Consistency in drug response profiling

Mpindi, John Patrick; Yadav, Bhagwan; Östling, Päivi; Gautam, Prson; Malani, Disha; Murumägi, Astrid; Hirasawa, Akira; Kangaspeska, Sara; Wennerberg, Krister; Kallioniemi, Olli; Aittokallio, Tero

doi:10.1038/nature20171

Cited by 79 publications

(84 citation statements)

References 10 publications

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“…However, follow-up analyses demonstrated that when robust response calculations are used, and when the evaluation metrics are aligned with the objectives of the functional profiling, acceptable consistency can be achieved, provided that the screening assays and experimental protocols are similar enough [60–62]. Off-target effects have also been observed with the CRISPR/Cas9 system [63], making these lessons likely useful also for improving future CRISPR/Cas9 study designs.…”

Section: Discussionmentioning

confidence: 99%

Seed-effect modeling improves the consistency of genome-wide loss-of-function screens and identifies synthetic lethal vulnerabilities in cancer cells

et al. 2017

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BackgroundGenome-wide loss-of-function profiling is widely used for systematic identification of genetic dependencies in cancer cells; however, the poor reproducibility of RNA interference (RNAi) screens has been a major concern due to frequent off-target effects. Currently, a detailed understanding of the key factors contributing to the sub-optimal consistency is still a lacking, especially on how to improve the reliability of future RNAi screens by controlling for factors that determine their off-target propensity.MethodsWe performed a systematic, quantitative analysis of the consistency between two genome-wide shRNA screens conducted on a compendium of cancer cell lines, and also compared several gene summarization methods for inferring gene essentiality from shRNA level data. We then devised novel concepts of seed essentiality and shRNA family, based on seed region sequences of shRNAs, to study in-depth the contribution of seed-mediated off-target effects to the consistency of the two screens. We further investigated two seed-sequence properties, seed pairing stability, and target abundance in terms of their capability to minimize the off-target effects in post-screening data analysis. Finally, we applied this novel methodology to identify genetic interactions and synthetic lethal partners of cancer drivers, and confirmed differential essentiality phenotypes by detailed CRISPR/Cas9 experiments.ResultsUsing the novel concepts of seed essentiality and shRNA family, we demonstrate how genome-wide loss-of-function profiling of a common set of cancer cell lines can be actually made fairly reproducible when considering seed-mediated off-target effects. Importantly, by excluding shRNAs having higher propensity for off-target effects, based on their seed-sequence properties, one can remove noise from the genome-wide shRNA datasets. As a translational application case, we demonstrate enhanced reproducibility of genetic interaction partners of common cancer drivers, as well as identify novel synthetic lethal partners of a major oncogenic driver, PIK3CA, supported by a complementary CRISPR/Cas9 experiment.ConclusionsWe provide practical guidelines for improved design and analysis of genome-wide loss-of-function profiling and demonstrate how this novel strategy can be applied towards improved mapping of genetic dependencies of cancer cells to aid development of targeted anticancer treatments.Electronic supplementary materialThe online version of this article (doi:10.1186/s13073-017-0440-2) contains supplementary material, which is available to authorized users.

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Section: Discussionmentioning

confidence: 99%

Seed-effect modeling improves the consistency of genome-wide loss-of-function screens and identifies synthetic lethal vulnerabilities in cancer cells

et al. 2017

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“…Previous literature on reproducibility highlighted the importance of considering agreement along both the perturbation and cell line axes of the data [23][24][25] . We assembled a combined dataset of cell line dependency profiles from both studies and computed all possible pairwise correlation distances between them, using genes that were dependencies in at least one cell line ( variable genes).…”

Section: Agreement Of Cell Line Dependency Profilesmentioning

confidence: 99%

Agreement between two large pan-cancer CRISPR-Cas9 gene dependency datasets

Dempster

Pacini

Pantel

et al. 2019

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AbstractGenome-scale CRISPR-Cas9 viability screens performed in cancer cell lines provide a systematic approach to identify cancer dependencies and new therapeutic targets. As multiple large-scale screens become available, a formal assessment of the reproducibility of these experiments becomes necessary. We analyzed data from recently published pan-cancer CRISPR-Cas9 screens performed at the Broad and Sanger institutes. Despite significant differences in experimental protocols and reagents, we found that the screen results are highly concordant across multiple metrics with both common and specific dependencies jointly identified across the two studies. Furthermore, robust biomarkers of gene dependency found in one dataset are recovered in the other. Through further analysis and replication experiments at each institute, we found that batch effects are driven principally by two key experimental parameters: the reagent library and the assay length. These results indicate that the Broad and Sanger CRISPR-Cas9 viability screens yield robust and reproducible findings.

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“…One involved a large collaborative project that I led for nearly a decade -the Cancer Cell Line Encyclopedia. Reported inconsistencies with a related project, called the Genomics of Drug Sensitivity in Cancer, prompted intense, clarifying discussions on precisely how measurements are taken and on what sorts of data give the best insights for developing therapies [4][5][6][7][8][9][10][11][12][13][14][15] .…”

Section: Robustnessmentioning

confidence: 99%