Utilization of a 3-D tissue engineered model to investigate the effects of perfusion on gynecologic cancer biology

Among gynecologic malignancies, ovarian cancer (OC) has the poorest survival rate, and its clinical management remains challenging due to the high rate of recurrence and chemoresistance. Improving survival for these patients is critical, although this requires the ability to translate preclinical st...

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Autores principales: Alba Martinez, Molly S Buckley, Carly B Scalise, Dezhi Wang, Ashwini A Katre, Michael J Birrer, Joel L Berry, Rebecca C Arend
Formato: article
Lenguaje:EN
Publicado: SAGE Publishing 2021
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Acceso en línea:https://doaj.org/article/2e1e086fd223474ca73103d1aaf6b6bf
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Sumario:Among gynecologic malignancies, ovarian cancer (OC) has the poorest survival rate, and its clinical management remains challenging due to the high rate of recurrence and chemoresistance. Improving survival for these patients is critical, although this requires the ability to translate preclinical studies to actual patient care: bench to bedside and back. Our objective was to develop a preclinical model that accurately represents tumor biology and its microenvironment. We utilized SKOV-3, OVCAR-8, and CS-99 cell lines to show that this model was suitable for in vitro assessment of cell proliferation. We tested OC cells independently and in co-culture with cancer associated fibroblasts (CAFs) or immune cells. Additionally, we used patient-derived ovarian carcinoma and carcinosarcoma samples to show that the system maintains the histologic morphology of the primary tissue after 7 days. Moreover, we tested the response to chemotherapy using both cell lines and patient-derived tumor specimens and confirmed that cell death was significantly higher in the treated group compared to the vehicle group. Finally, we immune profiled the 3-D model containing patient tissue after several days in the bioreactor system and revealed that the immune populations are still present. Our data suggest that this model is a suitable preclinical model to aid in research that will ultimately impact the treatment of patients with gynecologic cancer.