Interrogation of Functional Cell-Surface Markers Identifies CD151 Dependency in High-Grade Serous Ovarian Cancer

Medrano, Mauricio; Communal, Laudine; Brown, Kevin R.; Iwanicki, Marcin P.; Normand, Josee; Paterson, Joshua; Sircoulomb, Fabrice; Krzyzanowski, Paul M.; Novak, Marián; Doodnauth, Sasha A.; Suárez, Fernando; Cullis, Jane; Al‐awar, Rima; Neel, Benjamin G.; Mcpherson, John Douglas; Drapkin, Ronny; Ailles, Laurie; Mes-Masson, Anne-Marie; Rottapel, Robert

doi:10.1016/j.celrep.2017.02.028

Cited by 40 publications

(38 citation statements)

References 56 publications

(63 reference statements)

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“…We considered CRISPR and shRNA whole-genome screen data from multiple libraries and laboratories (Avana (Doench et al, 2014;Meyers et al, 2017), GeCKOv2 (Aguirre et al, 2016), TKO (Hart et al, 2015Steinhart et al, 2017), Sabatini (Wang et al, 2014 the Moffat shRNA library Marcotte et al, 2012Marcotte et al, , 2016Medrano et al, 2017)) and other large data sets (McDonald et al, 2017;Tsherniak et al, 2017) (Figure 1a and Supplementary Table 1). From raw read count data, we used the BAGEL pipeline (described in (Hart and Moffat, 2016) and improved here; see Supplementary Methods) to generate Bayes Factors for each gene in each cell line.…”

Section: Resultsmentioning

confidence: 99%

Hierarchical organization of the human cell from a cancer coessentiality network

Dede

Lenoir

Wang

et al. 2018

Preprint

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Genetic interactions mediate the emergence of phenotype from genotype. Systematic survey of genetic interactions in yeast showed that genes operating in the same biological process have highly correlated genetic interaction profiles, and this observation has been exploited to infer gene function in model organisms. Systematic surveys of digenic perturbations in human cells are also highly informative, but are not scalable, even with CRISPR-mediated methods. As an alternative, we developed an indirect method of deriving functional interactions. We show that genes having correlated knockout fitness profiles across diverse, non-isogenic cell lines are analogous to genes having correlated genetic interaction profiles across isogenic query strains, and similarly implies shared biological function. We constructed a network of genes with correlated fitness profiles across 400 CRISPR knockout screens in cancer cell lines into a "coessentiality network," with up to 500-fold enrichment for co-functional gene pairs, enabling strong inference of human gene function. Modules in the network are connected in a layered web that gives insight into the hierarchical organization of the cell.

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Section: Resultsmentioning

confidence: 99%

Hierarchical organization of the human cell from a cancer coessentiality network

Dede

Lenoir

Wang

et al. 2018

Preprint

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“…To determine C/EBPδ basal expression levels across ovarian (n=42) and breast cancer (n=54) cell lines, we used publically available RNA-sequence data from Medrano et al (Medrano, Communal et al 2017). The data uniformly showed higher C/EBPδ mRNA levels were associated with lower proliferation rates across breast and ovarian cancer cell lines ( Figure 3A-B).…”

Section: Breast and Ovarian Cancer Cell Linesmentioning

confidence: 99%

C/EBPδ demonstrates a dichotomous role in tumor initiation and promotion of epithelial carcinoma

Sowamber

Chehade

Bitar

et al. 2019

Preprint

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High Grade Serous Ovarian Cancer (HGSC) originates primarily from the fallopian tube epithelia. It is postulated that pre-malignant cells can migrate and implant onto the surface of the ovary. We previously reported that genes differentially expressed in the ovulatory phase can predispose the fallopian tube epithelia to transformation. Since ovulation is frequent, we hypothesize that C/EBPδ, a gene expressed in the luteal phase, can modulate the transformation of p53-mutated fallopian tube epithelial cells. Here, we show significantly decreased expression of C/EBPδ in HGSC compared to normal fallopian tube epithelia. We demonstrate that C/EBPδ, lost early during disease progression, is associated with a mesenchymal phenotype in normal fallopian tube epithelia. However, in a subset of HGSC, C/EBPδ expression is maintained. This pre-malignant subset of cells, that express C/EBPδ, promotes a mesenchymal to epithelial transition and promotes migration in the context of p53 mutation. While C/EBPδ over-expression induces cellular characteristics conducive to an EMT-MET switch, it also behaves as a tumor-suppressor, inhibiting cell cycle progression, indicative of its complex role in the pathogenesis of the disease.

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“…To this end, we re-analyzed a set of genome-scale pooled library shRNA screens in human cell lines [19][20][21]. All the screens were conducted with an shRNA library containing After observing major technical (i.e.…”

Section: Generating the Coessentiality Networkmentioning

confidence: 99%

“…Data from shRNA screens in pancreatic, ovarian, and breast cancer cell lines was downloaded from the Donnelly-Princess Margaret Screening Centre (formerly COLT [43]) at dpsc.ccbr.utoronto.ca. The shRNA and RNA-seq data are from three published studies of shRNA screens [19][20][21].…”

Section: Primary Data Processingmentioning

confidence: 99%

“…In this study, we describe the integrated analysis of a large compendium of genetic perturbation screens. Using over 100 genome-scale, pooled-library shRNA screens from breast [19], ovarian [20], and pancreatic [21] cancer cell lines, all conducted with a common shRNA library and using similar experimental designs, we show that optimizing for co-functionality reveals a gene coessentiality network whose structure is driven by the shared genetic vulnerabilities of the cell lines. We demonstrate that clusters of coessential genes define known as well as novel subgroups of cell lines, and show how the network can be integrated with tumor molecular data to predict known and novel drug targets and their biomarkers.…”

Section: Introductionmentioning

confidence: 99%

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Coessentiality and cofunctionality: a network approach to learning genetic vulnerabilities from cancer cell line fitness screens

Hart¹,

Koh

Moffat

2017

Preprint

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Genetic interaction networks are a powerful approach for functional genomics, and the synthetic lethal interactions that comprise these networks offer a compelling strategy for identifying candidate cancer targets. As the number of published shRNA and CRISPR perturbation screens in cancer cell lines expands, there is an opportunity for integrative analysis that goes further than pairwise synthetic lethality and discovers genetic vulnerabilities of related sets of cell lines. We re-analyze over 100 high-quality, genomescale shRNA screens in human cancer cell lines and derive a quantitative fitness score for each gene that accurately reflects genotype-specific gene essentiality. We identify pairs of genes with correlated essentiality profiles and merge them into a cancer coessentiality network, where shared patterns of genetic vulnerability in cell lines give rise to clusters of functionally related genes in the network. Network clustering discriminates among all three defined subtypes of breast cancer cell lines (basal, luminal,, and further identifies novel subsets of Her2+ and ovarian cancer cells. We demonstrate the utility of the network as a platform for both hypothesis-driven and data-driven discovery of context-specific essential genes and their associated biomarkers.

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Interrogation of Functional Cell-Surface Markers Identifies CD151 Dependency in High-Grade Serous Ovarian Cancer

Cited by 40 publications

References 56 publications

Hierarchical organization of the human cell from a cancer coessentiality network

Hierarchical organization of the human cell from a cancer coessentiality network

C/EBPδ demonstrates a dichotomous role in tumor initiation and promotion of epithelial carcinoma

Coessentiality and cofunctionality: a network approach to learning genetic vulnerabilities from cancer cell line fitness screens

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