Identification of exosomal miR-455-5p and miR-1255a as therapeutic targets for breast cancer

Abstract Accumulated evidence has demonstrated exosomes of cancer cells carry microRNAs (miRNAs) to non-malignant cells to induce metastasis. The present study aimed to identify crucial exosomal miRNAs for breast cancer (BC) using microarray data (GSE83669 and GSE50429) from Gene Expression Omnibus database, including exosomal samples from human BC cells (MCF7, MDA-MB-231) and normal mammary epithelial cell line (MCF10, MCF-10A), as well as original cell samples. Differentially expressed miRNAs (DEMs) were identified using EdgeR package, and mRNA targets were predicted using miRWalk2 database. The target genes were overlapped with BC genes from Comparative Toxicogenomics Database (CTD) to construct BC-related interaction network. Potential functions were analyzed by DAVID. The expression of crucial miRNAs and target genes were confirmed in other microarray datasets or TCGA sequencing data. Their associations with survival and other clinical characteristics were validated by Kaplan–Meier plotter and LinkedOmics database. As a result, 9 and 8 DEMs were identified to be shared in two datasets for exosomal and original cells, respectively. Further comparison showed that miR-455-5p was specifically differentially expressed in exosomes, and miR-1255a was commonly expressed in exosomal and original cells samples. miR-455-5p could interact with CDKN1B to influence cell cycle process and miR-1255a could regulate SMAD4 to participate in TGF-β signaling pathway. High expressed miR-455-5p (basal-like) and miR-1255a (overall) were associated with poor overall survival, while the high expression of their target genes was associated with excellent overall, recurrence-free or distant metastasis-free survival. In conclusion, the present study preliminarily indicates that exosomal miR-455-5p and miR-1255a may be novel therapeutic targets for BC.

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Decoding Psoriasis: Integrated Bioinformatics Approach to Understand Hub Genes and Involved Pathways

Current Pharmaceutical Design ◽

10.2174/1381612826666200311130133 ◽

2020 ◽

Vol 26 (29) ◽

pp. 3619-3630

Author(s):

Saumya Choudhary ◽

Dibyabhaba Pradhan ◽

Noor S. Khan ◽

Harpreet Singh ◽

George Thomas ◽

...

Keyword(s):

Gene Expression ◽

Differentially Expressed Gene ◽

Therapeutic Targets ◽

Interaction Network ◽

Gene Expression Omnibus ◽

Differentially Expressed ◽

Keratinocyte Differentiation ◽

Hub Genes ◽

Lesional Skin ◽

Ncbi Gene Expression Omnibus

Background: Psoriasis is a chronic immune mediated skin disorder with global prevalence of 0.2- 11.4%. Despite rare mortality, the severity of the disease could be understood by the accompanying comorbidities, that has even led to psychological problems among several patients. The cause and the disease mechanism still remain elusive. Objective: To identify potential therapeutic targets and affecting pathways for better insight of the disease pathogenesis. Method: The gene expression profile GSE13355 and GSE14905 were retrieved from NCBI, Gene Expression Omnibus database. The GEO profiles were integrated and the DEGs of lesional and non-lesional psoriasis skin were identified using the affy package in R software. The Kyoto Encyclopaedia of Genes and Genomes pathways of the DEGs were analyzed using clusterProfiler. Cytoscape, V3.7.1 was utilized to construct protein interaction network and analyze the interactome map of candidate proteins encoded in DEGs. Functionally relevant clusters were detected through Cytohubba and MCODE. Results: A total of 1013 genes were differentially expressed in lesional skin of which 557 were upregulated and 456 were downregulated. Seven dysregulated genes were extracted in non-lesional skin. The disease gene network of these DEGs revealed 75 newly identified differentially expressed gene that might have a role in development and progression of the disease. GO analysis revealed keratinocyte differentiation and positive regulation of cytokine production to be the most enriched biological process and molecular function. Cytokines -cytokine receptor was the most enriched pathways. Among 1013 identified DEGs in lesional group, 36 DEGs were found to have altered genetic signature including IL1B and STAT3 which are also reported as hub genes. CCNB1, CCNA2, CDK1, IL1B, CXCL8, MKI 67, ESR1, UBE2C, STAT1 and STAT3 were top 10 hub gene. Conclusion: The hub genes, genomic altered DEGs and other newly identified differentially dysregulated genes would improve our understanding of psoriasis pathogenesis, moreover, the hub genes could be explored as potential therapeutic targets for psoriasis.

