LncRNA MIR210HG promotes phenotype switching of pulmonary arterial smooth muscle cells through autophagy-dependent ferroptosis pathway.

Hypoxic pulmonary hypertension (HPH) is a pathophysiological syndrome in which pulmonary vascular pressure increases under hypoxic stimulation and there is an urgent need to develop emerging therapies for the treatment of HPH. LncRNA MIR210HG is a long non-coding RNA closely related to hypoxia and has been widely reported in a variety of tumor diseases. But its mechanism in hypoxic pulmonary hypertension is not clear. In this study, we identified for the first time the potential effect of MIR210HG on disease progression in HPH. Furthermore, we investigated the underlying mechanism through which elevated levels of MIR210HG promotes the transition from a contractile phenotype to a synthetic phenotype in PASMCs under hypoxia via activation of autophagy-dependent ferroptosis pathway. While overexpression of HIF-2α in PASMCs under hypoxia significantly reversed the phenotypic changes induced by MIR210HG knockdown. We further investigated the potential positive regulatory relationship between STAT3 and the transcription of MIR210HG in PASMCs under hypoxic conditions. In addition, we established both in vivo and in vitro models of HPH to validate the differential expression of specific markers associated with hypoxia. Our findings suggest a potential mechanism of LncRNA MIR210HG in the progression of HPH and offer potential targets for disease intervention and treatment.

Identification of prognostic signatures in remnant gastric cancer through an interpretable risk model based on machine learning: a multicenter cohort study.

OBJECTIVE: The purpose of this study was to develop an individual survival prediction model based on multiple machine learning (ML) algorithms to predict survival probability for remnant gastric cancer (RGC). METHODS: Clinicopathologic data of 286 patients with RGC undergoing operation (radical resection and palliative resection) from a multi-institution database were enrolled and analyzed retrospectively. These individuals were split into training (80%) and test cohort (20%) by using random allocation. Nine commonly used ML methods were employed to construct survival prediction models. Algorithm performance was estimated by analyzing accuracy, precision, recall, F1-score, area under the receiver operating characteristic curve (AUC), confusion matrices, five-fold cross-validation, decision curve analysis (DCA), and calibration curve. The best model was selected through appropriate verification and validation and was suitably explained by the SHapley Additive exPlanations (SHAP) approach. RESULTS: Compared with the traditional methods, the RGC survival prediction models employing ML exhibited good performance. Except for the decision tree model, all other models performed well, with a mean ROC AUC above 0.7. The DCA findings suggest that the developed models have the potential to enhance clinical decision-making processes, thereby improving patient outcomes. The calibration curve reveals that all models except the decision tree model displayed commendable predictive performance. Through CatBoost-based modeling and SHAP analysis, the five-year survival probability is significantly influenced by several factors: the lymph node ratio (LNR), T stage, tumor size, resection margins, perineural invasion, and distant metastasis. CONCLUSIONS: This study established predictive models for survival probability at five years in RGC patients based on ML algorithms which showed high accuracy and applicative value.

The role of long noncoding RNA MEG3 in fibrosis diseases.

Fibrosis is a prevalent pathological condition observed in various organs and tissues. It primarily arises from the excessive and abnormal accumulation of the extracellular matrix, resulting in the structural and functional impairment of tissues and organs, which can culminate in death. Many forms of fibrosis, including liver, cardiac, pulmonary, and renal fibrosis, are considered irreversible. Maternally expressed gene 3 (MEG3) is an imprinted RNA gene. Historically, the downregulation of MEG3 has been linked to tumor pathogenesis. However, recent studies indicate an emerging association of MEG3 with fibrotic diseases. In this review, we delve into the current understanding of MEG3's role in fibrosis, aiming to shed light on the molecular mechanisms of fibrosis and the potential of MEG3 as a novel therapeutic target.

What is already known on this topic ­ Fibrosis, a condition characterized by excess build-up of the extracellular matrix in various organs, can lead to organ failure and is often irreparable. This includes fibrosis of the liver, heart, lungs, and kidneys. MEG3, an RNA gene, which is known to be downregulated in tumors, has recently been linked to fibrosis. What is already known on this topic ­ Our review investigates this new connection between MEG3 and fibrosis. We aim to provide insights into the molecular mechanisms of fibrosis and illuminate the potential role of MEG3 as a promising therapeutic target for fibrosis treatments. What is already known on this topic ­ Our review investigates this new connection between MEG3 and fibrosis. We aim to provide insights into the molecular mechanisms of fibrosis and illuminate the potential role of MEG3 as a promising therapeutic target for fibrosis treatments.

