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A Quantitative Chemotherapy Genetic Interaction Map Reveals Factors Associated with PARP Inhibitor Resistance.

ABSTRACT: Chemotherapy is used to treat most cancer patients, yet our understanding of factors that dictate response and resistance to such drugs remains limited. We report the generation of a quantitative chemical-genetic interaction map in human mammary epithelial cells charting the impact of the knockdown of 625 genes related to cancer and DNA repair on sensitivity to 29 drugs, covering all classes of chemotherapy. This quantitative map is predictive of interactions maintained in other cell lines, identifies DNA-repair factors, predicts cancer cell line responses to therapy, and prioritizes synergistic drug combinations. We identify that ARID1A loss confers resistance to PARP inhibitors in cells and ovarian cancer patients and that loss of GPBP1 causes resistance to cisplatin and PARP inhibitors through the regulation of genes involved in homologous recombination. This map helps navigate patient genomic data and optimize chemotherapeutic regimens by delineating factors involved in the response to specific types of DNA damage.

SUBMITTER: Hu HM

PROVIDER: S-EPMC5935461 | biostudies-literature | 2018 Apr

REPOSITORIES: biostudies-literature

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A Quantitative Chemotherapy Genetic Interaction Map Reveals Factors Associated with PARP Inhibitor Resistance.

Hu Hsien-Ming HM Zhao Xin X Kaushik Swati S Robillard Lilliane L Barthelet Antoine A Lin Kevin K KK Lin Kevin K KK Shah Khyati N KN Simmons Andy D AD Raponi Mitch M Harding Thomas C TC Bandyopadhyay Sourav S

Cell reports 20180401 3

Chemotherapy is used to treat most cancer patients, yet our understanding of factors that dictate response and resistance to such drugs remains limited. We report the generation of a quantitative chemical-genetic interaction map in human mammary epithelial cells charting the impact of the knockdown of 625 genes related to cancer and DNA repair on sensitivity to 29 drugs, covering all classes of chemotherapy. This quantitative map is predictive of interactions maintained in other cell lines, iden ...[more]

PMID: 29669295

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Project description:All classes of RNA undergo processing. The two largest RNA processing complexes are those involved in rRNA biogenesis and mRNA splicing. Because of their complexity and essential roles, it has been difficult to dissect the functional interactions within these machines as well as to identify possible cross-talk with other steps in gene expression. Here we report the results of a high-density, quantitative genetic interaction map comprising 107,155 individual interactions involving 552 mutants, 166 of which are hypomorphic alleles of essential genes (This data is available at The Krogan Lab Interactome Database). Our data allow unique insights into the functional organization of the RNA processing machines. For example, we identify unexpected connections involving a component of the 19S proteasome, Sem1/Dss1. We show that Sem1 has genetic, physical and functional interactions with the mRNA export complex, Thp1-Sac3; it also interacts physically with a putative component of the COP9 signalosome, Csn12. We show using splicing-specific microarrays that Csn12 has an unanticipated role in mRNA splicing. Finally, we demonstrate the utility of this dataset in determining functions for uncharacterized ORFs. We show that deletion of the uncharacterized YNR004W causes a very similar splicing defect to that caused by deletion of TGS1, the enzyme that trimethylates the caps of snRNAs and snoRNAs. Keywords: E-MAP, RNA Processing, splicing, splicing-specific microarray, CSN12, COP9 signalosome Splicing-specific microarrays were used to assay the changes to splicing caused by deletion of several non-essential genes which had no previously characterized role in mRNA splicing but were suggested to be involved in this process by high-throughput genetic and/or protein-protein interaction data in Saccharomyces cerevisiae. The data includes samples collected from some mutants in log phase growth at 30 degrees C and from some mutants shifted to 16 degrees C, all competitively hybridized against wild type samples collected under the same conditions. .

Dataset Information

A Quantitative Chemotherapy Genetic Interaction Map Reveals Factors Associated with PARP Inhibitor Resistance.

Publications

A Quantitative Chemotherapy Genetic Interaction Map Reveals Factors Associated with PARP Inhibitor Resistance.

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