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Systematic Identification of Novel Cancer Genes through Analysis of Deep shRNA Perturbation Screens

https://doi.org/10.1101/807248
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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

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Hallmarks of Cancer: The Next Generation
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Predicting Cancer-Specific Vulnerability via Data-Driven Detection of Synthetic Lethality
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Functional Genomic Landscape of Human Breast Cancer Drivers, Vulnerabilities, and Resistance
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Project DRIVE: A Compendium of Cancer Dependencies and Synthetic Lethal Relationships Uncovered by Large-Scale, Deep RNAi Screening
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Comprehensive Characterization of Cancer Driver Genes and Mutations
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Cell-of-Origin Patterns Dominate the Molecular Classification of 10,000 Tumors from 33 Types of Cancer
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Perspective on Oncogenic Processes at the End of the Beginning of Cancer Genomics
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Comprehensive Molecular Characterization of the Hippo Signaling Pathway in Cancer
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HMGA1 Expression in Human Hepatocellular Carcinoma Correlates with Poor Prognosis and Promotes Tumor Growth and Migration in in vitro Models
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MSC-Regulated MicroRNAs Converge on the Transcription Factor FOXP2 and Promote Breast Cancer Metastasis
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The Cancer Cell Line Encyclopedia enables predictive modelling of anticancer drug sensitivity
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Discovery and saturation analysis of cancer genes across 21 tumour types
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Improved estimation of cancer dependencies from large-scale RNAi screens using model-based normalization and data integration
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Next-generation characterization of the Cancer Cell Line Encyclopedia
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The landscape of cancer cell line metabolism
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Systematic investigation of genetic vulnerabilities across cancer cell lines reveals lineage-specific dependencies in ovarian cancer
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LRRC4, a Putative Tumor Suppressor Gene, Requires a Functional Leucine-rich Repeat Cassette Domain to Inhibit Proliferation of Glioma Cells In Vitro by Modulating the Extracellular Signal-regulated Kinase/Protein Kinase B/Nuclear Factor-κB Pathway
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ConsensusClusterPlus: a class discovery tool with confidence assessments and item tracking
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TCGAbiolinks: an R/Bioconductor package for integrative analysis of TCGA data
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g:Profiler: a web server for functional enrichment analysis and conversions of gene lists (2019 update)
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Discovery of synthetic lethal interactions from large-scale pan-cancer perturbation screens
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ATARiS: Computational quantification of gene suppression phenotypes from multisample RNAi screens
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Study of a Novel Brain Relatively Specific Gene LRRC4 Involved in Glioma Tumorigenesis Suppression Using the Tet-on System
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Essential Gene Profiles in Breast, Pancreatic, and Ovarian Cancer Cells
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Boolean implication networks derived from large scale, whole genome microarray datasets
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Intra-tumor genetic heterogeneity and alternative driver genetic alterations in breast cancers with heterogeneous HER2 gene amplification
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gespeR: a statistical model for deconvoluting off-target-confounded RNA interference screens
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Mining TCGA Data Using Boolean Implications
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Bcl-2 inhibition sensitizes triple-negative human breast cancer cells to doxorubicin
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Influence of doxorubicin on apoptosis and oxidative stress in breast cancer cell lines
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Structural Maintenance of Chromosomes protein 1: Role in Genome Stability and Tumorigenesis
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What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

inferred← citeshttps://doi.org/10.1038/s41598-023-42992-4openalex-snapshot
SL-scan identifies synthetic lethal interactions in cancer using metabolic networks
inferred← citeshttps://doi.org/10.1038/s41598-024-51453-5openalex-snapshot
Uncovering hidden cancer self-dependencies through analysis of shRNA-level dependency scores
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