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

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http://hdl.handle.net/10138/199202

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Jaiswal , A , Peddinti , G , Akimov , Y , Wennerberg , K , Kuznetsov , S , Tang , J & Aittokallio , T 2017 , ' Seed-effect modeling improves the consistency of genome-wide loss-of-function screens and identifies synthetic lethal vulnerabilities in cancer cells ' , Genome medicine , vol. 9 , 51 . https://doi.org/10.1186/s13073-017-0440-2

Title: Seed-effect modeling improves the consistency of genome-wide loss-of-function screens and identifies synthetic lethal vulnerabilities in cancer cells
Author: Jaiswal, Alok; Peddinti, Gopal; Akimov, Yevhen; Wennerberg, Krister; Kuznetsov, Sergey; Tang, Jing; Aittokallio, Tero
Contributor: University of Helsinki, Institute for Molecular Medicine Finland
University of Helsinki, Institute for Molecular Medicine Finland
University of Helsinki, Institute for Molecular Medicine Finland
University of Helsinki, Institute for Molecular Medicine Finland
University of Helsinki, Institute for Molecular Medicine Finland
University of Helsinki, Institute for Molecular Medicine Finland
University of Helsinki, Institute for Molecular Medicine Finland
Date: 2017-06-01
Language: eng
Number of pages: 15
Belongs to series: Genome medicine
ISSN: 1756-994X
URI: http://hdl.handle.net/10138/199202
Abstract: Background: Genome-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. Methods: We 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. Results: Using 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. Conclusions: We 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.
Subject: RNAi screening
Gene essentiality
Seed essentiality
Off-target effects
Reproducibility
Seed effects
Synthetic lethality
Cancer cells
Precision oncology
RNA INTERFERENCE SCREENS
BREAST-CANCER
OVARIAN-CANCER
PI3K PATHWAY
GENE
REVEALS
CRISPR-CAS9
SUPPRESSION
DEPENDENCIES
CRISPR/CAS9
3111 Biomedicine
1184 Genetics, developmental biology, physiology
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