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Bioinformatics Analysis Reveals Functions of MicroRNAs in Rice Under the Drought Stress

Current Bioinformatics ◽

10.2174/1574893615666200207092410 ◽

2021 ◽

Vol 15 (8) ◽

pp. 927-936 ◽

Cited By ~ 3

Author(s):

Yan Peng ◽

Yuewu Liu ◽

Xinbo Chen

Keyword(s):

Drought Stress ◽

Target Genes ◽

Hot Spot ◽

Interaction Network ◽

Enrichment Analysis ◽

Differentially Expressed ◽

Protein Protein Interaction ◽

Promising Tool ◽

Differentially Expressed Mirnas ◽

Aba Biosynthesis

Background: Drought is one of the most damaging and widespread abiotic stresses that can severely limit the rice production. MicroRNAs (miRNAs) act as a promising tool for improving the drought tolerance of rice and have become a hot spot in recent years. Objective: In order to further extend the understanding of miRNAs, the functions of miRNAs in rice under drought stress are analyzed by bioinformatics. Method: In this study, we integrated miRNAs and genes transcriptome data of rice under the drought stress. Some bioinformatics methods were used to reveal the functions of miRNAs in rice under drought stress. These methods included target genes identification, differentially expressed miRNAs screening, enrichment analysis of DEGs, network constructions for miRNA-target and target-target proteins interaction. Results: (1) A total of 229 miRNAs with differential expression in rice under the drought stress, corresponding to 73 rice miRNAs families, were identiﬁed. (2) 1035 differentially expressed genes (DEGs) were identified, which included 357 up-regulated genes, 542 down-regulated genes and 136 up/down-regulated genes. (3) The network of regulatory relationships between 73 rice miRNAs families and 1035 DEGs was constructed. (4) 25 UP_KEYWORDS terms of DEGs, 125 GO terms and 7 pathways were obtained. (5) The protein-protein interaction network of 1035 DEGs was constructed. Conclusion: (1) MiRNA-regulated targets in rice might mainly involve in a series of basic biological processes and pathways under drought conditions. (2) MiRNAs in rice might play critical roles in Lignin degradation and ABA biosynthesis. (3) MiRNAs in rice might play an important role in drought signal perceiving and transduction.

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Characterization of Differentially Expressed miRNAs by CXCL12/SDF-1 in Human Bone Marrow Stromal Cells

BioMolecular Concepts ◽

10.1515/bmc-2021-0015 ◽

2021 ◽

Vol 12 (1) ◽

pp. 132-143

Author(s):

Matthew L. Potter ◽

Kathryn Smith ◽

Sagar Vyavahare ◽

Sandeep Kumar ◽

Sudharsan Periyasamy-Thandavan ◽

...

Keyword(s):

