Jie Zhang, Ping-Ping Jia, Qing-Le Liu, Ming-Hua Cong, Yun Gao, Han-Ping Shi, Wei-Nan Yu, Ming-Yong Miao

Objective: The aim of this study was to investigate the molecular mechanisms underlying cisplatin (DDP) resistance in non-small cell lung cancer (NSCLC) cells by constructing a competing endogenous RNA (ceRNA) network. Methods: The gene expression profiles of human lung adenocarcinoma DDP-resistant cell line (A549/DDP) and its progenitor (A549) were comparatively evaluated by whole-transcriptome sequencing. The differentially expressed genes (DEGs) were subjected to KEGG pathway analysis. The expression levels of mRNAs involved in several pathways associated with conferring DDP resistance to tumor cells were evaluated. The ceRNA network was constructed based on the mRNA expression levels and the sequencing data of miRNA and lncRNA. Several ceRNA regulatory relationships were validated. Results: We quantified the expression of 17 genes involved in the six pathways by quantitative real-time polymerase chain reaction (qRT-PCR). The differential protein expression levels of eight genes were quantified by western blotting. Western blot analysis revealed six differentially expressed proteins (MGST1, MGST3, ABCG2, FXYD2, ALDH3A1, and GST-ω1). Among the genes encoding these six proteins, ABCG2, ALDH3A1, MGST3, and FXYD2 exhibited interaction with 8 lncRNAs and 4 miRNAs in the ceRNA regulatory network. The expression levels of these lncRNAs and miRNAs were quantified in cells; among these, 6 lncRNAs and 4 miRNAs exhibited differential expression between A549/DDP and A549 groups, which were used to construct a ceRNA network. The ceRNA regulatory network of MSTRG51053.2-miR-432-5p-MGST3 was validated by luciferase reporter assay. Conclusion: The MSTRG51053.2 lncRNA may function as a ceRNA for miR-432-5p to regulate the DDP resistance in NSCLC. The MGST1, MGST3, GST-ω1, and ABCG2 mRNAs, miR-432-5p and miR-665 miRNAs, and MSTRG51053.2 and PPAN lncRNAs can serve as potential DDP drug targets to reverse DDP resistance in NSCLC.

Purpose: The aim of this study was to investigate the role of miRNA-486-5p in chronic obstructive pulmonary disease (COPD) progression and the underlying molecular mechanisms. Materials and Methods: Aberrant miRNA expression profiles between smokers and nonsmokers, and those between COPD patients and normal subjects were analyzed using microarray datasets and reverse-transcriptase quantitative polymerase chain reaction (qPCR). Enzyme-linked immunosorbent assay was used to determine the levels of inflammatory cytokines in cell supernatants. Expression levels of inflammatory cytokines, HAT1, TLR4, and miR-486-5p, were determined using qPCR or Western blotting. Luciferase reporter assays and fluorescence in situ hybridization were used to confirm the regulatory interaction between miR-486-6p and HAT1. Results: miR-486-5p was significantly upregulated in the COPD and smoker groups compared to the control group, as demonstrated using bioinformatics analysis and validated using qPCR assay of alveolar macrophages and peripheral monocytes. Moreover, miR-486-5p expression was significantly correlated with the expression of IL-6, IL-8, TNF-α, and IFN-γ. Luciferase reporter assays confirmed that miR-486-5p directly targeted HAT1, and cellular localization showed that miR-486-5p and HAT1 were highly expressed in the cytoplasm. miR-486-5p overexpression led to a significant upregulation of TLR4 and a significant downregulation of HAT1. Inversely, miR-486-5p inhibition led to a significant downregulation of TLR4 and a significant upregulation of HAT1. HAT1 knockdown using siRNA significantly upregulated the expression of TLR4, IL-6, IL-8, TNF-α, and IFN-γ. Conclusion: miR-486-5p was differentially expressed in the alveolar macrophages of COPD patients. miR-486-5p overexpression may enhance the TLR4-triggered inflammatory response in COPD patients by targeting HAT1.