High Expression of PSRC1 Predicts Poor Prognosis in Lung Adenocarcinoma.

Background: The incidence of lung cancer is increasing annually, but the mechanism of its occurrence and development requires further study. This study aimed to investigate the biological function and prognostic value of proline- and serine-rich coiled-coil 1 (PSRC1) in lung cancer. Methods: We used data from The Cancer Genome Atlas (TCGA) to analyze the association between clinical features and PSRC1 expression in non-small cell carcinoma. The relationship between PSRC1 expression and prognosis in lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC) was analyzed using Kaplan-Meier curves. The function of PSRC1 was identified using enrichment analysis, and the relationship between PSRC1 expression and immune cell infiltration was studied. In addition, the expression of PSRC1 in 150 patients with non-small cell carcinoma was detected using immunohistochemistry, and its clinical significance was analyzed. Results: It was found that the expression level of PSRC1 was higher in LUAD and LUSC tumor tissues than in normal tissues, and the results were confirmed by immunohistochemistry in 150 patients. TCGA data showed that high PSRC1 expression in LUAD was associated with poorer overall survival (p = 0.003) and progression-free interval (p = 0.012). Multivariable analysis showed that PSRC1 was an independent risk factor for LUAD. Functional enrichment analysis showed that PSRC1 is related to tumor development. Conclusion: High PSRC1 expression is significantly associated with LUAD survival and may be a promising prognostic biomarker.

Association between urinary phthalate metabolites and chronic obstructive pulmonary disease incidence in US adults: results from NHANES 2007-2018.

Despite associations between urinary phthalates and respiratory symptoms and disorders have been investigated, knowledge about their impact on COPD incidence remains limited. Using data of 8242 adults (aged 20-80 years) from the 2007-2018 National Health and Nutrition Examination Survey (NHANES), the association of mixed urinary phthalate metabolites with COPD incidence was evaluated. Among them, 789 were COPD patients, and the rest were non-COPD participants. In the single-pollutant models, a variety of phthalate metabolites were identified as independent positive factors for COPD incidence, including mono-(carboxynonyl) phthalate (MCNP), mono-(2-ethyl-5-carboxypentyl) phthalate (MECPP), mono-n-butyl phthalate (MnBP), mono-(3-carboxylpropyl) phthalate (MCPP), mono-ethyl phthalate (MEP), mono-(2-ethyl-5-hydroxyhexyl) phthalate (MEHHP), mono-(2-ethyl-5-oxohexyl) phthalate (MEOHP), and mono-benzyl phthalate (MBzP). Multi-pollutant models, including weighted quantile sum (WQS) regression, quantile-based g computation (qgcomp), and Bayesian kernel machine regression (BKMR) approaches consistently revealed the positive association between phthalates co-exposure and COPD incidence, and MCPP was recognized as the dominant positive driver. The positive association was more evident in the youth group and the male group. The interactions between certain phthalate metabolites in COPD were also observed. Given the limitations of the cross-sectional design of NHANES study, well-designed longitudinal studies are needed to verify or disprove these findings.

Novel clinical radiomic nomogram method for differentiating malignant from non-malignant pleural effusions.

Objectives: To establish a clinical radiomics nomogram that differentiates malignant and non-malignant pleural effusions. Methods: A total of 146 patients with malignant pleural effusion (MPE) and 93 patients with non-MPE (NMPE) were included. The ROI image features of chest lesions were extracted using CT. Univariate analysis was performed, and least absolute shrinkage selection operator and multivariate logistic analysis were used to screen radiomics features and calculate the radiomics score. A nomogram was constructed by combining clinical factors with radiomics scores. ROC curve and decision curve analysis (DCA) were used to evaluate the prediction effect. Results: After screening, 19 radiomics features and 2 clinical factors were selected as optimal predictors to establish a combined model and construct a nomogram. The AUC of the combined model was 0.968 (95% confidence interval [CI] = 0.944-0.986) in the training cohort and 0.873 (95% CI = 0.796-0.940) in the validation cohort. The AUC value of the combined model was significantly higher than those of the clinical and radiomics models (0.968 vs. 0.874 vs. 0.878, respectively). This was similar in the validation cohort (0.873, 0.764, and 0.808, respectively). DCA confirmed the clinical utility of the radiomics nomogram. Conclusion: CT-based radiomics showed better diagnostic accuracy and model fit than clinical and radiological features in distinguishing MPE from NMPE. The combination of both achieved better diagnostic performance. These findings support the clinical application of the nomogram in diagnosing MPE using chest CT.

