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A negative genetic interaction map in isogenic cancer cell lines reveals cancer cell vulnerabilities.

ABSTRACT: Improved efforts are necessary to define the functional product of cancer mutations currently being revealed through large-scale sequencing efforts. Using genome-scale pooled shRNA screening technology, we mapped negative genetic interactions across a set of isogenic cancer cell lines and confirmed hundreds of these interactions in orthogonal co-culture competition assays to generate a high-confidence genetic interaction network of differentially essential or differential essentiality (DiE) genes. The network uncovered examples of conserved genetic interactions, densely connected functional modules derived from comparative genomics with model systems data, functions for uncharacterized genes in the human genome and targetable vulnerabilities. Finally, we demonstrate a general applicability of DiE gene signatures in determining genetic dependencies of other non-isogenic cancer cell lines. For example, the PTEN(-/-) DiE genes reveal a signature that can preferentially classify PTEN-dependent genotypes across a series of non-isogenic cell lines derived from the breast, pancreas and ovarian cancers. Our reference network suggests that many cancer vulnerabilities remain to be discovered through systematic derivation of a network of differentially essential genes in an isogenic cancer cell model.

SUBMITTER: Vizeacoumar FJ

PROVIDER: S-EPMC3817404 | biostudies-literature | 2013 Oct

REPOSITORIES: biostudies-literature

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A negative genetic interaction map in isogenic cancer cell lines reveals cancer cell vulnerabilities.

Vizeacoumar Franco J FJ Arnold Roland R Vizeacoumar Frederick S FS Chandrashekhar Megha M Buzina Alla A Young Jordan T F JT Kwan Julian H M JH Sayad Azin A Mero Patricia P Lawo Steffen S Tanaka Hiromasa H Brown Kevin R KR Baryshnikova Anastasia A Mak Anthony B AB Fedyshyn Yaroslav Y Wang Yadong Y Brito Glauber C GC Kasimer Dahlia D Makhnevych Taras T Ketela Troy T Datti Alessandro A Babu Mohan M Emili Andrew A Pelletier Laurence L Wrana Jeff J Wainberg Zev Z Kim Philip M PM Rottapel Robert R O'Brien Catherine A CA Andrews Brenda B Boone Charles C Moffat Jason J

Molecular systems biology 20131008

Improved efforts are necessary to define the functional product of cancer mutations currently being revealed through large-scale sequencing efforts. Using genome-scale pooled shRNA screening technology, we mapped negative genetic interactions across a set of isogenic cancer cell lines and confirmed hundreds of these interactions in orthogonal co-culture competition assays to generate a high-confidence genetic interaction network of differentially essential or differential essentiality (DiE) gene ...[more]

PMID: 24104479

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Project description:BackgroundAmong breast cancers, the triple-negative breast cancer (TNBC) subtype has the worst prognosis with no approved targeted therapies and only standard chemotherapy as the backbone of systemic therapy. Unique metabolic changes in cancer progression provide innovative therapeutic opportunities. The receptor tyrosine kinases (RTKs) epidermal growth factor receptor (EGFR), and MET receptor are highly expressed in TNBC, making both promising therapeutic targets. RTK signaling profoundly alters cellular metabolism by increasing glucose consumption and subsequently diverting glucose carbon sources into metabolic pathways necessary to support the tumorigenesis. Therefore, detailed metabolic profiles of TNBC subtypes and their response to tyrosine kinase inhibitors may identify therapeutic sensitivities.MethodsWe quantified the metabolic profiles of TNBC cell lines representing multiple TNBC subtypes using gas chromatography mass spectrometry. In addition, we subjected MDA-MB-231, MDA-MB-468, Hs578T, and HCC70 cell lines to metabolic flux analysis of basal and maximal glycolytic and mitochondrial oxidative rates. Metabolic pool size and flux measurements were performed in the presence and absence of the MET inhibitor, INC280/capmatinib, and the EGFR inhibitor, erlotinib. Further, the sensitivities of these cells to modulators of core metabolic pathways were determined. In addition, we annotated a rate-limiting metabolic enzymes library and performed a siRNA screen in combination with MET or EGFR inhibitors to validate synergistic effects.ResultsTNBC cell line models displayed significant metabolic heterogeneity with respect to basal and maximal metabolic rates and responses to RTK and metabolic pathway inhibitors. Comprehensive systems biology analysis of metabolic perturbations, combined siRNA and tyrosine kinase inhibitor screens identified a core set of TCA cycle and fatty acid pathways whose perturbation sensitizes TNBC cells to small molecule targeting of receptor tyrosine kinases.ConclusionsSimilar to the genomic heterogeneity observed in TNBC, our results reveal metabolic heterogeneity among TNBC subtypes and demonstrate that understanding metabolic profiles and drug responses may prove valuable in targeting TNBC subtypes and identifying therapeutic susceptibilities in TNBC patients. Perturbation of metabolic pathways sensitizes TNBC to inhibition of receptor tyrosine kinases. Such metabolic vulnerabilities offer promise for effective therapeutic targeting for TNBC patients.

Dataset Information

A negative genetic interaction map in isogenic cancer cell lines reveals cancer cell vulnerabilities.

Publications

A negative genetic interaction map in isogenic cancer cell lines reveals cancer cell vulnerabilities.

Similar Datasets

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