High-throughput approaches to uncover synergistic drug combinations in leukemia

Emma J. Chory; Meng Wang; Michele Ceribelli; Aleksandra M. Michalowska; Stefan Golas; Erin Beck; Carleen Klumpp-Thomas; Lu Chen; Crystal McKnight; Zina Itkin; Kelli M. Wilson; David Holland; Sanjay Divakaran; James Bradner; Javed Khan; Berkley E. Gryder; Craig J. Thomas; Benjamin Z. Stanton

doi:10.1016/j.slasd.2023.04.004

High-throughput approaches to uncover synergistic drug combinations in leukemia

Emma J. Chory, Meng Wang, Michele Ceribelli, Aleksandra M. Michalowska, Stefan Golas, Erin Beck, Carleen Klumpp-Thomas, Lu Chen, Crystal McKnight, Zina Itkin, Kelli M. Wilson, David Holland, Sanjay Divakaran, James Bradner, Javed Khan, Berkley E. Gryder, Craig J. Thomas, Benjamin Z. Stanton

Research output: Contribution to journal › Article › peer-review

5 Scopus citations

Abstract

We report a comprehensive drug synergy study in acute myeloid leukemia (AML). In this work, we investigate a panel of cell lines spanning both MLL-rearranged and non-rearranged subtypes. The work comprises a resource for the community, with many synergistic drug combinations that could not have been predicted a priori, and open source code for automation and analyses. We base our definitions of drug synergy on the Chou-Talalay method, which is useful for visualizations of synergy experiments in isobolograms, and median-effects plots, among other representations. Our key findings include drug synergies affecting the chromatin state, specifically in the context of regulation of the modification state of histone H3 lysine-27. We report open source high throughput methodology such that multidimensional drug screening can be accomplished with equipment that is accessible to most laboratories. This study will enable preclinical investigation of new drug combinations in a lethal blood cancer, with data analysis and automation workflows freely available to the community.

Original language	English
Pages (from-to)	193-201
Number of pages	9
Journal	SLAS Discovery
Volume	28
Issue number	4
DOIs	https://doi.org/10.1016/j.slasd.2023.04.004
State	Published - Jun 2023
Externally published	Yes

Keywords

Acute myeloid leukemia
Combination index
Combination therapy
Epigenetics
Open-source automation
Precision medicine
Synergy

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10.1016/j.slasd.2023.04.004

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Chory, E. J., Wang, M., Ceribelli, M., Michalowska, A. M., Golas, S., Beck, E., Klumpp-Thomas, C., Chen, L., McKnight, C., Itkin, Z., Wilson, K. M., Holland, D., Divakaran, S., Bradner, J., Khan, J., Gryder, B. E., Thomas, C. J., & Stanton, B. Z. (2023). High-throughput approaches to uncover synergistic drug combinations in leukemia. SLAS Discovery, 28(4), 193-201. https://doi.org/10.1016/j.slasd.2023.04.004

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title = "High-throughput approaches to uncover synergistic drug combinations in leukemia",

abstract = "We report a comprehensive drug synergy study in acute myeloid leukemia (AML). In this work, we investigate a panel of cell lines spanning both MLL-rearranged and non-rearranged subtypes. The work comprises a resource for the community, with many synergistic drug combinations that could not have been predicted a priori, and open source code for automation and analyses. We base our definitions of drug synergy on the Chou-Talalay method, which is useful for visualizations of synergy experiments in isobolograms, and median-effects plots, among other representations. Our key findings include drug synergies affecting the chromatin state, specifically in the context of regulation of the modification state of histone H3 lysine-27. We report open source high throughput methodology such that multidimensional drug screening can be accomplished with equipment that is accessible to most laboratories. This study will enable preclinical investigation of new drug combinations in a lethal blood cancer, with data analysis and automation workflows freely available to the community.",

keywords = "Acute myeloid leukemia, Combination index, Combination therapy, Epigenetics, Open-source automation, Precision medicine, Synergy",