Molecular regulation and therapeutic implications of cell death in pulmonary hypertension.

Pulmonary hypertension (PH) is a clinical and pathophysiological syndrome caused by changes in pulmonary vascular structure or function that results in increased pulmonary vascular resistance and pulmonary arterial pressure, and it is characterized by pulmonary endothelial dysfunction, pulmonary artery media thickening, pulmonary vascular remodeling, and right ventricular hypertrophy, all of which are driven by an imbalance between the growth and death of pulmonary vascular cells. Programmed cell death (PCD), different from cell necrosis, is an active cellular death mechanism that is activated in response to both internal and external factors and is precisely regulated by cells. More than a dozen PCD modes have been identified, among which apoptosis, autophagy, pyroptosis, ferroptosis, necroptosis, and cuproptosis have been proven to be involved in the pathophysiology of PH to varying degrees. This article provides a summary of the regulatory patterns of different PCD modes and their potential effects on PH. Additionally, it describes the current understanding of this complex and interconnected process and analyzes the therapeutic potential of targeting specific PCD modes as molecular targets.

Metabolomic and transcriptomic analyses provide insights into variations in flavonoids contents between two Artemisia cultivars.

BACKGROUND: Plants in the genus Artemisia are rich in active ingredients and specialized metabolites. Many of these compounds, especially flavonoids, have potential medicinal and nutritional applications, and are of growing interest to scientists due to their wide range of pharmacological and biological activities. Artemisia cultivars are commonly used as raw materials for medicine, food, and moxibustion in China. However, most of the metabolites produced by Artemisia species have not been identified, and few studies have addressed differences in active compounds between species and cultivars. RESULTS: We here investigated two Artemisia cultivars, 'Nanyangshiyong' (NYSY) and 'Nanyangyaoyong' (NYYY), which are commonly used in foods and moxibustion, respectively. NYSY and NYYY were confirmed to be Artemisia argyi cultivars. Total flavonoids contents and antioxidant activities were higher in NYYY than in NYSY. A total of 882 metabolites were identified in the samples; most of the potentially medicinally active compounds, especially flavonoids (e.g., flavone, flavonol, isoflavone, and anthocyanin), were up-regulated in NYYY compared to NYSY. Furthermore, most of the genes related to flavonoids biosynthesis were up-regulated in NYYY. Correlation analysis was used to identify putative members of transcription factor families that may regulate genes encoding key flavonoids biosynthesis enzymes. CONCLUSIONS: We found that the antioxidant activities and flavonoids contents significantly varied between two Artemisia cultivars of the same species. We also uncovered metabolomic and transcriptomic evidence of the molecular phenomena underlying those differences in flavonoids contents between the two Artemisia cultivars. This study provides a wealth of data for future utilization and improvements of Artemisia cultivars, and highlights a need to study the specific metabolite profiles of plants that are used in foods and medicines.

Hypoxia-induced long non-coding RNA plasmacytoma variant translocation 1 upregulation aggravates pulmonary arterial smooth muscle cell proliferation by regulating autophagy via miR-186/Srf/Ctgf and miR-26b/Ctgf signaling pathways.

