Dataset Information

Bioinformatic identification of chemoresistance-associated microRNAs in breast cancer based on microarray data.

ABSTRACT: Breast cancer is the most commonly diagnosed cancer among females, and chemoresistance constitutes a major clinical obstacle to the treatment of this disease. MicroRNAs (miRNAs) are related to human cancer development, progression and drug resistance. To identify breast cancer chemoresistance-associated miRNAs, miRNA microarray dataset GSE71142, including five chemoresistant breast cancer tissues and five chemosensitive tissues, was downloaded from the Gene Expression Omnibus (GEO) database. Differentially expressed miRNAs (DE-miRNAs) were obtained by t-test and the potential target genes were predicted by miRWalk2.0. Functional and pathway enrichment analysis by WebGestalt was performed for the potential target genes of DE-miRNAs. Protein-protein interaction (PPI) network was established by STRING database and visualized by Cytoscape software. Enriched transcription factors by the target genes were obtained from FunRich. Breast cancer-associated miRNA?gene pairs were identified from miRWalk2.0. A total of 22 DE-miRNAs were screened out, including 10 upregulated miRNAs (e.g., miR-196a-5p) and 12 downregulated miRNAs (e.g., miR-4472) in the chemoresistant breast cancer tissues, compared with chemosensitive tissues. In total 1,278 target genes were screened out, and they were involved in breast cancer-related pathways such as pathways in cancer, signaling pathways regulating pluripotency of stem cells, endocrine resistance, breast cancer, mTOR signaling and Hippo signaling pathway. NOTCH1 and MAPK14 were identified as hub genes in the PPI network. EGR1 and SP1 were the most enriched transcription factors by the target genes. Several breast cancer-associated miRNA-gene pairs including miR-214-TP53 and miR-16-PPM1D were identified. The current bioinformatics study of miRNAs based on microarray may offer a new understanding into the mechanisms of breast cancer chemoresistance, and may identify novel miRNA therapeutic targets.

SUBMITTER: Wang YW

PROVIDER: S-EPMC5802023 | biostudies-literature | 2018 Mar

REPOSITORIES: biostudies-literature

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Bioinformatic identification of chemoresistance-associated microRNAs in breast cancer based on microarray data.

Wang Ya-Wen YW Zhang Weiguo W Ma Rong R

Oncology reports 20180110 3

Breast cancer is the most commonly diagnosed cancer among females, and chemoresistance constitutes a major clinical obstacle to the treatment of this disease. MicroRNAs (miRNAs) are related to human cancer development, progression and drug resistance. To identify breast cancer chemoresistance-associated miRNAs, miRNA microarray dataset GSE71142, including five chemoresistant breast cancer tissues and five chemosensitive tissues, was downloaded from the Gene Expression Omnibus (GEO) database. Dif ...[more]

PMID: 29328395

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Project description:BackgroundNeoadjuvant chemotherapy (NAC) is an effective therapeutic regimen for patients with breast cancer. However, some individuals cannot benefit from NAC because of drug resistance. To date, valid strategies about enhancing sensitivity of breast cancer to NAC are still scarce. miRNAs have been reported to proverbially be involved in the onset and development of malignancies including drug resistance.MethodsGSE73736 was downloaded from the GEO database. Student's t-test was conducted to acquire differentially expressed-miRNAs (DE-miRNAs). Potential target genes of DE-miRNAs were predicted by miRTarBase. Gene Ontology annotation and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses for these target genes were performed by database for annotation, visualization, and integrated discovery. Protein-protein interaction network was constructed by STRING database and visualized through Cytoscape software. The hub target gene-miRNA network was also established by Cytoscape software. Next, the expression of potential functional miRNAs in breast cancer cell lines and tissues was determined. Finally, the roles of miR-3617-3p, miR-3136-3p, and miR-520b in modulating breast cancer chemoresistance were further examined.ResultsA total of 123 DE-miRNAs were identified, including 60 upregulated miRNAs and 63 downregulated miRNAs in the chemoresistant breast cancer group when compared with the chemosensitive group. Six hundred and seventeen and 1,146 potential target genes for the top 10 most upregulated and downregulated miRNAs were predicted, respectively. Enrichment analyses revealed that these target genes were enriched in some cancer-associated or chemo-resistance-associated pathways, such as MAPK signaling pathway, wnt signaling pathway, and p53 signaling pathway. MAPK1 and PRDM10 were identified as hub genes in the protein-protein interaction network. The top 25 hub genes were potentially regulated by 16 DE-miRNAs, among which miR-3617-3p and miR-3136-3p were commonly upregulated, whereas miR-520b was downregulated in two chemoresistant breast cancer cells compared with chemosensitive cell. By analyzing TCGA data, we found that expression of miR-3136-3p and miR-520b was increased and decreased in breast cancer tissues, respectively. Moreover, functional experiments demonstrated that miR-3136-3p and miR-3617-3p could reduce chemosensitivity of breast cancer, whereas miR-520b could reverse chemoresistance.ConclusionThe present study, based on bioinformatics analysis and experimental validation, brings to light novel mechanisms of breast cancer NAC resistance.

