RESUMO
Patients with high-grade serous ovarian cancer (HGSC) who have no visible residual disease (R0) after primary surgery have the best clinical outcomes, followed by patients who undergo neoadjuvant chemotherapy (NACT) and have a response enabling interval cytoreductive surgery. Clinically useful biomarkers for predicting these outcomes are still lacking. Extracellular vesicles (EVs) have been recognized as liquid biopsy-based biomarkers for early cancer detection and disease surveillance in other disease settings. In this study, we performed extensive molecular characterization of serum-derived EVs and correlated the findings with therapeutic outcomes in patients with HGSC. Using EV-DNA whole-genome sequencing and EV-RNA sequencing, we identified distinct somatic EV-DNA alterations in cancer-hallmark genes and in ovarian cancer genes, as well as significantly altered oncogenic pathways between the R0 group and NACT groups. We also found significantly altered EV-RNA transcriptomic variations and enriched pathways between the groups. Taken together, our data suggest that the molecular characteristics of EVs could enable prediction of patients with HGSC who could undergo R0 surgery or respond to chemotherapy.
RESUMO
PURPOSE: Tumor-associated macrophages (TAMs) are known to contribute to adaptive resistance to anti-vascular endothelial growth factor (VEGF) antibody (AVA) therapy in ovarian cancer. BET (bromodomain and extra-terminal domain) inhibitors (BETi) may have unique roles in targeting TAMs. Our objective was to examine the effects of BETi on TAMs, especially in the context of enhancing the efficacy of AVA therapy. METHODS: We conducted a series of in vitro (MTT assay, apoptosis, flow cytometry, and RNA sequencing) and in vivo (xenograft ovarian cancer model) experiments to determine the biological effects of BETi combined with AVA in ovarian cancer. For statistical analysis, a two-tailed Student's t test (equal variance) or ANOVA was used for multiple groups' comparison, and p < 0.05 was considered significant. RESULTS: BETi resulted in a dose-dependent decrease in cell viability and induced apoptosis (p < 0.01) in ovarian cancer cells (SKOV3ip1, OVCAR5, and OVCAR8). Treatment with BETi significantly increased apoptosis in THP-1 monocytes and macrophages (PMA-differentiated THP-1; p < 0.01). Furthermore, BETi selectively induced greater apoptosis in M2-like macrophages (PMA and IL-4, IL-13-differentiated THP-1) (31.3%-36.1%) than in M1-like macrophages (PMA and LPS-differentiated THP-1) (12.4%-18.5%) (p < 0.01). Flow cytometry revealed that the percentage of M1-like macrophages (CD68+/CD80+) was significantly increased after treatment with low-dose BETi (ABBV-075 0.1 µM; p < 0.05), whereas the percentage of CD68+/CCR2+ macrophages was significantly decreased (p < 0.001); these findings suggest that BETi may selectively inhibit the survival of CCR2+ macrophages and re-polarize the macrophages into an M1-like phenotype. RNA-seq analysis revealed that BETi selectively targeted macrophage infiltration-related cytokines/chemokines in ovarian cancer (adjusted p < 0.05 and Log2 fold change ≥ 1.5). Finally, using in vivo ovarian cancer models, compared with control or monotherapy, the combination of BETi (ABBV-075) and bevacizumab resulted in greater inhibition of tumor growth and macrophage infiltration (p < 0.05) and longer survival of tumor-bearing mice (p < 0.001). CONCLUSIONS: Our findings indicate a previously unrecognized role for BETi in selectively targeting CCR2+ TAMs and enhancing the efficacy of AVA therapy in ovarian cancer.
