ArticleMedicine2022
Microarray data analysis to identify miRNA biomarkers and construct the lncRNA-miRNA-mRNA network in lung adenocarcinoma.
Article in Medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed, 8 citations in OpenAlex.
- lncRNA JPX promotes radioresistance in nasopharyngeal carcinoma via the miR-1301-3p/PIK3R2-mediated autophagy pathway.Translational cancer research · 2026Article
- The emerging role of machine learning-based methods in cancer classification using microRNA.Biochemistry and biophysics reports · 2026Review
- Single-Step Detection of microRNA via the Programmable DNAzyme Probe-Mediated Multiple Signal Recycling.ACS omega · 2025Article
- N6-methyladenosine (m6A) RNA methylation of LncRNA LINC01214 accelerates the progression of non-small cell lung cancer (NSCLC) by targeting miR-195-5p/ROCK1 axis.Cytotechnology · 2025Article
- Article
- Decoding LncRNA in COPD: Unveiling Prognostic and Diagnostic Power and Their Driving Role in Lung Cancer Progression.International journal of molecular sciences · 2024Review
- Matched Analyses of Brain Metastases versus Primary Non-Small Cell Lung Cancer Reveal a Unique microRNA Signature.International journal of molecular sciences · 2022Article
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Authors and funding
4 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
MicroRNAs (miRNAs), regulatory noncoding RNAs, are involved in gene regulation and may play a role in cancer development. The aim of this study was to identify miRNAs involved in lung adenocarcinoma (LUAD) using bioinformatics analysis. MiRNA (GSE135918), mRNA (GSE136043) and lncRNA (GSE130779) microarray datasets were downloaded from the Gene Expression Omnibus (GEO) database to identify differentially expressed miRNAs (DEMis), mRNAs (DEMs), and lncRNA (DELs) in LUAD. We used DEMs for functional enrichment analysis. MiRNA expression quantification from The Cancer Genome Atlas (TCGA) was used to validate DEMis. LncBase Predicted v.2, Targetscan, and MiRBase were used to predict lncRNAs and mRNAs. The LUAD data in TCGA were used for overall survival (OS) analysis. We screened the downregulation of 8 DEMis and upregulation of 6 DEMis, and found that 70 signal pathways changed. We chose 3 relevant signaling pathways in lung cancer development, WNT, PI3K-Akt, and Notch, and scanned for mRNAs involved in them that are potential targets of these miRNAs. Then a lncRNA-miRNA-mRNA network was constructed. We also found 7 miRNAs that were associated with poor OS in LUAD. Low expression level of hsa-miR-30a was highly associated with poor OS in LUAD (P < .001) and the target genes of hsa-miR-30a-3p were abundant in the Wnt and AKT signaling pathways. In addition, our results reported for the first time that hsa-miR-3944 and hsa-miR-3652 were highly expressed in LUAD. And the high expression level of hsa-miR-3944 was associated with poor OS (P < .05). Hsa-miR-30a-3p may suppress the occurrence and progression of lung cancer through Wnt and AKT signaling pathways and become a good biomarker in LUAD. Hsa-miR-3944 and hsa-miR-3652 may serve as new biomarkers in LUAD.
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