Project description:Polycystic ovary syndrome (PCOS) is the most common endocrine disease in women of reproductive age. MicroRNAs (miRNAs or miRs) serve important roles in the physiological and pathological process of PCOS. To identify PCOS‑associated miRNAs, the dataset GSE84376 was extracted from the Gene Expression Omnibus database. Differentially expressed miRNAs (DE‑miRNAs) were obtained from Gene‑Cloud Biotechnology Information and potential target genes were predicted using TargetScan, DIANA‑microT‑CDS, miRDB and miRTarBase tools. Gene Ontology enrichment analysis was performed using Metascape and a protein‑protein interaction network was constructed using Cytoscape. Transcription factors were obtained from FunRich. DE‑miRNAs were verified by reverse transcription‑quantitative PCR. At the screening phase, there were seven DE‑miRNAs in the PCOS group not present in the control group. In total, 935 target genes were identified, which are involved in the development and maturation of oocytes. Mitogen‑activated protein kinase 1, phosphatase and tensin homolog, cAMP responsive element binding protein 1, signal transducer and activator of transcription 3, interferon γ, Fms‑related tyrosine kinase 1, transcription factor p65, insulin receptor substrate 1, DnaJ homolog superfamily C member 10 and casein kinase 2 α 1 were identified as the top 10 hub genes in the protein‑protein interaction network. Specificity protein 1 was the most enriched transcription factor. At the validation phase, the levels of Homo sapiens (hsa)‑miR‑3188 and hsa‑miR‑3135b were significantly higher in the PCOS group than in the control group. In addition, the expression level of hsa‑miR‑3135b was significantly correlated with the number of oocytes retrieved, the fertilization rate and the cleavage rate (P<0.05). The present bioinformatics study on miRNAs may offer a novel understanding of the mechanism of PCOS, and may serve to identify novel miRNA therapeutic targets.

Project description:Breast Cancer (BC) is one of the most common primary malignant tumors, which is life threatening. Previous studies have demonstrated that microRNAs (miRNA) may regulate or affect the incidence of BC. However, results of these studies are inconsistent, due to factors including the different sequencing platforms and sample selection methods used. To explore the key miRNAs involved in the pathogenesis of BC, and to use these miRNAs to monitor the tumor progression of BC, a systematic review was performed on the previous studies examining BC miRNA; the function of the target genes that were modulated by these key miRNAs were also analyzed. A total of 8 representative miRNA datasets examining the pathogenesis of BC were selected. Key miRNAs were identified by comparing the overlap between these datasets. Then, the target genes of these key miRNAs were predicted through TargetScan. Furthermore, functional enrichment analysis of target genes and transcription factor (TF) binding analysis was also performed using the Database for Annotation, Visualization and Integrated Discovery and Tfacts database, respectively. A total of 6 key miRNAs were identified by comparing the differentially expressed miRNAs datasets in the pathogenesis of BC. Compared with normal tissues, 3 miRNAs were upregulated: Hsa-miR-21b; hsa-miR-29b; and hsa-miR-155; and 3 miRNAs were downregulated: Hsa-miR-10b; hsa-miR-125; and hsa-miR-145. The target genes regulated by the up- and downregulated miRNAs were significantly enriched in the biological processes of 'transcriptional regulation', and these target genes depended on RNA polymerase II promoter and DNA template, respective to the up- and downregulated genes. The downregulated key miRNAs were specifically enriched in the biological processes of 'ephrin receptor signaling pathway' (GO: 0048013) and 'axon guidance' (GO: 0007411). TF analysis of the key miRNA target genes revealed that 104 TFs interacted with the 319 target genes of the upregulated miRNAs, while the 92 TFs interacted with the 254 target genes of the downregulated miRNAs. In total, there were 133 TFs and 63 (47.3%) TFs shared by the 2 types (up- and downregulated) of target genes. In summary, 6 key miRNAs in BC were identified by systematic review; the corresponding target genes and TFs that bind to these target genes were also identified, and the potential functions of target genes were revealed. These data may be beneficial to increasing the accuracy of BC treatment through monitoring miRNA.

Project description:BackgroundHepatocellular carcinoma (HCC) is one of the most lethal cancer, mainly attributing to its high tendency to metastasis. Vascular invasion provides a direct path for solid tumor metastasis. Mounting evidence has demonstrated that microRNAs (miRNAs) are related to human cancer onset and progression including invasion and metastasis.MethodsIn search of invasion-metastasis-associated miRNAs in HCC, microarray dataset GSE67140 was downloaded from the Gene Expression Omnibus database. Differentially expressed miRNAs (DE-miRNAs) were obtained by R software package and the potential target genes were predicted by miRTarBase. The database for annotation, visualization and integrated discovery (DAVID) was introduced to perform functional annotation and pathway enrichment analysis for these potential targets of DE-miRNAs. Protein-protein interaction (PPI) network was established by STRING database and visualized by Cytoscape software. The effects of the miR-494-3p and miR-126-3p on migration and invasion of HCC cell lines were evaluated by conducting wound healing assay and transwell assay.ResultsA total of 138 DE-miRNAs were screened out, including 57 upregulated miRNAs and 81 downregulated miRNAs in human HCC tumors with vascular invasion compared with human HCC tumors without vascular invasion. 762 target genes of the top three upregulated and downregulated miRNAs were predicted, and they were involved in HCC-related pathways, such as pathway in cancer, focal adhesion and MAPK signaling pathway. In the PPI network, the top 10 hub nodes with higher degrees were identified as hub genes, such as TP53 and MYC. Through constructing the miRNA-hub gene network, we found that most of hub genes could be potentially modulated by miR-494-3p and miR-126-3p. Of note, miR-494-3p and miR-126-3p was markedly upregulated and downregulated in HCC cell lines and tissues, respectively. In addition, overexpression of miR-494-3p could significantly promote HCC migration and invasion whereas overexpression of miR-126-3p exerted an opposite effect.ConclusionsTargeting miR-494-3p and miR-126-3p may provide effective and promising approaches to suppress invasion and metastasis of HCC.

Dataset Information

Bioinformatic identification of chemoresistance-associated microRNAs in breast cancer based on microarray data.

Publications

Bioinformatic identification of chemoresistance-associated microRNAs in breast cancer based on microarray data.

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