• Genomics & Informatics
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• v.20 no.3
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• pp.26.1-26.19
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• 2022

Diabetes and its related complications are associated with long term damage and failure of various organ systems. The microvascular complications of diabetes considered in this study are diabetic retinopathy, diabetic neuropathy, and diabetic nephropathy. The aim is to identify the weighted co-expressed and differentially expressed genes (DEGs), major pathways, and their miRNA, transcription factors (TFs) and drugs interacting in all the three conditions. The primary goal is to identify vital DEGs in all the three conditions. The overlapped five genes (AKT1, NFKB1, MAPK3, PDPK1, and TNF) from the DEGs and the co-expressed genes were defined as key genes, which differentially expressed in all the three cases. Then the protein-protein interaction network and gene set linkage analysis (GSLA) of key genes was performed. GSLA, gene ontology, and pathway enrichment analysis of the key genes elucidates nine major pathways in diabetes. Subsequently, we constructed the miRNA-gene and transcription factor-gene regulatory network of the five gene of interest in the nine major pathways were studied. hsa-mir-34a-5p, a major miRNA that interacted with all the five genes. RELA, FOXO3, PDX1, and SREBF1 were the TFs interacting with the major five gene of interest. Finally, drug-gene interaction network elucidates five potential drugs to treat the genes of interest. This research reveals biomarker genes, miRNA, TFs, and therapeutic drugs in the key signaling pathways, which may help us, understand the processes of all three secondary microvascular problems and aid in disease detection and management.

• Asian Pacific Journal of Cancer Prevention
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• v.13 no.9
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• pp.4607-4611
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• 2012

Objective: Endometrial cancer (EC) is the most common gynecologic malignancy. Identification of potential biomarkers of EC would be helpful for the detection and monitoring of malignancy, improving clinical outcomes. Methods: The Weighted Gene Co-expression Network Analysis method was used to identify prognostic markers for EC in this study. Moreover, underlying molecular mechanisms were characterized by KEGG pathway enrichment and transcriptional regulation analyses. Results: Seven gene co-expression modules were obtained, but only the turquoise module was positively related with EC stage. Among the genes in the turquoise module, COL5A2 (collagen, type V, alpha 2) could be regulated by PBX (pre-B-cell leukemia homeobox 1)1/2 and HOXB1(homeobox B1) transcription factors to be involved in the focal adhesion pathway; CENP-E (centromere protein E, 312kDa) by E2F4 (E2F transcription factor 4, p107/p130-binding); MYCN (v-myc myelocytomatosis viral related oncogene, neuroblastoma derived [avian]) by PAX5 (paired box 5); and BCL-2 (B-cell CLL/lymphoma 2) and IGFBP-6 (insulin-like growth factor binding protein 6) by GLI1. They were predicted to be associated with EC progression via Hedgehog signaling and other cancer related-pathways. Conclusions: These data on transcriptional regulation may provide a better understanding of molecular mechanisms and clues to potential therapeutic targets in the treatment of EC.

• Interdisciplinary Bio Central
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• v.5 no.1
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• pp.1.1-1.8
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• 2013

High quality publicly-available transcriptomic data representing relationships in gene expression across a diverse set of biological conditions is used as a context network to explore transcriptomics of the CNS. The context network, 18367Hu-matrix, contains pairwise Pearson correlations for 22,215 human genes across18,637 human tissue samples1. To do this, we compute a network derived from biological samples from CNS cells and tissues, calculate clusters of co-expressed genes from this network, and compare the significance of these to clusters derived from the larger 18367Hu-matrix network. Sorting and visualization uses the publicly available software, MetaOmGraph (http://www.metnetdb.org/MetNet_MetaOm-Graph.htm). This identifies genes that characterize particular disease conditions. Specifically, differences in gene expression within and between two designations of glial cancer, astrocytoma and glioblastoma, are evaluated in the context of the broader network. Such gene groups, which we term outlier-networks, tease out abnormally expressed genes and the samples in which this expression occurs. This approach distinguishes 48 subnetworks of outlier genes associated with astrocytoma and glioblastoma. As a case study, we investigate the relationships among the genes of a small astrocytoma-only subnetwork. This astrocytoma-only subnetwork consists of SVEP1, IGF1, CHRNA3, and SPAG6. All of these genes are highly coexpressed in a single sample of anaplastic astrocytoma tumor (grade III) and a sample of juvenile pilocytic astrocytoma. Three of these genes are also associated with nicotine. This data lead us to formulate a testable hypothesis that this astrocytoma outlier-network provides a link between some gliomas/astrocytomas and nicotine.

