Androgen receptor plasticity and its implications for prostate cancer therapy

Snow, Oliver; Lallous, Nada; Singh, Kriti; Lack, Nathan A.; Rennie, Paul S.; Cherkasov, Artem

doi:10.1016/j.ctrv.2019.05.001

Cited by 48 publications

(35 citation statements)

References 77 publications

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“…Abiraterone acetate inhibits androgen biosynthesis by targeting cytochrome P450 17A1 (CYP17A1, also known as 17α hydroxylase/17,20-lyase), which catalyzes the conversion of pregnenolone to dehydroepiandrosterone (DHEA) in the adrenal glands [ 1 , 7 ]. Enzalutamide inhibits androgen signaling through competitive binding to the AR, resulting in inhibiting translocation of the receptor into the nucleus and its binding to the DNA, leading to a reduced expression of AR-regulated target genes [ 2 , 8 , 9 ]. Both drugs achieved stunning results.…”

Section: Introductionmentioning

confidence: 99%

“…The AR is a ligand-inducible nuclear steroid receptor transcription factor for testosterone and dihydrotestosterone that consists of an N-terminal domain (NTD) (carrying the constitutive activation function region), a DNA binding domain (DBD), a hinge region, and a ligand binding domain (LBD), the latter being the best studied section of the protein [ 34 ]. The AR is an especially plastic protein, with the ability to rapidly change between several conformations [ 8 ]. In addition, despite the relatively large number of available crystal structures (82 entries are reported in RCSB PDB (Protein Data Bank) for human AR, accessed 03.04.2020), structural information is mainly available on the LBD.…”

Section: Introductionmentioning

confidence: 99%

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Dual Inhibitory Action of a Novel AKR1C3 Inhibitor on Both Full-Length AR and the Variant AR-V7 in Enzalutamide Resistant Metastatic Castration Resistant Prostate Cancer

Kafka

Mayr

Temml

et al. 2020

Cancers

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The expanded use of second-generation antiandrogens revolutionized the treatment landscape of progressed prostate cancer. However, resistances to these novel drugs are already the next obstacle to be solved. Various previous studies depicted an involvement of the enzyme AKR1C3 in the process of castration resistance as well as in the resistance to 2nd generation antiandrogens like enzalutamide. In our study, we examined the potential of natural AKR1C3 inhibitors in various prostate cancer cell lines and a three-dimensional co-culture spheroid model consisting of cancer cells and cancer-associated fibroblasts (CAFs) mimicking enzalutamide resistant prostate cancer. One of our compounds, named MF-15, expressed strong antineoplastic effects especially in cell culture models with significant enzalutamide resistance. Furthermore, MF-15 exhibited a strong effect on androgen receptor (AR) signaling, including significant inhibition of AR activity, downregulation of androgen-regulated genes, lower prostate specific antigen (PSA) production, and decreased AR and AKR1C3 expression, indicating a bi-functional effect. Even more important, we demonstrated a persisting inhibition of AR activity in the presence of AR-V7 and further showed that MF-15 non-competitively binds within the DNA binding domain of the AR. The data suggest MF-15 as useful drug to overcome enzalutamide resistance.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Dual Inhibitory Action of a Novel AKR1C3 Inhibitor on Both Full-Length AR and the Variant AR-V7 in Enzalutamide Resistant Metastatic Castration Resistant Prostate Cancer

Kafka

Mayr

Temml

et al. 2020

Cancers

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“…After PPI network and hub gene analysis, 12 hub genes were identified, including 5 upregulated genes and 7 downregulated genes. Among the identified hub genes, some have been proven to be related to ENZ resistance or PCa progression, such as AR, ACKR3 (also named CXCR7) [20,21], CCR7 [22], and NDRG1 [23]. In addition, NK3 homeobox1 (NKX3-1) is a prostate tumor suppressor that is associated with the DNA repair response and binds to the androgen receptor [24].…”

Section: Discussionmentioning

confidence: 99%

Identification of Potential Key Genes and Pathways in Enzalutamide-Resistant Prostate Cancer Cell Lines: A Bioinformatics Analysis with Data from the Gene Expression Omnibus (GEO) Database

