Gene/Protein Disease Symptom Drug Enzyme Compound
Pivot Concepts:   Target Concepts:
Query: EC:2.7.11.2 (PDK1)
 2,238 document(s) hit in 31,850,051 MEDLINE articles (0.00 seconds)

Major efforts have been put in anti-angiogenic treatment for glioblastoma (GBM), an aggressive and highly vascularized brain tumor with dismal prognosis. However clinical outcome with anti-angiogenic agents has been disappointing and tumors quickly develop escape mechanisms. In preclinical GBM models we have recently shown that bevacizumab, a blocking antibody against vascular endothelial growth factor, induces hypoxia in treated tumors, which is accompanied by increased glycolytic activity and tumor invasiveness. Genome-wide transcriptomic analysis of patient derived GBM cells including stem cell lines revealed a strong up-regulation of glycolysis-related genes in response to severe hypoxia. We therefore investigated the importance of glycolytic enzymes in GBM adaptation and survival under hypoxia, both in vitro and in vivo. We found that shRNA-mediated attenuation of glycolytic enzyme expression interfered with GBM growth under normoxic and hypoxic conditions in all cellular models. Using intracranial GBM xenografts we identified seven glycolytic genes whose knockdown led to a dramatic survival benefit in mice. The most drastic effect was observed for PFKP (PFK1, +21.8%) and PDK1 (+20.9%), followed by PGAM1 and ENO1 (+14.5% each), HK2 (+11.8%), ALDOA (+10.9%) and ENO2 (+7.2%). The increase in mouse survival after genetic interference was confirmed using chemical inhibition of PFK1 with clotrimazole. We thus provide a comprehensive analysis on the importance of the glycolytic pathway for GBM growth in vivo and propose PFK1 and PDK1 as the most promising therapeutic targets to address the metabolic escape mechanisms of GBM.
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PMID:Comprehensive analysis of glycolytic enzymes as therapeutic targets in the treatment of glioblastoma. 2593 51

Heroin addiction is a complex psychiatric disorder with a chronic course and a high relapse rate, which results from the interaction between genetic and environmental factors. Heroin addiction has a substantial heritability in its etiology; hence, identification of individuals with a high genetic propensity to heroin addiction may help prevent the occurrence and relapse of heroin addiction and its complications. The study aimed to identify a small set of genetic signatures that may reliably predict the individuals with a high genetic propensity to heroin addiction. We first measured the transcript level of 13 genes (RASA1, PRKCB, PDK1, JUN, CEBPG, CD74, CEBPB, AUTS2, ENO2, IMPDH2, HAT1, MBD1, and RGS3) in lymphoblastoid cell lines in a sample of 124 male heroin addicts and 124 male control subjects using real-time quantitative PCR. Seven genes (PRKCB, PDK1, JUN, CEBPG, CEBPB, ENO2, and HAT1) showed significant differential expression between the 2 groups. Further analysis using 3 statistical methods including logistic regression analysis, support vector machine learning analysis, and a computer software BIASLESS revealed that a set of 4 genes (JUN, CEBPB, PRKCB, ENO2, or CEBPG) could predict the diagnosis of heroin addiction with the accuracy rate around 85% in our dataset. Our findings support the idea that it is possible to identify genetic signatures of heroin addiction using a small set of expressed genes. However, the study can only be considered as a proof-of-concept study. As the establishment of lymphoblastoid cell line is a laborious and lengthy process, it would be more practical in clinical settings to identify genetic signatures for heroin addiction directly from peripheral blood cells in the future study.
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PMID:Genetic signatures of heroin addiction. 2749 86

Cancer cells metabolize glucose through glycolysis to promote cell proliferation even with abundant oxygen. Multiple glycolysis genes are deregulated during cancer development. Despite intensive effort, the cause of their deregulation remains incompletely understood. Here in this study, we discovered that DHX33 plays a critical role in Warburg effect of cancer cells. DHX33 deficient cells have markedly reduced glycolysis activity. Through RNA-seq analysis, we found multiple critical genes involved in Warburg effect were downregulated after DHX33 deficiency. These genes include lactate dehydrogenase A (LDHA), pyruvate dehydrogenase kinase 1 (PDK1), pyruvate kinase muscle isoform 2 (PKM2), enolase 1 (ENO1), ENO2, hexokinase 1/2, among others. With LDHA, PDK1, and PKM2 as examples, we further revealed that DHX33 altered the epigenetic marks around the promoter of glycolytic genes. This is through DHX33 in complex with Gadd45a-a growth arrest and DNA damage protein. DHX33 is required for the loading of Gadd45a and DNA dioxygenase Tet1 at the promoter sites, which resulted in active DNA demethylation and enhanced histone H4 acetylation. We conclude that DHX33 changes local epigenetic marks in favor of the transcription of glycolysis genes to promote cancer cell proliferation. Our study highlights the significance of RNA helicase DHX33 in Warburg effect and cancer therapeutics.
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PMID:Function of DHX33 in promoting Warburg effect via regulation of glycolytic genes. 3261 65