Identification of gene and microRNA changes in response to smoking in human airway epithelium by bioinformatics analyses

Comparison of the effects of active and passive smoking of tobacco cigarettes, electronic nicotine delivery systems and tobacco heating products on the expression and secretion of oxidative stress and inflammatory response markers. A systematic review

OBJECTIVES

This work attempts to summarize current knowledge on the effects of active and passive smoking of cigarettes, electronic nicotine delivery systems and tobacco heating products on the expression and secretion of oxidative stress and inflammatory response mediators, and on their possible impact on chronic obstructive pulmonary disease development.

MATERIALS AND METHODS

The literature was searched by the terms: 'smoking', 'active smoking', 'passive smoking', 'main-stream smoke', 'side-stream smoke', 'secondhand smoke', 'cigarette' 'THP', 'tobacco heating product', 'ENDS', 'electronic nicotine delivery system', 'e-cigarette', 'electronic cigarette', oxidative stress', inflammatory response' and 'gene expression'.

RESULTS

Cigarette smoking (active and passive) induces oxidative stress and inflammatory response in the airways. We present the effect of active smoking of e-cigarettes (EC) and heat-not-burn (HnB) products on the increased expression and secretion of oxidative stress and inflammatory response markers. However, there is only a limited number of studies on the effect of their second-hand smoking, and those available mainly describe aerosol composition.

DISCUSSION

The literature provides data which confirm that active and passive cigarette smoking induces oxidative stress and inflammatory response in the airways and is a key risk factor of COPD development. Currently, there is a limited number of data about ENDS and THP active and passive smoking effects on the health of smokers and never-smokers. It is particularly important to assess the effect of such products during long-term use by never-smokers who choose them as the first type of cigarettes, and for never-smokers who are passively exposed to their aerosol.

The blood proteome of imminent lung cancer diagnosis

Identification of risk biomarkers may enhance early detection of smoking-related lung cancer. We measured between 392 and 1,162 proteins in blood samples drawn at most three years before diagnosis in 731 smoking-matched case-control sets nested within six prospective cohorts from the US, Europe, Singapore, and Australia. We identify 36 proteins with independently reproducible associations with risk of imminent lung cancer diagnosis (all p < 4 × 10-5). These include a few markers (e.g. CA-125/MUC-16 and CEACAM5/CEA) that have previously been reported in studies using pre-diagnostic blood samples for lung cancer. The 36 proteins include several growth factors (e.g. HGF, IGFBP-1, IGFP-2), tumor necrosis factor-receptors (e.g. TNFRSF6B, TNFRSF13B), and chemokines and cytokines (e.g. CXL17, GDF-15, SCF). The odds ratio per standard deviation range from 1.31 for IGFBP-1 (95% CI: 1.17-1.47) to 2.43 for CEACAM5 (95% CI: 2.04-2.89). We map the 36 proteins to the hallmarks of cancer and find that activation of invasion and metastasis, proliferative signaling, tumor-promoting inflammation, and angiogenesis are most frequently implicated.

The Profile of MicroRNA Expression and Potential Role in the Regulation of Drug-Resistant Genes in Doxorubicin and Topotecan Resistant Ovarian Cancer Cell Lines

Epithelial ovarian cancer has the highest mortality among all gynecological malignancies. The main reasons for high mortality are late diagnosis and development of resistance to chemotherapy. Resistance to chemotherapeutic drugs can result from altered expression of drug-resistance genes regulated by miRNA. The main goal of our study was to detect differences in miRNA expression levels in two doxorubicin (DOX)- and two topotecan (TOP)-resistant variants of the A2780 drug-sensitive ovarian cancer cell line by miRNA microarray. The next aim was to recognize miRNAs as factors responsible for the regulation of drug-resistance genes. We observed altered expression of 28 miRNA that may be related to drug resistance. The upregulation of miR-125b-5p and miR-935 and downregulation of miR-218-5p was observed in both DOX-resistant cell lines. In both TOP-resistant cell lines, we noted the overexpression of miR-99a-5p, miR-100-5p, miR-125b-5p, and miR-125b-2-3p and decreased expression of miR-551b-3p, miR-551b-5p, and miR-383-5p. Analysis of the targets suggested that expression of important drug-resistant genes such as the collagen type I alpha 2 chain (COL1A2), protein Tyrosine Phosphatase Receptor Type K (PTPRK), receptor tyrosine kinase—EPHA7, Roundabout Guidance Receptor 2 (ROBO2), myristoylated alanine-rich C-kinase substrate (MARCK), and the ATP-binding cassette subfamily G member 2 (ABCG2) can be regulated by miRNA.

