• Title/Summary/Keyword: miRNA database

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Finding Specific Disease Related microRNA Using by Ranking Score with Integrated miRNA Database (miRNA 데이터베이스 통합 및 순위 결정에 의한 특정 질병 관련 microRNA의 추출 방법)

  • Ha, Ji-Hwan;Kim, Hyun-Jin;Park, Sang-Hyun
    • Proceedings of the Korea Information Processing Society Conference
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    • 2014.04a
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    • pp.671-674
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    • 2014
  • 최근 MicroRNA(miRNA)가 질병 발생과 밀접한 연관성이 있다고 밝혀진 이래, 이와 관련된 연구가 활발히 진행되고 있다. 하지만 각종 질병 관련 miRNA의 기능과 역할 그리고 질병 발생 메카니즘 등이 명백히 밝혀진 것이 없는 실정이다. 본 논문에서는 여러 종류의 miRNA 데이터베이스(miRecords, miRTarBase, miR2Disease 등)를 통합하고, 본 논문에서 새로이 제안하는 scoring 방법과 특정 질병과 관련된 miRNA의 순위결정과정을 통하여 질병과 연관성이 높은 miRNA을 밝혀내는 방법을 제안한다. 새로이 제안하는 방법을 바탕으로 miRNA와 특정 질병과의 연관성을 효과적으로 밝혀냈다.

HisCoM-mimi: software for hierarchical structural component analysis for miRNA-mRNA integration model for binary phenotypes

  • Kim, Yongkang;Park, Taesung
    • Genomics & Informatics
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    • v.17 no.1
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    • pp.10.1-10.3
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    • 2019
  • To identify miRNA-mRNA interaction pairs associated with binary phenotypes, we propose a hierarchical structural component model for miRNA-mRNA integration (HisCoM-mimi). Information on known mRNA targets provided by TargetScan is used to perform HisCoM-mimi. However, multiple databases can be used to find miRNA-mRNA signatures with known biological information through different algorithms. To take these additional databases into account, we present our advanced application software for HisCoM-mimi for binary phenotypes. The proposed HisCoM-mimi supports both TargetScan and miRTarBase, which provides manually-verified information initially gathered by text-mining the literature. By integrating information from miRTarBase into HisCoM-mimi, a broad range of target information derived from the research literature can be analyzed. Another improvement of the new HisCoM-mimi approach is the inclusion of updated algorithms to provide the lasso and elastic-net penalties for users who want to fit a model with a smaller number of selected miRNAs and mRNAs. We expect that our HisCoM-mimi software will make advanced methods accessible to researchers who want to identify miRNA-mRNA interaction pairs related with binary phenotypes.

MicroRNA Expression Profile Analysis Reveals Diagnostic Biomarker for Human Prostate Cancer

  • Liu, Dong-Fu;Wu, Ji-Tao;Wang, Jian-Ming;Liu, Qing-Zuo;Gao, Zhen-Li;Liu, Yun-Xiang
    • Asian Pacific Journal of Cancer Prevention
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    • v.13 no.7
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    • pp.3313-3317
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    • 2012
  • Prostate cancer is a highly prevalent disease in older men of the western world. MicroRNAs (miRNAs) are small RNA molecules that regulate gene expression via posttranscriptional inhibition of protein synthesis. To identify the diagnostic potential of miRNAs in prostate cancer, we downloaded the miRNA expression profile of prostate cancer from the GEO database and analysed the differentially expressed miRNAs (DE-miRNAs) in prostate cancerous tissue compared to non-cancerous tissue. Then, the targets of these DE-miRNAs were extracted from the database and mapped to the STRING and KEGG databases for network construction and pathway enrichment analysis. We identified a total of 16 miRNAs that showed a significant differential expression in cancer samples. A total of 9 target genes corresponding to 3 DE-miRNAs were obtained. After network and pathway enrichment analysis, we finally demonstrated that miR-20 appears to play an important role in the regulation of prostate cancer onset. MiR-20 as single biomarker or in combination could be useful in the diagnosis of prostate cancer. We anticipate our study could provide the groundwork for further experiments.