author = "Chory, {Emma J.} and Meng Wang and Michele Ceribelli and Michalowska, {Aleksandra M.} and Stefan Golas and Erin Beck and Carleen Klumpp-Thomas and Lu Chen and Crystal McKnight and Zina Itkin and Wilson, {Kelli M.} and David Holland and Sanjay Divakaran and James Bradner and Javed Khan and Gryder, {Berkley E.} and Thomas, {Craig J.} and Stanton, {Benjamin Z.}",

note = "Publisher Copyright: {\textcopyright} 2023 The Author(s)",

year = "2023",

month = jun,

doi = "10.1016/j.slasd.2023.04.004",

language = "English",

volume = "28",

pages = "193--201",

journal = "SLAS Discovery",

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Chory, EJ, Wang, M, Ceribelli, M, Michalowska, AM, Golas, S, Beck, E, Klumpp-Thomas, C, Chen, L, McKnight, C, Itkin, Z, Wilson, KM, Holland, D, Divakaran, S, Bradner, J, Khan, J, Gryder, BE, Thomas, CJ & Stanton, BZ 2023, 'High-throughput approaches to uncover synergistic drug combinations in leukemia', SLAS Discovery, vol. 28, no. 4, pp. 193-201. https://doi.org/10.1016/j.slasd.2023.04.004

TY - JOUR

T1 - High-throughput approaches to uncover synergistic drug combinations in leukemia

AU - Chory, Emma J.

AU - Wang, Meng

AU - Ceribelli, Michele

AU - Michalowska, Aleksandra M.

AU - Golas, Stefan

AU - Beck, Erin

AU - Klumpp-Thomas, Carleen

AU - Chen, Lu

AU - McKnight, Crystal

AU - Itkin, Zina

AU - Wilson, Kelli M.

AU - Holland, David

AU - Divakaran, Sanjay

AU - Bradner, James

AU - Khan, Javed

AU - Gryder, Berkley E.

AU - Thomas, Craig J.

AU - Stanton, Benjamin Z.

PY - 2023/6

Y1 - 2023/6

N2 - We report a comprehensive drug synergy study in acute myeloid leukemia (AML). In this work, we investigate a panel of cell lines spanning both MLL-rearranged and non-rearranged subtypes. The work comprises a resource for the community, with many synergistic drug combinations that could not have been predicted a priori, and open source code for automation and analyses. We base our definitions of drug synergy on the Chou-Talalay method, which is useful for visualizations of synergy experiments in isobolograms, and median-effects plots, among other representations. Our key findings include drug synergies affecting the chromatin state, specifically in the context of regulation of the modification state of histone H3 lysine-27. We report open source high throughput methodology such that multidimensional drug screening can be accomplished with equipment that is accessible to most laboratories. This study will enable preclinical investigation of new drug combinations in a lethal blood cancer, with data analysis and automation workflows freely available to the community.

AB - We report a comprehensive drug synergy study in acute myeloid leukemia (AML). In this work, we investigate a panel of cell lines spanning both MLL-rearranged and non-rearranged subtypes. The work comprises a resource for the community, with many synergistic drug combinations that could not have been predicted a priori, and open source code for automation and analyses. We base our definitions of drug synergy on the Chou-Talalay method, which is useful for visualizations of synergy experiments in isobolograms, and median-effects plots, among other representations. Our key findings include drug synergies affecting the chromatin state, specifically in the context of regulation of the modification state of histone H3 lysine-27. We report open source high throughput methodology such that multidimensional drug screening can be accomplished with equipment that is accessible to most laboratories. This study will enable preclinical investigation of new drug combinations in a lethal blood cancer, with data analysis and automation workflows freely available to the community.

KW - Acute myeloid leukemia

KW - Combination index

KW - Combination therapy

KW - Epigenetics

KW - Open-source automation

KW - Precision medicine

KW - Synergy

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U2 - 10.1016/j.slasd.2023.04.004

DO - 10.1016/j.slasd.2023.04.004

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AN - SCOPUS:85158832002

SN - 2472-5552

VL - 28

SP - 193

EP - 201

JO - SLAS Discovery

JF - SLAS Discovery

IS - 4

ER -

High-throughput approaches to uncover synergistic drug combinations in leukemia

Abstract

Keywords

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