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Xiao Chen,1,2 Jie Yao,1 Meng-Yu Zhang,1 Rui Li,1 Xiao Liu,1 Yi-Qing Qu1 1Department of Pulmonary and Critical Care Medicine, Qilu Hospital of Shandong University, Jinan, People’s Republic of China; 2Department of Respiratory Medicine, Tai’an City Central Hospital, Tai’an, People’s Republic of ChinaCorrespondence: Yi-Qing Qu, Department of Pulmonary and Critical Care Medicine, Qilu Hospital of Shandong University, Wenhuaxi Road 107#, Jinan, 250012, People’s Republic of China, Tel +86 531 8216 9335, Fax +86 531 8296 7544, Email quyiqing@sdu.edu.cnPurpose: Non-small cell lung cancer (NSCLC) is currently a problem in the clinic and in society. Tumor-related macrophages (TAMs) in the tumor microenvironment (TME) play a vital role in the development of NSCLC.Patients and Methods: Bioinformatics was used to analyze the role of Indoleamine 2,3-dioxygenase 1 (IDO1) in NSCLC and the correlation of its expression with CD163 expression. The expression of CD163 and IDO1 was measured by immunohistochemistry, and their colocalization was assessed by immunofluorescence. M2 macrophage polarization was induced, and a coculture model of NSCLC cells and macrophages was established.Results: Bioinformatics analysis showed that IDO1 promoted the metastasis and differentiation of NSCLC and inhibited DNA repair. Moreover, the expression of IDO1 was positively correlated with CD163 expression. We discovered that IDO1 expression was related to M2 macrophage differentiation. In vitro, we showed that increased IDO1 expression promoted the invasion, proliferation, and metastasis of NSCLC cells.Conclusion: In conclusion, we determined that IDO1 can regulate the M2 polarization of TAMs and promote the progression of NSCLC, which provides partial theoretical evidence for the use of IDO1 inhibitors in the treatment of NSCLC.Keywords: IDO1, NSCLC, M2 macrophage, TAM, bioinformatics

Zhuang-E Shi,1 Meng-Yu Zhang,1 Jian-Yu Liu,1 Wen-Di Zhang,1 Dong-Mei Hu,1 Qing-Xiang Wang,1 Xiu-Li Ji,2 Yuan-Yuan Jiang,3 Yi-Qing Qu3 1Department of Pulmonary and Critical Care Medicine, Qilu Hospital, Cheeloo College of Medicine, Shandong University, Shandong Key Laboratory of Infectious Respiratory Diseases, Jinan, People’s Republic of China; 2Department of Pulmonary Disease, Jinan Traditional Chinese Medicine Hospital, Jinan, People’s Republic of China; 3Department of Pulmonary and Critical Care Medicine, Qilu Hospital of Shandong University, Shandong Key Laboratory of Infectious Respiratory Diseases, Jinan, People’s Republic of ChinaCorrespondence: Yi-Qing Qu, Department of pulmonary and Critical Care Medicine, Qilu Hospital of Shandong University, Shandong Key Laboratory of Infectious Respiratory Diseases, Jinan, People’s Republic of China, Tel +86 531 8216 9335, Fax +86 531 8296 7544, Email quyiqing@sdu.edu.cnPurpose: Chronic obstructive pulmonary disease (COPD) is a predominant cause of mortality worldwide. Autophagy, which depends on a lysosomal degradation pathway, plays an essential role in the occurrence of COPD. The aim of our study was to identify the potential function of autophagy and construct a BCL2-related competing endogenous RNA (ceRNA) network that induces autophagy in COPD.Methods: Blood sample data from GSE31568, GSE24709, and GSE61741 were collected from the Gene Expression Omnibus (GEO) database. Differentially expressed miRNAs in COPD and controls were identified via GEO2R. Transcription factors were obtained from FunRich. DIANA, miRDB, miRTarBase, and TargetScan were used to predict target genes of miRNAs. Autophagy genes were collected from the Human Autophagy Database (HADb). The GSE151052 dataset was used to identify autophagy-related differentially expressed genes in tissues. Functional enrichment and protein–protein interaction (PPI) network analyses were conducted via Metascape and the STRING network. Spearman correlation analysis was used to analyze the relationship between autophagy-related differentially expressed genes and lung function. The BCL2-related ceRNA network was modeled by Cytoscape.Results: We obtained 41 differentially expressed miRNAs and 10 significantly different transcription factors. We identified 19 autophagy-related differentially expressed genes that were significantly different (P< 0.05) in tissue samples. The most significant enrichment in Metascape was an autophagy item, which further confirmed autophagy participation in the occurrence of COPD. PPI network analysis found four genes (BCL2, BECN1, MAPK8, and ITPR1), among which BCL2 was correlated with both FEV1/FVC and FEV1 prediction. Finally, the BCL2-related ceRNA network was constructed to clarify the interaction of RNAs and occurrence of autophagy, including 18 miRNAs and 65 lncRNAs.Conclusion: We identified 19 autophagy-related differentially expressed genes that participated in COPD; among them, BCL2 was correlated with lung function, and a BCL2-related ceRNA network was constructed, which further revealed the potential mechanism of autophagy involvement in COPD.Keywords: COPD, autophagy, bioinformatics, lung function, BCL2, ceRNA

