High-throughput Drug Screening Identifies Fluoxetine as a Potential Therapeutic Agent for Neuroendocrine Prostate Cancer
Ontology highlight
ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE224715 | GEO | 2023/04/05
REPOSITORIES: GEO
Similar Datasets
Project description:We performed a high-throughput drug screening and identified Ketotifen, originally an FDA-approved antidepressant, as candidate therapeutic agent for NEPC. RNA-seq was performed of LASCPC-01 cells treated with Ketotifen or PBS.
2024-01-01 | GSE225007 | GEO
Project description:Selective serotonin reuptake inhibitors (SSRIs) such as fluoxetine are the most common treatment for major depression. However, approximately 50% of depressed patients fail to achieve an effective treatment response. Understanding how gene expression systems relate to treatment responses may be critical for understanding antidepressant resistance. Transcriptome profiling allows for the simultaneous measurement of expression levels for thousands of genes and the opportunity to utilize this information to determine mechanisms underlying antidepressant treatment responses. However, the best way to relate this immense amount of information to treatment resistance remains unclear. We take a novel approach to this question by examining dentate gyrus transcriptomes from the perspective of a stereotyped fluoxetine-induced gene expression program. Expression programs usually represent stereotyped changes in expression levels that occur as cells transition phenotypes. Fluoxetine will shift transcriptomes so they lie somewhere between a baseline state and a full-response at the end of the program. The position along this fluoxetine-induced gene expression program (program status) was measured using principal components analysis (PCA). The same expression program was initiated in treatment-responsive and resistant mice but treatment response was associated with further progression along the fluoxetine-induced gene expression program. The study of treatment-related differences in gene expression program status represents a novel way to conceptualize differences in treatment responses at a transcriptome level. Understanding how antidepressant-induced gene expression program progression is modulated represents an important area for future research and could guide efforts to develop novel augmentation strategies for antidepressant treatment resistant individuals. 38 samples, 2 dentate regions (dorsal/ventral), 3 groups (control, antidepressant resistant (4 mice), antidepressant responsive (7 mice), untreated (8 mice).
2013-12-31 | E-GEOD-43261 | biostudies-arrayexpress
Project description:Colon cancer is one of the most common tumors worldwide. Recent reports showed that patients treated with the antidepressant fluoxetine had reduced colon cancer risk, with effects similar to the chemotherapeutic 5-fluoro-uracil. Here, we examined the effects of fluoxetine and 5-fluoro-uracil on gene expression of HT29 colon cancer cell xenografts. HT29 xenografts in NOD/SCID mice were treated with vehicle (physiological solution), fluoxetine (30mg/kg/day), or 5-Fluoro-uracil (50 mg/kg/day).
2015-06-09 | E-GEOD-51904 | biostudies-arrayexpress
Project description:Colon cancer is one of the most common tumors worldwide. Recent reports showed that patients treated with the antidepressant fluoxetine had reduced colon cancer risk, with effects similar to the chemotherapeutic 5-fluoro-uracil. Here, we examined the effects of fluoxetine and 5-fluoro-uracil on gene expression of HT29 colon cancer cell xenografts.
2015-06-09 | GSE51904 | GEO
Project description:Selective serotonin reuptake inhibitors (SSRIs) such as fluoxetine are the most common treatment for major depression. However, approximately 50% of depressed patients fail to achieve an effective treatment response. Understanding how gene expression systems relate to treatment responses may be critical for understanding antidepressant resistance. Transcriptome profiling allows for the simultaneous measurement of expression levels for thousands of genes and the opportunity to utilize this information to determine mechanisms underlying antidepressant treatment responses. However, the best way to relate this immense amount of information to treatment resistance remains unclear. We take a novel approach to this question by examining dentate gyrus transcriptomes from the perspective of a stereotyped fluoxetine-induced gene expression program. Expression programs usually represent stereotyped changes in expression levels that occur as cells transition phenotypes. Fluoxetine will shift transcriptomes so they lie somewhere between a baseline state and a full-response at the end of the program. The position along this fluoxetine-induced gene expression program (program status) was measured using principal components analysis (PCA). The same expression program was initiated in treatment-responsive and resistant mice but treatment response was associated with further progression along the fluoxetine-induced gene expression program. The study of treatment-related differences in gene expression program status represents a novel way to conceptualize differences in treatment responses at a transcriptome level. Understanding how antidepressant-induced gene expression program progression is modulated represents an important area for future research and could guide efforts to develop novel augmentation strategies for antidepressant treatment resistant individuals.
2013-12-31 | GSE43261 | GEO
Project description:We constructed a comprehensive multi-omics map of the molecular effects of fluoxetine (an SSRI antidepressant), in 27 rat brain regions. We profiled gene expression (bulk RNA-seq, 210 datasets) and chromatin state (bulk chromatin immunoprecipitation sequencing (ChIP-seq) for the histone marker H3K27ac, 100 datasets) in a broad, unbiased panel of 27 brain regions across the entire rodent brain, in naive and fluoxetine-treated animals. We complemented this approach with single-cell RNA-seq (scRNA-seq) analysis of two brain regions. Using diverse integrative data analysis techniques we characterized the complex and multifaceted effects of fluoxetine on region-specific and cell-type-specific gene regulatory networks and pathways. Remarkably, we observed profound molecular changes across the brain (>4,000 differentially expressed genes and differentially acetylated ChIP-seq peaks each) that were highly region-dependent. We leveraged this atlas to identify fluoxetine-moduated genes and gene-regulatory loci, predict enriched motifs that suggest potential upstream regulators, and validate global mechanisms of fluoxetine action.
