ArticleGenes2022
Identification of the Key miRNAs and Genes Associated with the Regulation of Non-Small Cell Lung Cancer: A Network-Based Approach.
Article in Genes, 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.
- Review
- Integrated PET-IVIM-DKI MRI for predicting lymphovascular invasion in NSCLC.Insights into imaging · 2025Article
- Research trends in microRNA profiling as a biomarker for lung adenocarcinoma via liquid biopsy: A bibliometric analysis.Narra J · 2025Review
- A crucial role of miR-155 in the pathomechanism of acute kidney injury.Frontiers in pharmacology · 2025Review
- Analysis ofHeliyon · 2024Article
- Role of c-Myc in lung cancer: Progress, challenges, and prospects.Chinese medical journal pulmonary and critical care medicine · 2023Article
- Panel of miR-150 and linc00673, regulators of CCR6/CCL20 may serve as non-invasive diagnostic marker of non-small cell lung cancer.Scientific reports · 2023Article
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Authors and funding
6 authors.
Funding
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Abstract
Lung cancer is the major cause of cancer-associated deaths across the world in both men and women. Lung cancer consists of two major clinicopathological categories, i.e., small cell lung cancer (SCLC) and non-small cell lung cancer (NSCLC). Lack of diagnosis of NSCLC at an early stage in addition to poor prognosis results in ineffective treatment, thus, biomarkers for appropriate diagnosis and exact prognosis of NSCLC need urgent attention. The proposed study aimed to reveal essential microRNAs (miRNAs) involved in the carcinogenesis of NSCLC that probably could act as potential biomarkers. The NSCLC-associated expression datasets revealed 12 differentially expressed miRNAs (DEMs). MiRNA-mRNA network identified key miRNAs and their associated genes, for which functional enrichment analysis was applied. Further, survival and validation analysis for key genes was performed and consequently transcription factors (TFs) were predicted. We obtained twelve miRNAs as common DEMs after assessment of all datasets. Further, four key miRNAs and nine key genes were extracted from significant modules based on the centrality approach. The key genes and miRNAs reported in our study might provide some information for potential biomarkers profitable to increased prognosis and diagnosis of lung cancer.
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