Hypoxia is a key regulator of cancer progression and chemoresistance. Ambiguity remains about how cancer cells adapt to hypoxic microenvironments and transfer oncogenic factors to surrounding cells. In this study, we determined the effects of hypoxia on the bioactivity of sEVs in a panel of ovarian cancer (OvCar) cell lines. The data obtained demonstrate a varying degree of platinum resistance induced in OvCar cells when exposed to low oxygen tension (1% oxygen). Using quantitative mass spectrometry (Sequential Window Acquisition of All Theoretical Fragment Ion Mass Spectra, SWATH) and targeted multiple reaction monitoring (MRM), we identified a suite of proteins associated with glycolysis that change under hypoxic conditions in cells and sEVs. Interestingly, we identified a differential response to hypoxia in the OvCar cell lines and their secreted sEVs, highlighting the cells’ heterogeneity. Proteins are involved in metabolic reprogramming such as glycolysis, including putative hexokinase (HK), UDP-glucuronosyltransferase 1–6 (UD16), and 6-phosphogluconolactonase (6 PGL), and their presence correlates with the induction of platinum resistance. Furthermore, when normoxic cells were exposed to sEVs from hypoxic cells, platinum-resistance increased significantly (p < 0.05). Altered chemoresistance was associated with changes in glycolysis and fatty acid synthesis. Finally, sEVs isolated from a clinical cohort (n = 31) were also found to be enriched in glycolysis-pathway proteins, especially in patients with recurrent disease. These data support the hypothesis that hypoxia induces changes in sEVs composition and bioactivity that confers carboplatin resistance on target cells. Furthermore, we propose that the expression of sEV-associated glycolysis-pathway proteins is predictive of ovarian cancer recurrence and is of clinical utility in disease management.

Ovarian cancer (OC) is one of the most diagnosed gynecological cancers in women. Due to the lack of effective early stage screening, women are more often diagnosed at an advanced stage; therefore, it is associated with poor patient outcomes. There are a lack of tools to identify patients at the highest risk of developing this cancer. Moreover, early detection strategies, therapeutic approaches, and real-time monitoring of responses to treatment to improve survival and quality of life are also inadequate. Tumor development and progression are dependent upon cell-to-cell communication, allowing cancer cells to re-program cells not only within the surrounding tumor microenvironment, but also at distant sites. Recent studies established that extracellular vesicles (EVs) mediate bi-directional communication between normal and cancerous cells. EVs are highly stable membrane vesicles that are released from a wide range of cells, including healthy and cancer cells. They contain tissue-specific signaling molecules (e.g., proteins and miRNA) and, once released, regulate target cell phenotypes, inducing a pro-tumorigenic and immunosuppressive phenotype to contribute to tumor growth and metastasis as well as proximal and distal cell function. Thus, EVs are a “fingerprint” of their cell of origin and reflect the metabolic status. Additionally, via the capacity to evade the immune system and remain stable over long periods in circulation, EVs can be potent therapeutic agents. This review examines the potential role of EVs in the different aspects of the tumor microenvironment in OC, as well as their application in diagnosis, delivery of therapeutic agents, and disease monitoring.

Ovarian cancer is the most common gynaecological malignancy and the seventh most diagnosed cancer in females worldwide. Currently, it is the sixth leading cause of cancer related mortality among patients globally. The heterogenous origin of the disease and unambiguous nature of the clinical symptoms leading to delayed detection has been one of the key reasons for increasing mortality. Hence new approaches are required to understand the biology of ovarian cancer, where the use of cell culture models that mimic the physiology of the disease is fundamental. Cell culture serves as a crucial in vitro tool, contributing to our comprehension of various aspects of cell biology, tissue morphology, disease mechanisms, drug responses, protein production, and tissue engineering. A significant portion of in vitro studies rely on two-dimensional (2D) cell cultures, however, these cultures present notable limitations, for example disruptions in cellular and extracellular interactions, alterations in cell morphology, polarity, and division mechanisms. Recently, extracellular vesicles have been identified as crucial players in cell biology as part of the communication system that cancer cells use to metastasize. We optimized and compared three-dimensional (3D) culture of ovarian cancer cells lines (SKOV-3 and OVCAR-3) with two-dimensional models based on their protein and miRNA content. We further investigated whether extracellular vesicles from these models reflect changes in cancer cells, and aid in the identification of overall survival in women with ovarian cancer.

Ovarian cancer remains challenging to treat because of late diagnosis, heterogeneity, and poor response to existing therapies. Here, we present a streamlined and scalable extracellular vesicle (EV) engineering approach that enables efficient cargo packaging and enhances targeted cargo delivery to ovarian tumors in vivo. Systematic comparison of vesicle‐anchoring domains identifies an optimized scaffold for loading bioluminescent cargo into EVs. We characterized EV production from five cell lines commonly used for biopharmaceutical manufacturing and selected and stably engineered ExpiCHO cells as a robust, large‐scale source of engineered EVs (eEVs). To achieve molecular targeting, the transmembrane scaffold Δ688 PTGFRN is modified to display tissue‐targeting ligand Ephrin‐B2 (EB2) on the EV surface, exploiting its high‐affinity interaction with the Eph receptor B4 (EphB4), which is overexpressed in advanced ovarian carcinoma. Following systemic administration, these eEVs carrying bioluminescent cargo preferentially accumulate in EphB4‐positive cells in vivo and permit non‐invasive, spatiotemporal tracking via cargo‐mediated bioluminescence resonance energy transfer. In patient‐derived xenograft models with differential EphB4 expression, Ephrin‐B2–displaying eEVs show selective localization to EphB4‐positive tumors and report intratumoral cargo distribution. This work establishes a translational strategy for large‐scale eEV production, advancing EV‐based delivery platforms for precision targeting of EphB4‐expressing ovarian cancer.

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Background: Extracellular vesicles (EVs) represent a promising source of blood-based biomarkers for ovarian cancer detection, with growing interest in their application for early diagnosis. A systematic evaluation of EV subpopulations derived from plasma and serum is needed to determine their comparability for immunoaffinity-enriched proteomic profiling and to enable broader use of clinical biobank collections.Methods: We performed immunoaffinity-enriched proteomic profiling of EV from 243 paired EDTA plasma and serum samples within a nested case–control cohort from the UK Ovarian Cancer Population Study, including controls, benign, borderline, and high-grade serous ovarian cancer (HGSOC) cases. Integrative analyses assessed proteomic depth, plasma–serum concordance, and classification performance using machine learning approaches. Key findings were evaluated across EV subpopulations to determine their suitability for biomarker discovery and application across diverse clinical sample types.Finding: Plasma-derived EV subpopulations showed greater proteomic depth than serum, with 6439 versus 5451 protein groups identified and 2838 versus 840 proteins detected at 50% prevalence. Despite this difference, protein intensities were highly concordant between matrices (r=0.86, p<0.001), and this concordance was maintained across disease groups and cancer stages. For distinguishing HGSOC from non‑cancers, the EV‑augmented CA‑125 model achieved superior performance, with an AUROC of 0.97 in plasma and 0.96 in serum. It improved plasma sensitivity to 99% (95% CI 89–100) and specificity to 85% (95% CI 68–91), compared with 96% (95% CI 82–100) sensitivity and 65% (95% CI 51–73) specificity for CA‑125 alone, while maintaining similarly high discrimination in serum.Interpretation: Surface epitope-targeted EV subpopulation enrichment yields biologically specific proteomic profiling of HGSOC with highly concordant proteomic biomarker signatures across plasma and serum, supporting their interchangeable use.