• IMMUNE NETWORK
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• v.1 no.1
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• pp.14-25
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• 2001

Background: Bone marrow stromal cells (BMSCs) express many cell surface molecules, which regulate the proliferation and differentiation of immune cells within the bone marrow. Methods: To identify cell surface molecules, which can regulate cell proliferation through cell interaction, monoclonal antibodies (MoAbs) against BMSCs were produced. Among them, 1H8 MoAb, which recognized distinctly an 80 kDa protein, abolished myeloma cell proliferation that was induced by co-culturing with BMSCs. Results: IL-6 gene expression was increased when myeloma or stromal cells were treated with 1H8 MoAb. In addition, the expression of IL-6 receptor and CD40 was up-regulated by 1H8 treatment, suggesting that the molecule recognized by 1H8 MoAb is involved in cell proliferation by modulating the expression of cell growth-related genes. Myeloma cells contain high levels of reactive oxygen species (ROS), which are related to gene expression and tumorigenesis. Treatment with 1H8 decreased the intracellular ROS level and increased PAG antioxidant gene concomitantly. Finally, 1H8 induced the tyrosine phosphorylation of several proteins in U266. Conclusion: Taken together, 1H8 MoAb recognized the cell surface molecule and triggered the intracellular signals, which led to modulate gene expression and cell proliferation.

• Journal of Microbiology and Biotechnology
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• v.32 no.3
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• pp.387-395
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• 2022

Deciphering the metabolites of human diseases is an important objective of biomedical research. Here, we aimed to capture the core metabolites of Fanconi anemia (FA) using the bioinformatics method of a multi-omics composite network. Based on the assumption that metabolite levels can directly mirror the physiological state of the human body, we used a multi-omics composite network that integrates six types of interactions in humans (gene-gene, disease phenotype-phenotype, disease-related metabolite-metabolite, gene-phenotype, gene-metabolite, and metabolite-phenotype) to procure the core metabolites of FA. This method is applicable in predicting and prioritizing disease candidate metabolites and is effective in a network without known disease metabolites. In this report, we first singled out the differentially expressed genes upon different groups that were related with FA and then constructed the multi-omics composite network of FA by integrating the aforementioned six networks. Ultimately, we utilized random walk with restart (RWR) to screen the prioritized candidate metabolites of FA, and meanwhile the co-expression gene network of FA was also obtained. As a result, the top 5 metabolites of FA were tenormin (TN), guanosine 5'-triphosphate, guanosine 5'-diphosphate, triphosadenine (DCF) and adenosine 5'-diphosphate, all of which were reported to have a direct or indirect relationship with FA. Furthermore, the top 5 co-expressed genes were CASP3, BCL2, HSPD1, RAF1 and MMP9. By prioritizing the metabolites, the multi-omics composite network may provide us with additional indicators closely linked to FA.

• Asian Pacific Journal of Cancer Prevention
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• v.16 no.7
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• pp.2793-2800
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• 2015

In molecular-targeted cancer therapy, acquired resistance to gemcitabine is a major clinical problem that reduces its effectiveness, resulting in recurrence and metastasis of cancers. In spite of great efforts to reveal the overall mechanism of acquired gemcitabine resistance, no definitive genetic factors have been identified that are absolutely responsible for the resistance process. Therefore, we performed a cross-platform meta-analysis of three publically available microarray datasets for cancer cell lines with acquired gemcitabine resistance, using the R-based RankProd algorithm, and were able to identify a total of 158 differentially expressed genes (DEGs; 76 up- and 82 down-regulated) that are potentially involved in acquired resistance to gemcitabine. Indeed, the top 20 up- and down-regulated DEGs are largely associated with a common process of carcinogenesis in many cells. For the top 50 up- and down-regulated DEGs, we conducted integrated analyses of a gene regulatory network, a gene co-expression network, and a protein-protein interaction network. The identified DEGs were functionally enriched via Gene Ontology hierarchy and Kyoto Encyclopedia of Genes and Genomes pathway analyses. By systemic combinational analysis of the three molecular networks, we could condense the total number of DEGs to final seven genes. Notably, GJA1, LEF1, and CCND2 were contained within the lists of the top 20 up- or down-regulated DEGs. Our study represents a comprehensive overview of the gene expression patterns associated with acquired gemcitabine resistance and theoretical support for further clinical therapeutic studies.

