Literature DB >> 28530711

A combinatorial screen of the CLOUD uncovers a synergy targeting the androgen receptor.

Marco P Licciardello1, Anna Ringler1, Patrick Markt1, Freya Klepsch1, Charles-Hugues Lardeau1,2, Sara Sdelci1, Erika Schirghuber1,2, André C Müller1, Michael Caldera1, Anja Wagner3, Rebecca Herzog3, Thomas Penz1, Michael Schuster1, Bernd Boidol1,2, Gerhard Dürnberger1, Yasin Folkvaljon4, Pär Stattin4,5, Vladimir Ivanov6, Jacques Colinge1, Christoph Bock1,7,8, Klaus Kratochwill3, Jörg Menche1, Keiryn L Bennett1, Stefan Kubicek1,2.   

Abstract

Approved drugs are invaluable tools to study biochemical pathways, and further characterization of these compounds may lead to repurposing of single drugs or combinations. Here we describe a collection of 308 small molecules representing the diversity of structures and molecular targets of all FDA-approved chemical entities. The CeMM Library of Unique Drugs (CLOUD) covers prodrugs and active forms at pharmacologically relevant concentrations and is ideally suited for combinatorial studies. We screened pairwise combinations of CLOUD drugs for impairment of cancer cell viability and discovered a synergistic interaction between flutamide and phenprocoumon (PPC). The combination of these drugs modulates the stability of the androgen receptor (AR) and resensitizes AR-mutant prostate cancer cells to flutamide. Mechanistically, we show that the AR is a substrate for γ-carboxylation, a post-translational modification inhibited by PPC. Collectively, our data suggest that PPC could be repurposed to tackle resistance to antiandrogens in prostate cancer patients.

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Year:  2017        PMID: 28530711     DOI: 10.1038/nchembio.2382

Source DB:  PubMed          Journal:  Nat Chem Biol        ISSN: 1552-4450            Impact factor:   15.040


  48 in total

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Journal:  Nat Rev Drug Discov       Date:  2006-12       Impact factor: 84.694

2.  Monitoring drug target engagement in cells and tissues using the cellular thermal shift assay.

Authors:  Daniel Martinez Molina; Rozbeh Jafari; Marina Ignatushchenko; Takahiro Seki; E Andreas Larsson; Chen Dan; Lekshmy Sreekumar; Yihai Cao; Pär Nordlund
Journal:  Science       Date:  2013-07-05       Impact factor: 47.728

3.  Fulvestrant (ICI 182,780) down-regulates androgen receptor expression and diminishes androgenic responses in LNCaP human prostate cancer cells.

Authors:  Rumi S Bhattacharyya; Aruna V Krishnan; Srilatha Swami; David Feldman
Journal:  Mol Cancer Ther       Date:  2006-06       Impact factor: 6.261

4.  A haploid genetic screen identifies the major facilitator domain containing 2A (MFSD2A) transporter as a key mediator in the response to tunicamycin.

Authors:  Jan H Reiling; Clary B Clish; Jan E Carette; Malini Varadarajan; Thijn R Brummelkamp; David M Sabatini
Journal:  Proc Natl Acad Sci U S A       Date:  2011-06-15       Impact factor: 11.205

Review 5.  Vitamin K-dependent carboxylase.

Authors:  J W Suttie
Journal:  Annu Rev Biochem       Date:  1985       Impact factor: 23.643

6.  Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles.

Authors:  Aravind Subramanian; Pablo Tamayo; Vamsi K Mootha; Sayan Mukherjee; Benjamin L Ebert; Michael A Gillette; Amanda Paulovich; Scott L Pomeroy; Todd R Golub; Eric S Lander; Jill P Mesirov
Journal:  Proc Natl Acad Sci U S A       Date:  2005-09-30       Impact factor: 11.205

7.  Risk of prostate cancer death in long-term users of warfarin: a population-based case-control study.

Authors:  V Tagalakis; H Tamim; M Blostein; J A Hanley; S R Kahn
Journal:  Cancer Causes Control       Date:  2013-03-15       Impact factor: 2.506

8.  Molecular determinants of resistance to antiandrogen therapy.

Authors:  Charlie D Chen; Derek S Welsbie; Chris Tran; Sung Hee Baek; Randy Chen; Robert Vessella; Michael G Rosenfeld; Charles L Sawyers
Journal:  Nat Med       Date:  2003-12-21       Impact factor: 53.440

9.  Overcoming mutation-based resistance to antiandrogens with rational drug design.

Authors:  Minna D Balbas; Michael J Evans; David J Hosfield; John Wongvipat; Vivek K Arora; Philip A Watson; Yu Chen; Geoffrey L Greene; Yang Shen; Charles L Sawyers
Journal:  Elife       Date:  2013-04-09       Impact factor: 8.140

10.  abFASP-MS: affinity-based filter-aided sample preparation mass spectrometry for quantitative analysis of chemically labeled protein complexes.

