Dataset Information

Identification of microRNAs as potential biomarkers for lung adenocarcinoma using integrating genomics analysis.

ABSTRACT: Lung adenocarcinoma (LUAD) is the most common histological subtype of non-small cell lung cancer, but novel biomarkers for early diagnosis are lacking. Extensive effort has been exerted to identify miRNA biomarkers in LUAD. Unfortunately, high inter-lab variability and small sample sizes have produced inconsistent conclusions in this field. To resolve the above-mentioned limitations, we performed a comprehensive analysis based on LUAD miRNome profiling studies using the robust rank aggregation (RRA) method. Moreover, miRNA-gene interaction network, pathway enrichment analysis and Kaplan-Meier survival curves were used to investigate the clinical values and biological functions of the identified miRNAs. A total of six common differentially expressed miRNAs (DEMs) were identified in LUAD. An independent cohort further confirmed that four miRNAs (miR-21-5p, miR-210-3p, miR-182-5p and miR-183-5p) were up-regulated and two miRNAs (miR-126-3p and miR-218-5p) were down-regulated in LUAD tissues. Pathway enrichment analysis also suggested that the above-listed six DEMs may affect LUAD progression via the estrogen signaling pathway. Survival analysis based on the TCGA dataset revealed the potential prognostic values of six DEMs in patients with LUAD (P-value<0.01). In conclusion, we identified a panel of six miRNAs from LUAD using miRNome profiling studies. Our results provide evidence for the use of these six DEMs as novel diagnostic and prognostic biomarkers for LUAD patients.

SUBMITTER: Peng Z

PROVIDER: S-EPMC5609990 | biostudies-literature | 2017 Sep

REPOSITORIES: biostudies-literature

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Identification of microRNAs as potential biomarkers for lung adenocarcinoma using integrating genomics analysis.

Peng Zhuo Z Pan Longfei L Niu Zequn Z Li Wei W Dang Xiaoyan X Wan Lin L Zhang Rui R Yang Shuanying S

Oncotarget 20170718 38

Lung adenocarcinoma (LUAD) is the most common histological subtype of non-small cell lung cancer, but novel biomarkers for early diagnosis are lacking. Extensive effort has been exerted to identify miRNA biomarkers in LUAD. Unfortunately, high inter-lab variability and small sample sizes have produced inconsistent conclusions in this field. To resolve the above-mentioned limitations, we performed a comprehensive analysis based on LUAD miRNome profiling studies using the robust rank aggregation ( ...[more]

PMID: 28969058

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Project description:Brain metastases originating from lung adenocarcinoma (LAD) occur frequently. The aim of the current study was to assess potential biomarkers for the prognosis of lung adenocarcinoma brain metastasis (LAD-BM) through the analysis of gene expression microarrays. The current study downloaded two gene expression datasets, GSE14108 and GSE10245, from the Gene Expression Omnibus database. From GSE14108 and GSE10245, 19 LAD-BM samples and 40 primary LAD samples were selected for analysis. To identify the differentially expressed genes (DEGs), the current study compared the two sample groups, using the limma R package. Subsequently, pathway enrichment analysis was conducted using the Cluster Profiler R package, and the construction of the protein-protein interaction (PPI) network was executed utilizing the Search Tool for the Retrieval of Interacting Genes database. The microRNA-target network was built using the TargetScore R package. Then, these networks were established and visualized using Cytoscape software. An array of 463 DEGs was identified in the LAD-BM samples, including 256 upregulated and 207 downregulated genes. Based on functional term enrichment analysis using the Gene Ontology database and signaling pathway enrichment analysis using the Kyoto Encyclopedia of Genes and Genomes database, it was identified that the overlapping DEGs were primarily involved in chemokine-associated signal transduction, which may mediate lung cancer cell metastasis to the brain. Chemokine ligand 2, lysozyme, matrix metalloproteinase-2 (MMP-2), lysyl oxidase (LOX) and granzyme B were identified as potential biomarkers according to a topological analysis of the PPI networks. Two notable nodes, MMP-2 and LOX, appeared in the PPI network and were key points in the microRNA-target network, as they were regulated by hsa-let-7d. Many DEGs and microRNAs were regarded as prognostic biomarkers for lung adenocarcinoma metastasis in the current study. These DEGs were primarily associated with chemokine-mediated signaling pathways. In addition, MMP-2 and LOX were predicted to be targets of hsa-let-7d.

Dataset Information

Identification of microRNAs as potential biomarkers for lung adenocarcinoma using integrating genomics analysis.

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Identification of microRNAs as potential biomarkers for lung adenocarcinoma using integrating genomics analysis.

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