2022-09-04 | GSE193040 | GEO
Project description:We constructed a comprehensive multi-omics map of the molecular effects of fluoxetine (an SSRI antidepressant), in 27 rat brain regions. We profiled gene expression (bulk RNA-seq, 210 datasets) and chromatin state (bulk chromatin immunoprecipitation sequencing (ChIP-seq) for the histone marker H3K27ac, 100 datasets) in a broad, unbiased panel of 27 brain regions across the entire rodent brain, in naive and fluoxetine-treated animals. We complemented this approach with single-cell RNA-seq (scRNA-seq) analysis of two brain regions. Using diverse integrative data analysis techniques we characterized the complex and multifaceted effects of fluoxetine on region-specific and cell-type-specific gene regulatory networks and pathways. Remarkably, we observed profound molecular changes across the brain (>4,000 differentially expressed genes and differentially acetylated ChIP-seq peaks each) that were highly region-dependent. We leveraged this atlas to identify fluoxetine-moduated genes and gene-regulatory loci, predict enriched motifs that suggest potential upstream regulators, and validate global mechanisms of fluoxetine action.
2022-09-04 | GSE194289 | GEO
Project description:Both the mechanism of action and the factors determining the behavioral response to antidepressants are unknown. It has been shown that antidepressant treatment promotes the proliferation and survival of hippocampal neurons via enhanced serotonergic signaling, but it is still unclear whether hippocampal neurogenesis is responsible for the behavioral response to antidepressants. Furthermore, a large subpopulation of patients fails to respond to antidepressant treatment due to presumed underlying genetic factors. In the present study, we have used the phenotypic and genotypic variability of inbred mouse strains to show that there is a genetic component to both the behavioral and neurogenic effects of chronic fluoxetine treatment, and that this antidepressant induces an increase in hippocampal cell proliferation only in the strains that also show a positive behavioral response to treatment. The behavioral and neurogenic responses are associated with an upregulation of genes known to promote neuronal proliferation and survival. These results suggest that inherent genetic predisposition to increased serotonin-induced neurogenesis is a determinant of antidepressant efficacy. Keywords: drug response
2007-07-04 | GSE6476 | GEO
Project description:High-throughput Drug Screening Identifies Fluoxetine as a Potential Therapeutic Agent for Neuroendocrine Prostate Cancer
| PRJNA932252 | ENA
Project description:Both the mechanism of action and the factors determining the behavioral response to antidepressants are unknown. It has been shown that antidepressant treatment promotes the proliferation and survival of hippocampal neurons via enhanced serotonergic signaling, but it is still unclear whether hippocampal neurogenesis is responsible for the behavioral response to antidepressants. Furthermore, a large subpopulation of patients fails to respond to antidepressant treatment due to presumed underlying genetic factors. In the present study, we have used the phenotypic and genotypic variability of inbred mouse strains to show that there is a genetic component to both the behavioral and neurogenic effects of chronic fluoxetine treatment, and that this antidepressant induces an increase in hippocampal cell proliferation only in the strains that also show a positive behavioral response to treatment. The behavioral and neurogenic responses are associated with an upregulation of genes known to promote neuronal proliferation and survival. These results suggest that inherent genetic predisposition to increased serotonin-induced neurogenesis is a determinant of antidepressant efficacy. Experiment Overall Design: Male DBA/2J, age 3-5 weeks, were obtained from The Jackson Laboratory (Bar Harbor, ME) and maintained on a 12:12 light:dark cycle with lights on at 0700 hours. Following at least one week of acclimation, mice were provided with either untreated or fluoxetine-treated drinking water, available ad libitum. Fluoxetine-HCl was obtained from Spectrum Chemicals (Gardena, CA). Differences in daily water consumption were previously determined by measuring water intake for three weeks from at least 12 mice (6.4 mL (+/- .58 mL) per day). We also determined the average weight at 10 weeks of age (25.5 g +/- 1.4 g), and used this information to dilute fluoxetine in the water in order to provide a daily dosage of 0 or 18 mg/kg/mouse. Experiment Overall Design: Mice were 8-12 weeks of age at the time of behavioral testing, which was performed during the light phase between 1300h and 1600h. Behavioral despair was measured using a mouse Tail Suspension apparatus from Med Associates (Georgia, VT). Experiment Overall Design: Individual bilateral hippocampii from 21-day-treatment 0 and 18 mg/kg/day DBA/2J mice were homogenized in 500 µl TRIzol using a QIAgen Tissuelyser (15 minutes at 30 Hz, QIAgen, Chatsworth, CA). RNA was extracted by phenol-chloroform phase separation and further processed using the RNAeasy miniprep kit (QIAgen). For each treatment group of 12 animals, separate RNA pools were made using hippocampal RNA from 6 mice per pool. These biological replicates were processed separately through the entirety of the microarray procedure. Five µg of total RNA from each pool was used as a template to synthesize complementary DNA (cDNA) and biotinylated cRNA (Enzo kit, Affymetrix, Santa Clara, CA) using standard Affymetrix protocols. cRNA was hybridized to Affymetrix GeneChip Mouse Genome 430 2.0 Array. Data were analyzed using ArrayAssist software (Stratagene, La Jolla, CA) and normalized with the GCRMA algorithm. A probeset had to obtain a minimal intensity value 100 to be considered as detecting expression above background. Therefore, any probeset that failed to meet this cutoff was removed from the analysis. Ratios of intensity differences were generated and genes showing at least a two-fold difference between experimental conditions were identified for further analysis.
2008-06-14 | E-GEOD-6476 | biostudies-arrayexpress