Anti-angiogenic therapy has been demonstrated to increase progression-free survival in patients with many different solid cancers. Unfortunately, the benefit in overall survival is modest and the rapid emergence of drug resistance is a significant clinical problem. Over the last decade, several mechanisms have been identified to decipher the emergence of resistance. There is a multitude of changes within the tumor microenvironment (TME) in response to anti-angiogenic therapy that offers new therapeutic opportunities. In this review, we compile results from contemporary studies related to adaptive changes in the TME in the development of resistance to anti-angiogenic therapy. These include preclinical models of emerging resistance, dynamic changes in hypoxia signaling and stromal cells during treatment, and novel strategies to overcome resistance by targeting the TME.

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.

EP-100 is a synthetic lytic peptide that specifically targets the gonadotropin-releasing hormone receptor on cancer cells. To extend the utility of EP-100, we aimed to identify effective combination therapies with EP-100 for ovarian cancer and explore potential mechanisms of this combination. A series of in vitro (MTT assay, immunoblot analysis, reverse-phase protein array, comet assay, and immunofluorescence staining) and in vivo experiments were carried out to determine the biological effects of EP-100 alone and in combination with standard-of-care drugs. EP-100 decreased the viability of ovarian cancer cells and reduced tumor growth in orthotopic mouse models. Of five standard drugs tested (cisplatin, paclitaxel, doxorubicin, topotecan, and olaparib), we found that the combination of EP-100 and olaparib was synergistic in ovarian cancer cell lines. Further experiments revealed that combined treatment of EP-100 and olaparib significantly increased the number of nuclear foci of phosphorylated histone H2AX. In addition, the extent of DNA damage was significantly increased after treatment with EP-100 and olaparib in comet assay. We performed reverse-phase protein array analyses and identified that the PI3K/AKT pathway was inhibited by EP-100, which we validated with in vitro experiments. In vivo experiment using the HeyA8 mouse model demonstrated that mice treated with EP-100 and olaparib had lower tumor weights (0.06 ± 0.13 g) than those treated with a vehicle (1.19 ± 1.09 g), EP-100 alone (0.62 ± 0.78 g), or olaparib alone (0.50 ± 0.63 g). Our findings indicate that combining EP-100 with olaparib is a promising therapeutic strategy for ovarian cancer.

Background: Patients with high-grade serous ovarian cancer (HGSC) who have no visible residual disease (CGR) after primary surgery have the best clinical outcomes, followed by patients who undergo neoadjuvant chemotherapy (NACT) and have response enabling interval cytoreductive surgery. Through comprehensive omics analyses, we previously characterized molecular and cellular profiles of highly clinically defined HGSC from patients who had CGR versus those triaged to NACT. However, clinically useful predictive biomarkers for such distinctions 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. Here, we performed extensive molecular characterization of serum-derived EVs and correlated them with therapeutic outcomes in patients with HGSC. Methods: Serum-derived medium/large size EVs from patients with HGSC treated under a systematic surgical algorithm were isolated following standard methods of the International Society for Extracellular Vesicles. Patients had either complete gross resection after primary surgery (R0, n=3); poor response to NACT (NACT-PR, n=4), or excellent response to NACT with carboplatin and paclitaxel (NACT-ER, n=3); tissue and matched germline blood samples have already been comprehensively analyzed (Lee et al, Cell Reports, 2020). The isolated EV-DNA and EV-RNA were subjected to whole-genome sequencing and RNA sequencing, respectively. Results: We identified somatic EV-DNA alterations in cancer hallmark genes, including FAT1 and KMT2D as the most frequent mutated genes. Interestingly, we found alterations in ovarian cancer-related genes, including BRCA2 and RAD51 in R0; BRCA2 in NACT-ER; TP53, CDK13, CDK12, BRAF, AKT2, and ARID1A in NACT-PR patients. We also identified 26,338 genes expressed in the EV-RNA transcriptomic profiles. The analysis of the enrichment of cancer hallmark pathways showed that the R0 group was more enriched in the interferon α/γ, PI3K/AKT/mTOR signaling, and DNA repair pathways. Interestingly, we also identified 6,757 differentially expressed genes (DEGs) in the CGR versus the NACT groups (absolute log2-fold change ≥2 and adjusted p-value <0.05). Among the DEGs, we identified 67 genes that were cancer hallmark genes, and 21 of them were overexpressed in the NACT group and 46 were overexpressed in the R0 group. Noticeably, 11 DEGs were directly related to ovarian cancer: TP53, PTEN, CCND1, BARD1, PMS2, and MLH3 were significantly overexpressed in the NACT group, while BRCA2, CSMD3, and GABRA6 were overexpressed in the R0 group. Conclusions: Taken together, our preliminary data suggest that molecular characteristics of EVs could provide an accurate prediction of patients with HGSC who can undergo CGR with surgery and respond to chemotherapy. Citation Format: Li Zhao, Shaolin Ma, Nicole D. Fleming, Joseph Celestino, Mark S. Kim, Richard A. Hajek, Nicholas B. Jennings, Erika J. Thompson, Hongli Tang, Shannon N. Westin, Amir A. Jazaeri, Jianhua Zhang, P Andrew Futreal, Anil K. Sood, Sanghoon Lee. Distinct molecular profiles of serum-derived extracellular vesicles in high-grade serous ovarian cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 5106.

Background: A prognostic index validated for the outcomes of advanced high-grade serous ovarian cancer (HGSOC) patients with neoadjuvant chemotherapy (NACT) is still lacking. We therefore developed an ovarian neoadjuvant chemotherapy prognostic index (ONCPI) to enhance predictive accuracy. Methods: We analyzed clinicopathologic feature of advanced HGSOC patients receiving platinum-based NACT. Blood inflammatory composite markers were calculated and binary-transformed by optimal cutoffs. The omental hematoxylin and eosin (H&E) stained slides were selected for the assessment of chemotherapy response score (CRS). Logistic regression analyses and Cox proportional hazard regression model were utilized to develop a prognostic index. Results: Multivariate analysis showed that CRS and neutrophils-to-lymphocyte ratio (NLR) are independent risk factors for platinum-chemotherapy response. Meanwhile, Kaplan–Meier and Cox regression analysis revealed that CRS score was significantly correlated with PFS and OS, and NLR-high patients was associated with poor OS. We further developed an ONCPI model based on the CRS score and NLR level. Survival analysis suggested that patients with score 0 and 1 of ONCPI were significantly associated with improved PFS and OS. Conclusions: The ONCPI score emerges as a significant prognostic marker for predicting NACT outcomes in advanced HGSOC patients. Its integration into clinical practice and risk-stratified trial design is conceivable.

For decades, platinum resistance has remained one of the major barriers to improving outcomes in ovarian cancer. Patients with platinum-resistant ovarian c