Gene/Protein Disease Symptom Drug Enzyme Compound
Pivot Concepts:   Target Concepts:
Query: EC:6.3.5.5 (CPS)
 1,262 document(s) hit in 31,850,051 MEDLINE articles (0.00 seconds)

The role of hSWI/SNF complexes in transcriptional activation is well characterized; however, little is known about their function in transcriptional repression. We have previously shown that subunits of the mSin3A/histone deacetylase 2 (HDAC2) corepressor complex copurify with hSWI/SNF complexes. Here we show that the type II arginine-specific methyltransferase PRMT5, which is involved in cyclin E repression, can be found in association with Brg1 and hBrm-based hSWI/SNF complexes. We also show that hSWI/SNF-associated PRMT5 can methylate hypoacetylated histones H3 and H4 more efficiently than hyperacetylated histones H3 and H4. Protein-protein interaction studies indicate that PRMT5 and mSin3A interact with the same hSWI/SNF subunits as those targeted by c-Myc. These observations prompted us to examine the expression profile of the c-Myc target genes, carbamoyl-phosphate synthase-aspartate carbamoyltransferase-dihydroorotase (cad) and nucleolin (nuc). We found that cad repression is altered in cells that express inactive Brg1 and in cells treated with the HDAC inhibitor depsipeptide. Using chromatin immunoprecipitation assays, we found that Brg1, mSin3A, HDAC2, and PRMT5 are directly recruited to the cad promoter. These results suggest that hSWI/SNF complexes, through their ability to interact with activator and repressor proteins, control expression of genes involved in cell growth and proliferation.
 ...
PMID:mSin3A/histone deacetylase 2- and PRMT5-containing Brg1 complex is involved in transcriptional repression of the Myc target gene cad. 1455 96

In this study we selected three breast cancer cell lines (SKBR3, SUM149 and SUM190) with different oncogene expression levels involved in ERBB2 and EGFR signaling pathways as a model system for the evaluation of selective integration of subsets of transcriptomic and proteomic data. We assessed the oncogene status with reads per kilobase per million mapped reads (RPKM) values for ERBB2 (14.4, 400, and 300 for SUM149, SUM190, and SKBR3, respectively) and for EGFR (60.1, not detected, and 1.4 for the same 3 cell lines). We then used RNA-Seq data to identify those oncogenes with significant transcript levels in these cell lines (total 31) and interrogated the corresponding proteomics data sets for proteins with significant interaction values with these oncogenes. The number of observed interactors for each oncogene showed a significant range, e.g., 4.2% (JAK1) to 27.3% (MYC). The percentage is measured as a fraction of the total protein interactions in a given data set vs total interactors for that oncogene in STRING (Search Tool for the Retrieval of Interacting Genes/Proteins, version 9.0) and I2D (Interologous Interaction Database, version 1.95). This approach allowed us to focus on 4 main oncogenes, ERBB2, EGFR, MYC, and GRB2, for pathway analysis. We used bioinformatics sites GeneGo, PathwayCommons and NCI receptor signaling networks to identify pathways that contained the four main oncogenes and had good coverage in the transcriptomic and proteomic data sets as well as a significant number of oncogene interactors. The four pathways identified were ERBB signaling, EGFR1 signaling, integrin outside-in signaling, and validated targets of C-MYC transcriptional activation. The greater dynamic range of the RNA-Seq values allowed the use of transcript ratios to correlate observed protein values with the relative levels of the ERBB2 and EGFR transcripts in each of the four pathways. This provided us with potential proteomic signatures for the SUM149 and 190 cell lines, growth factor receptor-bound protein 7 (GRB7), Crk-like protein (CRKL) and Catenin delta-1 (CTNND1) for ERBB signaling; caveolin 1 (CAV1), plectin (PLEC) for EGFR signaling; filamin A (FLNA) and actinin alpha1 (ACTN1) (associated with high levels of EGFR transcript) for integrin signalings; branched chain amino-acid transaminase 1 (BCAT1), carbamoyl-phosphate synthetase (CAD), nucleolin (NCL) (high levels of EGFR transcript); transferrin receptor (TFRC), metadherin (MTDH) (high levels of ERBB2 transcript) for MYC signaling; S100-A2 protein (S100A2), caveolin 1 (CAV1), Serpin B5 (SERPINB5), stratifin (SFN), PYD and CARD domain containing (PYCARD), and EPH receptor A2 (EPHA2) for PI3K signaling, p53 subpathway. Future studies of inflammatory breast cancer (IBC), from which the cell lines were derived, will be used to explore the significance of these observations.
 ...
PMID:Genome wide proteomics of ERBB2 and EGFR and other oncogenic pathways in inflammatory breast cancer. 2364 60