Uncovering Hidden Cancer Self-Dependencies through Analysis of shRNA-Level Dependency Scores

Abstract

Large-scale short hairpin RNA (shRNA) screens on well-characterized human cancer cell lines have been widely used to identify novel cancer dependencies. However, the off-target effects of shRNA reagents pose a significant challenge in the analysis of these screens. To mitigate these off-target effects, various approaches have been proposed that aggregate different shRNA viability scores targeting a gene into a single gene-level viability score. Most computational methods for discovering cancer dependencies rely on these gene-level scores. In this paper, we propose a computational method, named NBDep, to find cancer self-dependencies by directly analyzing shRNA-level dependency scores instead of gene-level scores. The NBDep algorithm begins by removing known batch effects of the shRNAs and selecting a subset of concordant shRNAs for each gene. It then uses negative binomial random effects models to statistically assess the dependency between genetic alterations and the viabilities of cell lines by incorporating all shRNA dependency scores of each gene into the model. We applied NBDep to the shRNA dependency scores available at Project DRIVE, which covers 26 different types of cancer. The proposed method identified more well-known and putative cancer genes compared to alternative gene-level approaches in pan-cancer and cancer-specific analyses. Additionally, we demonstrated that NBDep controls type-I error and outperforms statistical tests based on gene-level scores in simulation studies.

Pathway-driven analysis of synthetic lethal interactions in cancer using perturbation screens

“…However, the limitations of computational algorithms used to calculate these scores could affect the accuracy of our results. Further research is required to refine existing reagent-level computational frameworks ( Allen et al, 2019 ; Toghrayee & Montazeri, 2023 Preprint ) such that they account for pathway information for finding cancer dependencies. Fourthly, our approach solely focused on individual components of signaling pathways to determine whether any alterations had occurred.…”