Identification of novel potential drugs and miRNAs biomarkers in lung cancer based on gene co-expression network analysis

  • Sara Hajipour;Sayed Mostafa Hosseini;Shiva Irani;Mahmood Tavallaie
    • Genomics & Informatics
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    • v.21 no.3
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    • pp.38.1-38.8
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    • 2023
  • Non-small cell lung cancer (NSCLC) is an important cause of cancer-associated deaths worldwide. Therefore, the exact molecular mechanisms of NSCLC are unidentified. The present investigation aims to identify the miRNAs with predictive value in NSCLC. The two datasets were downloaded from the Gene Expression Omnibus (GEO) database. Differentially expressed miRNAs (DEmiRNA) and mRNAs (DEmRNA) were selected from the normalized data. Next, miRNA-mRNA interactions were determined. Then, co-expression network analysis was completed using the WGCNA package in R software. The co-expression network between DEmiRNAs and DEmRNAs was calculated to prioritize the miRNAs. Next, the enrichment analysis was performed for DEmiRNA and DEmRNA. Finally, the drug-gene interaction network was constructed by importing the gene list to dgidb database. A total of 3,033 differentially expressed genes and 58 DEmiRNA were recognized from two datasets. The co-expression network analysis was utilized to build a gene co- expression network. Next, four modules were selected based on the Zsummary score. In the next step, a bipartite miRNA-gene network was constructed and hub miRNAs (let-7a-2-3p, let-7d-5p, let-7b-5p, let-7a-5p, and let-7b-3p) were selected. Finally, a drug-gene network was constructed while SUNITINIB, MEDROXYPROGESTERONE ACETATE, DOFETILIDE, HALOPERIDOL, and CALCITRIOL drugs were recognized as a beneficial drug in NSCLC. The hub miRNAs and repurposed drugs may act a vital role in NSCLC progression and treatment, respectively; however, these results must validate in further clinical and experimental assessments.

Identification of Hub Genes in the Pathogenesis of Ischemic Stroke Based on Bioinformatics Analysis

  • Yang, Xitong;Yan, Shanquan;Wang, Pengyu;Wang, Guangming
    • Journal of Korean Neurosurgical Society
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    • v.65 no.5
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    • pp.697-709
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    • 2022
  • Objective : The present study aimed to identify the function of ischemic stroke (IS) patients' peripheral blood and its role in IS, explore the pathogenesis, and provide direction for clinical research progress by comprehensive bioinformatics analysis. Methods : Two datasets, including GSE58294 and GSE22255, were downloaded from Gene Expression Omnibus database. GEO2R was utilized to obtain differentially expressed genes (DEGs). Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis of DEGs were performed using the database annotation, visualization and integrated discovery database. The protein-protein interaction (PPI) network of DEGs was constructed by search tool of searching interactive gene and visualized by Cytoscape software, and then the Hub gene was identified by degree analysis. The microRNA (miRNA) and miRNA target genes closely related to the onset of stroke were obtained through the miRNA gene regulatory network. Results : In total, 36 DEGs, containing 27 up-regulated and nine down-regulated DEGs, were identified. GO functional analysis showed that these DEGs were involved in regulation of apoptotic process, cytoplasm, protein binding and other biological processes. KEGG enrichment analysis showed that these DEGs mediated signaling pathways, including human T-cell lymphotropic virus (HTLV)-I infection and microRNAs in cancer. The results of PPI network and cytohubba showed that there was a relationship between DEGs, and five hub genes related to stroke were obtained : SOCS3, KRAS, PTGS2, EGR1, and DUSP1. Combined with the visualization of DEG-miRNAs, hsa-mir-16-5p, hsa-mir-181a-5p and hsa-mir-124-3p were predicted to be the key miRNAs in stroke, and three miRNAs were related to hub gene. Conclusion : Thirty-six DEGs, five Hub genes, and three miRNA were obtained from bioinformatics analysis of IS microarray data, which might provide potential targets for diagnosis and treatment of IS.