BACKGROUND: The lncRNA PVT1 reportedly functions as a competing endogenous RNA (ceRNA) of miR-186 and miR-26b in different tissue types. In this study, we investigated the possible involvement of the miR-186/Srf/Ctgf and miR-26b/Ctgf signaling pathways in the pathogenesis of hypoxia-induced PAH. METHODS: Expression of PVT1, miR-186, miR-26b, and Srf and Ctgf mRNAs were evaluated by real-time polymerase chain reaction. Protein expression of SRF, CTGF, LC3B-I, LC3B-II, and Beclin-I was evaluated using western blotting. The regulatory relationship between the lncRNA, miRNAs, and target mRNAs was explored using luciferase assays. Immunohistochemistry was used to evaluate the expression of SRF and CTGF in situ. MTT assay was performed to assess the proliferation of PASMCs. RESULTS: Exposure to hypoxia markedly altered the expression of PVT1, Srf, Ctgf, miR-186, and miR-26b in a rat model. MiR-186 binding sites in the sequences of Srf mRNA and PVT1 were confirmed by luciferase assays, indicating that miR-186 may interact with both PVT1 and Srf mRNA. Additionally, miR-26b binding sites were identified in the sequences of Ctgf mRNA and PVT1, suggesting that miR-26b may interact with both PVT1 and Ctgf mRNA. In line with this, we found that overexpression of PVT1 reduced expression of miR-26b and miR-186 but activated expression of Srf, Ctgf, LC3B-II, and Beclin-I. CONCLUSIONS: Upregulation of PVT1 by exposure to hypoxia promoted the expression of CTGF, leading to deregulation of autophagy and abnormal proliferation of PASMCs. Dysregulation of the miR-186/Srf/Ctgf and miR-26b/Ctgf signaling pathways may be involved in the pathogenesis of hypoxia-induced PASMCs.

The cuproptosis related genes signature predicts the prognosis and correlates with the immune status of clear cell renal cell carcinoma.

Background: Clear cell renal cell carcinoma (CCRCC) has a high incidence and poor prognosis. Cuproptosis, an independent pattern of cell death associated with copper, plays an important role in cancer proliferation and metastasis. The role of cuproptosis-related genes (CRGs) in CCRCC is unclear. Methods: Transcriptome and clinical information for CCRCC were downloaded from The Cancer Genome Atlas (TCGA) database. After dividing the training and testing cohort, a 4-CRGs risk signature (FDX1, DLD, DLAT, CDKN2A) was identified in the training cohort using Least absolute shrinkage and selection operator (LASSO) and Cox regression analysis. The effect of the 4-CRGs risk signature on prognosis was assessed using Kaplan-Meier (KM) curves and time-dependent receiver operating characteristic (ROC) curves and verified using the testing cohort. For different risk groups, the immune statue was assessed using the CIBERSORT algorithm, the ssGSEA method and immune checkpoint expression data. Finally, a competitive endogenous RNA (ceRNA) network was constructed using miRTarbase and starBase databases to identify molecules that may have a regulatory relationship with CRCCC. Results: There were significant changes in the overall survival (OS), immune microenvironment, immune function, and checkpoint gene expression among the different risk groups. A ceRNA network consisting of one mRNA, two miRNAs, and 12 lncRNAs was constructed. Conclusion: The 4-CRGs risk signature provides a new method to predict the prognosis of patients with CCRCC and the effect of immunotherapy. We propose a new cuproptosis-associated ceRNA network that can help to further explore the molecular mechanisms of CCRCC.

High Expression of DEPDC1B Predicts Poor Prognosis in Lung Adenocarcinoma.

Introduction: Lung adenocarcinoma (LUAD) is the most common type of lung cancer. DEP domain-containing 1 B (DEPDC1B) is involved in the development of several cancers; however, its role in LUAD is unknown. Therefore, we aimed to determine the biological function and prognostic value of DEPDC1B in LUAD. Material and Methods: We analyzed the correlation between DEPDC1B expression and the clinical features of LUAD and lung squamous cell carcinoma (LUSC). Survival was evaluated by generating Kaplan-Meier curves, which were used to analyze the relationship between DEPDC1B expression and prognosis in LUAD and LUSC. DEPDC1B expression in tumor and normal tissues from patients with LUAD and LUSC was determined using immunohistochemistry, and its clinical significance was analyzed. Finally, the correlation between the expression and biological function of DEPDC1B in LUAD was examined. Results: Our findings revealed that DEPDC1B expression was higher in tumor tissues than that in normal tissues from patients with LUAD and LUSC (P < 0.001). These results were confirmed in clinical samples from patients using immunohistochemistry. Analysis of a dataset from The Cancer Genome Atlas (TCGA) showed that high DEPDC1B expression was associated with poor prognosis only in patients with LUAD (P < 0.001). Similarly, high DEPDC1B expression was related to shorter overall survival (OS) and progression-free interval (PFI) in patients with LUAD. These associations were not observed in LUSC. Functional enrichment analysis suggested that DEPDC1B promoted tumor development in LUAD by regulating the cell cycle. Conclusion: High DEPDC1B expression predicts poor prognosis in patients with LUAD. Thus, DEPDC1B has potential as a therapeutic target for LUAD.

