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Mapping the genetic landscape of human cells

ABSTRACT: Seminal yeast studies have established the value of comprehensively mapping genetic interactions (GIs) for inferring gene function. Efforts in human cells using focused gene sets underscore the utility of this approach, but the feasibility of generating large-scale, diverse human GI maps remains unresolved. We developed a CRISPR interference platform for large-scale quantitative mapping of human GIs. We systematically perturbed 222,784 gene pairs in two cancer cell lines. The resultant maps cluster functionally related genes, assigning function to poorly characterized genes, including TMEM261, a new electron transport chain component. Individual GIs pinpoint unexpected relationships between pathways, exemplified by a specific cholesterol biosynthesis intermediate whose accumulation induces deoxynucleotide depletion, causing replicative DNA damage and a synthetic-lethal interaction with the ATR/9-1-1 DNA repair pathway. Our map provides a broad resource, establishes GI maps as a high-resolution tool for dissecting gene function, and serves as a blueprint for mapping the genetic landscape of human cells.

ORGANISM(S): Homo sapiens

PROVIDER: GSE116198 | GEO | 2018/07/19

REPOSITORIES: GEO

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Project description:Aberrant activities of fourteen Eph receptor tyrosine kinases (RTKs) and their eight ephrin ligands are often observed in human malignancies, where they control cancer development, progression, and aggressiveness. While multiple attempts have been made to target Eph receptors in tumors, their effectiveness has been hindered by distinct contexts in which these proteins operate to enhance or suppress the disease. One of the strategies to overcoming this challenge is to define the molecular landscape/genetic interactions (GIs) associated with pro- and anti-malignant activities of Ephs and ephrins, as this should outline context-specific genetic dependencies associated with these molecules. Here, we used a multi-step bioinformatics analysis of the TCGA database and the DepMap gene essentiality data from cancer cell lines to construct a network of GIs of Ephs and ephrins in human malignancies. Validation of the relevance of this network was centered on an unusual Eph receptor EPHB6, which is innately kinase-incompetent, but nevertheless, actively controls aggressiveness and tumor initiation in several cancer types. To select the most relevant GI from the generated network, we performed genome-wide screening and EPHB6 BioID analysis. While, the BioID approach pointed towards EPHB6 interactions with several RTKs, including all kinase-active members of the EGFR/ErbB class, its integration with shRNA screening and computationally predicted GIs, unambiguously pointed towards EGFR as a key EPHB6 partner. Indeed, our further experiments confirmed EPHB6 interactions with all kinase-competent ErbBs, including EGFR, and revealed its ability to modulate EGF-induced EGFR tyrosine phosphorylation and downstream signaling. This ultimately, enhanced proliferation of cancer cells, culminating in efficient tumor development. In agreement, we found high levels of EGFR to positively correlate with higher EPHB6 expression in several tumor types. Taken together, these observations indicate that EPHB6 should serve as an effective target in tumors with high EGFR levels and that co-targeting these receptors might provide therapeutic benefits. More importantly, these experiments provide a strong support for the relevance of our computational strategy and suggest that the generated network describing GIs of Eph receptors and their ligands is a valuable resource that can be used for developing new treatment approaches aiming to hunt these proteins in human malignancies.

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Mapping the genetic landscape of human cells

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