Identification of Androgen Receptor Modulators in a Prostate Cancer Cell Line Microarray Compendium
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PROVIDER: PRJNA429436 | ENA |
REPOSITORIES: ENA
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Project description:High-throughput transcriptomic (HTTr) technologies are increasingly being used to screen environmental chemicals in vitro to identify molecular targets and provide mechanistic context for regulatory testing. The androgen receptor (AR, NR3C4) regulates male sexual development, is involved in the pathogenesis of a number of cancers, and is often the target of endocrine disruptors. Here, we describe the development and validation of a novel gene expression biomarker to identify AR-modulating chemicals using a pattern matching method. AR biomarker genes were identified by their consistent expression after exposure to 4 AR agonists and opposite expression after exposure to 4 AR antagonists. A genetic filter was used to include only those genes that were regulated by AR. Most of the resulting 51 biomarker genes were shown to be directly regulated by AR as determined by ChIP-Seq analysis of AR-DNA interactions. The biomarker was evaluated as a predictive tool using the fold-change rank-based Running Fisher algorithm which compares the expression of AR biomarker genes under various treatment conditions. Using 163 comparisons from cells treated with 98 chemicals, the biomarker gave balanced accuracies for prediction of AR activation or AR suppression of 97% or 98%, respectively. The biomarker was able to correctly classify 16 out of 17 AR reference antagonists including those that are “weak” and “very weak”. Predictions based on comparisons from AR-positive LAPC-4 cells treated with 28 chemicals in antagonist mode were compared to those from an AR pathway model based on 11 in vitro high-throughput screening assays that queried different steps in AR signaling. The balanced accuracy was 93% for suppression. Using our approach, we identified conditions in which AR was modulated in a large collection of microarray profiles from prostate cancer cell lines including 1) AR constitutively active mutants or knockdown of AR, 2) depletion of androgens by castration or removal from media, and 3) modulators that work through indirect mechanisms including suppression of AR expression. These results demonstrate that the AR gene expression biomarker could be a useful tool in HTTr to identify AR modulators in large collections of microarray data derived from AR-positive prostate cancer cell lines.
2018-01-24 | GSE109021 | GEO
Project description:High-throughput transcriptomic (HTTr) technologies are increasingly being used to screen environmental chemicals in vitro to identify molecular targets and provide mechanistic context for regulatory testing. Here, we describe the development and validation of a novel gene expression biomarker to identify androgen receptor (AR)-modulating chemicals using a pattern matching method. Androgen receptor biomarker genes were identified by their consistent expression after exposure to 4 AR agonists and 4 AR antagonists and included only those genes that were regulated by AR. The 51 gene biomarker was evaluated as a predictive tool using the fold-change, rank-based Running Fisher algorithm. Using 158 comparisons from cells treated with 95 chemicals, the biomarker gave balanced accuracies for prediction of AR activation or AR suppression of 97% or 98%, respectively. The biomarker correctly classified 16 out of the 17 AR reference antagonists including those that are "weak" and "very weak". Predictions based on microarray profiles from AR-positive LAPC-4 cells treated with 28 chemicals in antagonist mode were compared with those from an AR pathway model which used 11 in vitro HT assays. The balanced accuracy for suppression was 93%. Using our approach, we identified conditions in which AR was modulated in a large collection of microarray profiles from prostate cancer cell lines including (1) constitutively active mutants or knockdown of AR, (2) decreases in availability of androgens by castration or removal from media, and (3) exposure to chemical modulators that work through indirect mechanisms including suppression of AR expression. These results demonstrate that the AR gene expression biomarker could be a useful tool in HTTr to identify AR modulators.
| S-EPMC6454424 | biostudies-literature
Project description:To investigate the mechanisms of drug resistance and castration resistance in prostate cancer, we performed proteomic sequencing on androgen-dependent prostate cancer cells (LNCaP) and androgen-independent cells (AI) treated with enzalutamide.
2024-11-26 | PXD058261 |
Project description:Background Microorganisms adapt their transcriptome by integrating multiple chemical and physical signals from their environment. Shake-flask cultivation does not allow precise manipulation of individual culture parameters and therefore precludes a quantitative analysis of the (combinatorial) influence of these parameters on transcriptional regulation. Steady-state chemostat cultures, which do enable accurate control, measurement and manipulation of individual cultivation parameters (e.g. specific growth rate, temperature, identity of the growth-limiting nutrient) appear to provide a promising experimental platform for such a combinatorial analysis. Results A microarray compendium of 170 steady-state chemostat cultures of the yeast Saccharomyces cerevisiae is presented and analyzed. The 170 microarrays encompass 55 unique conditions, which can be characterized by the combined settings of 10 different cultivation parameters. By applying a regression model to assess the impact of (combinations of) cultivation parameters on the transcriptome, most S. cerevisiae genes were shown to be influenced by multiple cultivation parameters, and in many cases by combinatorial effects of cultivation parameters. The inclusion of these combinatorial effects in the regression model led to higher explained variance of the gene expression patterns and resulted in higher function enrichment in subsequent analysis. We further demonstrate the usefulness of the compendium and regression analysis for interpretation of shake-flask-based transcriptome studies and for guiding functional analysis of (uncharacterized) genes and pathways. Conclusions Modeling the combinatorial effects of environmental parameters on the transcriptome is crucial for understanding transcriptional regulation. Chemostat cultivation offers a powerful tool for such an approach. Keywords: chemostat steady state samples
2009-02-05 | GSE11452 | GEO
Project description:RNA-Seq analysis of prostate cancer cell line LNCaP treated with vehicle (C), androgen (R), androgen and IMTPPE (R + IMTPPE), androgen and JJ-(+)-450 (androgen + (-)450), androgen and JJ-(-)450 (androgen + (-)450), androgen and enzalutamide (androgen +Enz). To evaluate if our compounds can inhibit AR function specifically and completely, LNCaP mRNA profiles of cells treated with IMTPPE, (+)-JJ-450 and (-)-JJ-450, comparing to enzalutamide. RNA isolation was performed using RNeasy Mini kit (Qiagen), RNA Sequencing was carried out by Genomics Research Core of University of Pittsburgh using Illumina NextSeq 500 system. The sequence reads that passed FASTQC were analyzed at the transcript level. Each sample was mapped to the Human Ensembl reference genome GRCh38. We definied different expression genes with a fold change ≥2.0 and FDR <0.05. Both (-)-JJ-450 and enzalutamide are very specific to AR, with 56 and 186 DE genes comparing to control samples respectively. IMTPPE and (+)-JJ-450 can inhibit most of the androgen responsive genes, but also some other genes were affected. (-)-JJ-450 is a novel compound inhibts AR function specifically and completely, and it is a potential lead compound for the treatment of CRPC, including those resistant to enzalutamide.