Identification of three hub genes related to the prognosis of idiopathic pulmonary fibrosis using bioinformatics analysis.

Background: Idiopathic pulmonary fibrosis (IPF) is a chronic respiratory disease characterized by peripheral distribution of bilateral pulmonary fibrosis that is more pronounced at the base. IPF has a short median survival time and a poor prognosis. Therefore, it is necessary to identify effective prognostic indicators to guide the treatment of patients with IPF. Methods: We downloaded microarray data of bronchoalveolar lavage cells from the Gene Expression Omnibus (GEO), containing 176 IPF patients and 20 controls. The top 5,000 genes in the median absolute deviation were classified into different color modules using weighted gene co-expression network analysis (WGCNA), and the modules significantly associated with both survival time and survival status were identified as prognostic modules. We used Lasso Cox regression and multivariate Cox regression to search for hub genes related to prognosis from the differentially expressed genes (DEGs) in the prognostic modules and constructed a risk model and nomogram accordingly. Moreover, based on the risk model, we divided IPF patients into high-risk and low-risk groups to determine the biological functions and immune cell subtypes associated with the prognosis of IPF using gene set enrichment analysis and immune cell infiltration analysis. Results: A total of 153 DEGs located in the prognostic modules, three (TPST1, MRVI1, and TM4SF1) of which were eventually defined as prognostic hub genes. A risk model was constructed based on the expression levels of the three hub genes, and the accuracy of the model was evaluated using time-dependent receiver operating characteristic (ROC) curves. The areas under the curve for 1-, 2-, and 3-year survival rates were 0.862, 0.885, and 0.833, respectively. The results of enrichment analysis showed that inflammation and immune processes significantly affected the prognosis of patients with IPF. The degree of mast and natural killer (NK) cell infiltration also increases the prognostic risk of IPF. Conclusions: We identified three hub genes as independent molecular markers to predict the prognosis of patients with IPF and constructed a prognostic model that may be helpful in promoting therapeutic gains for IPF patients.

Mortality and risk factors for COVID-19 in hemodialysis patients: A systematic review and meta-analysis.

Introduction: The present study systematically reviewed the clinical features and risk factors in patients undergoing maintenance hemodialysis (MHD) who also acquired coronavirus disease 2019 (COVID-19). More specifically, clinical manifestations, prognosis, and risk factors for death among this population were explored. Method: A literature search using the PubMed, Web of Science, and Embase databases, for articles involving patients with laboratory-confirmed COVID-19 and undergoing MHD published between January 1, 2020, and March 13, 2022, was performed. Random-effects meta-analyses were performed to calculate the weighted mean prevalence and corresponding 95% confidence interval (CI) or weighted means and 95% CI. Heterogeneity among studies was assessed using I2 statistics. Results: Twenty-two studies including 13,191 patients with COVID-19 undergoing MHD were selected. The most common symptoms included fever (53% [95% CI 41%-65%]) and cough (54% [95% CI 48%-60%]); however, 17% (95% CI 11%-22%) of the cases were asymptomatic. In subgroup analysis, the proportion of male patients (65% [95% CI 58%-71%]), and patients with coronary artery disease (30% [95% CI 17%-44%) and chronic obstructive pulmonary disease (9% [95% CI 4%-15%]) was greater in the non-survivor group compared with the survivor group. Furthermore, patients undergoing MHD, who were also positive for COVID-19, exhibited a high mortality rate (24% [95% CI 19%-28%]). Conclusions: MHD patients with COVID-19 may initially present as asymptomatic or with mild symptoms; nevertheless, in this study, these patients exhibited a higher risk for death compared with COVID-19 patients not undergoing MHD. Moreover, male sex and underlying cardiovascular and respiratory diseases increased the mortality risk.

Efficacy and Safety of Nanoadministration in the Treatment of Non-Small-Cell Lung Cancer Is Good to Some Extent: A Systematic Review and Meta-Analysis.