Identification of SRXN1 and KRT6A as Key Genes in Smoking-Related Non-Small-Cell Lung Cancer Through Bioinformatics and Functional Analyses

Background

Lung cancer is the leading cause of cancer-related mortality worldwide. Although cigarette smoking is an established risk factor for lung cancer, few reliable smoking-related biomarkers for non-small-cell lung cancer (NSCLC) are available. An improved understanding of these biomarkers would further the development of new biomarker-targeted therapies and lead to improvements in overall patient survival.

Methods

We performed bioinformatic analysis to screened potential target genes, then quantitative PCR, western, siRNA, CCK-8, flow cytometry, tumorigenicity assays in nude mice were performed to validated the function.

Results

In this study, we identified 83 smoking-related genes (SRGs) based on an integration analysis of two Gene Expression Omnibus (GEO) datasets, and 27 hub SRGs with potential carcinogenic effects by analyzing a dataset of smokers with NSCLC in The Cancer Genome Atlas (TCGA) database. A survival analysis revealed three genes with potential prognostic value, namely SRXN1, KRT6A and JAKMIP3. A univariate Cox analysis revealed significant associations of elevated SRXN1 and KRT6A expression with prognosis. A receiver operating characteristic (ROC) curve analysis indicated the high diagnostic value of SRXN1 and KRT6A for smoking and cancer. Quantitative PCR and western blotting validated the increased expression of SRXN1 and KRT6A mRNA and protein, respectively, in lung cancer cell lines and NSCLC tissues. In patients with NSCLC, SRXN1 and KRT6A expression was associated with the tumor–node–metastasis (TNM) stage, presence of metastasis, history of smoking and daily smoking consumption. Furthermore, inhibition of SRXN1 or KRT6A suppressed viability and enhanced apoptosis in the A549 human lung carcinoma cell line. Tumorigenicity assays in nude mice confirmed that the siRNA-mediated downregulation of SRXN1 and KRT6A expression inhibited tumor growth in vivo.

Conclusions

In summary, SRXN1 and KRT6A act as oncogenes in NSCLC and might be potential biomarkers of smoking exposure and the early diagnosis and prognosis of NSCLC in smokers, which is vital for lung cancer therapy.

A novel 14-gene signature for overall survival in lung adenocarcinoma based on the Bayesian hierarchical Cox proportional hazards model

There have been few investigations of cancer prognosis models based on Bayesian hierarchical models. In this study, we used a novel Bayesian method to screen mRNAs and estimate the effects of mRNAs on the prognosis of patients with lung adenocarcinoma. Based on the identified mRNAs, we can build a prognostic model combining mRNAs and clinical features, allowing us to explore new molecules with the potential to predict the prognosis of lung adenocarcinoma. The mRNA data (n = 594) and clinical data (n = 470) for lung adenocarcinoma were obtained from the TCGA database. Gene set enrichment analysis (GSEA), univariate Cox proportional hazards regression, and the Bayesian hierarchical Cox proportional hazards model were used to explore the mRNAs related to the prognosis of lung adenocarcinoma. Multivariate Cox proportional hazard regression was used to identify independent markers. The prediction performance of the prognostic model was evaluated not only by the internal cross-validation but also by the external validation based on the GEO dataset (n = 437). With the Bayesian hierarchical Cox proportional hazards model, a 14-gene signature that included CPS1, CTPS2, DARS2, IGFBP3, MCM5, MCM7, NME4, NT5E, PLK1, POLR3G, PTTG1, SERPINB5, TXNRD1, and TYMS was established to predict overall survival in lung adenocarcinoma. Multivariate analysis demonstrated that the 14-gene signature (HR 3.960, 95% CI 2.710–5.786), T classification (T₁, reference; T₃, HR 1.925, 95% CI 1.104–3.355) and N classification (N₀, reference; N₁, HR 2.212, 95% CI 1.520–3.220; N₂, HR 2.260, 95% CI 1.499–3.409) were independent predictors. The C-index of the model was 0.733 and 0.735, respectively, after performing cross-validation and external validation, a nomogram was provided for better prediction in clinical application. Bayesian hierarchical Cox proportional hazards models can be used to integrate high-dimensional omics information into a prediction model for lung adenocarcinoma to improve the prognostic prediction and discover potential targets. This approach may be a powerful predictive tool for clinicians treating malignant tumours.