Bone Marrow ◽

Fracture Healing ◽

Osteogenic Differentiation ◽

Stromal Cell ◽

Target Genes ◽

Fatty Acid Biosynthesis ◽

Gene Expression Omnibus ◽

Differentially Expressed ◽

Mirna Regulation ◽

Stromal Cell Derived Factor

Abstract Stromal cell-derived factor 1 (SDF-1) is known to influence bone marrow stromal cell (BMSC) migration, osteogenic differentiation, and fracture healing. We hypothesize that SDF-1 mediates some of its effects on BMSCs through epigenetic regulation, specifically via microRNAs (miRNAs). MiRNAs are small non-coding RNAs that target specific mRNA and prevent their translation. We performed global miRNA analysis and determined several miRNAs were differentially expressed in response to SDF-1 treatment. Gene Expression Omnibus (GEO) dataset analysis showed that these miRNAs play an important role in osteogenic differentiation and fracture healing. KEGG and GO analysis indicated that SDF-1 dependent miRNAs changes affect multiple cellular pathways, including fatty acid biosynthesis, thyroid hormone signaling, and mucin-type O-glycan biosynthesis pathways. Furthermore, bioinformatics analysis showed several miRNAs target genes related to stem cell migration and differentiation. This study's findings indicated that SDF-1 induces some of its effects on BMSCs function through miRNA regulation.

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Identification of microRNAs and genes as biomarkers of atrial fibrillation using a bioinformatics approach

Journal of International Medical Research ◽

10.1177/0300060519852235 ◽

2019 ◽

Vol 47 (8) ◽

pp. 3580-3589 ◽

Cited By ~ 2

Author(s):

Yingyuan Li ◽

Wulin Tan ◽

Fang Ye ◽

Faling Xue ◽

Shaowei Gao ◽

...

Keyword(s):

Atrial Fibrillation ◽

Target Genes ◽

Enrichment Analysis ◽

Gene Expression Omnibus ◽

Differentially Expressed ◽

Control Groups ◽

Protein Protein Interaction ◽

Differentially Expressed Mirnas ◽

Software Modules ◽

And Control

Objective We aimed to explore potential microRNAs (miRNAs) and target genes related to atrial fibrillation (AF). Methods Data for microarrays GSE70887 and GSE68475, both of which include AF and control groups, were downloaded from the Gene Expression Omnibus database. Differentially expressed miRNAs between AF and control groups were identified within each microarray, and the intersection of these two sets was obtained. These miRNAs were mapped to target genes in the miRNet database. Functional annotation and enrichment analysis of these target genes was performed in the DAVID database. The protein-protein interaction (PPI) network from the STRING database and the miRNA-target-gene network were merged into a PPI-miRNA network using Cytoscape software. Modules of this network containing miRNAs were detected and further analyzed. Results Ten differentially expressed miRNAs and 1520 target genes were identified. Three PPI-miRNA modules were constructed, which contained miR-424, miR-15a, miR-542-3p, and miR-421 as well as their target genes, CDK1, CDK6, and CCND3. Conclusion The identified miRNAs and genes may be related to the pathogenesis of AF. Thus, they may be potential biomarkers for diagnosis and targets for treatment of AF.

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Bioinformatical Analysis of miRNA-mRNA Interaction Network Underlying Macrophage Aging and Cholesterol-Responsive Difference between Young and Aged Macrophages

BioMed Research International ◽

10.1155/2020/9267475 ◽

2020 ◽

Vol 2020 ◽

pp. 1-11

Author(s):

Jianqing Li ◽

Xue Yin ◽

Bingyu Zhang ◽

Chen Li ◽

Peirong Lu

Keyword(s):

