Boosting Clear Cell Renal Carcinoma-Specific Drug Discovery Using a Deep Learning Algorithm and Single-Cell Analysis

Clear cell renal carcinoma (ccRCC), the most common subtype of renal cell carcinoma, has the high heterogeneity of a highly complex tumor microenvironment. Existing clinical intervention strategies, such as target therapy and immunotherapy, have failed to achieve good therapeutic effects. In this article, single-cell transcriptome sequencing (scRNA-seq) data from six patients downloaded from the GEO database were adopted to describe the tumor microenvironment (TME) of ccRCC, including its T cells, tumor-associated macrophages (TAMs), endothelial cells (ECs), and cancer-associated fibroblasts (CAFs). Based on the differential typing of the TME, we identified tumor cell-specific regulatory programs that are mediated by three key transcription factors (TFs), whilst the TF EPAS1/HIF-2α was identified via drug virtual screening through our analysis of ccRCC's protein structure. Then, a combined deep graph neural network and machine learning algorithm were used to select anti-ccRCC compounds from bioactive compound libraries, including the FDA-approved drug library, natural product library, and human endogenous metabolite compound library. Finally, five compounds were obtained, including two FDA-approved drugs (flufenamic acid and fludarabine), one endogenous metabolite, one immunology/inflammation-related compound, and one inhibitor of DNA methyltransferase (N4-methylcytidine, a cytosine nucleoside analogue that, like zebularine, has the mechanism of inhibiting DNA methyltransferase). Based on the tumor microenvironment characteristics of ccRCC, five ccRCC-specific compounds were identified, which would give direction of the clinical treatment for ccRCC patients.

Mapping the immune environment in clear cell renal carcinoma by single-cell genomics

Clear cell renal cell carcinoma (ccRCC) is one of the most immunologically distinct tumor types due to high response rate to immunotherapies, despite low tumor mutational burden. To characterize the tumor immune microenvironment of ccRCC, we applied single-cell-RNA sequencing (SCRS) along with T-cell-receptor (TCR) sequencing to map the transcriptomic heterogeneity of 25,688 individual CD45+ lymphoid and myeloid cells in matched tumor and blood from three patients with ccRCC. We also included 11,367 immune cells from four other individuals derived from the kidney and peripheral blood to facilitate the identification and assessment of ccRCC-specific differences. There is an overall increase in CD8+ T-cell and macrophage populations in tumor-infiltrated immune cells compared to normal renal tissue. We further demonstrate the divergent cell transcriptional states for tumor-infiltrating CD8+ T cells and identify a MKI67 + proliferative subpopulation being a potential culprit for the progression of ccRCC. Using the SCRS gene expression, we found preferential prediction of clinical outcomes and pathological diseases by subcluster assignment. With further characterization and functional validation, our findings may reveal certain subpopulations of immune cells amenable to therapeutic intervention.

Tyrosine kinase inhibitors and immunotherapy combinations in renal cell carcinoma

The treatment landscape of metastatic renal cell carcinoma (mRCC) has been transformed with the advent of antiangiogenics, notably tyrosine kinase inhibitors (TKIs) targeting vascular endothelial growth factor receptor (VEGFR), and immune checkpoint inhibitors (ICIs). Both treatment options have improved outcomes of patients and modified the natural history of mRCC. Clinical investigations have focused on evaluating combination regimens containing ICIs and VEGFR-directed TKIs. Namely, the combinations of axitinib plus pembrolizumab (KEYNOTE-426) and axitinib plus avelumab (JAVELIN RENAL 101) have shown improved outcomes compared with sunitinib in treatment-naïve patients with mRCC. In this review, we discuss the clinical data of single-agent TKIs and ICIs in mRCC and the rationale for the combination ICIs and TKIs based on preclinical and clinical evidence. We also explore the current challenges for regimen selection and development of predictive biomarkers.

Vascular endothelial growth factor and programmed death-1 pathway inhibitors in renal cell carcinoma

Advanced renal cell carcinoma has historically carried a poor prognosis with very limited treatment options. However, in recent years, the treatment landscape has changed drastically, with many new therapeutic options and improved survival for patients. Novel treatments consist of molecularly targeted agents against the vascular endothelial growth factor (VEGF) pathway as well as the immune checkpoint inhibitors, which stimulate an antitumor immune response. Recent strategy has focused on the development of combination therapy with the use of VEGF inhibitors and immune checkpoint inhibitors in the first-line setting. As more treatments are approved and the options for therapy expand further, there is a growing need for predictive biomarkers to personalize treatment choices for individual patients. Prospective clinical trials comparing the sequencing of treatments are needed to help determine the best therapeutic approach.

Individualised axitinib regimen for patients with metastatic renal cell carcinoma after treatment with checkpoint inhibitors: a multicentre, single-arm, phase 2 study

BACKGROUND

Checkpoint inhibitor therapy is a standard of care for patients with metastatic renal cell carcinoma. Treatment options after checkpoint inhibitor therapy include vascular endothelial growth factor receptor (VEGF-R) tyrosine kinase inhibitors, although no prospective data regarding their use in this setting exist. Axitinib is a VEGF-R inhibitor with clinical data supporting increased activity with dose titration. We aimed to investigate the activity of dose titrated axitinib in patients with metastatic renal cell carcinoma who were previously treated with checkpoint inhibitor.

METHODS

We did a multicentre, phase 2 trial of axitinib given on an individualised dosing algorithm. Patients at least 18 years of age with histologically or cytologically confirmed locally recurrent or metastatic renal cell carcinoma with clear cell histology, a Karnofsky Performance Status of 70% or more, and measurable disease who received checkpoint inhibitor therapy as the most recent treatment were eligible. There was no limit on number of previous therapies received. Patients received oral axitinib at a starting dose of 5 mg twice daily with dose titration every 14 days in 1 mg increments (ie, 5 mg twice daily to 6 mg twice daily, up to 10 mg twice daily maximum dose) if there was no axitinib-related grade 2 or higher mucositis, diarrhoea, hand-foot syndrome, or fatigue. If one or more of these grade 2 adverse events occurred, axitinib was withheld for 3 days before the same dose was resumed. Dose reductions were made if recurrent grade 2 adverse events despite treatment breaks or grade 3-4 adverse events occurred. The primary outcome was progression-free survival. Analyses were done per protocol in all patients who received at least one dose of axitinib. Recruitment has been completed and the trial is ongoing. This trial is registered with ClincalTrials.gov, number NCT02579811.

FINDINGS

Between Jan 5, 2016 and Feb 21, 2018, 40 patients were enrolled and received at least one dose of study treatment. With a median follow-up of 8·7 months (IQR 3·7-14·2), the median progression-free survival was 8·8 months (95% CI 5·7-16·6). Fatigue (83%) and hypertension (75%) were the most common all-grade adverse events. The most common grade 3 adverse event was hypertension (24 patients [60%]). There was one (3%) grade 4 adverse event (elevated lipase) and no treatment-related deaths occurred. Serious adverse events that were likely related to therapy occurred in eight (20%) patients; the most common were dehydration (n=4) and diarrhoea (n=2).

INTERPRETATION

Individualised axitinib dosing in patients with metastatic renal cell inoma previously treated with checkpoint inhibitors did not meet the prespecified threshold for progression free survival, but these data show that this individualised titration scheme is feasible and has robust clinical activity. These prospective results warrant consideration of axitinib in this setting.

FUNDING

Pfizer.