Background Long non-coding RNAs (lncRNAs) are increasingly recognized as the crucial mediators in the regulation of ferroptosis and iron metabolism. A systematic understanding of ferroptosis and iron-metabolism related lncRNAs (FIRLs) in lung adenocarcinoma (LUAD) is essential for new diagnostic and therapeutic strategies. Methods FIRLs were obtained through Pearson correlation analysis between ferroptosis and iron-metabolism related genes and all lncRNAs. Univariate and multivariate Cox regression analysis were used to identify optimal prognostic lncRNAs. Next, a novel signature was constructed and risk score of each patient was calculated. Survival analysis and ROC analysis were performed to evaluate the predictive performance using The Cancer Genome Atlas Lung Adenocarcinoma (TCGA-LUAD) and Gene Expression Omnibus (GEO) datasets, respectively. Furthermore, multivariate Cox and stratification analysis were used to assess prognostic value of this signature in whole cohort and various subgroups. The correlation of risk signature with immune infiltration and gene mutation was also discussed. The expression of lncRNAs was verified by quantitative real-time PCR (qRT-PCR). Results A 7-FIRLs signature including ARHGEF26-AS1, LINC01137, C20orf197, MGC32805, TMPO-AS1, LINC00324, and LINC01116 was established in the present study to assess the overall survival (OS) of LUAD. The survival analysis and ROC curve indicated good predictive performance of the signature in both the TCGA training set and the GEO validation set. Multivariate Cox and stratification analysis indicated that the 7‐FIRLs signature was an independent prognostic factor for OS. Nomogram exhibited robust validity in prognostic prediction. Differences in immune cells, immune functions and gene mutation were also found between high-risk and low-risk groups. Conclusions This risk signature based on the FIRLs may be promising for the clinical prediction of prognosis and immunotherapeutic responses in LUAD patients.

Background Pseudomonas fluorescens (P. fluorescens) has been detected in respiratory samples from patients. However, no previous reports have been published about these P. fluorescens cultures from lung tissues. Case presentation Here, we report a case of pneumonia caused by P. fluorescens. P. fluorescens was identified from lung biopsy specimens for the first time in this case. According to the antibiotic susceptibility testing (AST) of P. fluorescens, the patient was given ciprofloxacin treatment. The temperature of the patient then returned to normal. Chest CT examination revealed improvements in pulmonary inflammation. Conclusions These findings suggest that the patients with pneumonia caused by P. fluorescens should be treated in a timely manner according to the AST results.

The process of ubiquitination and deubiquitination is widely present in the human body's protein reactions and plays versatile roles in multiple diseases. Deubiquitinating enzymes (DUBs) are significant regulators of this process, which cleave the ubiquitin (Ub) moiety from various substrates and maintain protein stability. Lung adenocarcinoma (LUAD) is the most common type of non-small cell lung cancer (NSCLC) and remains refractory to treatment. To elucidate the mechanism of LUAD and advance new therapeutic targets, we review the latest research progress on DUBs in LUAD. We summarize the biological capabilities of these DUBs and further highlight those DUBs that may serve as anticancer target candidates for precision treatment. We also discuss deubiquitinase inhibitors, which are expected to play a role in targeted LUAD therapy.

Background and aim: The molecular signatures of lung adenocarcinoma (LUAD) are not well understood. Centromere protein F (CENPF) has been shown to promote oncogenesis in many cancers; however, its role in LUAD has not been illustrated. We explored the role of CENPF in LUAD. Methods: CENPF expression level was investigated in public online database firstly, the prognosis of CENPF in LUAD were also assessed by Kaplan-Meier analysis. Then quantitative reverse transcription-polymerase chain reaction (qRT-PCR) was performed using 13 matched pairs of clinical LUAD tissue samples. Subsequently, the impact of CENPF expression on cell proliferation, cell cycle, apoptosis, colony formation was investigated by 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyl tetrazolium bromide (MTT), flow cytometric analysis and colony formation assay, respectively. Finally, experimental xenograft lung cancer model of nude mice armpit of right forelimb to determine the effect of CENPF on LUAD tumorigenesis. Results: CENPF mRNA expression was significantly elevated in LUAD tissues compared with adjacent non-tumor lung tissues in Gene Expression Profiling Interactive Analysis (GEPIA) (P < 0.001). Up-regulated CENPF was remarkably positively associated with pathological stage, relapse free survival (RFS) as well as overall survival (OS) of LUAD patients. Besides, CENPF knockdown greatly suppressed A549 cell proliferation, induced S phase arrest, promoted apoptosis and decreased colony numbers of LUAD cells. Furthermore, knockdown of CENPF significantly inhibited the tumor growth of the LUAD cells in an experimental xenograft lung cancer model of nude mice armpit of right forelimb. Conclusion: Taken together, these results demonstrated that CENPF may serve as a potential biomarker of prognostic relevance and a potential therapeutic target for LUAD.

Jie Yang,1,2 Meng-Yu Zhang,1 Yi-Ming Du,2 Xiu-Li Ji,3 Yi-Qing Qu1 1Department of Pulmonary and Critical Care Medicine, Qilu Hospital of Shandong University, Shandong Key Laboratory of Infectious Respiratory Diseases, Jinan, People’s Republic of China; 2Department of Gerontology, The First Affiliated Hospital of Shandong First Medical University & Shandong Provincial Qianfoshan Hospital, Jinan, People’s Republic of China; 3Department of Pulmonary Disease, Jinan Traditional Chinese Medicine Hospital, Jinan, People’s Republic of ChinaCorrespondence: Yi-Qing Qu, Department of Pulmonary and Critical Care Medicine, Qilu Hospital of Shandong University; Shandong Key Laboratory of Infectious Respiratory Diseases, Wenhuaxi Road 107#, Jinan, 250012, People’s Republic of China, Tel +86 531 8216 9335, Fax +86 531 8296 7544, Email quyiqing@sdu.edu.cnPurpose: Cellular senescence participates in the occurrence and development of chronic obstructive pulmonary disease (COPD). This study aimed to identify senescence-related hub genes and explore effective diagnostic markers and therapeutic targets for COPD.Methods: The microarray data from the GSE38974 dataset was downloaded from the Gene Expression Omnibus (GEO) database. The overlapping genes between genes from the GSE38974 dataset and CellAge database were considered differentially expressed senescence-related genes (DESRGs). Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed using R software. Protein-protein interaction (PPI), miRNA-mRNA network, and competitive endogenous RNA (ceRNA) network were constructed and visualized by Cytoscape software. GSE100281 and GSE103174 datasets were employed to validate the expression and diagnostic value of hub genes. Reverse transcription-quantitative polymerase chain reaction (RT-qPCR) was used to measure the mRNA levels of hub genes in peripheral blood mononuclear cells (PBMCs) from COPD and control samples.Results: A total of 23 DESRGs were identified between COPD samples and healthy controls. Enrichment analysis revealed that DESRGs were mainly related to apoptosis and senescence. Moreover, four hub genes and two key clusters were acquired by Cytohubba and MCODE plugin, respectively. CDKN1A and HDAC1 were verified as final hub genes based on GSE100281 and GSE103174 datasets validation. The mRNA expression level of CDKN1A was negatively related to forced expiratory volume in 1 second/forced vital capacity (FEV1/FVC), and HDAC1 expression had the opposite correlation. Finally, an HDAC1-based ceRNA network, including 6 miRNAs and 11 lncRNAs, was constructed.Conclusion: We identified two senescence-related hub genes, CDKN1A and HDAC1, which may be effective biomarkers for COPD diagnosis and treatment. An HDAC1-related ceRNA network was constructed to clarify the role of senescence in COPD pathogenesis.Keywords: chronic obstructive pulmonary disease, senescence, bioinformatics, CDKN1A, HDAC1

