RELA-mediated upregulation of LINC03047 promotes ferroptosis in silica-induced pulmonary fibrosis via SLC39A14.

Long non-coding RNAs play a key role in silicosis, a fatal fibrotic lung disease, and there is an urgent need to develop new treatment targets. Long intergenic non-protein-coding RNA 3047 (LINC03047) is associated with cancer, but its role and mechanism in the progression of silicosis require further elucidation. This study investigated the function of LINC03047 in the epithelial-mesenchymal transition (EMT) during silicosis progression. LINC03047 expression was upregulated in SiO2-treated BEAS-2B and A549 cells, promoting SiO2-induced ferroptosis and subsequent EMT. Moreover, knockdown of LINC03047 significantly decreased the expression of solute carrier family 39 member 14 (SLC39A14), a ferrous iron transporter, and inhibition of SLC39A14 alleviated the ferroptosis and EMT caused by LINC03047 overexpression. We further investigated that NF-κB p65 (RELA) was critical for LINC03047 transcription in SiO2-treated BEAS-2B and A549 cells. In vivo experiments showed that SLC39A14 deficiency improved SiO2-induced lipid peroxidation and EMT. Collectively, our study reveals the function of the RELA/LINC03047/SLC39A14 axis in SiO2-induced ferroptosis and EMT, thereby contributing to the identification of novel drug targets for silicosis therapy.

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.

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.

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.

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.

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.

Association Between NAT2 Polymorphism and Lung Cancer Risk: A Systematic Review and Meta-Analysis.

Lung cancer is the leading cause of cancer-related death worldwide and has a high incidence rate. N-Acetyltransferase 2 (NAT2) is a polymorphic xenobiotic enzyme, which can catalyze N-acetylation and O-acetylation of various carcinogens such as aromatic, heterocyclic amines and hydrazines. At present, many studies have explored the effects of NAT2 polymorphism on lung cancer, but we found inconsistent results. We researched 18 published studies, involving 4,016 patients and 5,469 controls, to more accurately assess the effects of NAT2 polymorphism on lung cancer risk and to investigate whether smoking is associated. We used STATA software to analyze the extracted data and used STATA for subgroup analysis, sensitivity analysis, and to perform publication bias tests. To determine the correlation, we used the crude odds ratio (ORs) with 95% confidence interval (CIs). Our study was prospectively registered in PROSPERO (CRD42020159737). The odds ratio was 1.53 (95% CI: 1.21-1.95, I² = 45.2%, P=0.104) for the NAT2 slow + intermediate phenotype versus rapid phenotype. The results suggested that people with NAT2 non-rapid (slow + intermediate) phenotype have a significantly increased risk of lung cancer. In addition, NAT2 rapid phenotype was significantly associated with reduced risk of lung cancer, compared with slow phenotype or intermediate phenotype (slow phenotype vs . rapid phenotype: OR: 1.61, 95% CI: 1.07-2.42, I²= 50%, P= 0.075; intermediate phenotype vs . rapid phenotype: OR: 1.47, 95% CI: 1.15-1.88, I²= 40.3%, P= 0.137).

Predictive effect of PD-L1 expression for immune checkpoint inhibitor (PD-1/PD-L1 inhibitors) treatment for non-small cell lung cancer: A meta-analysis.

BACKGROUND: Programmed death-ligand-1 (PD-L1) is a well-known predictive biomarker in non-small cell lung cancer (NSCLC) patients, however, its accuracy remains controversial. Here, we investigated the correlation between PD-L1 expression level and efficacy of its inhibitors, and hence assessed the predictive effect of PD-L1 expression. METHODS: Studies that evaluated the efficacy of programmed death-1 (PD-1)/ PD-L1 inhibitors in advanced NSCLC patients according to tumor PD-L1 expression levels were searched for on Medline, Cochrane Library, and Embase. The pooled risk ratio (RR) and 95% confidence intervals (95% CIs) were calculated for the objective response rate (ORR) with overall survival (OS) and progression-free survival (PFS) were measured in terms of hazard ratio (HR) and the corresponding 95% CIs. RESULTS: 1432 NSCLC patients from six randomized controlled trials (RCTs) were included and three PD-1/PD-L1 inhibitors (atezolizumab, nivolumab, and pembrolizumab) were used to treat the patients. A significantly higher ORR was observed in the high PD-L1 expression group compared to the low expression group (0.35 [95% CI, 0.30-0.40] vs 0.11 [95% CI, 0.09-0.14]). The results of the subgroup analysis, grouped by the type of drugs and antibodies which assess immune checkpoint inhibitors were identical with the pooled result. However, our study showed that PD-L1 expression was neither prognostic nor predictive of overall survival (OS) or progression-free survival (PFS) in patients treated with PD-1/PD-L1 inhibitors compared to chemotherapy. CONCLUSIONS: PD-L1 can be a predictive biomarker for ORR. Nevertheless, PD-L1 expression is not a good predictive tool for OS and PFS.

Estrogen administration reduces the risk of pulmonary arterial hypertension by modulating the miR-133a signaling pathways in rats.

We aimed to investigate how estrogen (ES) is implicated in the pathogenesis of pulmonary arterial hypertension (PAH) potentially by reducing the extent of vascular remodeling in females. HE assay, Western Blot, IHC, and real-time PCR were carried out to observe the role of ES in regulating miR-133a expression and the levels of MYOSLID, SRF, CTGF, and vascular remodeling in rats. In addition, MTT assay and flow cytometry were utilized to observe how ES affects cell proliferation and cell cycle in PAH. Moreover, luciferase assays were carried out to clarity the regulatory relationship between miR-133a and its downstream targets. ES administration relieved the deregulation of miR-133a, MYOSLID, SRF, and CTGF in PAH rats. In addition, ES also reduced the thickening of blood vessels in PAH rats. ES could activate miR-133a promoter and arrest the cells in the G0/G1 cycle, thus dose-dependently suppressing the proliferation of cells. In addition, the presence of ES, MYOSLID siRNA, or miR-133a precursor all altered the expression of MYOSLID, SP1, SRF, and CTGF, thus establishing a molecular signaling pathway among these factors. Furthermore, miR-133a could bind to SP1, MYOSLID, SRF, and CTGF to reduce their expression. Moreover, SRF was proved to function as an activator of miR-133a promoter. Two feedback loops were established in this study: a negative feedback loop between SRF and miR-133a, and a positive loop among miR-133a/SRF/MLK1/MYOSLID. ES treatment upregulates miR-133a expression and reduces the incidence of PAH and vascular remodeling.

Prognostic Value of Baseline Neutrophil-to-Lymphocyte Ratio in Outcome of Immune Checkpoint Inhibitors.

A meta-analysis of 14 studies (16 cohorts) incorporating 1751 participants was performed to evaluate the correlation between baseline neutrophil-to-lymphocyte ratio (NLR) and outcome of immune checkpoint inhibitors (ICI). The pooled hazard ratio (HR) suggested elevated pretreatment NLR was associated with poor OS (HR: 2.61, 95% confidence intervals (CI): 1.77-3.86, p < 0.00001) and PFS (HR: 1.74, 95% CI: 1.34-2.27, p < 0.0001). Stratified analyses on tumor types, ICI agents, the cutoff value of NLR and study regions exhibited the similar outcomes. This study demonstrated that elevated NLR was a predictor of poor OS and PFS for ICI.