Purpose: The purpose of this study was to evaluate the efficacy and safety of a nanodrug delivery regimen compared with conventional drug administration for the treatment of lung cancer. Materials and Methods: Studies were retrieved through PubMed, Web of Science, and ScienceDirect. Primary and secondary outcome measures, including overall response rate (ORR), progression-free survival (PFS), overall survival (OS), and adverse events, were extracted from the retrieved literature and systematically evaluated. Results: Six trials, including 4806 advanced non-small-cell lung cancer patients, were included in this study. Compared with conventional drug administration in the treatment of lung cancer, the nanodrug delivery regimen improved the ORR (risk ratio = 1.43, 95% confidence interval (CI) = 1.25-1.63, p ≤ 0.001), prolonged PFS (hazard ratio (HR) = 0.83, 95% CI = 0.76-0.92, p ≤ 0.001), and obtained superior OS (HR = 0.91, 95% CI = 0.83-0.99, p ≤ 0.001). Regarding safety, the incidence of neutropenia, alopecia, sensory neuropathy, myalgia, and arthralgia was lower in the nanoadministration group, but the risk of thrombocytopenia, anaemia, and nausea was increased. Conclusion: Nanodrug administration is safe and effective in patients with non-small-cell lung cancer to some extent.

Seven autophagy-related lncRNAs are associated with the tumor immune microenvironment in predicting survival risk of nonsmall cell lung cancer.

BACKGROUND: Nonsmall cell lung cancer (NSCLC) ranks first among global cancer-related deaths. Despite the emergence of various immunological and targeted therapies, immune tolerance remains a barrier to treatment. METHODS: It has been found that this obstacle can be overcome by targeting autophagy-related genes (ATGs). ATGs were screened by coexpression analysis and the genes related to the prognosis of lung cancer were screened using Kaplan-Meier (K-M) survival analysis, univariate Cox regression and multivariate Cox regression. The prognostic risk model of ATGs was constructed and verified using K-M survival analysis and receiver operating characteristic (ROC) curve analysis. RESULTS: The prognostic risk model of ATGs was constructed. Gene set enrichment analysis (GSEA) showed that the function and pathway of ATG enrichment were closely related to immune cell function. CIBERSORT, LM22 matrix and Pearson correlation analysis showed that risk signals were significantly correlated with immune cell infiltration and immune checkpoint genes. CONCLUSIONS: We identified and independently verified the ATG (AL691432.2, MMP2-AS1, AC124067.2, CRNDE, ABALON, AL161431.1, NKILA) in NSCLC patients and found that immune regulation in the tumor microenvironment is closely related to this gene.

ARL14 as a Prognostic Biomarker in Non-Small Cell Lung Cancer.

PURPOSE: Non-small cell lung cancer (NSCLC) is the leading cause of cancer-related deaths worldwide. The mechanisms underlying NSCLC initiation and progression require further investigation. The purpose of this study was to investigate the role of ADP ribosylation factor-like GTPase 14 (ARL14) related to the progression of NSCLC. PATIENTS AND METHODS: We analyzed the correlation between clinical characteristics and ARL14 expression using data from The Cancer Genome Atlas (TCGA). Kaplan-Meier analysis was conducted to evaluate the prognostic value of ARL14 in NSCLC. Functions of ARL14 were identified by enrichment analysis. The relationship between ARL14 expression and immune cell infiltration was also studied. Furthermore, ARL14 expression was examined using immunohistochemistry, and its clinical significance was analyzed in 120 patients with NSCLC. RESULTS: Our study revealed that the expression level of ARL14 in patients with NSCLC was higher than that in normal tissues. Using TCGA data, higher ARL14 expression in lung adenocarcinoma was associated with residual tumor (P = 0.017), while it was associated with age (P = 0.003) and N stage (P = 0.009) in lung squamous cell carcinoma. Similar results were obtained from 120 patients with NSCLC. High ARL14 expression was associated with poor overall survival and progression-free survival in NSCLC. Multivariate analysis revealed that ARL14 was an independent risk factor for patients with NSCLC. Functional enrichment analysis indicated that ARL14 was related to the occurrence and development of tumors. CONCLUSION: Increased ARL14 expression was considerably correlated with poor survival in NSCLC, and it might be a promising prognostic biomarker for NSCLC.

Effect of Methylation Status of lncRNA-MALAT1 and MicroRNA-146a on Pulmonary Function and Expression Level of COX2 in Patients With Chronic Obstructive Pulmonary Disease.