COPD is a common disease of the respiratory system. Inflammation, cellular senescence and necroptosis are all pathological alterations of this disease, which may lead to emphysema and infection that aggravate disease progression. Mitochondria acting as respiration-related organelles is usually observed with abnormal changes in morphology and function in CS-stimulated models and COPD patients. Damaged mitochondria can activate mitophagy, a vital mechanism for mitochondrial quality control, whereas under the persistent stimulus of CS or other forms of oxidative stress, mitophagy is impaired, resulting in insufficient clearance of damaged mitochondria. However, the excessive activation of mitophagy also seems to disturb the pathology of COPD. In this review, we demonstrate the variations in mitochondria and mitophagy in CS-induced models and COPD patients and discuss the underlying regulatory mechanism of mitophagy and COPD, including the roles of inflammation, senescence, emphysema and infection.

Background and aim: Competing endogenous RNA (ceRNA) is believed to play vital roles in tumorigenesis. The goal of this study was to screen prognostic biomarkers in lung adenocarcinoma (LUAD). Methods: Common differentially expressed genes (DEGs) were collected from Gene Expression Omnibus (GEO) databases and The Cancer Genome Atlas databases (TCGA) using GEO2R and “limma” package in R, respectively. Overlapping DEGs were conducted using enrichment of functions and protein-protein interaction (PPI) network to discover significant candidate genes. By using a comprehensive analysis, we constructed an mRNA mediated ceRNA network. Survival rates were used Kaplan-Meier analysis. Statistical analysis was used to further identify the prognosis of studied genes. Results: Integrated analysis of GSE32863 and TCGA databases, a total of 886 overlapping DEGs, including 279 up-regulated and 607 down-regulated genes were identified. Considering the highest term of candidate genes in PPI, we identified TPX2, which was enriched in cell division signaling pathway. Besides, 35 differentially expressed miRNAs (DEmiRNAs) were predicted to target TPX2 and only 7 DEmiRNAs were identified to be prognostic biomarkers in LUAD. Then, 30 differentially expressed lncRNAs (DElncRNAs) were predicted to bind these 7 DEmiRNAs. Finally, we found that 7 DElncRNAs were correlated with the overall survival (all p

Background and aim: The outbreak of coronavirus disease 2019 (COVID-19) is quickly turning into a pandemic. We aimed to further clarify the clinical characteristics and the relationship between these features and disease severity. Methods: In this retrospective single-center study, demographic, clinical and laboratory data were collected and analyzed among moderate, severe and critically ill group patients. Results: 88 hospitalization patients confirmed COVID-19 were enrolled in this study. The average age of the patients was 57.11 years (SD, ±15.39). Of these 88 patients, the median body mass index (BMI) was 24.03 (IQR, 21.64-26.61; range 15.05-32.39), the median duration from disease onset to hospital admission were 11 days (IQR, 6.50-14.50). 46.59% patients had one or more comorbidities, with hypertension being the most common (26.14%), followed by diabetes mellitus (12.50%) and coronary atherosclerotic heart disease (CAD) (7.95%). Common symptoms at onset of disease were fever (71.59%), cough (59.09%), dyspnea (38.64%) and fatigue (29.55%). 88 patients were divided into moderate (47 [53.41%]), severe (32 [36.36%]) and critically ill (9 [10.23%]) groups. Compared with severe and moderate patients, lymphocytopenia occurred in 85.71% critically ill patients, and serum IL-2R, IL-6, IL-8, TNF-α, LDH, and cTnI were also increased in 71.42%, 83.33%, 57.14%, 71.43%, 100% and 42.86% in critically ill patients. Through our analysis, the age, comorbidities, lymphocyte count, eosinophil count, ferritin, CRP, LDH, PT and inflammatory cytokines were statistically significant along with the disease severity. Conclusion: We found some clinical characteristic and inflammatory cytokines could reveal the severity of COVID-19 during the outbreak phage. Our research could assist the clinicians recognize severe and critically ill patients timely and focus on the expectant treatment for each patient.

Background: Chronic obstructive pulmonary disease (COPD) is a progressive chronic airway disease of which tobacco smoking is a main risk factor. Numerous studies have revealed that microRNAs participate in the pathogenesis of COPD by regulating cell autophagy and apoptosis. The goal of this study was to elucidate the potential mechanism of miR-4458 in COPD. Methods: Reverse transcription-quantitative polymerase chain reaction (RT-qPCR) was employed to measure the levels of miR-4458 in cigarette smoke extract (CSE)-exposed human bronchial epithelial cells (HBECs) and peripheral blood mononuclear cells (PBMCs) of patients. The effects of miR-4458 on autophagy, cell viability and apoptosis in the CSE-exposed HBECs were assessed by western blot (WB), Cell Counting Kit-8 (CCK-8) assay and flow cytometric analysis. Targetscan and miRDB databases were used to predict the downstream targets of miR-4458.Luciferase reporter assay and rescue experiments were employed to ensure the target gene. Results: MiR-4458 was downregulated in CSE-exposed HBECs and PBMCs of COPD patients. The overexpression of miR-4458 attenuated autophagy and apoptosis in CSE-exposed HBECs, while the downregulation of miR-4458 led to opposite results. Bioinformatics analysis predicted that P53 was a target gene of miR-4458, and luciferase reporter assay further verified this prediction. Rescue experiments showed that miR-4458 regulated cell autophagy and apoptosis via the P53-mediated AKT–mTOR signaling pathway.Conclusions: This study reveals that miR-4458 plays a protective role in CSE-exposed HBECs. MiR-4458 is a promising therapeutic target for COPD treatment.