Target Genes ◽

Density Lipoprotein ◽

Interaction Network ◽

Metabolic Process ◽

Cholesterol Homeostasis ◽

Age Related Macular Degeneration ◽

Differentially Expressed ◽

Functional Annotations ◽

Age Related ◽

Bioinformatical Analysis

Purpose. Macrophage aging is involved with the occurrence and progression of age-related macular degeneration (AMD). The purpose of this study was to identify the specific microRNAs (miRNA), mRNAs, and their interactions underlying macrophage aging and response to cholesterol through bioinformatical analysis in order to get a better understanding of the mechanism of AMD. Methods. The microarray data were obtained from Gene Expression Omnibus (accession GSE111304 and GSE111382). The age-related differentially expressed genes in macrophages were identified using R software. Further miRNA-mRNA interactions were analyzed through miRWalk, mirTarBase, starBase, and then produced by Cytoscape. The functional annotations including Gene Ontology and KEGG pathways of the miRNA target genes were performed by the DAVID and the STRING database. In addition, protein-protein interaction network was constructed to identify the key genes in response to exogenous cholesterol. Results. When comparing aged and young macrophages, a total of 14 miRNAs and 101 mRNAs were detected as differentially expressed. Besides, 19 validated and 544 predicted miRNA-mRNA interactions were detected. Lipid metabolic process was found to be associated with macrophage aging through functional annotations of the miRNA targets. After being treated with oxidized and acetylated low-density lipoprotein, miR-714 and 16 mRNAs differentially expressed in response to both kinds of cholesterol between aged and young macrophages. Among them, 6 miRNA-mRNA predicted pairs were detected. The functional annotations were mainly related to lipid metabolism process and farnesyl diphosphate farnesyl transferase 1 (FDFT1) was identified to be the key gene in the difference of response to cholesterol between aged and young macrophages. Conclusions. Lipid metabolic process was critical in both macrophage aging and response to cholesterol thus was regarded to be associated with the occurrence and progression of AMD. Moreover, miR-714-FDFT1 may modulate cholesterol homeostasis in aged macrophages and have the potential to be a novel therapeutic target for AMD.

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Uncovering potential lncRNAs and nearby mRNAs in systemic lupus erythematosus from the Gene Expression Omnibus dataset

Epigenomics ◽

10.2217/epi-2019-0145 ◽

2019 ◽

Vol 11 (16) ◽

pp. 1795-1809 ◽

Cited By ~ 2

Author(s):

Haiyu Cao ◽

Dong Li ◽

Huixiu Lu ◽

Jing Sun ◽

Haibin Li

Keyword(s):

Gene Expression ◽

Systemic Lupus Erythematosus ◽

Lupus Erythematosus ◽

Noncoding Rnas ◽

Interaction Network ◽

Gene Expression Omnibus ◽

Differentially Expressed ◽

Systemic Lupus ◽

Protein Protein Interaction ◽

Protein Protein Interaction Network

Aim: The aim of this study was to find potential differentially expressed long noncoding RNAs (lncRNAs) and mRNAs in systemic lupus erythematosus. Materials & methods: Differentially expressed lncRNAs and mRNAs were obtained in the Gene Expression Omnibus dataset. Functional annotation of differentially expressed mRNAs was performed, followed by protein–protein interaction network analysis. Then, the interaction network of lncRNA-nearby targeted mRNA was built. Results: Several interaction pairs of lncRNA-nearby targeted mRNA including NRIR-RSAD2, RP11-153M7.5-TLR2, RP4-758J18.2-CCNL2, RP11-69E11.4-PABPC4 and RP11-496I9.1-IRF7/ HRAS/ PHRF1 were identified. Measles and MAPK were significantly enriched signaling pathways of differentially expressed mRNAs. Conclusion: Our study identified several differentially expressed lncRNAs and mRNAs. And their interactions may play a crucial role in the process of systemic lupus erythematosus.

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Identification of key genes, pathways and potential therapeutic agents for IgA nephropathy using an integrated bioinformatics analysis

Journal of the Renin-Angiotensin-Aldosterone System ◽

10.1177/1470320320919635 ◽

2020 ◽

Vol 21 (2) ◽

pp. 147032032091963

Author(s):

Xiaoxue Chen ◽

Mindan Sun

Keyword(s):

