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In silico prediction and validation of potential therapeutic genes in pancreatic ?-cells associated with type 2 diabetes.

ABSTRACT: Diabetes mellitus is becoming a major health burden worldwide. Pancreatic ?-cell death is a characteristic of type 2 diabetes (T2D), but the underlying mechanisms of pancreatic ?-cell death remain unknown. Therefore, the aim of the present study was to identify potential targets in the pancreatic islet of T2D. The GSE20966 dataset was obtained from the Gene Expression Omnibus (GEO) database, and differentially expressed genes (DEGs) were identified by using the GEO2R tool. The Gene Ontology terms and Kyoto Encyclopedia of Genes and Genomes Pathway enrichment analysis of DEGs were further assessed using the Database for Annotation, Visualization and Integrated Discovery. Furthermore, protein-protein interaction (PPI) networks were constructed for the up- and downregulated genes using STRING databases and were then visualized with Cytoscape. The body weight, fasting blood glucose (FBG), pancreatic index and biochemistry parameters were measured in db/db mice. Moreover, the morphology of the pancreas was detected by hematoxylin and eosin staining, and hub genes were assessed using reverse transcription-quantitative PCR (RT-qPCR) and western blot analysis. In total, 570 DEGs were screened, including 376 upregulated and 194 downregulated genes, which were associated with 'complement activation, classical pathway', 'proteolysis', 'complement activation' and 'pancreatic secretion pathway'. It was found that the body weight, FBG, alanine aminotransferase, aspartate aminotransferase, total cholesterol, triglycerides, blood urea nitrogen, creatinine, fasting serum insulin, glucagon and low-density lipoprotein cholesterol levels were significantly higher in db/db mice, while high-density lipoprotein cholesterol levels and the pancreatic index were significantly decreased. Furthermore, albumin, interleukin-8, CD44, C-C motif chemokine ligand 2, hepatocyte growth factor, cystic fibrosis transmembrane conductance regulator, histone cluster 1 H2B family member n, mitogen-activated protein kinase 11 and neurotrophic receptor tyrosine kinase 2 were identified as hub genes in PPI network. RT-qPCR and western blotting results demonstrated the same expression trend in hub genes as found by the bioinformatics analysis. Therefore, the present study identified a series of hub genes involved in the progression of pancreatic ?-cell, which may help to develop effective therapeutic strategy for T2D.

SUBMITTER: Zhou DY

PROVIDER: S-EPMC7485321 | biostudies-literature | 2020 Nov

REPOSITORIES: biostudies-literature

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<i>In silico</i> prediction and validation of potential therapeutic genes in pancreatic β-cells associated with type 2 diabetes.

Zhou Di Yi DY Mou Xin X Liu Kaiyuan K Liu Wen Hong WH Xu Ya Qing YQ Zhou Danyang D

Experimental and therapeutic medicine 20200904 5

Diabetes mellitus is becoming a major health burden worldwide. Pancreatic β-cell death is a characteristic of type 2 diabetes (T2D), but the underlying mechanisms of pancreatic β-cell death remain unknown. Therefore, the aim of the present study was to identify potential targets in the pancreatic islet of T2D. The GSE20966 dataset was obtained from the Gene Expression Omnibus (GEO) database, and differentially expressed genes (DEGs) were identified by using the GEO2R tool. The Gene Ontology term ...[more]

