Literature DB >> 28322442

Systems analysis of dynamic transcription factor activity identifies targets for treatment in Olaparib resistant cancer cells.

Joseph T Decker1, Eric C Hobson1, Yining Zhang2, Seungjin Shin3, Alexandra L Thomas4, Jacqueline S Jeruss4, Kelly B Arnold1, Lonnie D Shea1.   

Abstract

The development of resistance to targeted therapeutics is a challenging issue for the treatment of cancer. Cancers that have mutations in BRCA, a DNA repair protein, have been treated with poly(ADP-ribose) polymerase (PARP) inhibitors, which target a second DNA repair mechanism with the aim of inducing synthetic lethality. While these inhibitors have shown promise clinically, the development of resistance can limit their effectiveness as a therapy. This study investigated mechanisms of resistance in BRCA-mutated cancer cells (HCC1937) to Olaparib (AZD2281) using TRACER, a technique for measuring dynamics of transcription factor (TF) activity in living cells. TF activity was monitored in the parental HCC1937 cell line and two distinct resistant cell lines, one with restored wild-type BRCA1 and one with acquired resistance independent of BRCA1 for 48 h during treatment with Olaparib. Partial least squares discriminant analysis (PLSDA) was used to categorize the three cell types based on TF activity, and network analysis was used to investigate the mechanism of early response to Olaparib in the study cells. NOTCH signaling was identified as a common pathway linked to resistance in both Olaparib-resistant cell types. Western blotting confirmed upregulation of NOTCH protein, and sensitivity to Olaparib was restored through co-treatment with a gamma secretase inhibitor. The identification of NOTCH signaling as a common pathway contributing to PARP inhibitor resistance by TRACER indicates the efficacy of transcription factor dynamics in identifying targets for intervention in treatment-resistant cancer and provides a new method for determining effective strategies for directed chemotherapy. Biotechnol. Bioeng. 2017;114: 2085-2095.
© 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

Entities:  

Keywords:  PARP inhibitors; data-driven modeling; drug resistance

Mesh:

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Year:  2017        PMID: 28322442      PMCID: PMC5522358          DOI: 10.1002/bit.26293

Source DB:  PubMed          Journal:  Biotechnol Bioeng        ISSN: 0006-3592            Impact factor:   4.530


  39 in total

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Journal:  Nature       Date:  2005-04-14       Impact factor: 69.504

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