Comprehensive analysis of the LncRNAs, MiRNAs, and MRNAs acting within the competing endogenous RNA network of LGG

Messenger RNA (mRNA) and long noncoding RNA (lncRNA) targets interact via competitive microRNA (miRNA) binding. However, the roles of cancer-specific lncRNAs in the competing endogenous RNA (ceRNA) networks of low-grade glioma (LGG) remain unclear. This study obtained RNA sequencing data for normal solid tissue and LGG primary tumour tissue from The Cancer Genome Atlas database. We used a computational method to analyse the relationships among the mRNAs, lncRNAs, and miRNAs in these samples. Gene ontology (GO) function and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis was used to predict the biological processes (BPs) and pathways associated with these genes. Kaplan-Meier survival analysis was used to evaluate the association between the expression levels of specific mRNAs, lncRNAs, and miRNAs and overall survival. Finally, we created a ceRNA network describing the relationships among these mRNAs, lncRNAs, and miRNAs using Cytoscape 3.5.1. A total of 2555 differentially expressed (DE) mRNAs, 218 DElncRNAs, and 192 DEmiRNAs were identified using R. In addition, GO and KEGG pathway analysis of the mRNAs and lncRNAs in the ceRNA network identified 10 BPs, 10 cell components, 10 molecular functions, and 48 KEGG pathways as selectively enriched. A total of 55 lncRNAs, 50 miRNAs, and 10 mRNAs from this network were shown to be closely associated with overall survival in LGG. Finally, 59 miRNAs, 235 mRNAs, and 17 lncRNAs were used to develop a ceRNA network comprising 313 nodes and 1046 edges. This study helps expand our understanding of ceRNA networks and serves to clarify the underlying pathogenesis mechanism of LGG.

Host Factor Interaction Networks Identified by Integrative Bioinformatics Analysis Reveals Therapeutic Implications in COPD Patients With COVID-19

Background: The COVID-19 pandemic poses an imminent threat to humanity, especially for those who have comorbidities. Evidence of COVID-19 and COPD comorbidities is accumulating. However, data revealing the molecular mechanism of COVID-19 and COPD comorbid diseases is limited. Methods: We got COVID-19/COPD -related genes from different databases by restricted screening conditions (top500), respectively, and then supplemented with COVID-19/COPD-associated genes (FDR<0.05, |LogFC|≥1) from clinical sample data sets. By taking the intersection, 42 co-morbid host factors for COVID-19 and COPD were finally obtained. On the basis of shared host factors, we conducted a series of bioinformatics analysis, including protein-protein interaction analysis, gene ontology and pathway enrichment analysis, transcription factor-gene interaction network analysis, gene-microRNA co-regulatory network analysis, tissue-specific enrichment analysis and candidate drug prediction. Results: We revealed the comorbidity mechanism of COVID-19 and COPD from the perspective of host factor interaction, obtained the top ten gene and 3 modules with different biological functions. Furthermore, we have obtained the signaling pathways and concluded that dexamethasone, estradiol, progesterone, and nitric oxide shows effective interventions. Conclusion: This study revealed host factor interaction networks for COVID-19 and COPD, which could confirm the potential drugs for treating the comorbidity, ultimately, enhancing the management of the respiratory disease.

Overview of human 20 alpha-hydroxysteroid dehydrogenase (AKR1C1): Functions, regulation, and structural insights of inhibitors

Human aldo-keto reductase family 1C1 (AKR1C1) is an important enzyme involved in human hormone metabolism, which is mainly responsible for the metabolism of progesterone in the human body. AKR1C1 is highly expressed and has an important relationship with the occurrence and development of various diseases, especially some cancers related to hormone metabolism. Nowadays, many inhibitors against AKR1C1 have been discovered, including some synthetic compounds and natural products, which have certain inhibitory activity against AKR1C1 at the target level. Here we briefly reviewed the physiological and pathological functions of AKR1C1 and the relationship with the disease, and then summarized the development of AKR1C1 inhibitors, elucidated the interaction between inhibitors and AKR1C1 through molecular docking results and existing co-crystal structures. Finally, we discussed the design ideals of selective AKR1C1 inhibitors from the perspective of AKR1C1 structure, discussed the prospects of AKR1C1 in the treatment of human diseases in terms of biomarkers, pre-receptor regulation and single nucleotide polymorphisms, aiming to provide new ideas for drug research targeting AKR1C1.

