Research Paper Volume 14, Issue 20 pp 8357—8373
Identify miRNA-mRNA regulation pairs to explore potential pathogenesis of lung adenocarcinoma
- 1 Department of Geriatrics, The First People’s Hospital of Lianyungang, The Affiliated Lianyungang Hospital of Xuzhou Medical University, The Affiliated Hospital of Kangda College of Nanjing Medical University, Lianyungang 222002, P.R. China
- 2 First Clinical College of Nanjing Medical University, Nanjing 210029, P.R. China
- 3 Department of Gastroenterology, First Affiliated Hospital of Nanjing Medical University, Nanjing 210029, P.R. China
- 4 Department of Oncology, First Affiliated Hospital of Nanjing Medical University, Nanjing 210029, P.R. China
- 5 Department of Radiation Oncology, Nanjing Medical University Affiliated Cancer Hospital, Jiangsu Cancer Hospital, Jiangsu Institute of Cancer Research, Xuanwu, Nanjing 210009, P.R. China
Received: January 19, 2022 Accepted: October 10, 2022 Published: October 19, 2022
https://doi.org/10.18632/aging.204341How to Cite
Copyright: © 2022 Fan et al. This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Abstract
Purpose: MicroRNA (miRNA) function via base-pairing with complementary sequences within mRNA molecules. This study aims to identify critical miRNA-mRNA regulation pairs contributing to lung adenocarcinoma (LUAD) pathogenesis.
Patients and methods: MiRNA and mRNA microarray and RNA-sequencing datasets were downloaded from gene expression omnibus (GEO) and the cancer genome atlas (TCGA) databases. Differential miRNAs (DE-miRNAs) and mRNAs (DE-mRNAs) were screened by the GEO2R tool and R packages. DAVID, DIANA, and Hiplot tools were used to perform gene enrichment analysis. The pairs of miRNA-mRNA were screened from the experimentally validated miRNA-target interactions databases (miRTarBase and TarBase). External validation was carried out in 30 pairs of LUAD tissues by quantitative reverse transcription and polymerase chain reaction (qRT-PCR). The diagnostic value of the miRNA-mRNA regulation pairs was evaluated by receiver operating characteristic curve (ROC) and decision curve analysis (DCA). Biological function assay was were also performed to confirm the function of miRNA-mRNA axis in LUAD progression. The study also performed the clinical, survival and tumor-associated phenotypic analysis of miRNA-mRNA pairs.
Results: A total of 7 miRNA and 13 mRNA expression datasets from GEO were analyzed, and 11 DE-miRNAs (5 down-regulated and 6 up-regulated in LUAD tissues) and 128 DE-mRNAs (30 up-regulated and 98 down-regulated in LUAD tissues) were identified. The pairs of miR-1-3p(down) and CENPF(up) and miR-126-5p(down) and UGT8(up) were verified in the external validation cohort (30 LUAD vs. 30 NC) using qRT-PCR. Areas under the ROC curve of the two miRNA-mRNA regulation pairs panel were 0.973 in TCGA-LUAD and 0.771 in the external validation. The DCA also showed that the miRNA-mRNA regulation pairs had an excellent diagnostic performance distinguishing LUAD from normal controls. The expression of the regulation pairs is different in different ages, TNM stages, and gender. The overexpression of miR-1-3p and miR-126-5p significantly inhibited the proliferation and migration of LUAD cells. Correlation analysis showed that CENPF correlated with prognosis and tumor immunity.
Conclusions: The research identified potential miRNA-mRNA regulation pairs, providing a new idea for exploring the genesis and development of LUAD.
Abbreviations
miRNA: microRNA; LUAD: Lung Adenocarcinoma; GEO: gene expression omnibus; TCGA: the cancer genome atlas; qRT-PCR: Quantitative Reverse Transcription-Polymerase Chain Reaction; ROC: receiver operating characteristic curve; DCA: decision curve analysis; DE-miRNAs: differential miRNAs; DE-mRNAs: differential mRNAs; dbDEMC: database of Differentially Expressed MiRNAs in human Cancers; GO: Gene Ontology; KEGG: Kyoto Encyclopedia of Genes Genomes; ssGSEA: Single sample gene set Enrichment analysis; ESTIMATE: Estimation of STromal and Immune cells in MAlignant Tumour tissues using Expression data; TMB: tumor mutation burden; AUC: Area Under Curve; CI: confidence interval; NSCLC: non-small cell lung cancer.