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Objective: Cuproptosis‐related genes are closely related to lung adenocarcinoma (LUAD), which can be analyzed via the analysis of long noncoding RNA (lncRNA). To date, the clinical significance and function of cuproptosis‐related lncRNAs are still not well elucidated. Further analysis of cuproptosis‐related prognostic lncRNAs is of great significance for the treatment, diagnosis, and prognosis of LUAD. Methods: In this study, a multiple machine learning (ML)‐based computational approach was proposed for the identification of the cuproptosis‐related lncRNAs signature (CRlncSig) via comprehensive analysis of cuproptosis, lncRNAs, and clinical characteristics. The proposed approach integrated multiple ML algorithms (least absolute shrinkage and selection operator regression analysis, univariate and multivariate Cox regression) to effectively identify the CRlncSig. Results: Based on the proposed approach, the CRlncSig was identified from the 3450 cuproptosis‐related lncRNAs, which consist of 13 lncRNAs (CDKN2A‐DT, FAM66C, FAM83A‐AS1, AL359232.1, FRMD6‐AS1, AC027237.4, AC023090.1, AL157888.1, AL627443.3, AC026355.2, AC008957.1, AP000346.1, and GLIS2‐AS1). Conclusions: The CRlncSig could well predict the prognosis of different LUAD patients, which is different from other clinical features. Moreover, the CRlncSig was proved to be an effective indicator of patient survival via functional characterization analysis, which is relevant to cancer progression and immune infiltration. Furthermore, the results of RT‐PCR assay indicated that the expression level of FAM83A‐AS1 and AC026355.2 in A549 and H1975 cells (LUAD) was significantly higher than that in BEAS‐2B cells (normal lung epithelial). [ABSTRACT FROM AUTHOR]

Background: Non-small cell lung cancer (NSCLC) has led to the highest cancer-related mortality for decades. To enhance the efficiency of early diagnosis and therapy, more efforts are urgently needed to reveal the origins of NSCLC. In this study, we explored the effect of miR-542-5p in NSCLC with clinical samples and in vivo models and further explored the prospective function of miR-542-5p though bioinformatics methods.Methods: A total of 125 NSCLC tissue samples were collected, and the expression of miR-542-5p was detected by qRT-PCR. The relationship between miR-542-5p level and clinicopathological features was analyzed. The effect of miR-542-5p on survival time was also explored with K-M survival curves and Cox's regression. The effect of miR-542-5p on the tumorigenesis of NSCLC was verified with a chick chorioallantoic membrane (CAM) model. The potential target genes were predicted by bioinformatics tools, and relevant pathways were analyzed by GO and KEGG. Several hub genes were validated by Proteinatlas.Results: The expression of miR-542-5p was down-regulated in NSCLC tissues, and consistent results were also found in the subgroups of adenocarcinoma and squamous cell carcinoma. Down-regulation of miR-542-5p was found to be connected with advanced TNM stage, vascular invasion, lymphatic metastasis and EGFR. Survival analyses showed that patients with lower miR-542-5p levels had markedly poorer prognosis. Both tumor growth and angiogenesis were significantly suppressed by miR-542-5p mimic in the CAM model. The potential 457 target genes of miR-542-5p were enriched in several key cancer-related pathways, such as morphine addiction and the cAMP signaling pathway from KEGG. Interestingly, six genes (GABBR1, PDE4B, PDE4C, ADCY6, ADCY1 and GIPR) from the cAMP signaling pathway were confirmed to be overexpressed in NSCLCs tissues.Conclusions: This evidence suggests that miR-542-5p is a potential tumor-suppressed miRNA in NSCLC, which has the potential to act as a diagnostic and therapeutic target of NSCLC. [ABSTRACT FROM AUTHOR]