LncRNA XLOC_006390 facilitates cervical cancer tumorigenesis and metastasis as a ceRNA against miR-331-3p and miR-338-3p

  • Luan, Xiaotian;Wang, Yankui
    • Journal of Gynecologic Oncology
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    • v.29 no.6
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    • pp.95.1-95.17
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    • 2018
  • Objective: Cervical cancer is one of the most common malignant tumors. Our previous results showed that long non-coding RNA (lncRNA) XLOC_006390 plays an important role in cervical cancer. In this study, we have explored the mechanism of action of lncRNA XLOC_006390. Methods: LncRNA XLOC_006390 was proposed to exercise its function as a competing endogenous RNA (ceRNA), and its potential targeted miRNAs was predicted through the database LncBase Predicted v.2. Two miRNAs, miR-331-3p, and miR-338-3p, were chosen for the study. Expression of miRNAs and lncRNA in cervical cancer cells and tissues was detected by reverse transcription polymerase chain reaction. To determine the correlation, silencing of XLOC_006390, over-expression of miR-331-3p, and miR-338-3p was performed in SiHa and Caski cell lines, respectively. Results: Based on the interactive effect between miRNA and lncRNA, miR-331-3p and miR-338-3p were significantly downregulated in cervical cancer cells and tissues, and their expression levels were negatively related to that of lncRNA. Our results also showed that the expression of miR-331-3p target gene NRP2, miR-338-3p target genes PKM2, EYA2 was significantly downregulated when the XLOC_006390 was knocked down. Further, XLOC_006390 was found to facilitate cervical cancer tumorigenesis and metastasis by downregulating miR-331-3p and miR-338-3p expression. Conclusion: Taken together, our study demonstrated that XLOC_006390 may serve as a ceRNA and reversely regulates the expression of miR-331-3p and miR-338-3p, thus facilitating cervical cancer tumorigenesis and metastasis.

Insilico profiling of microRNAs in Korean ginseng (Panax ginseng Meyer)

  • Mathiyalagan, Ramya;Subramaniyam, Sathiyamoorthy;Natarajan, Sathishkumar;Kim, Yeon Ju;Sun, Myung Suk;Kim, Se Young;Kim, Yu-Jin;Yang, Deok Chun
    • Journal of Ginseng Research
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    • v.37 no.2
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    • pp.227-247
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    • 2013
  • MicroRNAs (miRNAs) are a class of recently discovered non-coding small RNA molecules, on average approximately 21 nucleotides in length, which underlie numerous important biological roles in gene regulation in various organisms. The miRNA database (release 18) has 18,226 miRNAs, which have been deposited from different species. Although miRNAs have been identified and validated in many plant species, no studies have been reported on discovering miRNAs in Panax ginseng Meyer, which is a traditionally known medicinal plant in oriental medicine, also known as Korean ginseng. It has triterpene ginseng saponins called ginsenosides, which are responsible for its various pharmacological activities. Predicting conserved miRNAs by homology-based analysis with available expressed sequence tag (EST) sequences can be powerful, if the species lacks whole genome sequence information. In this study by using the EST based computational approach, 69 conserved miRNAs belonging to 44 miRNA families were identified in Korean ginseng. The digital gene expression patterns of predicted conserved miRNAs were analyzed by deep sequencing using small RNA sequences of flower buds, leaves, and lateral roots. We have found that many of the identified miRNAs showed tissue specific expressions. Using the insilico method, 346 potential targets were identified for the predicted 69 conserved miRNAs by searching the ginseng EST database, and the predicted targets were mainly involved in secondary metabolic processes, responses to biotic and abiotic stress, and transcription regulator activities, as well as a variety of other metabolic processes.

MicroRNA Regulation in Systemic Lupus Erythematosus Pathogenesis

  • Yan, Sheng;Yim, Lok Yan;Lu, Liwei;Lau, Chak Sing;Chan, Vera Sau-Fong
    • IMMUNE NETWORK
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    • v.14 no.3
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    • pp.138-148
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    • 2014
  • MicroRNAs (miRNAs) are endogenous small RNA molecules best known for their function in post-transcriptional gene regulation. Immunologically, miRNA regulates the differentiation and function of immune cells and its malfunction contributes to the development of various autoimmune diseases including systemic lupus erythematosus (SLE). Over the last decade, accumulating researches provide evidence for the connection between dysregulated miRNA network and autoimmunity. Interruption of miRNA biogenesis machinery contributes to the abnormal T and B cell development and particularly a reduced suppressive function of regulatory T cells, leading to systemic autoimmune diseases. Additionally, multiple factors under autoimmune conditions interfere with miRNA generation via key miRNA processing enzymes, thus further skewing the miRNA expression profile. Indeed, several independent miRNA profiling studies reported significant differences between SLE patients and healthy controls. Despite the lack of a consistent expression pattern on individual dysregulated miRNAs in SLE among these studies, the aberrant expression of distinct groups of miRNAs causes overlapping functional outcomes including perturbed type I interferon signalling cascade, DNA hypomethylation and hyperactivation of T and B cells. The impact of specific miRNA-mediated regulation on function of major immune cells in lupus is also discussed. Although research on the clinical application of miRNAs is still immature, through an integrated approach with advances in next generation sequencing, novel tools in bioinformatics database analysis and new in vitro and in vivo models for functional evaluation, the diagnostic and therapeutic potentials of miRNAs may bring to fruition in the future.

