Comprehensive and unbiased multiparameter high-throughput screening by compaRe finds effective and subtle drug responses in AML models
- University of Copenhagen, Denmark
- University of Helsinki, Finland
- Rigshospitalet, Denmark
- University of Dundee, United Kingdom
- Memorial Sloan Kettering Cancer Center, United States
Abstract
Large-scale multiparameter screening has become increasingly feasible and straightforward to perform thanks to developments in technologies such as high-content microscopy and high-throughput flow cytometry. The automated toolkits for analyzing similarities and differences between large numbers of tested conditions have not kept pace with these technological developments. Thus, effective analysis of multiparameter screening datasets becomes a bottleneck and a limiting factor in unbiased interpretation of results. Here we introduce compaRe, a toolkit for large-scale multiparameter data analysis, which integrates quality control, data bias correction, and data visualization methods with a mass-aware gridding algorithm-based similarity analysis providing a much faster and more robust analyses than existing methods. Using mass and flow cytometry data from acute myeloid leukemia and myelodysplastic syndrome patients, we show that compaRe can reveal interpatient heterogeneity and recognizable phenotypic profiles. By applying compaRe to high-throughput flow cytometry drug response data in AML models, we robustly identified multiple types of both deep and subtle phenotypic response patterns, highlighting how this analysis could be used for therapeutic discoveries. In conclusion, compaRe is a toolkit that uniquely allows for automated, rapid, and precise comparisons of large-scale multiparameter datasets, including high-throughput screens.
Data availability
Mass cytometry datasets were downloaded from Cytobank Community with the experiment ID 44185. AML mouse and human high-throughput flow cytometry data have been deposited in FLOWRepository with the repository IDs FR-FCM-Z357 and FR-FCM-Z3DP respectively. Flow cytometry data of AML and MDS patients have been deposited in FLOWRepository with the repository ID FR-FCM-Z3ET. Acquisition, installation and more technical details are available in compaRe's online tutorial on (https://github.com/morchalabi/COMPARE-suite). Similarity measurement and clustering modules as stand-alone tools have been merged into a separate R package and are available for download at (https://github.com/morchalabi/compaRe).
Article and author information
Author details
Morteza Chalabi Hajkarim
Krister Wennerberg
Funding
Novo Nordisk Foundation center for Stem Cell Biology (NNF17CC0027852)
- Kirsten Grønbæk
- Kristian Helin
- Krister Wennerberg
- Kyoung-Jae Won
Kræftens Bekæmpelse (R223‐A13071)
- Kirsten Grønbæk
- Kristian Helin
- Krister Wennerberg
- Kyoung-Jae Won
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Ethics
Human subjects: The informed consent, and consent to publish of patient samples in this study has been approved by the Danish National Science Ethics Committee/National Videnskabsetisk Komite: Målrettet behandling af patienter med blodsygdomme, license no. 1705391.
Copyright
© 2022, Chalabi Hajkarim et al.
This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.
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Comprehensive and unbiased multiparameter high-throughput screening by compaRe finds effective and subtle drug responses in AML models
eLife 11:e73760.
https://doi.org/10.7554/eLife.73760