In this study, we aimed to explore key micro(mi)RNAs and their potential regulatory mechanisms induced by honokiol treatment in non-small cell lung cancer (NSCLC) cells. NSCLC A549 cells were treated with 0 (control) or 45 μM honokiol. Cell proliferation and migration were determined using CCK-8 and transwell assay, respectively, and apoptosis was determined using flow cytometry. RNA-sequencing was performed to detect the transcript expression levels. The differentially expressed miRNAs (DE-miRNAs) between the honokiol group and the control group were screened and analyzed for their functions and pathways. Then, protein-protein interaction (PPI) networks and miRNA-mRNA regulatory networks were constructed. In addition, survival analysis based on the key miRNAs was performed. Finally, the expression of the key miRNAs and their target genes were determined, and their effects on drug sensitivity were validated using their inhibitors. Cell proliferation and migration were inhibited (P < 0.01), and the apoptosis rate was increased (P < 0.01) after honokiol treatment compared to that in the control group. A total of 26 upregulated and 20 downregulated DE-miRNAs were screened. DE-miRNAs were enriched in 10 pathways and 48 biological processes, such as the PI3K/AKT signaling pathway (involving miR-148a-3p). The miRNA-mRNA regulatory networks involved eight upregulated (including miR-148a-3p and let-7c-5p) and seven downregulated miRNAs (including miR-7-5p) and 190 target mRNAs. Survival analysis revealed that let-7c-5p, miR-148a-3p, and miR-148a-5p levels correlated with NSCLC prognosis. The expression of let-7c-5p, miR-148a-3p, and miR-148a-5p was significantly increased and negatively correlated with the expression of their target genes. The cytological effects of honokiol on A549 cells was partly reversed by treatment with the inhibitors of Let-7c-5p and miR-148a-3p. Let-7c-5p, miR-148a-3p, miR-148a-5p, and miR-7-5p are favorable indicators of NSCLC patients treated with honokiol.

The present study aimed to explore specific molecular targets for the diagnosis and treatment of non‑small cell lung cancer (NSCLC). The expression profiles of microRNAs (miRNAs) and mRNAs were downloaded from the GEO (GSE102286 and GSE101929) and TCGA databases. After data preprocessing, differentially expressed genes (DEGs) and differentially expressed miRNAs (DEMs) in cancer and normal tissues were selected and used to construct a DEM‑DEG regulatory network and a protein‑protein interaction (PPI) network. The genes and miRNAs in these networks were subjected to functional enrichment and survival analyses. Several key DEMs and DEGs were verified using RT‑qPCR, and the results were statistically interpreted using a multivariate logistic regression analysis. In this study, 25 DEMs and 789 DEGs common to all datasets were identified, which were then used for the construction of a DEM‑DEG regulatory network and a PPI network module. Survival analyses of 19 DEMs in the DEM‑DEG regulatory network and 36 DEGs in the PPI network module revealed that 34 DEGs (including TOP2A, CCNB1, BIRC5, and TTK) and two miRNAs (miR‑21‑5p and miR‑31‑5p) were significantly associated with NSCLC prognosis. Moreover, RT‑qPCR analysis identified three DEGs and five DEMs that had changes in expression consistent with those observed in the bioinformatic analysis. Finally, a multivariate logistic regression analysis of the data showed that TOP2A, CCNB1, BIRC5, miR‑21‑5p, miR‑193b‑3p, miR‑210‑3p and miR‑31‑5p could be combined for the diagnosis of NSCLC. In conclusion, TOP2A, CCNB1, BIRC5, miR‑21‑5p, miR‑193b‑3p, miR‑210‑3p and miR‑31‑5p may therefore serve as important biomarkers and diagnostic targets for NSCLC.

This study aims to investigate the antitumor effect and the possible mechanism of a microecological preparation (JK5G) in mice. The mice treated with AOM/DSS were then randomly divided into the two model groups and the JK5G group, and the blank control group was included. Fecal samples were used for liquid chromatography–mass spectrometry and 16S rRNA gene sequencing analyses to reveal metabolic perturbations and gut flora disorders to demonstrate the effects of JK5G. Compared with the mice in the control group, the weight and food intake of mice after JK5G treatment were both upregulated. Moreover, JK5G could inhibit the growth of colon tumors and prolong the survival rate of mice, as well as inhibit the levels of cytokines in serum. The proportions of lymphocytes, T cells, CD3⁺CD4⁺ T cells, and CD3⁺CD8⁺ T cells in the spleen of the JK5G mice were all significantly increased compared to those in the control group (p < 0.05). Similarly, compared with the model group, the proportions of lymphocytes, B cells, T cells, natural killer T cells, CD3⁺CD4⁺ T cells, and CD3⁺CD8⁺ T cells in the intestinal tumors of the JK5G mice were significantly increased (p < 0.05). Furthermore, 16S rRNA high-throughput sequencing data revealed that Alloprevotella in the JK5G group was significantly upregulated, and Ruminiclostridium, Prevotellaceae_UCG_001, and Acetitomaculum were significantly downregulated. Fecal and serum metabolite analysis detected 939 metabolites, such as sildenafil and pyridoxamine, as well as 20 metabolites, including N-Palmitoyl tyrosine and dihydroergotamine, which were differentially expressed between the JK5G and model groups. Integrated analysis of 16s rRNA and metabolomics data showed that there were 19 functional relationship pairs, including 8 altered microbiota, such as Ruminiclostridium and Prevotellaceae_UCG_001, and 16 disturbed metabolites between the JK5G and model groups. This study revealed that JK5G treatment was involved in the growth of colorectal cancer, which may be associated with the role of JK5G in improving the nutritional status of mice and regulating the tumor microenvironment by regulating the changes of intestinal microbiota and metabolite bands on different pathways.