Cell microarray as a powerful tool to accelerate cancer research: focus on drug screening

• Autor(a) principal: Nunes, M.
• Data de Publicação: 2023
• Outros Autores: Nunes, D., Costa, A., Ricardo, S.
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
• Texto Completo: https://doi.org/10.48797/sl.2023.93
• topic: Poster

Background: Designing reliable in vitro assays is crucial to attain impactful results in oncology research. Cell Microarray (CMA) has become a key tool to accelerate cancer research as many samples can be evaluated at the same time in a single slide, allowing the evaluation of many prognostics, diagnostics, and therapy response biomarkers. Previously, we described a model of drug combination using antineoplastic and repurposed drugs to find alternative oncology regimens [1,2]. Objective: The purpose of this study is to adapt a histology-based method to evaluate the changes on biomarkers expression during drug efficacy tests and explore the mechanisms of therapy resistance in a chip-like tool such as a CMA. Methods: Two chemoresistant ovarian cancer models, i.e., OVCAR8 (Carboplatin-resistant) and OVCAR8 PTX RP (Carboplatin and Paclitaxel-resistant) cell lines [3] were incubated for 48 h with Carboplatin and Paclitaxel, alone and combined with repurposed drugs (Pitavastatin, Metformin and Ivermectin), using their half-maximal inhibitory concentration (IC50) previously assessed. Next, we collected the cells subjected to all assay conditions and constructed a CMA, gathering all the conditions in a single paraffin block [3-5]. Results: CMA have the potential to accelerate cancer research studies since it allows the evaluation and comparison of a variety of cell culture conditions, such as several cell lines, time-points, and different therapeutical conditions, on a single microscope slide [4,5]. Conclusions: This approach represents a rapid and cost-effective screening tool to accelerate anti-cancer drug efficacy studies, allowing the discovery of biomarkers capable to predict therapy responses and to unveil the mechanism of action of new drugs, repurposed drugs, and drug combinations.