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)

Pancreatic ductal adenocarcinoma (PDAC) is the most lethal human malignant tumor, with a dismal 5-year survival rate of less than 5%. The lack of specific symptoms at early tumor stages and the paucity of biomarkers contribute to the poor diagnosis of pancreatic ductal adenocarcinoma. To improve prognosis, a screening biomarker for early diagnosis of pancreatic cancer is in urgent need. We searched the databases of expression profiling by array on GEO, aiming at comparing gene expression profile of matched pairs of pancreatic tumor and adjacent non-tumor tissues, and we screen out 4 suitable series of gene expression microarray data ("GSE15471", "GSE18670", "GSE28735" and "GSE58561"). After carefully analyzing, 13 DEGs (MYOF, SLC6A6, S100P, HK2, IFI44L, OSBPL3, IGF2BP3, PDK4, IL1R2, ERO1A, EGLN3, PLAC8 and ACSL5) are significantly differentially expressed in four microarray databases in common. After analyzing mRNA expression data and clinical follow-up survey provided in the TCGA database and clinicopathological data of 137 pancreatic ductal adenocarcinoma patients, we carefully demonstrated that three of these differentially expressed genes (ERO1A, OSBPL3 and IFI44L) are correlated with poor prognosis of pancreatic ductal adenocarcinoma patients. In addition, we revealed that cell-matrix adhesion and extracellular matrix were top significantly regulated pathways in pancreatic ductal adenocarcinoma and depicted two protein-protein interactions networks of extracellular matrix related Genes which are dysregulated according to 4 gene expression microarray data mentioned above ("GSE15471", "GSE18670", "GSE28735" and "GSE58561"), hoping to shed light on the etiology of PDAC and mechanisms of drug resistance in PDAC in this study.
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PMID:Integrated expression profiles analysis reveals novel predictive biomarker in pancreatic ductal adenocarcinoma. 2888 52

Lung cancer is a heterogeneous and complex disease with the highest incidence and mortality rate. The present study aims at defining the lung cancer phenome specificity of lipidomic profiles, screening target lipid-dependent transcriptional alternations, identifying target lipid-associated target genes, and exploring molecular mechanisms. Lung cancer-specific and lung cancer subtype-specific target lipids palmitic acid (C16:0) and stearic acid (C18:0) were found as target lipids by integrating clinical phenomics, lipidomics, and transcriptomics and exhibited antiproliferative effects in sensitive cells. The metabolism-associated gene ACSL5 or inflammation-associated gene CCL3 was identified in lung adenocarcinoma or small lung cancer cells, respectively. C16:0 or C18:0 could upregulate ACSL5 or CSF2 expression in a time- and dose-dependent pattern, and the deletion of both genes led to the insensitivity of cells. Target lipids increased the expression of PDK4 gene in different patterns and inhibited cell proliferation through alterations of intracellular energy. Thus, our data provide a new strategy to investigate the trans-points between clinical and phenomics and lipidomics and target lipid-associated molecular mechanisms to benefit from the discovery of new therapies.
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PMID:Roles of acyl-CoA synthetase long-chain family member 5 and colony stimulating factor 2 in inhibition of palmitic or stearic acids in lung cancer cell proliferation and metabolism. 3234 12