Yi-Can Yang,1 Meng-Yu Zhang,1 Jian-Yu Liu,1 Yuan-Yuan Jiang,2 Xiu-Li Ji,3 Yi-Qing Qu2 1Department of Pulmonary and Critical Care Medicine, Qilu Hospital, Cheeloo College of Medicine, Shandong University; Shandong Key Laboratory of Infectious Respiratory Diseases, Jinan, People’s Republic of China; 2Department of Pulmonary and Critical Care Medicine, Qilu Hospital of Shandong University; Shandong Key Laboratory of Infectious Respiratory Diseases, Jinan, People’s Republic of China; 3Department of Pulmonary Disease, Jinan Traditional Chinese Medicine Hospital, Jinan, People’s Republic of ChinaCorrespondence: Yi-Qing Qu, Department of Pulmonary and Critical Care Medicine, Qilu Hospital, Shandong University, Shandong Key Laboratory of Infectious Respiratory Diseases, Wenhuaxi Road 107#, Jinan, 250012, People’s Republic of China, Tel +86 531 8216 9335, Fax +86 531 8296 7544, Email quyiqing@sdu.edu.cnPurpose: Ferroptosis and immune infiltration are involved in the pathogenesis of chronic obstructive pulmonary disease (COPD). We aim to identify ferroptosis-related hub genes and analyze their association with immune infiltration in COPD through bioinformatics methods.Materials and Methods: The mRNA microarray data of GSE38974 were downloaded from Gene Expression Omnibus to obtain differentially expressed genes (DEGs). The DEGs were intersected with ferroptosis-related genes (FRGs) from FerrDb to obtain differentially expressed FRGs. GO and KEGG enrichment and protein–protein interaction (PPI) analyses of differentially expressed FRGs were conducted in R software and STRING database. The key module and hub genes were screened by Cytoscape software. MiRNAs, transcription factors and signal molecules were predicted in miRNet and NetworkAnalyst. The disease correlation in the Comparative Toxicomics Database (CTD) and the receiver operating characteristic (ROC) curves of hub genes were analyzed. Immune infiltration was evaluated by CIBERSORT algorithm. Spearman correlation analyses were conducted between hub genes and differentially infiltrated immune cells.Results: Fifteen differentially expressed FRGs were identified, which were enriched in some terms involving airway inflammatory responses and structural remodeling. Five hub genes were selected including HIF1A, IL6, PTGS2, CDKN1A and ATM. Inference scores in CTD indicated their association with COPD. Two miRNAs, five transcription factors and one signal molecule were predicted. The combination of hub genes could be a fine diagnostic indicator of COPD (AUC: 0.981, CI: 0.940-1.000). Immune infiltration evaluation showed that monocytes and M0 macrophages were upregulated in COPD lung tissues, while CD8 T cells, activated NK cells, M2 macrophages, resting dendritic cells and resting mast cells were downregulated. The hub genes were significantly associated with differentially infiltrated immune cells.Conclusion: We identified five ferroptosis-related hub genes (HIF1A, IL6, PTGS2, CDKN1A and ATM) in COPD, and found that they may influence the pathogenesis of COPD by regulating ferroptosis and thus affecting infiltrating immune cells.Keywords: COPD, ferroptosis, immune infiltration, bioinformatics

Background: Autophagy plays an important role in lung adenocarcinoma (LUAD). In this study, we aimed to explore the autophagy-related gene (ARG) expression pattern and to identify promising autophagy-related biomarkers to improve the prognosis of LUAD.Methods: The gene expression profiles and clinical information of LUAD patients were downloaded from the Cancer Genome Atlas (TCGA), and validation cohort information was extracted from the Gene Expression Omnibus database. The Human Autophagy Database (HADb) was used to extract ARGs. Gene expression data were analyzed using the limma package and visualized using the ggplot2 package as well as the pheatmap package in R software. Functional enrichment analysis was also performed for the differentially expressed ARGs (DEARGs). Then, consensus clustering revealed autophagy-related tumor subtypes, and differentially expressed genes (DEGs) were screened according to the subtypes. Next, the univariate Cox and multivariate Cox regression analyses were used to identify independent prognostic ARGs. After overlapping DEGs and the independent prognostic ARGs, the predictive risk model was established and validated. Correlation analyses between ARGs and clinicopathological variables were also explored. Finally, the TIMER and TISIDB databases were used to further explore the correlation analysis between immune cell infiltration levels and the risk score as well as clinicopathological variables in the predictive risk model.Results: A total of 222 genes from the HADb were identified as ARGs, and 28 of the 222 genes were pooled as DEARGs. The most significant GO term was autophagy (p = 3.05E-07), and KEGG analysis results indicated that 28 DEARGs were significantly enriched in the ErbB signaling pathway (p < 0.001). Then, consensus clustering analysis divided the LUAD into two clusters, and a total of 168 DEGs were identified according to cluster subtypes. Then univariate and multivariate Cox regression analyses were used to identify 12 genes that could serve as independent prognostic indicators. After overlapping 168 DEGs and 12 genes, 10 genes (ATG4A, BAK1, CAPNS1, CCR2, CTSD, EIF2AK3, ITGB1, MBTPS2, SPHK1, ST13) were selected for the further exploration of the prognostic pattern. Survival analysis results indicated that this risk model identified the prognosis (p = 4.379E-10). Combined with the correlation analysis results between ARGs and clinicopathological variables, five ARGs were screened as prognostic genes. Among them, SPHK1 expression levels were positively correlated with CD4+ T cells and dendritic cell infiltration levels.Conclusions: In this study, we constructed a predictive risk model and identified a five autophagy subtype-related gene expression pattern to improve the prognosis of LUAD. Understanding the subtypes of LUAD is helpful to accurately characterize the LUAD and develop personalized treatment.

