Bioinformatics prediction of differential miRNAs in non-small cell lung cancer

Abstract

Background: Non-small cell lung cancer (NSCLC) accounts for 85% of all lung cancers. The drug resistance of NSCLC has clinically increased. This study aimed to screen miRNAs associated with NSCLC using bioinformatics analysis. We hope that the screened miRNA can provide a research direction for the subsequent treatment of NSCLC.

Methods: We screened out the common miRNAs after compared the NSCLC-related genes in the TCGA database and GEO database. Selected miRNA was performed ROC analysis, survival analysis, and enrichment analysis (GO term and KEGG pathway).

Results: A total of 21 miRNAs were screened in the two databases. And they were all highly expressed in normal and low in cancerous tissues. Hsa-mir-30a was selected by ROC analysis and survival analysis. Enrichment analysis showed that the function of hsa-mir-30a is mainly related to cell cycle regulation and drug metabolism.

Conclusion: Our study found that hsa-mir-30a was differentially expressed in NSCLC, and it mainly affected NSCLC by regulating the cell cycle and drug metabolism.

Fig 1. Screening of miRNAs shared by TCGA database and GEO database.

A: The volcano map of miRNAs differentially expressed in NSCLC screened under the TCGA database. (P>0.05). B: Screening differentially expressed miRNA volcano maps in NSCLC under the GSE135918 database (p>0.05). The red dots on the volcano map represent differential miRNAs. C: Venn diagram of intersection of TCGA and GSE135918, the numbers represent the number of miRNAs.

Fig 2. MiRNA clustering heat map showed the expression of 21 miRNAs.

The abscissa represents the differential miRNA. The ordinate represents the sample, Normal, Tumor: NSCLC tissue. The color scale represents the abundance of gene expression, p<0.05.

Fig 3. MiRNA expression in boxplots.

A: Boxplot of hsa-mir-30a. B: Boxplot of hsa-mir-338. C: Boxplot of hsa-mir-451a. D: Boxplot of hsa-mir-4732. The abscissa represents the sample, Normal: Paracancerous tissue, Tumor: NSCLC tissue. The ordinate represents the expression level of miRNA, p<0.05.

Fig 4. ROC analysis of miRNA.

A: ROC analysis hsa-mir-338. B: ROC analysis hsa-mir-30a. C: ROC analysis hsa-mir-451a. D: ROC analysis hsa-mir-4732. The AUC>0.8 of the selected miRNA indicates that the result is meaningful.

Fig 5. Survival analysis of differentially expressed hsa-mir-30a.

The abscissa and ordinate represent respectively survival time (days) and survival rate. The blue and red lines represent respectively the low-risk and high-risk curves, p<0.05.

Fig 6. GO term and KEGG pathway regulated by hsa-mir-30a related mRNAs.

A: GO term function prediction. The ordinate represents GO term description information, CC: cell composition, MF: molecular function, the abscissa is the number of differential genes enriched to the term, p<0.05. The color of the P-value ranges from blue (0.04) to red (0.01). B: KEGG function prediction. The ordinate represents gene-related pathways, the abscissa represents Gene Ratio, and the size of dots represents the number of genes. The color of the P-value ranges from blue (0.00025) to red (0.00005). The smaller the P-value, the higher the enrichment of the KEGG function.