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Cellular Metabolic Heterogeneity In Vivo Is Recapitulated in Tumor Organoids()

Heterogeneous populations within a tumor have varying metabolic profiles, which can muddle the interpretation of bulk tumor imaging studies of treatment response. Although methods to study tumor metabolism at the cellular level are emerging, these methods provide a single time point “snapshot” of tu...

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Autores principales: Sharick, Joe T., Jeffery, Justin J., Karim, Mohammad R., Walsh, Christine M., Esbona, Karla, Cook, Rebecca S., Skala, Melissa C.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Neoplasia Press 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6514366/
https://www.ncbi.nlm.nih.gov/pubmed/31078067
http://dx.doi.org/10.1016/j.neo.2019.04.004
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author Sharick, Joe T.
Jeffery, Justin J.
Karim, Mohammad R.
Walsh, Christine M.
Esbona, Karla
Cook, Rebecca S.
Skala, Melissa C.
author_facet Sharick, Joe T.
Jeffery, Justin J.
Karim, Mohammad R.
Walsh, Christine M.
Esbona, Karla
Cook, Rebecca S.
Skala, Melissa C.
author_sort Sharick, Joe T.
collection PubMed
description Heterogeneous populations within a tumor have varying metabolic profiles, which can muddle the interpretation of bulk tumor imaging studies of treatment response. Although methods to study tumor metabolism at the cellular level are emerging, these methods provide a single time point “snapshot” of tumor metabolism and require a significant time and animal burden while failing to capture the longitudinal metabolic response of a single tumor to treatment. Here, we investigated a novel method for longitudinal, single-cell tracking of metabolism across heterogeneous tumor cell populations using optical metabolic imaging (OMI), which measures autofluorescence of metabolic coenzymes as a report of metabolic activity. We also investigated whether in vivo cellular metabolic heterogeneity can be accurately captured using tumor-derived three-dimensional organoids in a genetically engineered mouse model of breast cancer. OMI measurements of response to paclitaxel and the phosphatidylinositol-3-kinase inhibitor XL147 in tumors and organoids taken at single cell resolution revealed parallel shifts in metaboltruic heterogeneity. Interestingly, these previously unappreciated heterogeneous metabolic responses in tumors and organoids could not be attributed to tumor cell fate or varying leukocyte content within the microenvironment, suggesting that heightened metabolic heterogeneity upon treatment is largely due to heterogeneous metabolic shifts within tumor cells. Together, these studies show that OMI revealed remarkable heterogeneity in response to treatment, which could provide a novel approach to predict the presence of potentially unresponsive tumor cell subpopulations lurking within a largely responsive bulk tumor population, which might otherwise be overlooked by traditional measurements.
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spelling pubmed-65143662019-05-28 Cellular Metabolic Heterogeneity In Vivo Is Recapitulated in Tumor Organoids() Sharick, Joe T. Jeffery, Justin J. Karim, Mohammad R. Walsh, Christine M. Esbona, Karla Cook, Rebecca S. Skala, Melissa C. Neoplasia Original article Heterogeneous populations within a tumor have varying metabolic profiles, which can muddle the interpretation of bulk tumor imaging studies of treatment response. Although methods to study tumor metabolism at the cellular level are emerging, these methods provide a single time point “snapshot” of tumor metabolism and require a significant time and animal burden while failing to capture the longitudinal metabolic response of a single tumor to treatment. Here, we investigated a novel method for longitudinal, single-cell tracking of metabolism across heterogeneous tumor cell populations using optical metabolic imaging (OMI), which measures autofluorescence of metabolic coenzymes as a report of metabolic activity. We also investigated whether in vivo cellular metabolic heterogeneity can be accurately captured using tumor-derived three-dimensional organoids in a genetically engineered mouse model of breast cancer. OMI measurements of response to paclitaxel and the phosphatidylinositol-3-kinase inhibitor XL147 in tumors and organoids taken at single cell resolution revealed parallel shifts in metaboltruic heterogeneity. Interestingly, these previously unappreciated heterogeneous metabolic responses in tumors and organoids could not be attributed to tumor cell fate or varying leukocyte content within the microenvironment, suggesting that heightened metabolic heterogeneity upon treatment is largely due to heterogeneous metabolic shifts within tumor cells. Together, these studies show that OMI revealed remarkable heterogeneity in response to treatment, which could provide a novel approach to predict the presence of potentially unresponsive tumor cell subpopulations lurking within a largely responsive bulk tumor population, which might otherwise be overlooked by traditional measurements. Neoplasia Press 2019-05-09 /pmc/articles/PMC6514366/ /pubmed/31078067 http://dx.doi.org/10.1016/j.neo.2019.04.004 Text en © 2019 The Authors http://creativecommons.org/licenses/by-nc-nd/4.0/ This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Original article
Sharick, Joe T.
Jeffery, Justin J.
Karim, Mohammad R.
Walsh, Christine M.
Esbona, Karla
Cook, Rebecca S.
Skala, Melissa C.
Cellular Metabolic Heterogeneity In Vivo Is Recapitulated in Tumor Organoids()
title Cellular Metabolic Heterogeneity In Vivo Is Recapitulated in Tumor Organoids()
title_full Cellular Metabolic Heterogeneity In Vivo Is Recapitulated in Tumor Organoids()
title_fullStr Cellular Metabolic Heterogeneity In Vivo Is Recapitulated in Tumor Organoids()
title_full_unstemmed Cellular Metabolic Heterogeneity In Vivo Is Recapitulated in Tumor Organoids()
title_short Cellular Metabolic Heterogeneity In Vivo Is Recapitulated in Tumor Organoids()
title_sort cellular metabolic heterogeneity in vivo is recapitulated in tumor organoids()
topic Original article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6514366/
https://www.ncbi.nlm.nih.gov/pubmed/31078067
http://dx.doi.org/10.1016/j.neo.2019.04.004
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