PD-L1 as a Urine Biomarker in Renal Cell Carcinoma-A Case Series and Proof-of-Concept Study.

BACKGROUND: Renal cell carcinoma (RCC) is among the most lethal urologic malignancies once metastatic. Current treatment approaches for metastatic RCC (mRCC) involve immune checkpoint inhibitors (ICIs) that target the PD-L1/PD-1 axis. High PD-L1 expression in tumor tissue has been identified as a negative prognostic factor in RCC. However, the role of PD-L1 as a liquid biomarker has not yet been fully explored. Herein, we analyze urine levels of PD-L1 in mRCC patients before and after either ICI therapy or surgical intervention, as well as in a series of patients with treatment-naïve RCC. PATIENTS AND METHODS: The mid-stream urine of patients with mRCC (n = 4) or treatment-naïve RCC, i.e., prior to surgery from two centers (cohort I, n = 49: cohort II, n = 29) was analyzed for PD-L1 by ELISA. The results from cohort I were compared to a control group consisting of patients treated for non-malignant urologic diseases (n = 31). In the mRCC group, urine PD-L1 levels were measured before and after tumor nephrectomy (n = 1) or before and after ICI therapy (n = 3). Exosomal PD-L1 in the urine was analyzed in selected patients by immunoblotting. RESULTS: A strong decrease in urine PD-L1 levels was found after tumor nephrectomy or following systemic treatment with ICIs. In patients with treatment-naïve RCC (cohort I), urine PD-L1 levels were significantly elevated in the RCC group in comparison to the control group (median 59 pg/mL vs. 25.7 pg/mL, p = 0.011). PD-L1 urine levels were found to be elevated, in particular, in low-grade RCCs in cohorts I and II. Exosomal PD-L1 was detected in the urine of a subset of patients. CONCLUSION: In this proof-of-concept study, we show that PD-L1 can be detected in the urine of RCC patients. Urine PD-L1 levels were found to correlate with the treatment response in mRCC patients and were significantly elevated in treatment-naïve RCC patients.

BAP1 and PTEN mutations shape the immunological landscape of clear cell renal cell carcinoma and reveal the intertumoral heterogeneity of T cell suppression: a proof-of-concept study.

Clear cell renal cell carcinoma (ccRCC) is an immunologically vulnerable tumor entity, and immune checkpoint inhibitors are now widely used to treat patients with advanced disease. Whether and to what extent immune responses in ccRCC are shaped by genetic alterations, however, is only beginning to emerge. In this proof-of-concept study, we performed a detailed correlative analysis of the mutational and immunological landscapes in a series of 23 consecutive kidney cancer patients. We discovered that a high infiltration with CD8 + T cells was not dependent on the number of driver mutations but rather on the presence of specific mutational events, namely pathogenic mutations in PTEN or BAP1. This observation encouraged us to compare mechanisms of T cell suppression in the context of four different genetic patterns, i.e., the presence of multiple drivers, a PTEN or BAP1 mutation, or the absence of detectable driver mutations. We found that ccRCCs harboring a PTEN or BAP1 mutation showed the lowest level of Granzyme B positive tumor-infiltrating lymphocytes (TILs). A multiplex immunofluorescence analysis revealed a significant number of CD8 + TILs in the vicinity of CD68 + macrophages/monocytes in the context of a BAP1 mutation but not in the context of a PTEN mutation. In line with this finding, direct interactions between CD8 + TILs and CD163 + M2-polarized macrophages were found in BAP1-mutated ccRCC but not in tumors with other mutational patterns. While an absence of driver mutations was associated with more CD8 + TILs in the vicinity of FOXP3 + Tregs and CD68 + monocytes/macrophages, the presence of multiple driver mutations was, to our surprise, not found to be strongly associated with immunosuppressive mechanisms. Our results highlight the role of genetic alterations in shaping the immunological landscape of ccRCC. We discovered a remarkable heterogeneity of mechanisms that can lead to T cell suppression, which supports the need for personalized immune oncological approaches.

Kidney Cancer Models for Pre-Clinical Drug Discovery: Challenges and Opportunities.

Renal cell carcinoma (RCC) is among the most lethal urological malignancies once metastatic. The introduction of immune checkpoint inhibitors has revolutionized the therapeutic landscape of metastatic RCC, nevertheless, a significant proportion of patients will experience disease progression. Novel treatment options are therefore still needed and in vitro and in vivo model systems are crucial to ultimately improve disease control. At the same time, RCC is characterized by a number of molecular and functional peculiarities that have the potential to limit the utility of pre-clinical model systems. This includes not only the well-known genomic intratumoral heterogeneity (ITH) of RCC but also a remarkable functional ITH that can be shaped by influences of the tumor microenvironment. Importantly, RCC is among the tumor entities, in which a high number of intratumoral cytotoxic T cells is associated with a poor prognosis. In fact, many of these T cells are exhausted, which represents a major challenge for modeling tumor-immune cell interactions. Lastly, pre-clinical drug development commonly relies on using phenotypic screening of 2D or 3D RCC cell culture models, however, the problem of "reverse engineering" can prevent the identification of the precise mode of action of drug candidates thus impeding their translation to the clinic. In conclusion, a holistic approach to model the complex "ecosystem RCC" will likely require not only a combination of model systems but also an integration of concepts and methods using artificial intelligence to further improve pre-clinical drug discovery.