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Nuclear Receptor Coactivators: Mechanism and Therapeutic Targeting in Cancer
Published in Surinder K. Batra, Moorthy P. Ponnusamy, Gene Regulation and Therapeutics for Cancer, 2021
Andrew Cannon, Christopher Thompson, Rakesh Bhatia, Sushil Kumar
While the role of NCOA1 in gastric cancer (GC) has not been explored extensively, a study by Frycz et al. using next-generation sequencing of GC patient tumor samples identified that tumors arising from the gastric cardia had significantly reduced expression of NCOA1 compared to surrounding normal tissue [22]. When comparing the expression of hormone receptors in matched gastric cardia tissue samples, expression of NCOA1, NCOR1, estrogen receptor 2 (ESRβ), androgen receptor (AR), steroid dehydrogenase (HSD3B1) and steroid sulfatase (STS) were significantly decreased in CRC samples; aromatase was significantly increased; but no significant differences were observed for ESRα, PELP1, CREBBP, or NR2F1. The significant decrease in STS and aromatase levels suggested that despite no detection of major estrogen synthesis inhibition, the inability of desulfation of STS substrates and reduced NCOA1 may be inhibiting estradiol-protective effects in the gastric cardia. However, this study did not address the role of reduced NCOR1 expression, which reduces the associated transcriptional repression exhibited by this nuclear protein.
Endocrine Therapies
Published in David E. Thurston, Ilona Pysz, Chemistry and Pharmacology of Anticancer Drugs, 2021
In the absence of a steroid hormone, estrogen receptors are mainly located in the cytoplasm of cells. Hormone binding then triggers a number of events starting with dimerization of the receptor, migration from the cytoplasm into the nucleus (i.e., translocation) followed by binding to specific sequences of DNA known as the hormone response elements (i.e., the HREs). The DNA/receptor complex then recruits other proteins that are responsible for the transcription of downstream DNA into mRNA and finally translation into proteins that can affect cell function. Examples of recruited “activator” proteins include protein 1 and Sp-1, both of which promote transcription via several co-activators such as PELP-1.
Bioscience indications for chronic disease management and neuromedical interventions following traumatic brain injury
Published in Mark J. Ashley, David A. Hovda, Traumatic Brain Injury, 2017
Mark J. Ashley, Grace S. Griesbach, David L. Ripley, Matthew J. Ashley
Estrogen receptors have been found to be selectively upregulated in certain areas of the brain following injury. Estrogen has important roles in modulating brain homeostasis, synaptic plasticity, cognition, and neuroprotection377 through traditional and nontraditional cell-signaling mechanisms.378–380 Some of the receptors code for specific genetic intracellular signals responsible for neurogenesis. In particular, some of these messengers, such as c-Fos and PELP1, appear to demonstrate properties responsible for activation of genetic mechanisms responsible for cellular repair. A potential area for clinical impact of estrogen may be in its apparent neuroregenerative properties. Some receptor-mediated responses may be responsible for causing stem cells to differentiate into neuroprogenitor cells and protect nerve cells from programmed cell death.381–385
A new class of agents for estrogen-receptor-positive breast cancer
Published in Expert Review of Clinical Pharmacology, 2018
Dede N. Ekoue, Nisha Unni, Ganesh V. Raj
Well-characterized ERα coregulators include scaffolding proteins like proline, glutamate, and leucine-rich protein 1 (PELP1), transcriptional regulators like the steroid receptor coactivators (SRC) and cAMP response element-binding protein (CBP/p300), chromatin remodelers and pioneering factors like the SWItch/Sucrose non-fermentable (SWI/SNF) proteins, forkhead box protein A1, and bromodomains, and proteins involved in ubiquitin-mediated degradation, like the E3 ubiquitin protein ligases [13]. These ERα coregulator interactions serve as a physiologic rheostat to modulate ERα function [13]. The net effect of the interaction of ERα with these coregulators is often both context driven and specific for the cellular milieu within which these interactions occur [14,15]. ERα may either interact directly with the coregulators through specific domains or indirectly as part of a complex with scaffolding proteins [13]. One well-characterized domain for ERα interaction with its coregulators is the nuclear receptor (NR) box or LXXLL (L, leucine; X, any amino acid) motifs [16]. The functional interaction between ERE-bound ERα enables coregulators that are incapable of DNA binding, to modulate ERα transcription [13,16].
Molecular subtypes and differentiation programmes of glioma stem cells as determinants of extracellular vesicle profiles and endothelial cell-stimulating activities
Published in Journal of Extracellular Vesicles, 2018
C. Spinelli, L. Montermini, B. Meehan, A. R. Brisson, S. Tan, D. Choi, I. Nakano, J. Rak
We reasoned that numerical and molecular shifts in the characteristics of GSC-derived EVs under different growth conditions likely reflect a more fundamental change in the vesiculation process. To assess the nature and plausible consequences of this regulation, we developed proteomic profiles (LC-MS/MS) of the 100K EV fraction purified from conditioned media of PN GSC and MES GSC, as well as PN DIFF and MES DIFF cells. At least four different peptides were used for representation and quantification of individual proteins. Interestingly, while the total amount of proteins present in these preparations was comparable (Figure 7(a)), albeit higher in MES cells, the protein compositions were markedly different between EV pools released from different donor cells (Figure 7(b-d)). For example, 733 proteins were common for EVs from MES and PN GSCs, but 1036 and 154 were unique to these respective donors. Similar comparisons depicted as Venn diagrams indicate the existence of proteins uniquely associated with reprogramming of the EV cargo by GSC subtype, differentiation and both (Figure 7(b)). We have also analysed top 50 proteins enriched in each cell-specific EV fraction. These comparisons indicate a degree of similarity (but also differences) between 100K EV fractions from each cellular source, but a clear separation between GSC and DIFF growth conditions (Tables S2). We also quantified the enrichment of EV proteins during GSC to DIFF transition for both PN and MES lines as depicted in the volcano plot (Figure 7(c-d)). The levels of several proteins were found to change by a factor of > 2-fold and were both significant (P < 0.05) and subtype specific. For example, for PN GSC line the differentiation process induced an increase in EV-associated ALDR, Galectin-1, Sorcin, TSP1, HSPB1, while similar treatment of MES cells lead to enrichment of IQGAP1, PA2G4, PELP1, HNRNP family, NPM1, EIF3. We then explored the functional aspects of this enrichment using Gene Ontology (GO) tools for term enrichment analysis focusing on subcellular localization (Figure 8(a-b)) and biological process (Figure 8(c-d)). This audit yielded further support of EV subtype specificity in that PN GSCs emitted EVs containing proteins strongly associated with plasma membrane and extracellular domains, while EV proteins derived from MES GSCs were largely assigned to nuclear compartments (Figure 8(a)). Differentiated GSCs emitted EVs derived mainly from the cytoplasm but there were also differences between PN and MES subtypes (Figure 8(b)). Similarly, auditing EV proteome for molecular function suggested a link to signal transduction and cell communication in the case of PN GSC, PN DIFF and MES DIFF cells, while EVs from MES GSCs were enriched for proteins linked to nucleic acids and proteins metabolism (Figure 8(c-d)).