Zheng

Dou

et al. 2020

BioMed Research International

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Enzalutamide (ENZ) has been approved for the treatment of advanced prostate cancer (PCa), but some patients develop ENZ resistance initially or after long-term administration. Although a few key genes have been discovered by previous efforts, the complete mechanisms of ENZ resistance remain unsolved. To further identify more potential key genes and pathways in the development of ENZ resistance, we employed the GSE104935 dataset, including 5 ENZ-resistant (ENZ-R) and 5 ENZ-sensitive (ENZ-S) PCa cell lines, from the Gene Expression Omnibus (GEO) database. Integrated bioinformatics analyses were conducted, such as analysis of differentially expressed genes (DEGs), Gene Ontology (GO) enrichment analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis, protein-protein interaction (PPI) analysis, gene set enrichment analysis (GSEA), and survival analysis. From these, we identified 201 DEGs (93 upregulated and 108 downregulated) and 12 hub genes (AR, ACKR3, GPER1, CCR7, NMU, NDRG1, FKBP5, NKX3-1, GAL, LPAR3, F2RL1, and PTGFR) that are potentially associated with ENZ resistance. One upregulated pathway (hedgehog pathway) and seven downregulated pathways (pathways related to androgen response, p53, estrogen response, TNF-α, TGF-β, complement, and pancreas β cells) were identified as potential key pathways involved in the occurrence of ENZ resistance. Our findings may contribute to further understanding the molecular mechanisms of ENZ resistance and provide some clues for the prevention and treatment of ENZ resistance.

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“…One important aspect of resistant AR mutants is that they do not simply render the drug ineffective but can even turn the drug from an antagonist into an agonist, thus promoting cancer growth. This characteristic seems to be unique to the AR and thus emphasizes the need to identify gain-of-function mutations that cause this phenotype so that patients can be screened and taken off treatment before resistance develops [ 5 ]. Additionally, understanding and predicting those mutations that cause resistance will enable us to design better drugs that might avoid this mechanism in the future.…”

Section: Introductionmentioning

confidence: 99%

Deep Learning Modeling of Androgen Receptor Responses to Prostate Cancer Therapies

Snow

Lallous

Ester

et al. 2020

IJMS

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Gain-of-function mutations in human androgen receptor (AR) are among the major causes of drug resistance in prostate cancer (PCa). Identifying mutations that cause resistant phenotype is of critical importance for guiding treatment protocols, as well as for designing drugs that do not elicit adverse responses. However, experimental characterization of these mutations is time consuming and costly; thus, predictive models are needed to anticipate resistant mutations and to guide the drug discovery process. In this work, we leverage experimental data collected on 68 AR mutants, either observed in the clinic or described in the literature, to train a deep neural network (DNN) that predicts the response of these mutants to currently used and experimental anti-androgens and testosterone. We demonstrate that the use of this DNN, with general 2D descriptors, provides a more accurate prediction of the biological outcome (inhibition, activation, no-response, mixed-response) in AR mutant-drug pairs compared to other machine learning approaches. Finally, the developed approach was used to make predictions of AR mutant response to the latest AR inhibitor darolutamide, which were then validated by in-vitro experiments.

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Androgen receptor plasticity and its implications for prostate cancer therapy

Cited by 48 publications

References 77 publications

Dual Inhibitory Action of a Novel AKR1C3 Inhibitor on Both Full-Length AR and the Variant AR-V7 in Enzalutamide Resistant Metastatic Castration Resistant Prostate Cancer

Dual Inhibitory Action of a Novel AKR1C3 Inhibitor on Both Full-Length AR and the Variant AR-V7 in Enzalutamide Resistant Metastatic Castration Resistant Prostate Cancer

Identification of Potential Key Genes and Pathways in Enzalutamide-Resistant Prostate Cancer Cell Lines: A Bioinformatics Analysis with Data from the Gene Expression Omnibus (GEO) Database

Deep Learning Modeling of Androgen Receptor Responses to Prostate Cancer Therapies

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