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1.
J Periodontal Res ; 53(5): 916-923, 2018 Oct.
Article in English | MEDLINE | ID: mdl-29974476

ABSTRACT

BACKGROUND AND OBJECTIVE: Elevated levels of matrix metalloproteinase-7 (MMP7) have been observed in serum samples of subjects with type 2 diabetes mellitus (T2DM) and in gingival tissues of subjects with periodontitis. The aim of the present study was to collect in vivo and in silico evidence on the role of MMP7 in the interplay between T2DM and generalized periodontitis (GP). MATERIAL AND METHODS: The extent of MMP7 expression and localization were immunohistochemically analyzed in gingival tissues of patients with GP with T2DM (T2DM/GP, n = 11), systemically healthy patients with GP (n = 7), and systemically and periodontally healthy controls (n = 11). An in silico network model was built to determine the interactions between MMP7 and T2DM pathways. Regulation of neutrophil transmigration by MMP7 was analyzed in a knock-out mice model. RESULTS: In human gingival tissues, the proportion of cells with robust MMP7 expression was elevated in patients with T2DM/GP in comparison to controls (P = .014). According to the in silico analysis, "hydroxyl radical" and "hydrogen peroxide" compounds were among the most central nodes of the network, and were within the shortest paths connecting "glucose" to "MMP7." In MMP7 knock-out mice, an intense accumulation of neutrophils was observed in the gingival epithelium as compared to wild-type mice (P = .0001). CONCLUSION: Elevated MMP7 expression in gingival tissues of patients with T2DM/GP is related to the activation of reactive oxygen species by hyperglycemia. Suppression of MMP7 expression results in impaired neutrophil transmigration in gingiva.


Subject(s)
Diabetes Mellitus, Type 2/metabolism , Matrix Metalloproteinase 7/metabolism , Periodontitis/metabolism , Adult , Aged , Animals , Case-Control Studies , Female , Humans , Immunoenzyme Techniques , Male , Mice , Mice, Knockout , Middle Aged , Periodontitis/diagnostic imaging , Radiography, Panoramic , Turkey
2.
Cell Death Dis ; 5: e1250, 2014 May 22.
Article in English | MEDLINE | ID: mdl-24853428

ABSTRACT

Autism and Alzheimer's disease (AD) are, respectively, neurodevelopmental and degenerative diseases with an increasing epidemiological burden. The AD-associated amyloid-ß precursor protein-α has been shown to be elevated in severe autism, leading to the 'anabolic hypothesis' of its etiology. Here we performed a focused microarray analysis of genes belonging to NOTCH and WNT signaling cascades, as well as genes related to AD and apoptosis pathways in cerebellar samples from autistic individuals, to provide further evidence for pathological relevance of these cascades for autism. By using the limma package from R and false discovery rate, we demonstrated that 31% (116 out of 374) of the genes belonging to these pathways displayed significant changes in expression (corrected P-values <0.05), with mitochondria-related genes being the most downregulated. We also found upregulation of GRIN1, the channel-forming subunit of NMDA glutamate receptors, and MAP3K1, known activator of the JNK and ERK pathways with anti-apoptotic effect. Expression of PSEN2 (presinilin 2) and APBB1 (or F65) were significantly lower when compared with control samples. Based on these results, we propose a model of NMDA glutamate receptor-mediated ERK activation of α-secretase activity and mitochondrial adaptation to apoptosis that may explain the early brain overgrowth and disruption of synaptic plasticity and connectome in autism. Finally, systems pharmacology analyses of the model that integrates all these genes together (NOWADA) highlighted magnesium (Mg(2+)) and rapamycin as most efficient drugs to target this network model in silico. Their potential therapeutic application, in the context of autism, is therefore discussed.


Subject(s)
Alzheimer Disease/genetics , Autistic Disorder/genetics , Cerebellum/metabolism , Connectome , Alzheimer Disease/drug therapy , Alzheimer Disease/pathology , Alzheimer Disease/physiopathology , Apoptosis/genetics , Autistic Disorder/drug therapy , Autistic Disorder/pathology , Autistic Disorder/physiopathology , Cerebellum/drug effects , Cerebellum/pathology , Cerebellum/physiopathology , Computer Simulation , Databases, Genetic , Drug Design , Gene Expression Profiling/methods , Gene Expression Regulation , Gene Regulatory Networks , Genetic Predisposition to Disease , Humans , Molecular Targeted Therapy , Oligonucleotide Array Sequence Analysis , Phenotype , Prognosis , Signal Transduction/genetics , Systems Biology , Transcription, Genetic
3.
Mol Biosyst ; 10(6): 1461-8, 2014 Jun.
Article in English | MEDLINE | ID: mdl-24668219

ABSTRACT

Pancreatic ductal adenocarcinoma (PDAC) is recognized world-wide as an aggressive disease with poor prognosis in patients with or without resection. Further knowledge about the biological mechanisms of PDAC is necessary to enable the identification of novel molecular markers and therapeutic targets for early diagnosis and improved treatment. Transcription factors are the final effectors of signaling pathways and regulate a number of cellular functions. Changes in their expression may contribute to cellular transformation and tumor progression. Thus, the aim of the present study was to identify the Master Regulators (MRs) of transcription potentially involved in PDAC disease. To achieve this goal, we utilized microarray data to correlate MR genes with the tumor phenotype. Analyses were performed with RTN, Limma, and Survival packages in the R environment. We identified Tubby-like protein 3 (TULP3) as a MR of transcription in PDAC samples. The prognostic value of TULP3 was assessed in three independent cohort analyses. Our data demonstrated that pancreatic cancer patients exhibiting high transcriptional levels of TULP3 showed a poor overall survival rate. High expression levels of TULP3 may play an essential role in pancreatic cancer progression and possibly lead to a poor clinical outcome. Our results highlight the potential use of TULP3 as a clinical prognostic biomarker for pancreatic adenocarcinoma.


Subject(s)
Adenocarcinoma/pathology , Carcinoma, Pancreatic Ductal/pathology , Computational Biology/methods , Proteins/genetics , Adenocarcinoma/genetics , Algorithms , Biomarkers, Tumor/genetics , Carcinoma, Pancreatic Ductal/genetics , Databases, Genetic , Humans , Intracellular Signaling Peptides and Proteins , Microarray Analysis/methods , Survival Analysis
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