This study aimed to investigate the role of methylation of MALAT1 and miR-146a in the pathogenesis of chronic obstructive pulmonary disease (COPD). COPD patients were grouped according to their methylation status of MALAT1 and miR-146a promoters, and we found that forced vital capacity, volume that has been exhaled at the end of the first second of forced expiration, and diffusion capacity for carbon monoxide were the highest in the MALAT1 HYPO + miR-146a HYPER group and lowest in the MALAT1 HYPER + miR-146a HYPO group, and COPD patients with hypermethylated MALAT1 showed lower expression of MALAT1 than that in the COPD patients with hypomethylated MALAT1. Meanwhile, miR-146a was the most significantly upregulated in the MALAT1 HYPER + miR-146a HYPO group and the most significantly downregulated in the MALAT1 HYPO + miR-146a HYPER group. Both prostaglandin E1 and cyclooxygenase 2 (COX2) expression were the highest in the MALAT1 HYPO + miR-146a HYPER group and the lowest in the MALAT1 HYPER + miR-146a HYPO group. In conclusion, our results established a MALAT1/miR-146a/COX2 signaling axis. The overexpression of MALAT1 could increase the expression of COX2 by inhibiting the expression of miR-146a, thus affecting the pulmonary function of COPD patients.

Integrated analysis of the molecular mechanisms in idiopathic pulmonary fibrosis.

Rationale: Idiopathic pulmonary fibrosis (IPF) is one of the most aggressive forms of idiopathic interstitial pneumonia. Some miRNAs may be associated with IPF and may affect the occurrence and development of IPF in various pathways. Many miRNAs and genes that may be involved in the development of IPF have been discovered using chip and high throughput technologies. Methods: We analyzed one miRNA and four mRNA databases. We identified hub genes and pathways related to IPF using GO, KEGG enrichment analysis, gene set variation analysis (GSVA), PPI network construction, and hub gene analysis. A comprehensive analysis of differentially expressed miRNAs (DEMs), predicted miRNA target genes, and differentially expressed genes (DEGs) led to the creation of a miRNA-mRNA regulatory network in IPF. Results: We found 203 DEGs and 165 DEMs that were associated with IPF. The findings of enrichment analyses showed that these DEGs were mainly involved in antimicrobial humoral response, antimicrobial humoral immune response mediated by antimicrobial peptide, extracellular matrix organization, cell killing, and organ or tissue specific immune response. The VEGFA, CDH5, and WNT3A genes overlapped between hub genes and the miRNA-mRNA regulatory network. The miRNAs including miR-199b-5p, miR-140-5p, miR-199a-5p, miR-125A-5p, and miR-107 that we predicted would regulate the VEGFA, CDH5, and WNT3A genes, which were also associated with IPF or other fibrosis-related diseases. GSVA indicated that metabolic processes of UTP and IMP, immune response, regulation of Th2 cell cytokine production, and positive regulation of NK cell-mediated immunity are associated with the pathogenesis and treatment of IPF. These pathways also interact with VEGFA, CDH5, and WNT3A. Conclusion: These findings provide a new research direction for the diagnosis and treatment of IPF.

Nivolumab monotherapy or combination therapy with ipilimumab for lung cancer: a systemic review and meta-analysis.

BACKGROUND: The high incidence and mortality of lung cancer have seriously affected human life and health. Nivolumab is a monoclonal antibody that can inhibit programmed death 1 (PD-1) and Ipilimumab is a monoclonal antibody against CTLA-4(cytotoxic T lymphocyte-associated antigen 4), both of which can prevent the immune escape of tumor cells. Our goal was to synthesize evidence from published randomized controlled trials involving the safety and efficacy of either Nivolumab alone or in combination for the treatment of unresectable lung cancer. METHODS: We searched the following electronic databases: PubMed, Embase, and Cochrane libraries, and screened the retrieved records for eligibility. We used the Stata16 software for the analyses. The results of the analysis are expressed as hazard ratios (HRs) or risk ratios (RRs) and their corresponding 95% confidence intervals (CI). RESULTS: The final analysis included seven trials involving 3817 patients. Among patients with advanced lung cancer, patients using immunotherapy had better overall survival (OS), progression-free survival (PFS), and an objective response rate (ORR) than patients receiving chemotherapy. The HR of Nivolumab monotherapy or combination therapy with OS was compared with that of chemotherapy (HR: 0.73, 95% CI 0.64-0.83; HR: 0.67, 95% CI 0.55-0.81), and the HR of PFS was (HR: 0.81, 95% CI 0.69-0.94; HR: 0.67, 95% CI 0.55-0.82). CONCLUSIONS: Immunotherapy has been shown to have more clinically meaningful survival benefits for patients with lung cancer, whether monotherapy or combination immunotherapy. CRD42020213440.