Transcriptomic Response of Primary Human Bronchial Cells to Repeated Exposures of Cigarette and ENDS Preparations

Cigarette smoke deregulates several biological pathways by modulating gene expression in airway epithelial cells and altering the physiology of the airway epithelium. The effects of repeated exposures of electronic cigarette delivery systems (ENDS) on gene expression in airway epithelium are relatively unknown. In order to assess the effect of repeated exposures of ENDS, primary normal human bronchial epithelial (NHBE) cells grown at air-liquid interface (ALI) were exposed to cigarette and ENDS preparations daily for 10 days. Cigarette smoke preparations significantly altered gene expression in a dose-dependent manner compared to vehicle control, including genes linked to oxidative stress, xenobiotic metabolism, cancer pathways, epithelial-mesenchymal transition, fatty acid metabolism, degradation of collagen and extracellular matrix, O-glycosylation, and chemokines/cytokines, which are known pathways found to be altered in smokers. Conversely, ENDS preparations had minimal effect on transcriptional pathways. This study revealed that a sub-chronic exposure of primary NHBE cultures to cigarette and ENDS preparations differentially regulated genes and canonical pathways, with minimal effect observed with ENDS preparations compared to cigarette preparations. This study also demonstrates the versatility of primary NHBE cultures at ALI to evaluate repeat-dose exposures of tobacco products.

Immunomodulatory Effects of Hydrolyzed Seawater Pearl Tablet (HSPT) on Th1/Th2 Functionality in a Mice Model of Chronic Obstructive Pulmonary Disease (COPD) Induced by Cigarette Smoke

Chronic obstructive pulmonary disease (COPD) is predicted to become the third leading cause of death around the world. The present study is designed to investigate whether hydrolyzed seawater pearl tablet (HSPT) has immunoregulatory effects on the Th1/Th2 functionality in cigarette smoke-induced COPD model mice. The determination of the amino acid composition of HSPT was carried out by high-performance liquid chromatography (HPLC) with precolumn phenylisothiocyanate (PITC) derivatization. COPD model mice were constructed by cigarette smoking (CS) treatment and HSPT was administered. HSPT inhibited the infiltration of inflammation in the airway of the lung, reduced influx of eosinophils (EOSs), lymphocytes (LYMs), neutrophils (NEUs), and macrophages (MACs) in the bronchoalveolar lavage fluid (BALF), decreased the levels of IFN-γ, IL-2, IL-4, and IL-10 in the serum and lung, and decreased the expression of aforementioned cytokines in the spleen and lung in CS-treated mice. Besides, HSPT also had the ability to reduce the amount of CD3⁺CD4⁺ T cells and modulate the Th1/Th2 balance. Taken together, this study supports the consensus that CS is a critical factor to induce and aggravate COPD. HSPT could regulate the balance of Th1/Th2 in CS-induced COPD model mice, indicating its effects on inhibiting the development of COPD.

Identification of key genes in calcific aortic valve disease by integrated bioinformatics analysis

Calcific aortic valve disease (CAVD) is highly prevalent in our aging world and has no effective pharmaceutical treatment. Intense efforts have been made but the underlying molecular mechanisms of CAVD are still unclear.This study was designed to identify the critical genes and pathways in CAVD by bioinformatics analysis. Microarray datasets of GSE12644, GSE51472, and GSE83453 were obtained from Gene Expression Omnibus database. Differentially expressed genes (DEGs) were identified and functional and pathway enrichment analysis was performed. Subsequently, the protein-protein interaction network (PPI) was constructed with Search Tool for the Retrieval of Interacting Genes and was visualized with Cytoscape to identify the most significant module. Hub genes were identified by Cytoscape plugin cytoHubba.A total of 179 DEGs, including 101 upregulated genes and 78 downregulated genes, were identified. The enriched functions and pathways of the DEGs include inflammatory and immune response, chemotaxis, extracellular matrix (ECM) organization, complement and coagulation cascades, ECM receptor interaction, and focal adhesion. The most significant module in the PPI network was analyzed and genes among it were mainly enriched in chemotaxis, locomotory behavior, immune response, chemokine signaling pathway, and extracellular space. In addition, DEGs, with degrees ≥ 10 and the top 10 highest Maximal Chique Centrality (MCC) score, were identified as hub genes. CCR1, MMP9, VCAM1, and ITGAX, which were of the highest degree or MCC score, were manually reviewed.The DEGs and hub genes identified in the present study help us understand the molecular mechanisms underlying the pathogenesis of CAVD and might serve as candidate therapeutic targets for CAVD.