Open AccessBioinformatics prediction of differential miRNAs in non-small cell lung cancer
Author(s) -
Kui Xiao,
Shenggang Liu,
Yijia Xiao,
Yan Wang,
Zhiruo Zhu,
Yaohui Wang,
De Tong,
Jiehan Jiang
Publication year - 2021
Publication title -
plos one
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.99
H-Index - 332
ISSN - 1932-6203
DOI - 10.1371/journal.pone.0254854
Subject(s) - kegg , microrna , lung cancer , biology , survival analysis , cell cycle , oncology , drug resistance , adenocarcinoma , bioinformatics , cancer research , cell , gene , computational biology , cancer , medicine , transcriptome , gene expression , genetics
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.