Identification of Candidate Porcine miRNA-302/367 Cluster and Its Function in Somatic Cell Reprogramming

  • Son, Dong-Chan;Hwang, Jae Yeon;Lee, Chang-Kyu
    • Reproductive and Developmental Biology
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    • v.38 no.2
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    • pp.79-84
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    • 2014
  • MicroRNAs (miRNAs) are approximately 22 nucleotides of small noncoding RNAs that control gene expression at the posttranscriptional level through translational inhibition and destabilization of their target mRNAs. The miRNAs are phylogenetically conserved and have been shown to be instrumental in a wide variety of key biological processes including cell cycle regulation, apoptosis, metabolism, imprinting, and differentiation. Recently, a paper has shown that expression of the miRNA-302/367 cluster expressed abundantly in mouse and human embryonic stem cells (ESCs) can directly reprogram mouse and human somatic cells to induced pluripotent stem cells (iPSCs) efficiently in the absence of any of the four factors, Oct4, Sox2, c-Myc, and Klf4. To apply this efficient method to porcine, we analyzed porcine genomic sequence containing predicted porcine miRNA-302/367 cluster through ENSEMBL database, generated a non-replicative episomal vector system including miRNA-302/367 cluster originated from porcine embryonic fibroblasts (PEF), and tried to make porcine iPSCs by transfection of the miRNA-302/367 cluster. Colonies expressing EGFP and forming compact shape were found, but they were not established as iPSC lines. Our data in this study show that pig miRNA-302/367 cluster could not satisfy requirement of PEF reprogramming conditions for pluripotency. To make pig iPSC lines by miRNA, further studies on the role of miRNAs in pluripotency and new trials of transfection with conventional reprogramming factors are needed.

MiRNA Synergistic Network Construction and Enrichment Analysis for Common Target Genes in Small-cell Lung Cancer

  • Zhang, Tie-Feng;Cheng, Ke-Wen;Shi, Wei-Yin;Zhang, Jin-Tao;Liu, Ke-Di;Xu, Shu-Guang;Chen, Ji-Quan
    • Asian Pacific Journal of Cancer Prevention
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    • v.13 no.12
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    • pp.6375-6378
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    • 2012
  • Background: Small-cell lung cancer (also known as SCLC) is an aggressive form and untreated patients generally die within about 3 months. To obtain further insight into mechanism underlying malignancy with this cancer, an miRNA synergistic regulatory network was constructed and analyzed in the present study. Method: A miRNA microarray dataset was downloaded from the NCBI GEO database (GSE27435). A total of 546 miRNAs were identified to be expressed in SCLC cells. Then a miRNA synergistic network was constructed, and the included miRNAs mapped to the network. Topology analysis was also performed to analyze the properties of the synergistic network. Consequently, we could identified constitutive modules. Further, common target genes of each module were identified with CFinder. Finally, enrichment analysis was performed for target genes. Results: In this study, a miRNA synergistic network with 464 miRNAs and 2981 edges was constructed. According to the topology analysis, the topological properties between the networks constructed by LC related miRNAs and LC unrelated miRNAs were significantly different. Moreover, a module cilque0 could be identified in our network using CFinder. The module included three miRNAs (hsa-let-7c, hsa-let-7b and hsa-let-7d). In addition, several genes were found which were predicted to be common targets of cilque0. The enrichment analysis demonstrated that these target genes were enriched in MAPK signaling pathways. Conclusions: Although limitations exist in the current data, the results uncovered here are important for understanding the key roles of miRNAs in SCLC. However, further validation is required since our results were based on microarray data derived from a small sample size.