Gene/Protein Disease Symptom Drug Enzyme Compound
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Query: EC:2.7.11.12 (PKG)
 2,515 document(s) hit in 31,850,051 MEDLINE articles (0.00 seconds)

New method for purification of phosphatase inhibitor 1 (PPI-1) was developed which avoid the phosphorylation of PPI-1 during the purification and provides a high yield of highly pure preparation. Using this preparation, it was shown that PPI-1 was stoichiometrically phosphorylated by cGMP-dependent protein kinase at Thr-35 and the phosphorylated PPI-1 potently inhibited protein phosphatase 1. Addition of the phosphorylated PPI-1 to beta-escin-skinned single smooth muscle cells resulted in force development of the cells at the submaximal pCa2+. The results suggest that the phosphorylation of PPI-1 can be the mechanism for modifying the Ca2+ sensitivity of smooth muscle contractile response.
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PMID:Enhancement of smooth muscle contraction with protein phosphatase inhibitor 1: activation of inhibitor 1 by cGMP-dependent protein kinase. 860 41

BACKGROUND This study aimed to identify key genes contributing to pathological complete response (pCR) to chemotherapy by mRNA sequencing (RNA-seq). MATERIAL AND METHODS RNA was extracted from the frozen biopsy tissue of patients with pathological complete response and patients with non-pathological complete response. Sequencing was performed on the HiSeq2000 platform. Differentially expressed genes (DEGs) were identified between the pCR group and non-pCR (NpCR) group. Pathway enrichment analysis of DEGs was performed. A protein-protein interaction network was constructed, then module analysis was performed to identify a subnetwork. Finally, transcription factors were predicted. RESULTS A total of 673 DEGs were identified, including 419 upregulated ones and 254 downregulated ones. The PPI network constructed consisted of 276 proteins forming 471 PPI pairs, and a subnetwork containing 18 protein nodes was obtained. Pathway enrichment analysis revealed that PLCB4 and ADCY6 were enriched in pathways renin secretion, gastric acid secretion, gap junction, inflammatory mediator regulation of TRP channels, retrograde endocannabinoid signaling, melanogenesis, cGMP-PKG signaling pathway, calcium signaling pathway, chemokine signaling pathway, cAMP signaling pathway, and rap1 signaling pathway. CNR1 was enriched in the neuroactive ligand-receptor interaction pathway, retrograde endocannabinoid signaling pathway, and rap1 signaling pathway. The transcription factor-gene network consists of 15 transcription factors and 16 targeted genes, of which 5 were downregulated and 10 were upregulated. CONCLUSIONS We found key genes that may contribute to pCR to chemotherapy, such as PLCB4, ADCY6, and CNR1, as well as some transcription factors.
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PMID:RNA Sequencing Uncovers Molecular Mechanisms Underlying Pathological Complete Response to Chemotherapy in Patients with Operable Breast Cancer. 2888 Aug 52

Background: Glioblastoma multiforme (GBM), the most common and aggressive human malignant brain tumor, is notorious for its limited treatment options and poor prognosis. MicroRNAs (miRNAs) are found to be involved in tumorigenesis of GBM. However, a comprehensive miRNA-mRNA regulatory network has still not been established. Methods: A miRNA microarray dataset (GSE90603) was obtained from GEO database. Then, we employed GEO2R tool to perform differential expression analysis. Potential transcription factors and target genes of screened differentially expressed miRNAs (DE-miRNAs) were predicted. The GBM mRNA dataset were downloaded from TCGA database for identifying differentially expressed genes (DEGs). Next, GO annotation and KEGG pathway enrichment analysis was conducted. PPI network was then established, and hub genes were identified via Cytoscape software. The expression and prognostic roles of hub genes was further evaluated. Results: Total 33 DE-miRNAs, consisting of 10 upregulated DE-miRNAs and 23 downregulated DE-miRNAs, were screened. SP1 was predicted to potentially regulate most of screened DE-miRNAs. Three thousand and twenty seven and 3,879 predicted target genes were obtained for upregulated and downregulated DE-miRNAs, respectively. Subsequently, 1,715 upregulated DEGs and 1,259 downregulated DEGs were identified. Then, 149 and 295 potential downregulated and upregulated genes commonly appeared in target genes of DE-miRNAs and DEGs were selected for GO annotation and KEGG pathway enrichment analysis. The downregulated genes were significantly enriched in cGMP-PKG signaling pathway and calcium signaling pathway whereas the upregulated genes were enriched in pathways in cancer and PI3K-Akt signaling pathway. Construction and analysis of PPI network showed that STXBP1 and TP53 were recognized as hub genes with the highest connectivity degrees. Expression analytic result of the top 20 hub genes in GBM using GEPIA database was generally identical with previous differential expression analysis for TCGA data. EGFR, PPP3CB, and MYO5A expression was significantly associated with patients' OS. Conclusions: In this study, we established a potential GBM-related miRNA-mRNA regulatory network, which explores a comprehensive understanding of the molecular mechanisms and provides key clues in seeking novel therapeutic targets for GBM. In the future, more experiments need to be performed to validate our current findings.
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PMID:Construction of Potential Glioblastoma Multiforme-Related miRNA-mRNA Regulatory Network. 3097 89