Authors:  Marie L Huber; Roberto Sacco; Katja Parapatics; Anna Skucha; Kseniya Khamina; André C Müller; Elena L Rudashevskaya; Keiryn L Bennett
Journal:  J Proteome Res       Date:  2014-01-17       Impact factor: 4.466

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  14 in total

1.  Anticancer drug synergy prediction in understudied tissues using transfer learning.

Authors:  Yejin Kim; Shuyu Zheng; Jing Tang; Wenjin Jim Zheng; Zhao Li; Xiaoqian Jiang
Journal:  J Am Med Inform Assoc       Date:  2021-01-15       Impact factor: 4.497

2.  SYNPRED: prediction of drug combination effects in cancer using different synergy metrics and ensemble learning.

Authors:  António J Preto; Pedro Matos-Filipe; Joana Mourão; Irina S Moreira
Journal:  Gigascience       Date:  2022-09-26       Impact factor: 7.658

3.  Chemical Genetic Screens Identify Kinase Inhibitor Combinations that Target Anti-Apoptotic Proteins for Cancer Therapy.

Authors:  Jacob I Contreras; Caroline M Robb; Hannah M King; Jared Baxter; Ayrianne J Crawford; Smit Kour; Smitha Kizhake; Yogesh A Sonawane; Sandeep Rana; Michael A Hollingsworth; Xu Luo; Amarnath Natarajan
Journal:  ACS Chem Biol       Date:  2018-04-05       Impact factor: 5.100

Review 4.  Machine learning approaches for drug combination therapies.

Authors:  Betül Güvenç Paltun; Samuel Kaski; Hiroshi Mamitsuka
Journal:  Brief Bioinform       Date:  2021-11-05       Impact factor: 11.622

5.  Analysis framework and experimental design for evaluating synergy-driving gene expression.

Authors:  Nadine Schrode; Carina Seah; P J Michael Deans; Gabriel Hoffman; Kristen J Brennand
Journal:  Nat Protoc       Date:  2021-01-11       Impact factor: 13.491

6.  Determining direct binders of the Androgen Receptor using a high-throughput Cellular Thermal Shift Assay.

Authors:  Joseph Shaw; Mathew Leveridge; Charlotta Norling; Jakob Karén; Daniel Martinez Molina; Daniel O'Neill; James E Dowling; Paul Davey; Suzanna Cowan; Michael Dabrowski; Martin Main; Davide Gianni
Journal:  Sci Rep       Date:  2018-01-09       Impact factor: 4.379

7.  Drug Target Commons: A Community Effort to Build a Consensus Knowledge Base for Drug-Target Interactions.

Authors:  Jing Tang; Zia-Ur-Rehman Tanoli; Balaguru Ravikumar; Zaid Alam; Anni Rebane; Markus Vähä-Koskela; Gopal Peddinti; Arjan J van Adrichem; Janica Wakkinen; Alok Jaiswal; Ella Karjalainen; Prson Gautam; Liye He; Elina Parri; Suleiman Khan; Abhishekh Gupta; Mehreen Ali; Laxman Yetukuri; Anna-Lena Gustavsson; Brinton Seashore-Ludlow; Anne Hersey; Andrew R Leach; John P Overington; Gretchen Repasky; Krister Wennerberg; Tero Aittokallio
Journal:  Cell Chem Biol       Date:  2017-12-21       Impact factor: 8.116

8.  SYNERGxDB: an integrative pharmacogenomic portal to identify synergistic drug combinations for precision oncology.

Authors:  Heewon Seo; Denis Tkachuk; Chantal Ho; Anthony Mammoliti; Aria Rezaie; Seyed Ali Madani Tonekaboni; Benjamin Haibe-Kains
Journal:  Nucleic Acids Res       Date:  2020-07-02       Impact factor: 16.971

Review 9.  Recent advances in combinatorial drug screening and synergy scoring.

Authors:  Tea Pemovska; Johannes W Bigenzahn; Giulio Superti-Furga
Journal:  Curr Opin Pharmacol       Date:  2018-09-05       Impact factor: 5.547

10.  Screening for insulin-independent pathways that modulate glucose homeostasis identifies androgen receptor antagonists.

Authors:  Sri Teja Mullapudi; Christian Sm Helker; Giulia Lm Boezio; Hans-Martin Maischein; Anna M Sokol; Stefan Guenther; Hiroki Matsuda; Stefan Kubicek; Johannes Graumann; Yu Hsuan Carol Yang; Didier Yr Stainier
Journal:  Elife       Date:  2018-12-06       Impact factor: 8.140

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