Background. Acute lung injury (ALI) is a fatal syndrome frequently induced by lipopolysaccharide (LPS) released from the bacterial cell wall. LPS could also trigger autophagy of lung bronchial epithelial cell to relieve the inflammation, while the overwhelming LPS would impair the balance of autophagy consequently inducing serious lung injury. Methods. We observed the autophagy variation of 16HBE, human bronchial epithelial cell, under exposure to different concentrations of LPS through western blot, immunofluorescence staining, and electron microscopy. Eight strands of 16HBE were divided into two groups upon 1000 ng/ml LPS stimulation or not, which were sent to be sequenced at whole transcriptome. Subsequently, we analyzed the sequencing data in functional enrichment, pathway analysis, and candidate gene selection and constructed a hsa-miR-663b-related competing endogenous RNA (ceRNA) network. Results. We set a series of concentrations of LPS to stimulate 16HBE and observed the variation of autophagy in related protein expression and autophagosome count. We found that the effective concentration of LPS was 1000 ng/ml at 12 hours of exposure and sequenced the 1000 ng/ml LPS-stimulated 16HBE. As a result, a total of 750 differentially expressed genes (DEGs), 449 differentially expressed lncRNAs (DElncRNAs), 76 differentially expressed circRNAs (DEcircRNAs), and 127 differentially expressed miRNAs (DEmiRNAs) were identified. We constructed the protein-protein interaction (PPI) network to visualize the interaction between DEGs and located 36 genes to comprehend the core discrepancy between LPS-stimulated 16HBE and the negative control group. In combined analysis of differentially expressed RNAs (DERNAs), we analyzed all the targeted relationships of ceRNA in DERNAs and figured hsa-miR-663b as a central mediator in the ceRNA network to play when LPS induced the variation of autophagy in 16HBE. Conclusion. Our research indicated that the hsa-miR-663b-related ceRNA network may contribute to the key regulatory mechanism in LPS-induced changes of autophagy and ALI.

Aims Pyroptosis and inflammation are involved in the development of chronic obstructive pulmonary disease (COPD). However, the cigarette smoke-mediated mechanism of COPD remains unclear. In this study, we aimed to investigate the role of nucleotide-binding domain-like receptor protein-3 (NLRP3) inflammasome-mediated pyroptosis in the death of human bronchial epithelial (HBE) cells after cigarette smoke extract (CSE) exposure. Main methods The protein level of NLRP3 in lung tissue was measured after cigarette smoke exposure in vivo. In vitro, HBE cells were treated with CSE. Subsequently, the activity of caspase-1, lactate dehydrogenase (LDH) release, release of interleukin (IL)-1β and NLRP3 expression levels were measured. The involvement of reactive oxygen species (ROS) was also explored. Key findings After exposure to CSE, increased release of LDH, the transcriptional and translational upregulation of NLRP3, the caspase-1 activity levels, and enhanced IL-1β and IL-18 release were observed in 16HBE cells. In addition, NLRP3 was required to activate the caspase-1. Our results suggested that pre-stimulated of 16HBE with a caspase-1 inhibitor, or using NLRP3 siRNA to silence NLRP3 expression, also caused the decrease of IL-1β release and pyroptosis. Significances. CSE induced inflammation and contributed to pyroptosis through the ROS/NLRP3/caspase-1 pathway in 16HBE cells. The NLRP3 inflammasome participates in CSE-induced HBE cell damage and pyroptosis, which could provide new insights into COPD.

Kinesin family member 3A (KIF3A) plays a crucial role in the carcinogenesis of different types of human cancer. The present study aimed to identify the role of KIF3A in the carcinogenesis of non-small cell lung cancer (NSCLC). KIF3A protein expression was determined in 163 patients with NSCLC using immunohistochemistry staining. The prognosis of patients with NSCLC was determined using Kaplan-Meier survival and Cox regression analyses. The function of KIF3A on the carcinogenesis and metastasis of NSCLC was determined in vitro. Furthermore, a protein-protein interaction (PPI) network of KIF3A was constructed and the potential interacting molecules were identified using bioinformatic analysis. The protein expression levels of KIF3A were significantly lower in the NSCLC tissues compared with that in the adjacent tissues, and low KIF3A expression level was associated with unfavorable survival outcomes in patients with NSCLC. Furthermore, KIF3A knockdown increased proliferation, invasion and metastasis, and inhibited apoptosis of NSCLC cells. KIF3A was demonstrated to interact with intraflagellar transport 57 (IFT57) in the PPI network. In addition, validation analyses indicated that KIF3A mRNA expression levels were positively correlated with IFT57 mRNA expression levels in clinical NSCLC samples and NSCLC cell lines. Taken together, the results of the present study suggested that KIF3A is a key tumor suppressor gene for carcinogenesis and metastasis of NSCLC, it may also function as a biomarker and interacts with IFT57 in the progression of NSCLC.

Lung adenocarcinoma (LUAD) has become the main histologic type, which account for nearly 40% of lung cancer. The present study aimed to investigate the gene expression signature in smoking related LUAD. A total of 45 smoking related DEGs in LUAD were identified and functional enrichment analysis was also performed. Then Cox's regression model and Kaplan-Meier analysis were used to screen potential prognostic genes. Finally, AURKA and FAM83A were left for further immune-related mechanism exploration. Kaplan-Meier analysis indicated survival rates are related to different immune cell (B cell and Dendritic cell) infiltration levels. Mechanistically, we further explore the correlation between AURKA and FAM83A gene expression levels and tumor-infiltrating lymphocytes (TILs) level as well as their response to immunomodulators. The results suggested that AURKA and FAM83A are highly expressed in smoking related LUAD, and negatively correlated to B cell and Dendritic cell infiltration levels. At the same time, B cell and Dendritic cell infiltration levels also related to the prognosis of LUAD. We further revealed AURKA and FAM83A could be novel targets to improve the prognosis of LUAD through regulated the response to immunomodulators.