2019-06-06 | GSE115395 | GEO
Project description:Castration resistant prostate cancers (CRPCs) lose sensitivity to androgen deprivation therapies but frequently remain dependent on oncogenic transcription driven by androgen receptor (AR) and its splice variants. To discover novel modulators of AR variant activity, we used a lysate-based small molecule microarray (SMM) assay and identified KI-ARv-03 as an AR variant complex binder that reduces AR-driven transcription and proliferation in prostate cancer cells. We deduced KI-ARv-03 to be a potent, selective inhibitor of CDK9, an important cofactor for AR, MYC, and other oncogenic transcription factors. Further optimization resulted in KB-0742 , an orally bioavailable, selective CDK9 inhibitor with potent anti-tumor activity in CRPC models. In 22Rv1 cells, KB-0742 rapidly downregulates nascent transcription, preferentially depleting short half-life transcripts and AR-driven oncogenic programs. In vivo , oral administration of KB-0742 significantly reduced tumor growth in CRPC, supporting CDK9 inhibition as a promising therapeutic strategy to target AR dependence in CRPC.
2020-10-05 | GSE156882 | GEO
Project description:Castration resistant prostate cancers (CRPCs) lose sensitivity to androgen deprivation therapies but frequently remain dependent on oncogenic transcription driven by androgen receptor (AR) and its splice variants. To discover novel modulators of AR variant activity, we used a lysate-based small molecule microarray (SMM) assay and identified KI-ARv-03 as an AR variant complex binder that reduces AR-driven transcription and proliferation in prostate cancer cells. We deduced KI-ARv-03 to be a potent, selective inhibitor of CDK9, an important cofactor for AR, MYC, and other oncogenic transcription factors. Further optimization resulted in KB-0742 , an orally bioavailable, selective CDK9 inhibitor with potent anti-tumor activity in CRPC models. In 22Rv1 cells, KB-0742 rapidly downregulates nascent transcription, preferentially depleting short half-life transcripts and AR-driven oncogenic programs. In vivo , oral administration of KB-0742 significantly reduced tumor growth in CRPC, supporting CDK9 inhibition as a promising therapeutic strategy to target AR dependence in CRPC.
2020-10-05 | GSE156881 | GEO
Project description:Castration resistant prostate cancers (CRPCs) lose sensitivity to androgen deprivation therapies but frequently remain dependent on oncogenic transcription driven by androgen receptor (AR) and its splice variants. To discover novel modulators of AR variant activity, we used a lysate-based small molecule microarray (SMM) assay and identified KI-ARv-03 as an AR variant complex binder that reduces AR-driven transcription and proliferation in prostate cancer cells. We deduced KI-ARv-03 to be a potent, selective inhibitor of CDK9, an important cofactor for AR, MYC, and other oncogenic transcription factors. Further optimization resulted in KB-0742 , an orally bioavailable, selective CDK9 inhibitor with potent anti-tumor activity in CRPC models. In 22Rv1 cells, KB-0742 rapidly downregulates nascent transcription, preferentially depleting short half-life transcripts and AR-driven oncogenic programs. In vivo , oral administration of KB-0742 significantly reduced tumor growth in CRPC, supporting CDK9 inhibition as a promising therapeutic strategy to target AR dependence in CRPC.
2020-10-05 | GSE156884 | GEO
Project description:Aberrant androgen receptor (AR)-mediated transcription is a critical driver in progression of human prostate cancer. It's known that different doses of androgens can elicit differential transcriptional and proliferative responses in prostate-tumor cells. Here, we set out to examine the androgenic regulation of glycoprotein expression in the membrane fraction of prostate-tumor cells that could serve as mediators or markers of androgen-induced proliferative responses observed in prostate-tumor cells. A bioanalytical workflow involving lectin-affinity chromatography and label-free quantitative mass spectrometry was used to identify androgen-sensitive glycomembrane protein expression associated with androgen-mediated proliferation. This study would facilitate the identification of surface membrane proteins involved in androgen-mediated proliferation and provide potential therapeutic targets in the detection treatment of proliferation prostate-tumors.
2022-03-01 | PXD002913 | Pride
Project description:Global definition of androgen and anti-androgen effects on LNCaP transcriptomes using Affymetrix U133A oligonucleotide microarray. LNCaP in androgen-depleted medium was treated with androgen (DHT) and anti-androgen (CPA) for different time points (2 hours, 4 hours, 8 hours, and 24 hours). Untreated or Vehicle (Ethanol) treated samples as control.
2023-07-27 | GSE223251 | GEO