on the plasma membrane. Hyaluronan has an effect on all cancer cell behaviors, such as evasion of apoptosis, limitless replicative potential, sustained angiogenesis, and metastasis. It is noteworthy that hyaluronan metabolism can be dramatically altered by growth factors and matrikines during inflammation, as well as by the metabolic homeostasis of cells. The regulation of HA deposition and its dimensions are pivotal for tumor progression and cancer patient prognosis. Nevertheless, because of all the factors involved, modulating hyaluronan metabolism could be tough. Several commercial drugs have already been described as potential or effective modulators; however, deeper investigations are needed to study their possible side effects. Moreover, other matrix molecules could be identified and targeted as upstream regulators of synthetic or degrading enzymes. Finally, co-cultures of cancer, fibroblasts, and immune cells could reveal potential new targets among secreted factors. [ABSTRACT FROM AUTHOR]

Simple Summary: The 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. [ABSTRACT FROM AUTHOR]