Long non-coding RNAs and microRNAs (miRNAs) have been reported to participate in the progression of non-small-cell lung cancer (NSCLC). Long intergenic non-protein-coding RNA 472 (LINC00472), miR-149-3p, and miR-4270 were found to be involved in tumor activities, suggesting potential roles in NSCLC. Thus, this study aimed to examine the ability of LINC00472 to influence the progression of NSCLC with the involvement of miR-149-3p and miR-4270. Initially, differentially expressed long non-coding RNAs (lncRNAs), downstream regulatory miRNAs, and genes related to NSCLC were identified. Next, the interaction among LINC00472, miR-149-3p and miR-4270, and KLLN and the p53-signaling pathway was determined. The effect of LINC00472 on the expression of E-cadherin, N-cadherin, and Vimentin was examined through gain-of-function and loss-of-function experiments. Lastly, the effects of LINC00472 on NSCLC tumor growth were assessed in vivo . LINC00472 and KLLN were found to exhibit low levels, while miR-149-3p and miR-4270 were highly expressed in NSCLC. In addition, the overexpression of LINC00472 was observed to upregulate KLLN and activate the p53-signaling pathway, which ultimately inhibited the invasion, migration, and EMT of NSCLC cells via miR-149-3p and miR-4270, corresponding to decreased N-cadherin and Vimentin and increased E-cadherin. The overexpression of LINC00472 exerted an inhibitory effect on tumor growth in vivo . Taken together, the key evidence suggests that the overexpression of LINC00472 can downregulate miR-149-3p and miR-4270 to upregulate KLLN and activate the p53-signaling pathway, thus inhibiting the development of NSCLC. This study highlights the potential of LINC00472 as a promising therapeutic target for NSCLC treatment.

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ABSTRACT. This study aimed to investigate the effect of RNAimediated silencing of the Livin gene on biological properties of the colon cancer cell line LoVo. Interference vectors pSilencer4.1-Ll and pSilencer4.1-L2 targeting the Livin gene were constructed and transfected into LoVo cells. The expression of the Livin gene was determined by RT-PCR and Western blotting. The apoptosis, cell cycle, colony formation, proliferation of LoVo cells, as well as their sensitivity to cisplatin, were detected by flow cytometry, colony formation assay and MTT. Livin mRNA and protein expression in LoVo cells could be effectively silenced by pSilencer4.1-Ll but not pSilencer4.1-L2. In the pSilencer4.1-Ll transfection group, the apoptosis rate of LoVo cells was significantly higher than in the control group (24.2 ± 3.2 vs 8.1 ± 1.4%, P < 0.01), and after 72 h, cell proliferation was clearly decreased (about 70% inhibition). Compared with the control group, the colony formation rate in pSilencer4.1-Ll transfection group was obviously decreased (15 RNAi-mediated Livin gene silencing in LoVo cells ± 4.6 vs 85 ± 5.8%, P < 0.01), with increased proportion of S phase cells (45.7 ± 4.9 vs 28.0 ± 3.0%, P < 0.01), decreased proportion of G1 phase cells (43.0 ± 5.2 vs 62.8 ± 5.1%, P < 0.01), and increased sensitivity to cisplatin (apoptosis rate increased from 43.4 ± 6.9 to 65.3 ± 6.2%, P < 0.01). pSilencer4.1-Ll can effectively silence Livin gene expression in LoVo colon cancer cells, inhibit cell proliferation and colony formation, induce apoptosis, and enhance sensitivity to cisplatin.

Background Lung adenocarcinoma (LUAD) is a lung cancer subtype with poor prognosis. We investigated the prognostic value of methylation‐ and homologous recombination deficiency (HRD)‐associated gene signatures in LUAD. Methods Data on RNA sequencing, somatic mutations, and methylation were obtained from TCGA database. HRD scores were used to stratify patients with LUAD into high and low HRD groups and identify differentially mutated and expressed genes (DMEGs). Pearson correlation analysis between DMEGs and methylation yielded methylation‐associated DMEGs. Cox regression analysis was used to construct a prognostic model, and the distribution of clinical features in the high‐ and low‐risk groups was compared. Results Patients with different HRD scores showed different DNA mutation patterns. There were 272 differentially mutated genes and 6294 differentially expressed genes. Fifty‐seven DMEGs were obtained; the top 10 upregulated genes were COL11A1, EXO1, ASPM, COL12A1, COL2A1, COL3A1, COL5A2, DIAPH3, CAD, and SLC25A13, while the top 10 downregulated genes were C7, ERN2, DLC1, SCN7A, SMARCA2, CARD11, LAMA2, ITIH5, FRY, and EPHB6. Forty‐two DMEGs were negatively correlated with 259 methylation sites. Gene ontology and pathway enrichment analysis of the DMEGs revealed enrichment of loci involved in extracellular matrix‐related remodeling and signaling. Six out of the 42 methylation‐associated DMEGs were significantly associated with LUAD prognosis and included in the prognostic model. The model effectively stratified high‐ and low‐risk patients, with the high‐risk group having more patients with advanced stage disease. Conclusion We developed a novel prognostic model for LUAD based on methylation and HRD. Methylation‐associated DMEGs may function as biomarkers and therapeutic targets for LUAD. Further studies are needed to elucidate their roles in LUAD carcinogenesis.