Comprehensive and unbiased multiparameter high-throughput screening by compaRe finds effective and subtle drug responses in AML models Journal Article


Authors: Hajkarim, M. C.; Karjalainen, E.; Osipovitch, M.; Dimopoulos, K.; Gordon, S.; Ambri, F.; Rasmussen, K. D.; Grønbæk, K.; Helin, K.; Wennerberg, K.; Won, K. J.
Article Title: Comprehensive and unbiased multiparameter high-throughput screening by compaRe finds effective and subtle drug responses in AML models
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. © 2022, eLife Sciences Publications Ltd. All rights reserved.
Keywords: signal transduction; cancer chemotherapy; controlled study; lenalidomide; nonhuman; flow cytometry; quality control; animal cell; mouse; phenotype; animal tissue; cell viability; cluster analysis; animal experiment; animal model; vincristine; cell differentiation; cytotoxicity; high throughput screening; simulation; myelodysplastic syndrome; immune response; algorithm; cd4+ t lymphocyte; immunophenotyping; upregulation; interleukin 17; nilotinib; fluorescence activated cell sorting; retinoic acid; feces analysis; colony forming unit; head and neck squamous cell carcinoma; acute myeloid leukemia; trametinib; mapk signaling; human; article; copanlisib; tazemetostat; mass cytometry; birabresib; molibresib
Journal Title: eLife
Volume: 11
ISSN: 2050-084X
Publisher: eLife Sciences Publications Ltd.  
Date Published: 2022-02-15
Start Page: e73760
Language: English
DOI: 10.7554/elife.73760
PUBMED: 35166670
PROVIDER: scopus
PMCID: PMC9020823
DOI/URL:
Notes: Article -- Export Date: 1 April 2022 -- Source: Scopus
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  1. Kristian Helin
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