Differentially Expressed Genes ◽

Immunoglobulin A ◽

Therapeutic Targets ◽

Gene Expression Omnibus ◽

Functional Enrichment ◽

Differentially Expressed ◽

Signal Pathways ◽

Immunoglobulin A Nephropathy ◽

Hub Genes ◽

Limma Package

Purpose: This study aims to identify immunoglobulin-A-nephropathy-related genes based on microarray data and to investigate novel potential gene targets for immunoglobulin-A-nephropathy treatment. Methods: Immunoglobulin-A-nephropathy chip data was obtained from the Gene Expression Omnibus database, which included 10 immunoglobulin-A-nephropathy and 22 normal samples. We used the limma package of R software to screen differentially expressed genes in immunoglobulin-A-nephropathy and normal glomerular compartment tissues. Functional enrichment (including cellular components, molecular functions, biological processes) and signal pathways were performed for the differentially expressed genes. The online analysis database (STRING) was used to construct the protein-protein interaction networks of differentially expressed genes, and Cytoscape software was used to identify the hub genes of the signal pathway. In addition, we used the Connectivity Map database to predict possible drugs for the treatment of immunoglobulin-A-nephropathy. Results: A total of 348 differentially expressed genes were screened including 107 up-regulated and 241 down-regulated genes. Functional analysis showed that up-regulated differentially expressed genes were mainly concentrated on leukocyte migration, and the down-regulated differentially expressed genes were significantly enriched in alpha-amino acid metabolic process. A total of six hub genes were obtained: JUN, C3AR1, FN1, AGT, FOS, and SUCNR1. The small-molecule drugs thapsigargin, ciclopirox and ikarugamycin were predicted therapeutic targets against immunoglobulin-A-nephropathy. Conclusion: Differentially expressed genes and hub genes can contribute to understanding the molecular mechanism of immunoglobulin-A-nephropathy and providing potential therapeutic targets and drugs for the diagnosis and treatment of immunoglobulin-A-nephropathy.

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Bioinformatic Analysis of Circular RNA-Associated ceRNA Network Associated with Hepatocellular Carcinoma

BioMed Research International ◽

10.1155/2019/8308694 ◽

2019 ◽

Vol 2019 ◽

pp. 1-14 ◽

Cited By ~ 1

Author(s):

Jiacheng Wu ◽

Shui Liu ◽

Yien Xiang ◽

Xianzhi Qu ◽

Yingjun Xie ◽

...

Keyword(s):

Hepatocellular Carcinoma ◽

Pathway Analysis ◽

Target Genes ◽

Kegg Pathway ◽

Interaction Network ◽

Bioinformatic Analysis ◽

Differentially Expressed ◽

Qrt Pcr ◽

Cerna Network ◽

Kegg Pathway Analysis

Hepatocellular carcinoma (HCC) is the sixth most common cancer worldwide and is associated with a high mortality rate and poor treatment efficacy. In an attempt to investigate the mechanisms involved in the pathogenesis of HCC, bioinformatic analysis and validation by qRT-PCR were performed. Three circRNA GEO datasets and one miRNA GEO dataset were selected for this purpose. Upon combined biological prediction, a total of 11 differentially expressed circRNAs, 15 differentially expressed miRNAs, and 560 target genes were screened to construct a circRNA-related ceRNA network. GO analysis and KEGG pathway analysis were performed for the 560 target genes. To further screen key genes, a protein-protein interaction network of the target genes was constructed using STRING, and the genes and modules with higher degree were identified by MCODE and CytoHubba plugins of Cytoscape. Subsequently, a module was screened out and subjected to GO enrichment analysis and KEGG pathway analysis. This module included eight genes, which were further screened using TCGA. Finally, UBE2L3 was selected as a key gene and the hsa_circ_0009910–miR-1261–UBE2L3 regulatory axis was established. The relative expression of the regulatory axis members was confirmed by qRT-PCR in 30 pairs of samples, including HCC tissues and adjacent nontumor tissues. The results suggested that hsa_circ_0009910, which was upregulated in HCC tissues, participates in the pathogenesis of HCC by acting as a sponge of miR-1261 to regulate the expression of UBE2L3. Overall, this study provides support for the possible mechanisms of progression in HCC.

