Mucins and truncated O-glycans unveil phenotypic discrepancies between serous ovarian cancer cell lines and primary tumours

• Autor(a) principal: Coelho, Ricardo
• Data de Publicação: 2018
• Outros Autores: Marcos-Silva, Lara, Mendes, Nuno, Pereira, Daniela, Brito, Catarina, Jacob, Francis, Steentoft, Catharina, Mandel, Ulla, Clausen, Henrik, David, Leonor, Ricardo, Sara
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
• Texto Completo: https://doi.org/10.3390/ijms19072045
• topic: COSMC; MUC1; MUC16; Ovarian cancer cell lines; Serous ovarian carcinomas; Truncated O-glycans; Catalysis; Molecular Biology; Spectroscopy; Computer Science Applications; Physical and Theoretical Chemistry; Organic Chemistry; Inorganic Chemistry; SDG 3 - Good Health and Well-being

Optimal research results rely on the selection of cellular models capable of recapitulating the characteristics of primary tumours from which they originate. The expression of mucins (MUC16 and MUC1) and truncated O-glycans (Tn, STn and T) represents a characteristic footprint of serous ovarian carcinomas (SOCs). Therefore, selecting ovarian cancer (OVCA) cell lines that reflect this phenotype is crucial to explore the putative biological role of these biomarkers in the SOC setting. Here, we investigated a panel of OVCA cell lines commonly used as SOC models, and tested whether, when cultured in 2D and 3D conditions, these recapitulate the mucin and O-glycan expression profiles of SOCs. We further explored the role of truncating the O-glycosylation capacity in OVCAR3 cells through knockout of the COSMC chaperone, using in vitro and in vivo assays. We found that the majority of OVCA cell lines of serous origin do not share the mucin and truncated O-glycan footprint of SOCs, although 3D cultures showed a higher resemblance. We also found that genetic truncation of the O-glycosylation capacity of OVCAR3 cells did not enhance oncogenic features either in vitro or in vivo. This study underscores the importance of well-characterized cellular models to study specific features of ovarian cancer.