A Phase 2 Study of Sitravatinib in Combination with Nivolumab in Patients with Advanced or Metastatic Urothelial Carcinoma.

BACKGROUND AND OBJECTIVE: Checkpoint inhibitor therapy (CPI) has demonstrated survival benefits in urothelial carcinoma (UC); however, not all patients benefit from CPI due to resistance. Combining sitravatinib, a multitargeted receptor tyrosine kinase inhibitor of TYRO3, AXL, and MERTK (TAM) receptors and VEGFR2, with CPI may improve antitumor responses. Our objective was to assess the efficacy and safety of sitravatinib plus nivolumab in patients with advanced/metastatic UC. METHODS: The 516-003 trial (NCT03606174) is an open-label, multicohort phase 2 study evaluating sitravatinib plus nivolumab in patients with advanced/metastatic UC enrolled in eight cohorts depending on prior treatment with CPI, platinum-based chemotherapy (PBC), or antibody-drug conjugate (ADC). Overall, 244 patients were enrolled and treated with sitravatinib plus nivolumab (median follow-up 14.1-38.2 mo). Sitravatinib (free-base capsules 120 mg once daily [QD] or malate capsule 100 mg QD) plus nivolumab (240 mg every 2 wk/480 mg every 4 wk intravenously). KEY FINDINGS AND LIMITATIONS: The primary endpoint was objective response rate (ORR; RECIST v1.1). The secondary endpoints included progression-free survival (PFS) and safety. The Predictive probability design and confidence interval methods were used. Among patients previously treated with PBC, ORR, and median PFS were 32.1% and 3.9 mo in CPI-naïve patients (n = 53), 14.9% and 3.9 mo in CPI-refractory patients (n = 67), and 5.4% and 3.7 mo in CPI- and ADC-refractory patients (n = 56), respectively. Across all cohorts, grade 3 treatment-related adverse events (TRAEs) occurred in 51.2% patients and grade 4 in 3.3%, with one treatment-related death (cardiac failure). Immune-related adverse events occurred in 50.4% patients. TRAEs led to sitravatinib/nivolumab discontinuation in 6.1% patients. CONCLUSIONS AND CLINICAL IMPLICATIONS: Sitravatinib plus nivolumab demonstrated a manageable safety profile but did not result in clinically meaningful ORRs in patients with advanced/metastatic UC in the eight cohorts studied. PATIENT SUMMARY: In this study, the combination of two anticancer drugs, sitravatinib and nivolumab, resulted in manageable side effects but no meaningful responses in patients with bladder cancer.

Phase II trial of neoadjuvant sitravatinib plus nivolumab in patients undergoing nephrectomy for locally advanced clear cell renal cell carcinoma.

Sitravatinib is an immunomodulatory tyrosine kinase inhibitor that can augment responses when combined with programmed death-1 inhibitors such as nivolumab. We report a single-arm, interventional, phase 2 study of neoadjuvant sitravatinib in combination with nivolumab in patients with locally advanced clear cell renal cell carcinoma (ccRCC) prior to curative nephrectomy (NCT03680521). The primary endpoint was objective response rate (ORR) prior to surgery with a null hypothesis ORR = 5% and the alternative hypothesis set at ORR = 30%. Secondary endpoints were safety; pharmacokinetics (PK) of sitravatinib; immune effects, including changes in programmed cell death-ligand 1 expression; time-to-surgery; and disease-free survival (DFS). Twenty patients were evaluable for safety and 17 for efficacy. The ORR was 11.8%, and 24-month DFS probability was 88·0% (95% CI 61.0 to 97.0). There were no grade 4/5 treatment-related adverse events. Sitravatinib PK did not change following the addition of nivolumab. Correlative blood and tissue analyses showed changes in the tumour microenvironment resulting in an immunologically active tumour by the time of surgery (median time-to-surgery: 50 days). The primary endpoint of this study was not met as short-term neoadjuvant sitravatinib and nivolumab did not substantially increase ORR.

A Preliminary Study of Deep-Learning Algorithm for Analyzing Multiplex Immunofluorescence Biomarkers in Body Fluid Cytology Specimens.

INTRODUCTION: Multiplex biomarker analysis of cytological body fluid specimens is often used to assist cytologists in distiguishing metastatic cancer cells from reactive mesothelial cells. However, evaluating biomarker expression visually may be challenging, especially when the cells of interest are scant. Deep-learning algorithms (DLAs) may be able to assist cytologists in analyzing multiple biomarker expression at the single cell level in the multiplex fluorescence imaging (MFI) setting. This preliminary study was performed to test the feasibility of using DLAs to identify immunofluorescence-stained metastatic adenocarcinoma cells in body fluid cytology samples. METHODS: A DLA was developed to analyze MFI-stained cells in body fluid cytological samples. A total of 41 pleural fluid samples, comprising of 20 positives and 21 negatives, were retrospectively collected. Multiplex immunofluorescence labeling for MOC31, BerEP4, and calretinin, were performed on cell block sections, and results were analyzed by manual analysis (manual MFI) and DLA analysis (MFI-DLA) independently. RESULTS: All cases with positive original cytological diagnoses showed positive results either by manual MFI or MFI-DLA, but 2 of the 14 (14.3%) original cytologically negative cases had rare cells with positive MOC31 and/or BerEP4 staining in addition to calretinin. Manual MFI analysis and MFI-DLA showed 100% concordance. CONCLUSION: MFI combined with DLA provides a potential tool to assist in cytological diagnosis of metastatic malignancy in body fluid samples. Larger studies are warranted to test the clinical validity of the approach.

Biomarkers that may predict response to immunotherapy in ovarian malignancies.

PURPOSE OF REVIEW: Immune checkpoint blockade (ICB) is a promising area of cancer therapeutic research. Therapies targeting the programmed cell death protein 1 (PD-1)/programmed death-ligand 1 (PD-L1) mechanism of tumor immune evasion have resulted in durable responses in many difficult-to-treat tumor types. While these inhibitors are being actively investigated in clinical trials for ovarian cancer, most patients fail to respond to initial treatment with immune therapy. This review focuses on biomarkers for predicting response to treatment, and discusses clinical trials using ICB for recurrent ovarian cancer. RECENT FINDINGS: While PD-L1 detection by immunohistochemistry (IHC) is approved as a companion or complementary diagnostic in some cancers, there are many limitations with its use as a predictive marker. Recent research has explored biomarkers beyond PD-L1 that assess for somatic mutations, immune cell infiltrate, and gene signatures. SUMMARY: With improved understanding of the tumor microenvironment and genomic classifications of ovarian tumors, new diagnostics and biomarkers that supplement conventional IHC may help predict response to therapy.

Assembly of complex cell microenvironments using geometrically docked hydrogel shapes.

Cellular communities in living tissues act in concert to establish intricate microenvironments, with complexity difficult to recapitulate in vitro. We report a method for docking numerous cellularized hydrogel shapes (100-1,000 µm in size) into hydrogel templates to construct 3D cellular microenvironments. Each shape can be uniquely designed to contain customizable concentrations of cells and molecular species, and can be placed into any spatial configuration, providing extensive compositional and geometric tunability of shape-coded patterns using a highly biocompatible hydrogel material. Using precisely arranged hydrogel shapes, we investigated migratory patterns of human mesenchymal stem cells and endothelial cells. We then developed a finite element gradient model predicting chemotactic directions of cell migration in micropatterned cocultures that were validated by tracking ∼2,500 individual cell trajectories. This simple yet robust hydrogel platform provides a comprehensive approach to the assembly of 3D cell environments.