PMID: 32952650

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Project description:BackgroundPancreatic beta-cells are the target of an autoimmune attack in type 1 diabetes mellitus (T1DM). This is mediated in part by cytokines, such as interleukin (IL)-1beta and interferon (IFN)-gamma. These cytokines modify the expression of hundreds of genes, leading to beta-cell dysfunction and death by apoptosis. Several of these cytokine-induced genes are potentially regulated by the IL-1beta-activated transcription factor (TF) nuclear factor (NF)-kappaB, and previous studies by our group have shown that cytokine-induced NF-kappaB activation is pro-apoptotic in beta-cells. To identify NF-kappaB-regulated gene networks in beta-cells we presently used a discriminant analysis-based approach to predict NF-kappaB responding genes on the basis of putative regulatory elements.ResultsThe performance of linear and quadratic discriminant analysis (LDA, QDA) in identifying NF-kappaB-responding genes was examined on a dataset of 240 positive and negative examples of NF-kappaB regulation, using stratified cross-validation with an internal leave-one-out cross-validation (LOOCV) loop for automated feature selection and noise reduction. LDA performed slightly better than QDA, achieving 61% sensitivity, 91% specificity and 87% positive predictive value, and allowing the identification of 231, 251 and 580 NF-kappaB putative target genes in insulin-producing INS-1E cells, primary rat beta-cells and human pancreatic islets, respectively. Predicted NF-kappaB targets had a significant enrichment in genes regulated by cytokines (IL-1beta or IL-1beta + IFN-gamma) and double stranded RNA (dsRNA), as compared to genes not regulated by these NF-kappaB-dependent stimuli. We increased the confidence of the predictions by selecting only evolutionary stable genes, i.e. genes with homologs predicted as NF-kappaB targets in rat, mouse, human and chimpanzee.ConclusionThe present in silico analysis allowed us to identify novel regulatory targets of NF-kappaB using a supervised classification method based on putative binding motifs. This provides new insights into the gene networks regulating cytokine-induced beta-cell dysfunction and death.

Project description:Background:Type 2 diabetes mellitus (T2DM) known as non-insulin-dependent diabetes mellitus, which is increasingly acknowledged as being associated with an increased risk for a series of cancers. Pancreatic cancer is currently the fourth most common cause of cancer-related mortality, which has been proved to be worsened by internal diabetic condition. However, the underlying molecular mechanisms are less addressed. Furthermore, current knowledge revealed that therapeutic strategy by anti-diabetes for pancreatic cancer under diabetes condition have no satisfactory efficacy, and nor by chemotherapy in our study. Methods:To clarify these mysteries and widen our knowledge, both obesity-associated and non-obese-associated T2DM mouse models were generated by chemical induction with streptozotocin (STZ) and leptin receptor knockout (db/db) in mice. Then, the process of tumor progression was researched, and the gene expression profiling of pancreatic cancer in mice was performed using RNA-seq. Results:Our results showed that pancreatic cancer malignancy was increased with notable proliferation and metastatic potential in two diabetic mice model. Totally, 136 and 64 significantly differentially expressed genes (DEGs) were identified in STZ and db/db mice by transcriptomic analysis. The results also suggested that different carcinogenesis-related genes and potential molecular mechanisms contribute to the malignancy of pancreatic cancer in obesity-associated and non-obesity-associated T2DM. In obesity-associated db/db mice, the GO subcategories associated with most of the genes with downregulated expression are involved in the immune response. However, in non-obesity-associated STZ mice, in addition to the immune response category, the enriched subcategories also included angiogenesis and the extracellular matrix. While, two genes respectively encoding MMP-2 and MMP-9 were simultaneously abnormal up-regulated in pancreatic cancer tissue from diabetic mice of both STZ and db/db, that could act as potential therapeutic targets for significantly suppressing the malignant progression. Furthermore, an optimizing therapeutic strategy was further proposed that combining MMP-2/9 inhibitor with gemcitabine significantly enhanced anti-tumor effects on pancreatic cancer under diabetic condition, providing a theoretical basis for clinical applications. Conclusions:Generally, this study provides a comprehensive insight into diabetes as a risk factor for pancreatic cancer and has the potential to guide the development of enhanced treatment strategies.

Dataset Information

In silico prediction and validation of potential therapeutic genes in pancreatic ?-cells associated with type 2 diabetes.

Publications

<i>In silico</i> prediction and validation of potential therapeutic genes in pancreatic β-cells associated with type 2 diabetes.

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