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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: Martinez, Alba, Buckley, Molly S, Scalise, Carly B, Wang, Dezhi, Katre, Ashwini A, Birrer, Michael J, Berry, Joel L, Arend, Rebecca C
Formato: Online Artículo Texto
Lenguaje:English
Publicado: SAGE Publications 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8606733/
https://www.ncbi.nlm.nih.gov/pubmed/34820113
http://dx.doi.org/10.1177/20417314211055015
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author Martinez, Alba
Buckley, Molly S
Scalise, Carly B
Wang, Dezhi
Katre, Ashwini A
Birrer, Michael J
Berry, Joel L
Arend, Rebecca C
author_facet Martinez, Alba
Buckley, Molly S
Scalise, Carly B
Wang, Dezhi
Katre, Ashwini A
Birrer, Michael J
Berry, Joel L
Arend, Rebecca C
author_sort Martinez, Alba
collection PubMed
description 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.
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spelling pubmed-86067332021-11-23 Utilization of a 3-D tissue engineered model to investigate the effects of perfusion on gynecologic cancer biology Martinez, Alba Buckley, Molly S Scalise, Carly B Wang, Dezhi Katre, Ashwini A Birrer, Michael J Berry, Joel L Arend, Rebecca C J Tissue Eng Original Article 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. SAGE Publications 2021-11-17 /pmc/articles/PMC8606733/ /pubmed/34820113 http://dx.doi.org/10.1177/20417314211055015 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by-nc/4.0/This article is distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 License (https://creativecommons.org/licenses/by-nc/4.0/) which permits non-commercial use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access page (https://us.sagepub.com/en-us/nam/open-access-at-sage).
spellingShingle Original Article
Martinez, Alba
Buckley, Molly S
Scalise, Carly B
Wang, Dezhi
Katre, Ashwini A
Birrer, Michael J
Berry, Joel L
Arend, Rebecca C
Utilization of a 3-D tissue engineered model to investigate the effects of perfusion on gynecologic cancer biology
title Utilization of a 3-D tissue engineered model to investigate the effects of perfusion on gynecologic cancer biology
title_full Utilization of a 3-D tissue engineered model to investigate the effects of perfusion on gynecologic cancer biology
title_fullStr Utilization of a 3-D tissue engineered model to investigate the effects of perfusion on gynecologic cancer biology
title_full_unstemmed Utilization of a 3-D tissue engineered model to investigate the effects of perfusion on gynecologic cancer biology
title_short Utilization of a 3-D tissue engineered model to investigate the effects of perfusion on gynecologic cancer biology
title_sort utilization of a 3-d tissue engineered model to investigate the effects of perfusion on gynecologic cancer biology
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8606733/
https://www.ncbi.nlm.nih.gov/pubmed/34820113
http://dx.doi.org/10.1177/20417314211055015
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