Abnormal glycolysis is one of the hallmarks of cancer and plays an important role in its development. This study was devoted to identify glycolysis related genes as prognostic biomarkers for non-small cell lung cancer (NSCLC). The mRNA expression profile and clinical follow-up data were obtained using The Cancer Genome Atlas (TCGA) database. The validation set was obtained by bootstrap method of random repeated sampling. A total of 200 glycolysis-related genes were obtained from Gene Set Enrichment Analysis (GSEA) and 46 genes were significantly associated with overall survival (OS). Five genes (PKP2, LDHA, HMMR, COL5A1 and B3GNT3) were eventually identified to calculate risk score of NSCLC patients. The univariate and multivariate Cox regression analysis indicated that the risk score was an independent prognostic factor (training set: HR=2.126, 95% CI [1.605, 2.815], p

Background: In recent years, LncRNA acts as a member of competing endogenous RNA (ceRNA), playing an important role in drug resistance of lung cancer. The aim of this study was to identify potential biomarkers about cisplatin resistant lung cancer cells using a comprehensive ceRNA network.Methods: GSE6410 (GPL-201) analyzed gene expression changes about cispaltin resistance in A549 NSCLC cells. GSE43249 (GPL-14613) included noncoding RNA expression profiling derived from the cisplatin resistant A549 lung cells. GEO2R, an online analysis tool, analyzed the differentially expressed mRNAs and miRNAs (DEmRNAs and DEmiRNAs). To explore the functional enrichment implication of differentially expressed mRNAs, we used the GO and KEGG pathway analysis. Through miRDB、Targetscan、Starbase、miRWalk, we found targeted miRNAs. The Kaplan-Meier curve method was used to show clinical survival analysis of targeted RNAs (P). The Starbase database predicted potential lncRNAs mediated targeted miRNAs. Eventually, the novel ceRNA network of lncRNAs, miRNAs, mRNA was constructed by cytoscape3.7.2.Results:118 differentially expressed mRNAs were the basis of the mediated ceRNA network. DAVID and Kaplan-Meier picked out BAX, an apoptosis regulator. Venn Diagram demonstrated 8 miRNAs commomly regulating Bax. Starbase predicted lncRNA XIST mediated miRNAs. Finally, lncRNA XIST maybe a useful biomarker regulating cisplatin resistance in lung cancer cells.Conclusions: LncRNA XIST competitively bound to miRNA 520 in the regulation of cisplatin resistance by BAX , participating apoptosis in the p53 signaling pathway.

Background: Tumor microenvironment (TME) plays a significant role in the development of cancer. However, the roles of TME in lung squamous cell carcinoma (LUSC) are not well studied. In our study, we aimed to identify differentially expressed tumor microenvironment-related genes as biomarker for predicting the prognosis of LUSC.Methods: We combined The Cancer Genome Atlas (TCGA) and Estimation of Stromal and Immune cells in Malignant Tumor tissue using Expression data (ESTIMATE) datasets to identified differentially expressed genes in lung squamous cell carcinoma microenvironment. Then, functional enrichment analysis and protein-protein interaction (PPI) network were conducted. The top six genes in the PPI network were regarded as tumor microenvironment-related hub genes. Finally, the relationship between hub genes and tumor-infiltrating immune cells was deciphered using TIMER.Results: Our study revealed that immune and stromal scores are associated with specific clinicopathologic variables in LUSC. These variables include gender, age, distant metastasis and prognosis. In addition, a total of 874 upregulated and 72 downregulated genes were identified. Functional enrichment analysis demonstrated a correlation between DEGs and the tumor microenvironment, tumor immune cells differentiation and activation. C3AR1, CSF1R, CCL2, CCR1, TYROBP, CD14were selected as the hub genes. A positive correlation was obtained between the expression of hub genes and the abundance of six immune cells.Conclusions: The results of the present study showed that ESTIMATE algorithm-based stromal and immune scores may be a reference indicator of cancer prognosis. We identified five TME-related genes, which could be used to predict the prognosis of LUSC patients.

Pudilan Xiaoyan Oral Liquid has effects in clearing away heat and detoxifying,and is used to treat pharynx and throat swelling caused by the syndrome of excessive heat and toxin accumulation. Its efficacy is to relieve swelling and pain( redness,swelling and hot pain). It is included in the Chinese Pharmacopoeia of 2015 Edition,and has been listed in provincial health insurance directories of Shaanxi,Jiangsu,Liaoning,Hunan,Tianjin,Xinjiang and Hebei. It has been recommended by health departments of Beijing,Chongqing and other provinces as a preferred drug for the prevention and treatment of H1 N1 and HFMD,and listed in the diagnosis and Treatment Guide of HFMD by the Ministry of Health,the Clinical Application Guide of Chinese Patent Medicine edited by the Lung Department Disease Branch of China Association of Chinese Medicine,and the Clinical Practice Guide of Single Administration/Combined Administration of Antibiotics in Treatment of Common Infectious Diseases by China Association of Chinese Medicine. To further improve the clinicianapos;s understanding of drugs and better guide the rational clinical application,we invited front-line clinical experts from respiratory department,infectious department and dermatology of traditional Chinese and Western medicine to develop and compile the expert consensus. The consensus fully considered the clinical evidence and the expert clinical experience to give recommendations for clinical problems with evidence support and consensus suggestions for clinical problems without evidence support by the nominal group method.This consensus is based on clinical research evidence and expert experience in a simple and clear format,which provides a preliminary reference for the clinical use of the drug.

ShuFeng JieDu capsule (SFJDC), a traditional Chinese medicine, has been recommended for the treatment of COVID-19 infections. However, the pharmacological mechanism of SFJDC still remains vague to date. The active ingredients and their target genes of SFJDC were collected from TCMSP. COVID-19 is a type of Novel Coronavirus Pneumonia (NCP). NCP-related target genes were collected from GeneCards database. The ingredients-targets network of SFJDC and PPI networks were constructed. The candidate genes were screened by Venn diagram package for enrichment analysis. The gene-pathway network was structured to obtain key target genes. In total, 124 active ingredients, 120 target genes of SFJDC and 251 NCP-related target genes were collected. The functional annotations cluster 1 of 23 candidate genes (CGs) were related to lung and Virus infection. RELA, MAPK1, MAPK14, CASP3, CASP8 and IL6 were the key target genes. The results suggested that SFJDC cloud be treated COVID-19 by multi-compounds and multi-pathways, and this study showed that the mechanism of traditional Chinese medicine (TCM) in the treatment of disease from the overall perspective.