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Construction of a Potential Breast Cancer-Related miRNA-mRNA Regulatory Network

BioMed Research International ◽

10.1155/2020/6149174 ◽

2020 ◽

Vol 2020 ◽

pp. 1-18

Author(s):

Xinhong Liu ◽

Feng Chen ◽

Fang Tan ◽

Fang Li ◽

Ruokun Yi ◽

...

Keyword(s):

Breast Cancer ◽

Transcription Factors ◽

Target Genes ◽

Differential Expression Analysis ◽

Mirna Gene ◽

Differentially Expressed ◽

Pathway Enrichment Analysis ◽

Epithelial Tissue ◽

Hub Genes ◽

Geo Database

Background. Breast cancer is a malignant tumor that occurs in the epithelial tissue of the breast gland and has become the most common malignancy in women. The regulation of the expression of related genes by microRNA (miRNA) plays an important role in breast cancer. We constructed a comprehensive breast cancer-miRNA-gene interaction map. Methods. Three miRNA microarray datasets (GSE26659, GSE45666, and GSE58210) were obtained from the GEO database. Then, the R software “LIMMA” package was used to identify differential expression analysis. Potential transcription factors and target genes of screened differentially expressed miRNAs (DE-miRNAs) were predicted. The BRCA GE-mRNA datasets (GSE109169 and GSE139038) were downloaded from the GEO database for identifying differentially expressed genes (DE-genes). Next, GO annotation and KEGG pathway enrichment analysis were conducted. A PPI network was then established, and hub genes were identified via Cytoscape software. The expression and prognostic roles of hub genes were further evaluated. Results. We found 6 upregulated differentially expressed- (DE-) miRNAs and 18 downregulated DE-miRNAs by analyzing 3 Gene Expression Omnibus databases, and we predicted the upstream transcription factors and downstream target genes for these DE-miRNAs. Then, we used the GEO database to perform differential analysis on breast cancer mRNA and obtained differentially expressed mRNA. We found 10 hub genes of upregulated DE-miRNAs and 10 hub genes of downregulated DE-miRNAs through interaction analysis. Conclusions. In this study, we have performed an integrated bioinformatics analysis to construct a more comprehensive BRCA-miRNA-gene network and provide new targets and research directions for the treatment and prognosis of BRCA.

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System Analysis of MIRNAs in Maize Internode Elongation

Biomolecules ◽

10.3390/biom9090417 ◽

2019 ◽

Vol 9 (9) ◽

pp. 417

Author(s):

Chuanxi Peng ◽

Xing Wang ◽

Tianyu Feng ◽

Rui He ◽

Mingcai Zhang ◽

...

Keyword(s):

Target Genes ◽

System Analysis ◽

Interaction Network ◽

Enrichment Analysis ◽

Functional Enrichment Analysis ◽

Functional Enrichment ◽

Differentially Expressed ◽

Internode Elongation ◽

Differentially Expressed Mirnas ◽

Post Transcriptional Regulation

MicroRNAs (miRNAs), the post-transcriptional gene regulators, are known to play an important role in plant development. The identification of differentially expressed miRNAs could better help us understand the post-transcriptional regulation that occurs during maize internode elongation. Accordingly, we compared the expression of MIRNAs between fixed internode and elongation internode samples and classified six differentially expressed MIRNAs as internode elongation-responsive miRNAs including zma-MIR160c, zma-MIR164b, zma-MIR164c, zma-MIR168a, zma-MIR396f, and zma-MIR398b, which target mRNAs supported by transcriptome sequencing. Functional enrichment analysis for predictive target genes showed that these miRNAs were involved in the development of internode elongation by regulating the genes respond to hormone signaling. To further reveal how miRNA affects internode elongation by affecting target genes, the miRNA–mRNA–PPI (protein and protein interaction) network was constructed to summarize the interaction of miRNAs and these target genes. Our results indicate that miRNAs regulate internode elongation in maize by targeting genes related to cell expansion, cell wall synthesis, transcription, and regulatory factors.

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