Immune checkpoint inhibitors (ICI) represent the cornerstone for the treatment of patients with metastatic clear cell renal cell carcinoma (ccRCC). Despite a favorable response for a subset of patients, others experience primary progressive disease, highlighting the need to precisely understand the plasticity of cancer cells and their cross-talk with the microenvironment to better predict therapeutic response and personalize treatment. Single-cell RNA sequencing of ccRCC at different disease stages and normal adjacent tissue (NAT) from patients identified 46 cell populations, including 5 tumor subpopulations, characterized by distinct transcriptional signatures representing an epithelial-to-mesenchymal transition gradient and a novel inflamed state. Deconvolution of the tumor and microenvironment signatures in public data sets and data from the BIONIKK clinical trial (NCT02960906) revealed a strong correlation between mesenchymal-like ccRCC cells and myofibroblastic cancer-associated fibroblasts (myCAF), which are both enriched in metastases and correlate with poor patient survival. Spatial transcriptomics and multiplex immune staining uncovered the spatial proximity of mesenchymal-like ccRCC cells and myCAFs at the tumor–NAT interface. Moreover, enrichment in myCAFs was associated with primary resistance to ICI therapy in the BIONIKK clinical trial. These data highlight the epithelial–mesenchymal plasticity of ccRCC cancer cells and their relationship with myCAFs, a critical component of the microenvironment associated with poor outcome and ICI resistance. Significance: Single-cell and spatial transcriptomics reveal the proximity of mesenchymal tumor cells to myofibroblastic cancer-associated fibroblasts and their association with disease outcome and immune checkpoint inhibitor response in clear cell renal cell carcinoma.

Three drug combinations, ipilimumab-nivolumab (Ipi-Nivo), pembrolizumab-axitinib (Pembro-Axi), and avelumab-axitinib (Ave-Axi), have received regulatory approval in the USA and Europe for the treatment of metastatic renal cell carcinoma with clear cell component (mRCC). However, no head-to-head comparison data are available to identify the best option. Therefore, we aimed to compare these new treatments in a first-line setting. We conducted a systematic search in PubMed, the Cochrane Library, and clinicaltrials.gov for any randomized controlled trials of treatment-naïve patients with mRCC, from January 2015 to October 2019. The process was performed according to PRISMA guidelines. We performed a Bayesian network meta-analysis with two different approaches, a contrast-based model comparing HRs and ORs between studies and arm-based using parametric modeling. The outcomes for the analysis were overall survival, progression-free survival (PFS), and objective response rate. Our search identified 3 published phase 3 randomized clinical trials (2835 patients). In the contrast-based model, Ave-Axi (SUCRA = 83%) and Pembro-Axi (SUCRA = 80%) exhibited the best ranking probabilities for PFS. For overall survival (OS), Pembro-Axi (SUCRA = 96%) was the most preferable option against Ave-Axi and Ipi-Nivo. Objective response rate analysis showed Ave-Axi as the best (SUCRA: 94%) and Pembro-Axi as the second best option. In the parametric models, the risk of progression was comparable for Ave-Axi and Ipi-Nivo, whereas Pembro-Axi exhibited a lower risk during the first 6 months of treatment and a higher risk afterwards. Furthermore, Pembro-Axi exhibited a net advantage in terms of OS over the two other regimens, while Ave-Axi was the least preferable option. Overall evidence suggests that pembrolizumab plus axitinib seems to have a slight advantage over the other two combinations.

The development of antiangiogenic treatments, followed by immune checkpoint inhibitors (ICI), has significantly changed the management of metastatic clear cell renal cell cancer. Several phase III trials show the superiority of combination therapy, dual immunotherapy (ICI-ICI) or ICI plus tyrosine kinase inhibitors (TKI) of the vascular endothelium growth factor (VEGF) over sunitinib monotherapy. The question is therefore what is the best combination for a given patient? A strategy based on the International Metastatic Database Consortium (IMDC) classification is currently recommended with pembrolizumab + axitinib, cabozantinib + nivolumab, and lenvatinib + pembrolizumab (for all patients) or nivolumab + ipilimumab (for patients with intermediate or poor risk), which are the first-line treatment standards of care. However, several issues remain unresolved and require further investigation, such as the PD-L1 status, the relevance of possible options based on the patient’s profile, and consideration of second-line and subsequent treatments.

Purpose: Immune checkpoint inhibitors (ICI) have revolutionized the treatment of patients with clear-cell renal cell carcinomas (ccRCC). Although analyses of transcriptome, genetic alterations, and the tumor microenvironment (TME) have shed light into mechanisms of response and resistance to these agents, the role of epigenetic alterations in this process remains fully unknown. Experimental Design: We investigated the methylome of six ccRCC cohorts as well as one cell line dataset. Of note, we took advantage of the BIONIKK trial aiming to tailor treatments according to Paris Descartes 4-gene expression subgroups, and performed Illumina EPIC profiling for 46 samples related to patients treated with ipilimumab plus nivolumab, and 17 samples related to patients treated with sunitinib. Results: A group of tumors associated with enhancer demethylation was discovered, namely TED. TED was associated with tumors with sarcomatoid differentiation and poor clinical outcome. TED harbored TET1 promoter demethylation, activated the gene expression signature of epithelial–mesenchymal transition and IL6/JAK/STAT3 pathways, and displayed a TME characterized by both immune activation and suppressive populations, fibroblast infiltration, and endothelial depletion. In addition, TED was a predictive factor of resistance to the combination of first-line ipilimumab-nivolumab in the BIONIKK clinical trial. Finally, TED was associated with activation of specific regulons, which we also found to be predictive of resistance to immunotherapy in an independent cohort. Conclusions: We report on the discovery of a novel epigenetic phenotype associated with resistance to ICIs that may pave the way to better personalizing patients’ treatments. See related commentary by Zhou and Kim, p. 1170

Background: In metastatic prostate cancer (PCa) patients, androgen-deprivation therapy (ADT) combined with chemotherapy or next-generation androgen receptor targeted agents is a new standard treatment. The objective of the present study is to assess longitudinal PSA kinetics during treatment using mathematical modeling, to identify the modeled PSA kinetic parameters able to exhibit early prognostic/predictive values. Methods: Phase III clinical trial dataset (NCT00764166) comparing ADT +/− docetaxel in 250 locally treated patients for PCa with rising PSA levels, who were at high risk of metastatic disease was assessed. A kinetic-pharmacodynamic (K-PD) model was used to fit PSA kinetics during the first 100 treatment days, to estimate the modeled PSA production rate K (KPROD) and elimination constant rate K (KELIM). The prognostic value of these parameters, considered as categorized (favorable vs. unfavorable) covariates regarding PSA progression-free survival (PSA-PFS) and overall survival (OS), was assessed using univariate/multivariate analyses. Results: Data from 177/250 patients was assessed. KELIM exhibited a significant prognostic value regarding PSA-PFS and KPROD regarding OS (univariate analysis). In the PSA-PFS final multivariate model, KELIM and the primary therapy type were significant. The OS multivariate model integrated both KPROD and baseline PSA doubling-time. Conclusion: In this first study assessing the modeled PSA kinetics prognostic value in PCa patients treated with systemic treatments, KELIM and KPROD exhibited respective prognostic values regarding PSA-PFS and OS.