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pmid:24573402

Identification of differentially expressed microRNAs in metastatic melanoma using next-generation sequencing technology.

Min Qi · Xiaoyuan Huang · Lei Zhou · Jianglin Zhang

International journal of molecular medicine · 2014 doi:10.3892/ijmm.2014.1668

Paper

complete

Experiment

complete

Data

partial

Analysis

complete

Execution

absent

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title
Identification of differentially expressed microRNAs in metastatic melanoma using next-generation sequencing technology.
doi
10.3892/ijmm.2014.1668
pmid
24573402
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Min Qi
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Xiaoyuan Huang
[2]
Lei Zhou
[3]
Jianglin Zhang
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International journal of molecular medicine
year
2014
abstract
In this study, we investigated differentially expressed microRNAs (miRNAs or miRs) and their functions in metastatic melanoma using next-generation sequencing technology. The GSE36236 data set was downloaded from the Gene Expression Omnibus (GEO) database and 4 primary cutaneous melanoma samples (used as controls) and 3 metastatic melanoma samples were selected from 31 samples for further analysis. Firstly, the differentially expressed miRNAs were screened by limma package in R language. Secondly, the target genes of the miRNAs were retrieved with TargetScanHuman 6.2, and the interactions among these genes were identified by String and an interaction network was established. Finally, functional and pathway analyses were performed for the genes in the network using Expression Analysis Systematic Explorer (EASE). A total of 4 differentially expressed miRNAs (hsa-miR-146, hsa-miR-27, hsa-miR-877 and hsa-miR-186) were obtained between the metastatic melanoma and primary cutaneous melanoma samples. We predicted 101 high-confidence target genes of hsa-miR-27 and obtained a network with 41 interactions. Finally, functional and pathway analyses revealed that the genes in the network were significantly enriched at the transcriptional level. Differentially expressed miRNAs were identified in the metastatic melanoma compared with the primary cutaneous melanoma samples and the target genes of hsa-miR-27 were found to be significantly enriched at the transcriptional level. The results presented in our study may prove helpful in the diagnosis and treatment of metastatic melanoma.
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After the expression levels were determined, the differentially expressed miRNAs were screened out between the metastatic melanoma and primary cutaneous melanoma (controls) samples with limma package in R language (21); a p-value <0.05 and |logFC|>1 were set as the cut-off values.
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After the expression levels were determined, the differentially expressed miRNAs were screened out between the metastatic melanoma and primary cutaneous melanoma (controls) samples with limma package in R language (21); a p-value <0.05 and |logFC|>1 were set as the cut-off values.
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The GSE36236 data set was downloaded from the Gene Expression Omnibus (GEO) database and 4 primary cutaneous melanoma samples (used as controls) and 3 metastatic melanoma samples were selected from 31 samples for further analysis.
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Headline result: A total of 4 differentially expressed miRNAs were obtained between metastatic melanoma and primary cutaneous melanoma samples. Statistical method: differentially expressed miRNAs were screened using the limma package in R. Route to source data: the GSE36236 dataset was downloaded from the Gene Expression Omnibus (GEO) database, from which 4 primary cutaneous melanoma control samples and 3 metastatic melanoma samples were selected for analysis.
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A total of 4 differentially expressed miRNAs (hsa-miR-146, hsa-miR-27, hsa-miR-877 and hsa-miR-186) were obtained between the metastatic melanoma and primary cutaneous melanoma samples.
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Firstly, the differentially expressed miRNAs were screened by limma package in R language.
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The GSE36236 data set was downloaded from the Gene Expression Omnibus (GEO) database and 4 primary cutaneous melanoma samples (used as controls) and 3 metastatic melanoma samples were selected from 31 samples for further analysis.
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Headline result: A total of 4 differentially expressed miRNAs were obtained between metastatic melanoma and primary cutaneous melanoma samples. Statistical method: differentially expressed miRNAs were screened using the limma package in R. Route to source data: the GSE36236 dataset was downloaded from the Gene Expression Omnibus (GEO) database, from which 4 primary cutaneous melanoma control samples and 3 metastatic melanoma samples were selected for analysis.
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