| Literature DB >> 21865353 |
Elaine Marshall1, Jacqueline Lowrey, Sheila MacPherson, Jacqueline A Maybin, Frances Collins, Hilary O D Critchley, Philippa T K Saunders.
Abstract
CONTEXT: The endometrium is a multicellular, steroid-responsive tissue that undergoes dynamic remodeling every menstrual cycle in preparation for implantation and, in absence of pregnancy, menstruation. Androgen receptors are present in the endometrium.Entities:
Mesh:
Substances:
Year: 2011 PMID: 21865353 PMCID: PMC3380091 DOI: 10.1210/jc.2011-0272
Source DB: PubMed Journal: J Clin Endocrinol Metab ISSN: 0021-972X Impact factor: 5.958
Endometrium androgen target gene set identified by stringent in silico screening of publicly available data sets
| Gene ID | Name | Predicted change | Gene ID | Name | Predicted change |
|---|---|---|---|---|---|
| NM_018677 | Up | NM_000805 | Down | ||
| NM_000610 | Up | NM_002425 | Down | ||
| NM_006079 | Up | NM_006207 | Down | ||
| NM_000115 | Up | NM_021127 | Down | ||
| NM_005797 | Up | NM_138818 | Down | ||
| NM_000187 | Up | NM_024745 | Down | ||
| NM_000240 | Up | NM_007117 | Down | ||
| NM_003621 | Up |
ID, Identification.
The predicted change in expression in response to androgens is based on studies in prostatic cells (22, 23).
Fig. 1.Expression of candidate androgen-regulated gene mRNA in total tissue extracts from human endometrium and decidua as determined by quantitative RT-PCR. Samples were homogenized from functional endometrium recovered during the proliferative (P) and midsecretory phases (MS) as well as from first-trimester decidua (Dec). Concentrations displayed relative to those in proliferative phase in each case (n = 4–6 per group).
Fig. 2.Time-dependent changes in androgen-regulated gene expression in primary hESC. Cells were incubated with vehicle (gray bars) or 10−8 m DHT (black bars) for 2, 8, and 24 h (n = 6 each time point). Concentration of mRNA was quantified by quantitative RT-PCR and expressed as fold change compared with time-matched vehicle-treated hESC. Note that with the exception of CD44, incubation of cells with DHT resulted in either a significant reduction in concentration of mRNA or no significant change but with a trend to a reduction. For most genes, changes in mRNA expression were time dependent with the most striking change in total concentrations at 2 h for eight of 12 of the genes. *, P < 0.05; **, P < 0.01; ***, P < 0.001.
Fig. 3.Pathway analysis of endometrial androgen target gene set. Note 12 of 15 androgen-regulated genes identified by in silico screening (indicated with multicolored circles) were predicted to interact in a single Metacore pathway centered on AR; intermediate molecules are indicated to show putative intermediate signaling molecules. Key shows the functional classification of the target genes and the arrows indicate predicted regulation (red, negative; green, positive).
Gene ontology processes associated with the androgen candidate gene set identified by androgen candidate gene ontology identified using Metacore
| Processes | Target | Z-score | |
|---|---|---|---|
| Regulation of biological quality (57.5%), regulation of apoptosis (42.5%), regulation of programmed cell death (42.5%) | 14 | 5.74e-43 | 119.50 |
| Regulation of biological quality (54.5%), embryonic placenta development (13.6%), oxygen homeostasis (9.1%) | 6 | 2.18e-16 | 61.16 |
| Regulation of ion transport (27.0%), positive regulation of hydrolase activity (32.4%), positive regulation of phospholipase activity (24.3%) | 4 | 5.94e-10 | 35.52 |
Note that the term target indicates the number of candidate genes/proteins/compounds (objects) in a data set that are associated with a given network/process. The P value (the probability of a random intersection) indicates a measure of relevance of the intersection between a gene/protein and an entity in a particular ontology. The lower the P value, the higher is the nonrandomness of finding such intersection. The Z-score ranks the networks with regard to the number of objects present in the networks. The higher the Z-score, the higher the number of objects from the data set.
Subnetworks within the candidate gene set and associated processes identified by androgen candidate gene ontology identified using Metacore
| Network | GO processes | Z-score | |
|---|---|---|---|
| AR, CD44, EDNRB, CITED2, gastrin | Response to stress, regulation of catalytic activity | 3.00e-32 | 86.27 |
| PDGF-R-β, CITED2, CD44 | Response to hormone stimulus, regulation of locomotion | 7.21e-20 | 56.87 |
| AR, CITED2, CD44, PMAIP1 | Regulation of apoptosis, regulation of programmed cell death, regulation of developmental process | 2.14e-14 | 43.52 |
| ACSS1, gastrin, pyrophosphate cytoplasm, acetyl-CoA cytoplasm | Acetyl-CoA biosynthetic process, IL-8 production | 1.24e-08 | 43.12 |
| EDNRB, HGD, TRH receptor, c-Src, connexin 43 | Dopamine receptor signaling pathway, regulation of nucleotide biosynthetic process | 3.06e-07 | 25.93 |
| CITED2, ACSA, EDNRB, HNF4-α, HIF1A | Developmental process, response to hypoxia | 2.52e-07 | 26.76 |
Note that the term target indicates the number of candidate genes/proteins/compounds (objects) in a data set that are associated with a given network/process. The P value (the probability of a random intersection) indicates a measure of relevance of the intersection between a gene/protein and an entity in a particular ontology. The lower the P value, the higher is the nonrandomness of finding such intersection. The Z-score ranks the networks with regard to the number of objects present in the networks. The higher the Z-score, the higher the number of objects from the data set. GO, Gene ontology.
Fig. 4.Treatment of hESC with DHT alters apoptosis and proliferation. A, Apoptosis as measured by caspase-3/7 assay in cells treated with staurosporine. Note addition of DHT had a significant impact (*, P < 0.05) on the rate of apoptosis when compared with controls but that the impact of DHT was blunted in the presence of E2 (n = 4). B, Wound-healing assay. Addition of DHT had a significant impact (*, P < 0.05) compared with its vehicle control (ethanol), whereas flutamide alone had no impact compared with vehicle (methanol) and pretreatment of cells with flutamide blocked the DHT-dependent reduction in wound closure. DHT, 10−8 m; flutamide, 10−5 m; n = 6.