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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]

The mechanisms underlying lung cancer radioresistance remain to be fully elucidated. The DNA repair pathway is a predominant target of radiotherapy, which is considered to be involved in the acquired radioresistance of cancer cells. The present study aimed to establish a radioresistant cell model using the A549 human lung cancer cell line, and to further investigate the potential mechanisms underlying the radioresistance. The A549R radioresistant lung cancer cell variant was established by exposing the parental A549 cells to repeated γ-ray irradiation at a total dose of 60 Gy. Colony formation assays were then used to determine cell survival following γ-ray exposure. The established radioresistant cells were subsequently treated with or without the NU7026 DNA-PKcs inhibitor. The levels of DNA damage were determined by counting the number of fluorescent γ-H2AX foci in the cells. The cellular capacity for DNA repair was assessed using antibodies for the detection of various DNA repair pathway proteins. The radioresistant sub-clones exhibited significantly decreased survival following NU7026 treatment, compared with the parental cells, as determined by colony formation assays (P<0.05), and this finding was found to be dose-dependent. Treatment with the DNA-dependent protein kinase (DNA-PK) inhibitor significantly reduced γ-H2AX foci formation (P<0.05) following acute radiation exposure in the radioresistant sub-clones, compared with the parental control cells. The decreased levels of γ-H2AX were accompanied by an increase in the percentage of apoptotic cells in the radioresistant cell line following post-radiation treatment with the DNA-PKcs inhibitor. The expression levels of proteins associated with the DNA repair pathway were altered markedly in the cells treated with NU7026. The results of the present study suggested that radioresistance may be associated with enhanced DNA repair following exposure to radiation, resulting in reduced apoptosis. Therefore, the quantity of γ-H2AX determines the radioresistance of cells. The DNA repair pathway is important in mediating radioresistance, and treatment with the DNA-PKcs inhibitor, NU7026 restored the acquired radiation resistance. [ABSTRACT FROM AUTHOR]