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Metabolic Heterogeneity in Patient Tumor-Derived Organoids by Primary Site and Drug Treatment

New tools are needed to match cancer patients with effective treatments. Patient-derived organoids offer a high-throughput platform to personalize treatments and discover novel therapies. Currently, methods to evaluate drug response in organoids are limited because they overlook cellular heterogenei...

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Autores principales: Sharick, Joe T., Walsh, Christine M., Sprackling, Carley M., Pasch, Cheri A., Pham, Dan L., Esbona, Karla, Choudhary, Alka, Garcia-Valera, Rebeca, Burkard, Mark E., McGregor, Stephanie M., Matkowskyj, Kristina A., Parikh, Alexander A., Meszoely, Ingrid M., Kelley, Mark C., Tsai, Susan, Deming, Dustin A., Skala, Melissa C.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7242740/
https://www.ncbi.nlm.nih.gov/pubmed/32500020
http://dx.doi.org/10.3389/fonc.2020.00553
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author Sharick, Joe T.
Walsh, Christine M.
Sprackling, Carley M.
Pasch, Cheri A.
Pham, Dan L.
Esbona, Karla
Choudhary, Alka
Garcia-Valera, Rebeca
Burkard, Mark E.
McGregor, Stephanie M.
Matkowskyj, Kristina A.
Parikh, Alexander A.
Meszoely, Ingrid M.
Kelley, Mark C.
Tsai, Susan
Deming, Dustin A.
Skala, Melissa C.
author_facet Sharick, Joe T.
Walsh, Christine M.
Sprackling, Carley M.
Pasch, Cheri A.
Pham, Dan L.
Esbona, Karla
Choudhary, Alka
Garcia-Valera, Rebeca
Burkard, Mark E.
McGregor, Stephanie M.
Matkowskyj, Kristina A.
Parikh, Alexander A.
Meszoely, Ingrid M.
Kelley, Mark C.
Tsai, Susan
Deming, Dustin A.
Skala, Melissa C.
author_sort Sharick, Joe T.
collection PubMed
description New tools are needed to match cancer patients with effective treatments. Patient-derived organoids offer a high-throughput platform to personalize treatments and discover novel therapies. Currently, methods to evaluate drug response in organoids are limited because they overlook cellular heterogeneity. In this study, non-invasive optical metabolic imaging (OMI) of cellular heterogeneity was characterized in breast cancer (BC) and pancreatic cancer (PC) patient-derived organoids. Baseline heterogeneity was analyzed for each patient, demonstrating that single-cell techniques, such as OMI, are required to capture the complete picture of heterogeneity present in a sample. Treatment-induced changes in heterogeneity were also analyzed, further demonstrating that these measurements greatly complement current techniques that only gauge average cellular response. Finally, OMI of cellular heterogeneity in organoids was evaluated as a predictor of clinical treatment response for the first time. Organoids were treated with the same drugs as the patient's prescribed regimen, and OMI measurements of heterogeneity were compared to patient outcome. OMI distinguished subpopulations of cells with divergent and dynamic responses to treatment in living organoids without the use of labels or dyes. OMI of organoids agreed with long-term therapeutic response in patients. With these capabilities, OMI could serve as a sensitive high-throughput tool to identify optimal therapies for individual patients, and to develop new effective therapies that address cellular heterogeneity in cancer.
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spelling pubmed-72427402020-06-03 Metabolic Heterogeneity in Patient Tumor-Derived Organoids by Primary Site and Drug Treatment Sharick, Joe T. Walsh, Christine M. Sprackling, Carley M. Pasch, Cheri A. Pham, Dan L. Esbona, Karla Choudhary, Alka Garcia-Valera, Rebeca Burkard, Mark E. McGregor, Stephanie M. Matkowskyj, Kristina A. Parikh, Alexander A. Meszoely, Ingrid M. Kelley, Mark C. Tsai, Susan Deming, Dustin A. Skala, Melissa C. Front Oncol Oncology New tools are needed to match cancer patients with effective treatments. Patient-derived organoids offer a high-throughput platform to personalize treatments and discover novel therapies. Currently, methods to evaluate drug response in organoids are limited because they overlook cellular heterogeneity. In this study, non-invasive optical metabolic imaging (OMI) of cellular heterogeneity was characterized in breast cancer (BC) and pancreatic cancer (PC) patient-derived organoids. Baseline heterogeneity was analyzed for each patient, demonstrating that single-cell techniques, such as OMI, are required to capture the complete picture of heterogeneity present in a sample. Treatment-induced changes in heterogeneity were also analyzed, further demonstrating that these measurements greatly complement current techniques that only gauge average cellular response. Finally, OMI of cellular heterogeneity in organoids was evaluated as a predictor of clinical treatment response for the first time. Organoids were treated with the same drugs as the patient's prescribed regimen, and OMI measurements of heterogeneity were compared to patient outcome. OMI distinguished subpopulations of cells with divergent and dynamic responses to treatment in living organoids without the use of labels or dyes. OMI of organoids agreed with long-term therapeutic response in patients. With these capabilities, OMI could serve as a sensitive high-throughput tool to identify optimal therapies for individual patients, and to develop new effective therapies that address cellular heterogeneity in cancer. Frontiers Media S.A. 2020-05-15 /pmc/articles/PMC7242740/ /pubmed/32500020 http://dx.doi.org/10.3389/fonc.2020.00553 Text en Copyright © 2020 Sharick, Walsh, Sprackling, Pasch, Pham, Esbona, Choudhary, Garcia-Valera, Burkard, McGregor, Matkowskyj, Parikh, Meszoely, Kelley, Tsai, Deming and Skala. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Oncology
Sharick, Joe T.
Walsh, Christine M.
Sprackling, Carley M.
Pasch, Cheri A.
Pham, Dan L.
Esbona, Karla
Choudhary, Alka
Garcia-Valera, Rebeca
Burkard, Mark E.
McGregor, Stephanie M.
Matkowskyj, Kristina A.
Parikh, Alexander A.
Meszoely, Ingrid M.
Kelley, Mark C.
Tsai, Susan
Deming, Dustin A.
Skala, Melissa C.
Metabolic Heterogeneity in Patient Tumor-Derived Organoids by Primary Site and Drug Treatment
title Metabolic Heterogeneity in Patient Tumor-Derived Organoids by Primary Site and Drug Treatment
title_full Metabolic Heterogeneity in Patient Tumor-Derived Organoids by Primary Site and Drug Treatment
title_fullStr Metabolic Heterogeneity in Patient Tumor-Derived Organoids by Primary Site and Drug Treatment
title_full_unstemmed Metabolic Heterogeneity in Patient Tumor-Derived Organoids by Primary Site and Drug Treatment
title_short Metabolic Heterogeneity in Patient Tumor-Derived Organoids by Primary Site and Drug Treatment
title_sort metabolic heterogeneity in patient tumor-derived organoids by primary site and drug treatment
topic Oncology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7242740/
https://www.ncbi.nlm.nih.gov/pubmed/32500020
http://dx.doi.org/10.3389/fonc.2020.00553
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