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Using genetically encoded fluorescent biosensors to interrogate ovarian cancer metabolism

BACKGROUND: Epithelial ovarian cancer (OC) is the most lethal gynecological malignancy and patients present with significant metastatic burden, particularly to the adipose-rich microenvironment of the omentum. Recent evidence has highlighted the importance of metabolic adaptations in enabling this m...

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Autores principales: Bose, Shree, Yao, Haipei, Huang, Qiang, Whitaker, Regina, Kontos, Christopher D., Previs, Rebecca A., Shen, Xiling
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9585869/
https://www.ncbi.nlm.nih.gov/pubmed/36266675
http://dx.doi.org/10.1186/s13048-022-01046-5
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author Bose, Shree
Yao, Haipei
Huang, Qiang
Whitaker, Regina
Kontos, Christopher D.
Previs, Rebecca A.
Shen, Xiling
author_facet Bose, Shree
Yao, Haipei
Huang, Qiang
Whitaker, Regina
Kontos, Christopher D.
Previs, Rebecca A.
Shen, Xiling
author_sort Bose, Shree
collection PubMed
description BACKGROUND: Epithelial ovarian cancer (OC) is the most lethal gynecological malignancy and patients present with significant metastatic burden, particularly to the adipose-rich microenvironment of the omentum. Recent evidence has highlighted the importance of metabolic adaptations in enabling this metastasis, leading to significant interest in evolving the arsenal of tools used to study OC metabolism. In this study, we demonstrate the capability of genetically encoded fluorescent biosensors to study OC, with a focus on 3D organoid models that better recapitulate in vivo tumor microenvironments. MATERIALS AND METHODS: Plasmids encoding the metabolic biosensors HyPer, iNap, Peredox, and Perceval were transfected into 15 ovarian cancer cell lines to assay oxidative stress, NADPH/NADP+, NADH/NAD+, and ATP/ADP, respectively. Fluorescence readings were used to assay dynamic metabolic responses to omental conditioned media (OCM) and 100 μM carboplatin treatment. SKOV3 cells expressing HyPer were imaged as 2D monolayers, 3D organoids, and as in vivo metastases via an intravital omental window. We further established organoids from ascites collected from Stage III/IV OC patients with carboplatin-resistant or carboplatin-sensitive tumors (n = 8 total). These patient-derived organoids (PDOs) were engineered to express HyPer, and metabolic readings of oxidative stress were performed during treatment with 100 μM carboplatin. RESULTS: Exposure to OCM or carboplatin induced heterogenous metabolic changes in 15 OC cell lines, as measured using metabolic sensors. Oxidative stress of in vivo omental metastases, measured via intravital imaging of metastasizing SKOV3-HyPer cells, was more closely recapitulated by SKOV3-HyPer organoids than by 2D monolayers. Finally, carboplatin treatment of HyPer-expressing PDOs induced higher oxidative stress in organoids derived from carboplatin-resistant patients than from those derived from carboplatin-sensitive patients. CONCLUSIONS: Our study showed that biosensors provide a useful method of studying dynamic metabolic changes in preclinical models of OC, including 3D organoids and intravital imaging. As 3D models of OC continue to evolve, the repertoire of biosensors will likely serve as valuable tools to probe the metabolic changes of clinical importance in OC. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13048-022-01046-5.
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spelling pubmed-95858692022-10-22 Using genetically encoded fluorescent biosensors to interrogate ovarian cancer metabolism Bose, Shree Yao, Haipei Huang, Qiang Whitaker, Regina Kontos, Christopher D. Previs, Rebecca A. Shen, Xiling J Ovarian Res Research BACKGROUND: Epithelial ovarian cancer (OC) is the most lethal gynecological malignancy and patients present with significant metastatic burden, particularly to the adipose-rich microenvironment of the omentum. Recent evidence has highlighted the importance of metabolic adaptations in enabling this metastasis, leading to significant interest in evolving the arsenal of tools used to study OC metabolism. In this study, we demonstrate the capability of genetically encoded fluorescent biosensors to study OC, with a focus on 3D organoid models that better recapitulate in vivo tumor microenvironments. MATERIALS AND METHODS: Plasmids encoding the metabolic biosensors HyPer, iNap, Peredox, and Perceval were transfected into 15 ovarian cancer cell lines to assay oxidative stress, NADPH/NADP+, NADH/NAD+, and ATP/ADP, respectively. Fluorescence readings were used to assay dynamic metabolic responses to omental conditioned media (OCM) and 100 μM carboplatin treatment. SKOV3 cells expressing HyPer were imaged as 2D monolayers, 3D organoids, and as in vivo metastases via an intravital omental window. We further established organoids from ascites collected from Stage III/IV OC patients with carboplatin-resistant or carboplatin-sensitive tumors (n = 8 total). These patient-derived organoids (PDOs) were engineered to express HyPer, and metabolic readings of oxidative stress were performed during treatment with 100 μM carboplatin. RESULTS: Exposure to OCM or carboplatin induced heterogenous metabolic changes in 15 OC cell lines, as measured using metabolic sensors. Oxidative stress of in vivo omental metastases, measured via intravital imaging of metastasizing SKOV3-HyPer cells, was more closely recapitulated by SKOV3-HyPer organoids than by 2D monolayers. Finally, carboplatin treatment of HyPer-expressing PDOs induced higher oxidative stress in organoids derived from carboplatin-resistant patients than from those derived from carboplatin-sensitive patients. CONCLUSIONS: Our study showed that biosensors provide a useful method of studying dynamic metabolic changes in preclinical models of OC, including 3D organoids and intravital imaging. As 3D models of OC continue to evolve, the repertoire of biosensors will likely serve as valuable tools to probe the metabolic changes of clinical importance in OC. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13048-022-01046-5. BioMed Central 2022-10-20 /pmc/articles/PMC9585869/ /pubmed/36266675 http://dx.doi.org/10.1186/s13048-022-01046-5 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Bose, Shree
Yao, Haipei
Huang, Qiang
Whitaker, Regina
Kontos, Christopher D.
Previs, Rebecca A.
Shen, Xiling
Using genetically encoded fluorescent biosensors to interrogate ovarian cancer metabolism
title Using genetically encoded fluorescent biosensors to interrogate ovarian cancer metabolism
title_full Using genetically encoded fluorescent biosensors to interrogate ovarian cancer metabolism
title_fullStr Using genetically encoded fluorescent biosensors to interrogate ovarian cancer metabolism
title_full_unstemmed Using genetically encoded fluorescent biosensors to interrogate ovarian cancer metabolism
title_short Using genetically encoded fluorescent biosensors to interrogate ovarian cancer metabolism
title_sort using genetically encoded fluorescent biosensors to interrogate ovarian cancer metabolism
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9585869/
https://www.ncbi.nlm.nih.gov/pubmed/36266675
http://dx.doi.org/10.1186/s13048-022-01046-5
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