• Genomics & Informatics
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• v.21 no.4
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• pp.46.1-46.10
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• 2023

Colon adenocarcinoma (COAD) is the predominant type of colorectal cancer. Early diagnosis and treatment can significantly improve the prognosis of COAD patients. Anoctamin 7 (ANO7), an anion channel protein, has been implicated in prostate cancer and other types of cancer. In this study, we analyzed the expression of ANO7 and its correlation with clinicopathological characteristics among COAD patients using the Gene Expression Profiling Interactive Analysis 2 (GEPIA2) and the University of Alabama at Birmingham CANcer (UALCAN) databases. The GEPIA2, Kaplan-Meier plotter, and the Survival Genie platform were employed for survival analysis. The co-expression network and potential function of ANO7 in COAD were analyzed using GeneFriends, the Database for Annotation, Visualization and Integrated Discovery (DAVID), GeneMANIA, and Pathway Studio. Our data analysis revealed a significant reduction in ANO7 expression levels within COAD tissues compared to normal tissues. Additionally, ANO7 expression was found to be associated with race and histological subtype. The COAD patients exhibiting low ANO7 expression had lower survival rates compared to those with high ANO7 expression. The genes correlated with ANO7 were significantly enriched in proteolysis and mucin type O-glycan biosynthesis pathway. Furthermore, ANO7 demonstrated a direct interaction and a positive co-expression correlation with mucin 2 (MUC2). In conclusion, our findings suggest that ANO7 might serve as a potential prognostic biomarker and potentially plays a role in proteolysis and mucin biosynthesis in the context of COAD.

• IMMUNE NETWORK
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• v.11 no.6
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• pp.376-382
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• 2011

Background: Carbon monoxide (CO) is a cytoprotective and homeostatic molecule with important signaling capabilities in physiological and pathophysiological situations. CO protects cells/tissues from damage by free radicals or oxidative stress. NAD(P)H:quinone oxidoreductase (NQO1) is a highly inducible enzyme that is regulated by the Kelch-like ECH-associated protein 1 (Keap1)/nuclear factor erythroid 2-related factor 2 (Nrf2)/antioxidant response element (ARE) pathway, which is central to efficient detoxification of reactive metabolites and reactive oxygen species (ROS). Methods: We generated NQO1 promoter construct. HepG2 cells were treated with CO Releasing Molecules-2 (CORM-2) or CO gas and the gene expressions were measured by RT-PCR, immunoblot, and luciferase assays. Results: CO induced expression of NQO1 in human hepatocarcinoma cell lines by activation of Nrf2. Exposure of HepG2 cells to CO resulted in significant induction of NQO1 in dose- and time-dependent manners. Analysis of the NQO1 promoter indicated that an antioxidant responsible element (ARE)-containing region was critical for the CO-induced Nrf2-dependent increase of NQO1 gene expression in HepG2 cells. Conclusion: Our results suggest that CO-induced Nrf2 increases the expression of NQO1 which is well known to detoxify reactive metabolites and ROS.

• Horticultural Science & Technology
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• v.32 no.6
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• pp.845-852
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• 2014

Among various abiotic stress factors, soil salinity decreases the photosynthetic rate, growth, and yield of plants. Recently, many genes have been reported to enhance salt tolerance. The objective of this study was to characterize the Brassica rapa Salt Stress Resistance (BrSSR) gene, of which the function was unclear, although the full-length sequence was known. To characterize the role of BrSSR, a B. rapa Chinese cabbage inbred line ('CT001') was transformed with pSL94 vector containing the full length BrSSR cDNA. Quantitative real-time polymerase chain reaction (qRT-PCR) analysis showed that the expression of BrSSR in the transgenic line was 2.59-fold higher than that in the wild type. Analysis of phenotypic characteristics showed that plants overexpressing BrSSR were resistant to salinity stress and showed normal growth. Microarray analysis of BrSSR over-expressing plants confirmed that BrSSR was strongly associated with ERD15 (AT2G41430), a gene encoding a protein containing a PAM2 motif (AT4G14270), and GABA-T (AT3G22200), all of which have been associated with salt tolerance, in the co-expression network of genes related to salt stress. The results of this study indicate that BrSSR plays an important role in plant growth and tolerance to salinity.

• Proceedings of the Korean Society for Bioinformatics Conference
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• 2003.10a
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• pp.164-169
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• 2003

In this paper, we propose the integrated Bayesian network framework to reconstruct genetic regulatory networks from genome expression data. The proposed model overcomes the dimensionality problem of multivariate analysis by building coherent sub-networks from confined gene clusters and combining these networks via intermediary points. Gene Shaving algorithm is used to cluster genes that share a common function or co-regulation. Retrieved clusters incorporate prior biological knowledge such as Gene Ontology, pathway, and protein protein interaction information for extracting other related genes. With these extended gene list, system builds genetic sub-networks using Bayesian network with MDL score and Sparse Candidate algorithm. Identifying functional modules of genes is done by not only microarray data itself but also well-proved biological knowledge. This integrated approach can improve there liability of a network in that false relations due to the lack of data can be reduced. Another advantage is the decreased computational complexity by constrained gene sets. To evaluate the proposed system, S. Cerevisiae cell cycle data [1] is applied. The result analysis presents new hypotheses about novel genetic interactions as well as typical relationships known by previous researches [2].