RESUMO
Antibody-drug conjugates (ADCs) constitute a rapidly expanding category of biopharmaceuticals that are reshaping the landscape of targeted chemotherapy. The meticulous process of selecting therapeutic targets, aided by specific monoclonal antibodies' high specificity for binding to designated antigenic epitopes, is pivotal in ADC research and development. Despite ADCs' intrinsic ability to differentiate between healthy and cancerous cells, developmental challenges persist. In this study, we present a rationalized pipeline encompassing the initial phases of the ADC development, including target identification and validation. Leveraging an in-house, computationally constructed ADC target database, termed ADC Target Vault, we identified a set of novel ovarian cancer targets. We effectively demonstrate the efficacy of Surface Plasmon Resonance (SPR) technology and in vitro models as predictive tools, expediting the selection and validation of targets as ADC candidates for ovarian cancer therapy. Our analysis reveals three novel robust antibody/target pairs with strong binding and favourable antibody internalization rates in both wild-type and cisplatin-resistant ovarian cancer cell lines. This approach enhances ADC development and offers a comprehensive method for assessing target/antibody combinations and pre-payload conjugation biological activity. Additionally, the strategy establishes a robust platform for high-throughput screening of potential ovarian cancer ADC targets, an approach that is equally applicable to other cancer types.
RESUMO
Exosomes are physiologically secreted nanoparticles recently established as natural delivery systems involved in cell-to-cell communication and content exchange. Due to their inherent targeting potential, exosomes are currently being harnessed for the development of anti-cancer therapeutics. Clinical trials evaluating their effectiveness are demonstrating safety and promising outcomes. However, challenging large-scale production, isolation, modification and purification of exosomes are current limitations for the use of naturally occurring exosomes in the clinic. Exosome mimetics hold the promise to improve the delivery of bioactive molecules with therapeutic efficacy, while achieving scalability and increasing bioavailability. In this study, we propose the development of Immune Derived Exosome Mimetics (IDEM) as a scalable approach to target and defeat ovarian cancer cells. IDEM were fabricated from monocytic cells by combining sequential filtration steps through filter membranes with different porosity and size exclusion chromatography columns. The physiochemical and molecular characteristics of IDEM were compared to those of natural exosomes (EXO). Nanoparticle Tracking Analysis confirmed a 2.48-fold increase in the IDEM production yields compared to EXO, with similar exosomal markers profiles (CD81, CD63) as demonstrated by flow cytometry and ELISA. To exploit the prospective of IDEM to deliver chemotherapeutics, doxorubicin (DOXO) was used as a model drug. IDEM showed higher encapsulation efficiency and drug release over time compared to EXO. The uptake of both formulations by SKOV-3 ovarian cancer cells was assessed by confocal microscopy and flow cytometry, showing an incremental drug uptake over time. The analysis of the cytotoxic and apoptotic effect of DOXO-loaded nanoparticles both in 2D and 3D culture systems proved IDEM as a more efficient system as compared to free DOXO, unraveling the advantage of IDEM in reducing side-effects while increasing cytotoxicity of targeted cells, by delivering smaller amount of the chemotherapeutic agent. The high yields of IDEM obtained compared to natural exosomes together with the time-effectiveness and reproducibility of their production method make this approach potentially exploitable for clinical applications. Most importantly, the appreciable cytotoxic effect observed on ovarian cancer in vitro systems sets the ground for the development of compelling nanotherapeutic candidates for the treatment of this malady and will be further evaluated.
