Gene/Protein Disease Symptom Drug Enzyme Compound
Pivot Concepts:   Target Concepts:
Query: EC:2.7.11.13 (protein kinase C)
 49,245 document(s) hit in 31,850,051 MEDLINE articles (0.00 seconds)

The development of a mammalian brain is a complex and long-lasting process. Not surprisingly, preterm birth is the leading cause of death in newborns and children. Advances in perinatal care reduced mortality, but morbidity still represents a major burden. New therapeutic approaches are thus desperately needed. Given that mesenchymal stem/stromal cells (MSCs) emerged as a promising candidate for cell therapy, we transplanted MSCs derived from the Wharton's Jelly (WJ-MSCs) to reduce the burden of immature brain injury in a murine animal model. WJ-MSCs transplantation resulted in protective activity characterized by reduced myelin loss and astroglial activation. WJ-MSCs improved locomotor behavior as well. To address the underlying mechanisms, we tested the key regulators of responses to DNA-damaging agents, such as cyclic AMP-dependent protein kinase/calcium-dependent protein kinase (PKA/PKC), cyclin-dependent kinase (CDK), ataxia-telangiectasia-mutated/ATM- and Rad3-related (ATM/ATR) substrates, protein kinase B (Akt), and 14-3-3 binding protein partners. We characterized WJ-MSCs using a specific profiler polymerase chain reaction array. We provide evidence that WJ-MSCs target pivotal regulators of the cell fate such as CDK/14-3-3/Akt signaling. We identified leukemia inhibitory factor as a potential candidate of WJ-MSCs' induced modifications as well. We hypothesize that WJ-MSCs may exert adaptive responses depending on the type of injury they are facing, making them prominent candidates for cell therapy in perinatal injuries.
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PMID:Wharton's Jelly Mesenchymal Stem Cells Protect the Immature Brain in Rats and Modulate Cell Fate. 2784 57

Protein phosphorylation is a major form of post-translational modification (PTM) that regulates diverse cellular processes. In silico methods for phosphorylation site prediction can provide a useful and complementary strategy for complete phosphoproteome annotation. Here, we present a novel bioinformatics tool, PhosphoPredict, that combines protein sequence and functional features to predict kinase-specific substrates and their associated phosphorylation sites for 12 human kinases and kinase families, including ATM, CDKs, GSK-3, MAPKs, PKA, PKB, PKC, and SRC. To elucidate critical determinants, we identified feature subsets that were most informative and relevant for predicting substrate specificity for each individual kinase family. Extensive benchmarking experiments based on both five-fold cross-validation and independent tests indicated that the performance of PhosphoPredict is competitive with that of several other popular prediction tools, including KinasePhos, PPSP, GPS, and Musite. We found that combining protein functional and sequence features significantly improves phosphorylation site prediction performance across all kinases. Application of PhosphoPredict to the entire human proteome identified 150 to 800 potential phosphorylation substrates for each of the 12 kinases or kinase families. PhosphoPredict significantly extends the bioinformatics portfolio for kinase function analysis and will facilitate high-throughput identification of kinase-specific phosphorylation sites, thereby contributing to both basic and translational research programs.
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PMID:PhosphoPredict: A bioinformatics tool for prediction of human kinase-specific phosphorylation substrates and sites by integrating heterogeneous feature selection. 2876 Oct 71

Breast cancer is the most common cancer in women, and some patients develop recurrence after standard therapy. Effective predictors are urgently needed to detect recurrence earlier. The activation of Hedgehog signaling in breast cancer is correlated with poor prognosis. PTCH1 is an essential membrane receptor of Hedgehog. However, there are few reports about mutations in Hedgehog genes in breast cancer. We conducted a comprehensive study via an experimental and bioinformatics approach to detect mutated genes in breast cancer. Twenty-two breast cancer patients who developed recurrence within 24 months postoperatively were enrolled with 22 control cancer patients. Targeted deep sequencing was performed to assess the mutations among individuals with breast cancer using a panel of 143 cancer-associated genes. Bioinformatics and public databases were used to predict the protein functions of the mutated genes. Mutations were identified in 44 breast cancer specimens, and the most frequently mutated genes were BRCA2, APC, ATM, BRCA1, NF1, TET2, TSC1, TSC2, NOTCH1, MSH2, PTCH1, TP53, PIK3CA, FBXW7, and RB1. Mutation of these genes was correlated with protein phosphorylation and autophosphorylation, such as peptidyl-tyrosine and protein kinase C phosphorylation. Among these highly mutated genes, mutations of PTCH1 were associated with poor prognosis and increased recurrence of breast cancer, especially mutations in exons 22 and 23. The public sequencing data from the COSMIC database were exploited to predict the functions of the mutations. Our findings suggest that mutation of PTCH1 is correlated with early recurrence of breast cancer patients and will become a powerful predictor for recurrence of breast cancer.
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PMID:Mutation of the PTCH1 gene predicts recurrence of breast cancer. 3170 74


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