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A pipeline for malignancy and therapy agnostic assessment of cancer drug response using cell mass measurements
Functional precision medicine offers a promising complement to genomics-based cancer therapy guidance by testing drug efficacy directly on a patient’s tumor cells. Here, we describe a workflow that utilizes single-cell mass measurements with inline brightfield imaging and machine-learning based imag...
Autores principales: | , , , , , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9701192/ https://www.ncbi.nlm.nih.gov/pubmed/36435843 http://dx.doi.org/10.1038/s42003-022-04270-3 |
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author | Kimmerling, Robert J. Stevens, Mark M. Olcum, Selim Minnah, Anthony Vacha, Madeleine LaBella, Rachel Ferri, Matthew Wasserman, Steven C. Fujii, Juanita Shaheen, Zayna Sundaresan, Srividya Ribadeneyra, Drew Jayabalan, David S. Agte, Sarita Aleman, Adolfo Criscitiello, Joseph A. Niesvizky, Ruben Luskin, Marlise R. Parekh, Samir Rosenbaum, Cara A. Tamrazi, Anobel Reid, Clifford A. |
author_facet | Kimmerling, Robert J. Stevens, Mark M. Olcum, Selim Minnah, Anthony Vacha, Madeleine LaBella, Rachel Ferri, Matthew Wasserman, Steven C. Fujii, Juanita Shaheen, Zayna Sundaresan, Srividya Ribadeneyra, Drew Jayabalan, David S. Agte, Sarita Aleman, Adolfo Criscitiello, Joseph A. Niesvizky, Ruben Luskin, Marlise R. Parekh, Samir Rosenbaum, Cara A. Tamrazi, Anobel Reid, Clifford A. |
author_sort | Kimmerling, Robert J. |
collection | PubMed |
description | Functional precision medicine offers a promising complement to genomics-based cancer therapy guidance by testing drug efficacy directly on a patient’s tumor cells. Here, we describe a workflow that utilizes single-cell mass measurements with inline brightfield imaging and machine-learning based image classification to broaden the clinical utility of such functional testing for cancer. Using these image-curated mass measurements, we characterize mass response signals for 60 different drugs with various mechanisms of action across twelve different cell types, demonstrating an improved ability to detect response for several slow acting drugs as compared with standard cell viability assays. Furthermore, we use this workflow to assess drug responses for various primary tumor specimen formats including blood, bone marrow, fine needle aspirates (FNA), and malignant fluids, all with reports generated within two days and with results consistent with patient clinical responses. The combination of high-resolution measurement, broad drug and malignancy applicability, and rapid return of results offered by this workflow suggests that it is well-suited to performing clinically relevant functional assessment of cancer drug response. |
format | Online Article Text |
id | pubmed-9701192 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-97011922022-11-28 A pipeline for malignancy and therapy agnostic assessment of cancer drug response using cell mass measurements Kimmerling, Robert J. Stevens, Mark M. Olcum, Selim Minnah, Anthony Vacha, Madeleine LaBella, Rachel Ferri, Matthew Wasserman, Steven C. Fujii, Juanita Shaheen, Zayna Sundaresan, Srividya Ribadeneyra, Drew Jayabalan, David S. Agte, Sarita Aleman, Adolfo Criscitiello, Joseph A. Niesvizky, Ruben Luskin, Marlise R. Parekh, Samir Rosenbaum, Cara A. Tamrazi, Anobel Reid, Clifford A. Commun Biol Article Functional precision medicine offers a promising complement to genomics-based cancer therapy guidance by testing drug efficacy directly on a patient’s tumor cells. Here, we describe a workflow that utilizes single-cell mass measurements with inline brightfield imaging and machine-learning based image classification to broaden the clinical utility of such functional testing for cancer. Using these image-curated mass measurements, we characterize mass response signals for 60 different drugs with various mechanisms of action across twelve different cell types, demonstrating an improved ability to detect response for several slow acting drugs as compared with standard cell viability assays. Furthermore, we use this workflow to assess drug responses for various primary tumor specimen formats including blood, bone marrow, fine needle aspirates (FNA), and malignant fluids, all with reports generated within two days and with results consistent with patient clinical responses. The combination of high-resolution measurement, broad drug and malignancy applicability, and rapid return of results offered by this workflow suggests that it is well-suited to performing clinically relevant functional assessment of cancer drug response. Nature Publishing Group UK 2022-11-26 /pmc/articles/PMC9701192/ /pubmed/36435843 http://dx.doi.org/10.1038/s42003-022-04270-3 Text en © The Author(s) 2022, corrected publication 2023 https://creativecommons.org/licenses/by/4.0/Open Access This 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 license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license 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 license, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Kimmerling, Robert J. Stevens, Mark M. Olcum, Selim Minnah, Anthony Vacha, Madeleine LaBella, Rachel Ferri, Matthew Wasserman, Steven C. Fujii, Juanita Shaheen, Zayna Sundaresan, Srividya Ribadeneyra, Drew Jayabalan, David S. Agte, Sarita Aleman, Adolfo Criscitiello, Joseph A. Niesvizky, Ruben Luskin, Marlise R. Parekh, Samir Rosenbaum, Cara A. Tamrazi, Anobel Reid, Clifford A. A pipeline for malignancy and therapy agnostic assessment of cancer drug response using cell mass measurements |
title | A pipeline for malignancy and therapy agnostic assessment of cancer drug response using cell mass measurements |
title_full | A pipeline for malignancy and therapy agnostic assessment of cancer drug response using cell mass measurements |
title_fullStr | A pipeline for malignancy and therapy agnostic assessment of cancer drug response using cell mass measurements |
title_full_unstemmed | A pipeline for malignancy and therapy agnostic assessment of cancer drug response using cell mass measurements |
title_short | A pipeline for malignancy and therapy agnostic assessment of cancer drug response using cell mass measurements |
title_sort | pipeline for malignancy and therapy agnostic assessment of cancer drug response using cell mass measurements |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9701192/ https://www.ncbi.nlm.nih.gov/pubmed/36435843 http://dx.doi.org/10.1038/s42003-022-04270-3 |
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