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Meta-Analysis
. 2017 Sep 19;15(1):175.
doi: 10.1186/s12957-017-1244-y.

Analysis of microRNA (miRNA) expression profiles reveals 11 key biomarkers associated with non-small cell lung cancer

Ke Wang  1 , Mingwei Chen  2 , Wei Wu  3
Affiliations
Meta-Analysis

Analysis of microRNA (miRNA) expression profiles reveals 11 key biomarkers associated with non-small cell lung cancer

Ke Wang et al. World J Surg Oncol. .

Abstract

Background: Non-small cell lung cancer (NSCLC) accounts for more than 85% of lung cancer cases which cause most of cancer-related deaths globally. However, the results vary largely in different studies due to different platforms and sample sizes. Here, we aim to identify the key miRNAs in the carcinogenesis of NSCLC that might be potential biomarkers for this cancer.

Methods: Meta-analysis was performed on miRNA profile using seven datasets of NSCLC studies. Furthermore, we predicted and investigated the functions of genes regulated by key miRNAs.

Results: Eleven key miRNAs were identified, including 2 significantly upregulated ones (hsa-miR-21-5p and hsa-miR-233-3p) and 9 downregulated ones (hsa-miR-126-3p, hsa-miR-133a-3p, hsa-miR-140-5p, hsa-miR-143-5p, hsa-miR-145-5p, hsa-miR-30a-5p, hsa-miR-30d-3p, hsa-miR-328-3pn, and hsa-miR-451). The functional enrichment analysis revealed that both up- and downregulated miRNAs were proportionally associated with regulation of transcription from RNA polymerase II promoter. According to transcription factor analysis, there were 65 (43.9%) transcription factors influenced by both up- and downregulated miRNAs.

Conclusions: In this study, 11 meta-signature miRNAs, as well as their target genes and transcription factors, were found to play significant role in carcinogenesis of NSCLC. These target genes identified in our study may be profitable to diagnosis and prognostic prediction of NSCLC as biomarkers.

Keywords: Biomarker; Meta-analysis; Non-small cell lung cancer; miRNAs.

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Competing interests

The authors declare that they have no competing interests.

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Figures

Fig. 1
Fig. 1
Flow chart of the analysis
Fig. 2
Fig. 2
Distribution of tumor-specific miRNA expression changes in NSCLC as reported by primary studies. Short blue and red vertical bars indicate downregulated and upregulated miRNAs, respectively. The x-axis listed the miRNA expression profiles from different studies; the y-axis displayed databases
Fig. 3
Fig. 3
a The size of deregulated miRNA varies greatly across the studies. b Numbers of deregulated miRNA supported by different number of dataset (x-axis). Y-axis designates the number of significantly upregulated (blue) or downregulated (red) miRNAs
Fig. 4
Fig. 4
Pathway enrichment of miRNA targets. Pathway enrichment analyses were concordant for all the 7 meta-signature miRNAs. Beside hsa-miR-125b, other 6 meta-signature miRNAs generated rich GO terms. The color from green to red in heatmap represents the increasing GO terms
Fig. 5
Fig. 5
The NSCLC pathway enrichment of target genes of selected microRNAs. a Pathways influenced by two upregulated miRNAs. b Pathways influenced by nine down-regulated miRNAs
Fig. 6
Fig. 6
Analysis of transcription factor regulated by miRNAs. a Comparison of specific transcription factors influenced by up (blue)- and downregulated (red) miRNAs, and the number of overlapping transcription factors. b E value and cross-ratio statistics of important transcription factor. X-axis listed the names of significantly regulated TFs. Y-axis were the E value scores in log for the blue bars, the red curve was the intersection percentage of each TF
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