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C-MORE: A high-content single-cell morphology recognition methodology for liquid biopsies toward personalized cardiovascular medicine
Cellular morphology has the capacity to serve as a surrogate for cellular state and functionality. However, primary cardiomyocytes, the standard model in cardiovascular research, are highly heterogeneous cells and therefore impose methodological challenges to analysis. Hence, we aimed to devise a ro...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8606902/ https://www.ncbi.nlm.nih.gov/pubmed/34841289 http://dx.doi.org/10.1016/j.xcrm.2021.100436 |
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author | Furkel, Jennifer Knoll, Maximilian Din, Shabana Bogert, Nicolai V. Seeger, Timon Frey, Norbert Abdollahi, Amir Katus, Hugo A. Konstandin, Mathias H. |
author_facet | Furkel, Jennifer Knoll, Maximilian Din, Shabana Bogert, Nicolai V. Seeger, Timon Frey, Norbert Abdollahi, Amir Katus, Hugo A. Konstandin, Mathias H. |
author_sort | Furkel, Jennifer |
collection | PubMed |
description | Cellular morphology has the capacity to serve as a surrogate for cellular state and functionality. However, primary cardiomyocytes, the standard model in cardiovascular research, are highly heterogeneous cells and therefore impose methodological challenges to analysis. Hence, we aimed to devise a robust methodology to deconvolute cardiomyocyte morphology on a single-cell level: C-MORE (cellular morphology recognition) is a workflow from bench to data analysis tailored for heterogeneous primary cells using our R package cmoRe. We demonstrate its utility in proof-of-principle applications such as modulation of canonical hypertrophy pathways and linkage of genotype-phenotype in human induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs). In our pilot study, exposure of cardiomyocytes to blood plasma prior to versus after aortic valve replacement allows identification of a disease fingerprint and reflects partial reversibility following therapeutic intervention. C-MORE is a valuable tool for cardiovascular research with possible fields of application in basic research and personalized medicine. |
format | Online Article Text |
id | pubmed-8606902 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-86069022021-11-26 C-MORE: A high-content single-cell morphology recognition methodology for liquid biopsies toward personalized cardiovascular medicine Furkel, Jennifer Knoll, Maximilian Din, Shabana Bogert, Nicolai V. Seeger, Timon Frey, Norbert Abdollahi, Amir Katus, Hugo A. Konstandin, Mathias H. Cell Rep Med Article Cellular morphology has the capacity to serve as a surrogate for cellular state and functionality. However, primary cardiomyocytes, the standard model in cardiovascular research, are highly heterogeneous cells and therefore impose methodological challenges to analysis. Hence, we aimed to devise a robust methodology to deconvolute cardiomyocyte morphology on a single-cell level: C-MORE (cellular morphology recognition) is a workflow from bench to data analysis tailored for heterogeneous primary cells using our R package cmoRe. We demonstrate its utility in proof-of-principle applications such as modulation of canonical hypertrophy pathways and linkage of genotype-phenotype in human induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs). In our pilot study, exposure of cardiomyocytes to blood plasma prior to versus after aortic valve replacement allows identification of a disease fingerprint and reflects partial reversibility following therapeutic intervention. C-MORE is a valuable tool for cardiovascular research with possible fields of application in basic research and personalized medicine. Elsevier 2021-11-03 /pmc/articles/PMC8606902/ /pubmed/34841289 http://dx.doi.org/10.1016/j.xcrm.2021.100436 Text en © 2021 The Authors https://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 | Article Furkel, Jennifer Knoll, Maximilian Din, Shabana Bogert, Nicolai V. Seeger, Timon Frey, Norbert Abdollahi, Amir Katus, Hugo A. Konstandin, Mathias H. C-MORE: A high-content single-cell morphology recognition methodology for liquid biopsies toward personalized cardiovascular medicine |
title | C-MORE: A high-content single-cell morphology recognition methodology for liquid biopsies toward personalized cardiovascular medicine |
title_full | C-MORE: A high-content single-cell morphology recognition methodology for liquid biopsies toward personalized cardiovascular medicine |
title_fullStr | C-MORE: A high-content single-cell morphology recognition methodology for liquid biopsies toward personalized cardiovascular medicine |
title_full_unstemmed | C-MORE: A high-content single-cell morphology recognition methodology for liquid biopsies toward personalized cardiovascular medicine |
title_short | C-MORE: A high-content single-cell morphology recognition methodology for liquid biopsies toward personalized cardiovascular medicine |
title_sort | c-more: a high-content single-cell morphology recognition methodology for liquid biopsies toward personalized cardiovascular medicine |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8606902/ https://www.ncbi.nlm.nih.gov/pubmed/34841289 http://dx.doi.org/10.1016/j.xcrm.2021.100436 |
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