ArticleAssay and drug development technologies2016
Reconfiguring the AR-TIF2 Protein-Protein Interaction HCS Assay in Prostate Cancer Cells and Characterizing the Hits from a LOPAC Screen.
Article in Assay and drug development technologies, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
8 citing papers in PubMed, 10 citations in OpenAlex.
- Miniaturization and characterization of patient derived hepatocellular carcinoma tumor organoid cultures for cancer drug discovery applications.SLAS discovery : advancing life sciences R & D · 2025Article
- Characterization of allosteric modulators that disrupt androgen receptor co-activator protein-protein interactions to alter transactivation-Drug leads for metastatic castration resistant prostate cancer.SLAS discovery : advancing life sciences R & D · 2023Article
- A Bittersweet Computational Journey among Glycosaminoglycans.Biomolecules · 2021Review
- Steroid receptor/coactivator binding inhibitors: An update.Molecular and cellular endocrinology · 2019Review
- Targeting Transcription Factors for Cancer Treatment.Molecules (Basel, Switzerland) · 2018Review
- Targeting epigenetic regulators for cancer therapy: mechanisms and advances in clinical trials.Signal transduction and targeted therapyReview
- Assays to Interrogate the Ability of Compounds to Inhibit the AF-2 or AF-1 Transactivation Domains of the Androgen Receptor.Assay and drug development technologiesArticle
- High-Content Screening Campaign to Identify Compounds That Inhibit or Disrupt Androgen Receptor-Transcriptional Intermediary Factor 2 Protein-Protein Interactions for the Treatment of Prostate Cancer.Assay and drug development technologiesArticle
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Authors and funding
6 authors at 2 institutions in 1 country.
Funding
Abstract
The continued activation of androgen receptor (AR) transcription and elevated expression of AR and transcriptional intermediary factor 2 (TIF2) coactivator observed in prostate cancer (CaP) recurrence and the development of castration-resistant CaP (CRPC) support a screening strategy for small-molecule inhibitors of AR-TIF2 protein-protein interactions (PPIs) to find new drug candidates. Small molecules can elicit tissue selective effects, because the cells of distinct tissues express different levels and cohorts of coregulatory proteins. We reconfigured the AR-TIF2 PPI biosensor (PPIB) assay in the PC-3 CaP cell line to determine whether AR modulators and hits from an AR-TIF2 PPIB screen conducted in U-2 OS cells would behave differently in the CaP cell background. Although we did not observe any significant differences in the compound responses between the assay performed in osteosarcoma and CaP cells, the U-2 OS AR-TIF2 PPIB assay would be more amenable to screening, because both the virus and cell culture demands are lower. We implemented a testing paradigm of counter-screens and secondary hit characterization assays that allowed us to identify and deprioritize hits that inhibited/disrupted AR-TIF2 PPIs and AR transcriptional activation (AR-TA) through antagonism of AR ligand binding or by non-specifically blocking nuclear receptor trafficking. Since AR-TIF2 PPI inhibitor/disruptor molecules act distally to AR ligand binding, they have the potential to modulate AR-TA in a cell-specific manner that is distinct from existing anti-androgen drugs, and to overcome the development of resistance to AR antagonism. We anticipate that the application of this testing paradigm to characterize the hits from an AR-TIF2 PPI high-content screening campaign will enable us to prioritize the AR-TIF2 PPI inhibitor/disruptor leads that have potential to be developed into novel therapeutics for CaP and CRPC.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.