YuPingFeng (YPF) granules are a classic herbal formula extensively used in clinical practice in China for the treatment of COPD. However, the pathological mechanisms of YPF in COPD remain undefined. In the present research, a network pharmacology-based strategy was implemented to elucidate the underlying multicomponent, multitarget, and multipathway modes of action of YPF against COPD. First, we identified putative YPF targets based on TCMSP databases and constructed a network containing interactions between putative YPF targets and known therapeutic targets of COPD. Next, two topological parameters, “degree” and “closeness,” were calculated to identify target genes in the network. The major hubs were imported to the MetaCore database for pathway enrichment analysis. In total, 23 YPF active ingredients and 83 target genes associated with COPD were identified. Through protein interaction network analysis, 26 genes were identified as major hubs due to their topological importance. GO and KEGG enrichment analysis results revealed YPF to be mainly associated with the response to glucocorticoids and steroid hormones, with apoptotic and HIF-1 signalling pathways being dominant and correlative pathways. The promising utility of YPF in the treatment of COPD has been demonstrated by a network pharmacology approach.

Background. Lung cancer is the leading cause of cancer-related mortality worldwide, and non-small cell lung cancer (NSCLC) accounts for over 80% of all lung cancers. Serum microRNAs (miRNAs), due to their high stability, have the potential to become valuable noninvasive biomarkers. This present study was aimed to identify the serum miRNAs expression signatures for the diagnosis and prognosis of NSCLC using bioinformatics analysis. Methods. A total of 12 miRNAs profiling studies have been identified in Pubmed, Gene Expression Omnibus (GEO), and ArreyExpress databases. Differentially expressed miRNAs (DEmiRNAs) were analyzed according to GEO2R online tool and RRA method from R. Then, prediction of DEmiRNAs’ target genes from TargetScan, PicTar, miRDB, Tarbase, and miRanda database. Furthermore, we using reverse transcription– quantitative polymerase chain reaction (RT-qPCR) to evaluate the expression levels of DEmiRNAs in serum samples obtained from NSCLC patients and healthy controls. Subsequently, the clinical significance of the tested miRNAs was determined using receiver operating characteristic (ROC) analysis and Cox regression analysis. Results. A total of 27 DEmiRNAs were identified and 5 of them (miR-1228-3p, miR-1228-5p, miR-133a-3p, miR-1273f, miR-545-3p) were significantly up-regulated and 4 of them (miR-181a-5p, miR-266-5p, miR-361-5p, miR-130a-3p) were significantly down-regulated in NSCLC patients compared with healthy controls. RT-qPCR validated that miR-1228-3p (P =0.006) and miR-181a-5p (P =0.030) were significantly differentially expressed in the serum of NSCLC patients and healthy controls. ROC analysis on miR-1228-3p and miR-181a-5p revealed the area under the curve (AUC) of 0.685 (95% confidence interval [CI], 0.563–0.806; P =0.006) and 0.647 (95% CI, 0.506–0.758; P =0.049). ROC analysis on miR-1228-3p combined miR-181a-5p revealed the AUC of 0.711 (95% CI, 0.593–0.828; P =0.002). Multivariate Cox regression analysis demonstrated that the high serum miR-1228-3p level was an independent factor for the poor prognosis of NSCLC patients. Conclusions. Serum miR-1228-3p and miR-181a-5p are potential noninvasive biomarkers for the diagnosis and prognosis of NSCLC patients.

Xiao Liu,1,* Jingge Qu,2,* Weixiao Xue,1 Liangai He,1 Jun Wang,3 Xuejiao Xi,1 Xiaoxia Liu,1 Yunhong Yin,1 Yiqing Qu1 1Department of Respiratory Medicine, Qilu Hospital of Shandong University, Jinan, People’s Republic of China; 2Department of Rheumatology, Second Hospital of Harbin Medical University, Harbin, People’s Republic of China; 3Department of Respiratory Medicine, Second Hospital of Shandong Traditional Chinese Medicine University, Jinan, People’s Republic of China *These authors contributed equally to this work Objectives: MicroRNAs (miRNAs) play essential roles in the development of COPD. In this study, we aimed to identify and validate potential miRNA biomarkers in frequent and non-frequent exacerbators of COPD patients using bioinformatic analysis.Materials and methods: The candidate miRNA biomarkers in COPD were screened from Gene Expression Omnibus (GEO) dataset and identified using GEO2R online tool. Then, we performed bioinformatic analyses including target prediction, gene ontology (GO), pathway enrichment analysis and construction of protein–protein interaction (PPI) network. Furthermore, the expression of the identified miRNAs in peripheral blood monocular cells (PBMCs) of COPD patients was validated using quantitative real-time polymerase chain reaction (qRT-PCR).Results: MiR-23a, miR-25, miR-145 and miR-224 were identified to be significantly downregulated in COPD patients compared with healthy controls. GO analysis showed the four miRNAs involved in apoptotic, cell differentiation, cell proliferation and innate immune response. Pathway analysis showed that the targets of these miRNAs were associated with p53, TGF-β, Wnt, VEGF and MAPK signal pathway. In healthy controls, the miR-25 and miR-224 levels were significantly decreased in smokers compared with nonsmokers (P

