ArticleGenome medicine2017
Seed-effect modeling improves the consistency of genome-wide loss-of-function screens and identifies synthetic lethal vulnerabilities in cancer cells.
Article in Genome medicine, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.
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4 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Multi-modal meta-analysis of cancer cell line omics profiles identifies ECHDC1 as a novel breast tumor suppressor.Molecular systems biology · 2021Pooled it
- Combined gene essentiality scoring improves the prediction of cancer dependency maps.EBioMedicine · 2019Article
- TranscriptAchilles: a genome-wide platform to predict isoform biomarkers of gene essentiality in cancer.GigaScience · 2019Article
- Genomic technologies-from tools to therapies.Genome medicine · 2017Article
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7 authors.
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Abstract
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.
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