// Xiao Liu 1 , Hao Li 1 , Yunhong Yin 1 , Dedong Ma 1 and Yiqing Qu 1 1 Department of Respiratory Medicine, Qilu Hospital of Shandong University, Jinan, China Correspondence to: Yiqing Qu, email: // Keywords : Sjogren’s syndrome, systemic lupus erythematosus, diffuse cystic lung changes Received : January 23, 2017 Accepted : March 02, 2017 Published : March 08, 2017 Abstract Sjogren’s syndrome (SS) is a chronic inflammatory autoimmune disease that can occur as a unique existence (primary Sjogren’s syndrome) or merge with other systemic diseases like systemic lupus erythematosus (SLE), rheumatoid arthritis or systemic sclerosis (secondary Sjogren’s syndrome). Data on the two diseases occurrence order are inadequate. Primary Sjogren’s syndrome (pSS) may relatively uncommonly lead to diffuse cystic lung changes. We represent a female who was diagnosed pSS with diffuse cystic lung alterations developed SLE two years later. SS was diagnosed on account of the existence of dryness of eye and mouth, Schirmer’s test, biopsy of the minor salivary glands of her lip, positive anti-SSA and anti-SSB antibody in the serum. Chest computed tomography image showed bilateral diffuse cystic changes with a wide variation in cyst size and distribution. SLE was finally diagnosed based on bilateral lower limb skin rash, gonarthritis and omarthritis, low level of complement, antinuclear antibody 1:640 and positive antibodies to double-stranded DNA. Improvement was achieved with therapy of corticosteroids, hydroxychloroquine and antibiotics. This report provides us clinical, diagnosis and treatment perception of SS-onset SLE as patient presenting diffuse cystic lung changes.

// Chunyu Li 1 , Yunhong Yin 1 , Xiao Liu 1 , Xuejiao Xi 1 , Weixiao Xue 1 , Yiqing Qu 1 1 Department of Respiratory Medicine, Qilu Hospital of Shandong University, Jinan 250012, China Correspondence to: Yiqing Qu, email: yiqing_qu@163.com Keywords: NSCLC, microRNA, robust rank aggregation, integrative analysis, biomarker Received: December 23, 2016 Accepted: February 13, 2017 Published: February 21, 2017 ABSTRACT Recently, increasing studies of miRNA expression profiling has confirmed that miRNA plays an essential role in non-small cell lung cancer (NSCLC). However, inconsistent or discrepant results exist in these researches. In present study, we performed an integrative analysis of 32 miRNA profiling studies compared the differentially expressed miRNA between NSCLC tissue and non-cancerous lung tissue to identify candidate miRNAs associated with NSCLC. 7 upregulated and 10 downregulated miRNAs were identified as miRNA integrated-signature using Robust Rank Aggregation (RRA) method. qRT-PCR demonstrated that miR-21-5p, miR-210, miR-205-5p, miR-182-5p, miR-31-5p, miR-183-5p and miR-96-5p were up-regulated, whereas miR-126-3p, miR-30a-5p, miR-451a, miR-143-3p and miR-30d-5p were down-regulated more than 2 folds in the NSCLC, which was further validated in Tumor Cancer Genome Atlas (TCGA) database. Receiver operating characteristic (ROC) curve analysis confirmed that 9 miRNAs had good predictive performance (AUC > 0.9). Cox regression analysis revealed that miR-21-5p (hazard ratio [HR]: 1.616, 95% CI: 1.114–2.342, p = 0.011) and miR-30d-5p (HR: 0.578, 95% CI: 0.400–0.835, p = 0.003) were independent prognostic factors in NSCLC for overall survival. The accumulative effects of the two miRNAs on the prognosis of NSCLC were further estimated. The results showed that patients with two positive markers had a worse prognosis than those with one or none positive marker. In conclusion, this study contributes to the comprehension of the role of miRNAs in NSCLC and provides a basis for further clinical application.

Background: DNA methylation acts as a key component in epigenetic modifications of genomic function and functions as disease-specific prognostic biomarkers for lung squamous cell carcinoma (LUSC). This present study aimed to identify methylation-driven genes as prognostic biomarkers for LUSC using bioinformatics analysis. Materials and Methods: Differentially expressed RNAs were obtained using the edge R package from 502 LUSC tissues and 49 adjacent non-LUSC tissues. Differentially methylated genes were obtained using the limma R package from 504 LUSC tissues and 69 adjacent non-LUSC tissues. The methylation-driven genes were obtained using the MethylMix R package from 500 LUSC tissues with matched DNA methylation data and gene expression data and 69 non-LUSC tissues with DNA methylation data. Gene ontology and ConsensusPathDB pathway analysis were performed to analyze the functional enrichment of methylation-driven genes. Univariate and multivariate Cox regression analyses were performed to identify the independent effect of differentially methylated genes for predicting the prognosis of LUSC. Results: A total of 44 methylation-driven genes were obtained. Univariate and multivariate Cox regression analyses showed that twelve aberrant methylated genes (ATP6V0CP3, AGGF1P3, RP11-264L1.4, HIST1H4K, LINC01158, CH17-140K24.1, CTC-523E23.14, ADCYAP1, COX11P1, TRIM58, FOXD4L6, CBLN1) were entered into a Cox predictive model associated with overall survival in LUSC patients. Methylation and gene expression combined survival analysis showed that the survival rate of hypermethylation and low-expression of DQX1 and WDR61 were low. The expression of DQX1 had a significantly negatively correlated with the methylation site cg02034222. Conclusion: Methylation-driven genes DQX1 and WDR61 might be potential biomarkers for predicting the prognosis of LUSC.

Long non-coding RNAs (lncRNAs) act as a member of competing endogenous RNAs (ceRNAs) and plays a significant role in tumorigenesis. The aim of this study was to identify potential lncRNA biomarkers for predicting the prognosis of lung squamous cell carcinoma (LUSC) using a comprehensive analysis of lncRNA mediated ceRNA network. Differentially expressed RNAs datasets were obtained using edge R package in 502 LUSC tissues and 49 adjacent non-LUSC tissues from the Cancer Genome Atlas (TCGA). Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were performed to identify functional enrichment implication of lncRNA related differentially expressed mRNAs. Survival analysis was used Kaplan-Meier curve method. Univariate and multivariate Cox regression analysis were performed to construct a predictive model with lncRNA biomarkers. A total of 2185 lncRNAs, 170 miRNAs and 2053 mRNAs were differentially expressed between LUSC tissues and adjacent non-LUSC tissues. The novel constructed ceRNA network incorporated 184 LUSC-specific lncRNAs, 18 miRNAs, and 49 mRNAs. About 11 of 184 differentially expressed lncRNAs and 1 of 18 differentially expressed miRNAs and 5 of 49 differentially expressed mRNAs were conspicuously related to overall survival (