Identification and Validation of Aging Related Genes Signature in Chronic Obstructive Pulmonary Disease.

PURPOSE: Chronic Obstructive Pulmonary Disease (COPD) is regarded as an accelerated aging disease. Aging-related genes in COPD are still poorly understood. METHOD: Data set GSE76925 was obtained from the Gene Expression Omnibus (GEO) database. The "limma" package identified the differentially expressed genes. The weighted gene co-expression network analysis (WGCNA) constructes co-expression modules and detect COPD-related modules. The least absolute shrinkage and selection operator (LASSO) and the support vector machine recursive feature elimination (SVM-RFE) algorithms were chosen to identify the hub genes and the diagnostic ability. Three external datasets were used to identify differences in the expression of hub genes. Real-time reverse transcription polymerase chain reaction (RT-qPCR) was used to verify the expression of hub genes. RESULT: We identified 15 differentially expressed genes associated with aging (ARDEGs). The SVM-RFE and LASSO algorithms pinpointed four potential diagnostic biomarkers. Analysis of external datasets confirmed significant differences in PIK3R1 expression. RT-qPCR results indicated decreased expression of hub genes. The ROC curve demonstrated that PIK3R1 exhibited strong diagnostic capability for COPD. CONCLUSION: We identified 15 differentially expressed genes associated with aging. Among them, PIK3R1 showed differences in external data sets and RT-qPCR results. Therefore, PIK3R1 may play an essential role in regulating aging involved in COPD.

A novel nomogram model for lung adenocarcinoma subtypes based on RNA-modification regulatory genes.

Background: In non-small cell lung cancer (NSCLC), lung adenocarcinoma (LUAD) is the most common subtype. RNA modification has become the frontier and hotspot of current tumor research. Results: In this study, 109 genes that regulate RNA modifications were identified according to The Cancer Genome Atlas (TCGA). A differential gene expression analysis identified 46 differentially expressed RNA modification regulatory genes (DERRGs). LUAD samples were stratified into two distinct clusters based on the expression of these DERRGs. A significant correlation was observed between these clusters and patient survival rates, as well as clinical features. Furthermore, a four-DERRG signature (EIF3B, HNRNPC, IGF2BP1, and METTL3) developed using LASSO regression. According to the calculated risk scores from this signature, LUAD patients were categorized into high-risk and low-risk groups. Patients in the low-risk group exhibited a more favorable prognosis. A prognostic nomogram was crafted, integrating the four-DERRGs signature with clinical parameters. The nomogram was revealed that OS, age, clinical stage, immune cell infiltration, and immune checkpoint molecule expression were significantly linked to the OS of LUAD. GSEA analysis found that the DERRGs were primarily regulated immune pathways. Conclusions: This study developed four DERRGs signatures and formulated a nomogram model for precise prognosis estimation in LUAD patients. The study's insights are instrumental for advancing diagnosis, prognosis, and therapeutic strategies for LUAD.

Pan-cancer prognosis, immune infiltration, and drug resistance characterization of lung squamous cell carcinoma tumor microenvironment-related genes.

Background: The tumor microenvironment (TME) plays an important role in cancer development; however, its implications in lung squamous cell carcinoma (LUSC) and pan-cancer have been poorly understood. Methods: In this study, The Cancer Genome Atlas (TCGA) and Estimation of Stromal and Immune cells in Malignant Tumor tissue using Expression Data (ESTIMATE) datasets were applied to identify differentially expressed genes. Additionally, online public databases were utilized for in-depth bioinformatics analysis of pan-cancer datasets to investigate the prognostic implications of TME-related genes further. Results: Our study demonstrated a significant association between stromal scores, immune scores, and specific clinical characteristics in LUSC patients. C3AR1, CSF1R, CCL2, CCR1, and CD14 were identified as prognostic genes related to the TME. All TME-related prognostic genes demonstrated varying degrees of correlation with immune infiltration subtypes and tumor cell stemness. Moreover, our study revealed that TME-related prognostic genes, particularly C3AR1 and CCR1, might contribute to drug resistance in cancer cells. Conclusions: The identified TME-related prognostic genes, particularly C3AR1 and CCR1, have potential implications for understanding and targeting drug resistance mechanisms in cancer cells.

Prognostic value of lactic dehydrogenase-to-albumin ratio in critically ill patients with acute respiratory distress syndrome: a retrospective cohort study.

Background: Lactic dehydrogenase (LDH)-to-albumin ratio (LAR) was an independent risk factor for mortality in the patients with acute respiratory distress syndrome (ARDS) due to coronavirus disease 2019 (COVID-19), while the relationship among LAR and short-term, long-term, in-hospital mortalities of ARDS remains unclear. The current study aims to investigate the association between LAR and significant prognosis in patients with ARDS. Methods: We conducted a retrospective cohort study and analyzed patients with ARDS on the Medical Information Mart for Intensive Care IV (MIMIC-IV) version 2.0 database. In the current study, 30-day mortality was defined as the primary outcome; 90-day mortality and in-hospital mortality were defined as secondary outcomes. Multivariate regression analysis, Kaplan-Meier curve analysis and subgroup analysis were performed to research the association between LAR and prognosis in patients with ARDS. Results: A total of 358 critically ill patients with ARDS were enrolled in the current study. The mean age of the participants was 62.6±16.0 and the median of LAR was 14.3. According to the Kaplan-Meier curve analysis, the higher LAR group had a higher 30-day, 90-day and in-hospital mortalities. We also analyzed the 30-day mortality to receiver operating characteristic (ROC) curves by comparing the value between LAR and LAR + simplified acute physiology score II (SAPS II). The area under the curve (AUC) of the LAR group was 0.694 [95% confidence interval (CI): 0.634-0.754, P<0.001], and 0.661 for the LAR + SAPS II (95% CI: 0.599-0.722, P<0.001). For 30-day mortality, after adjusting for covariates, hazard ratios (HRs) (95% CIs) for tertile 2 (LAR 8.7-30.9) and tertile 3 (LAR >30.9) were 2.00 (1.37, 2.92) and 2.50 (1.50, 4.15), respectively. Similar results were also observed for 90-day mortality and in-hospital mortality. Conclusions: Elevated LAR levels are associated with increased 30- and 90-day mortalities, as well as in-hospital mortality in patients with ARDS, which means LAR levels may predict the mortalities of ARDS patients.

YuPingFeng (YPF) upregulates caveolin-1 (CAV1) to alleviate pulmonary fibrosis through the TGF-ß1/Smad2 pathway.

ETHNOPHARMACOLOGICAL RELEVANCE: Traditional Chinese medicine (TCM) is considered a valuable asset in China's medical tradition. YPF is a classic prescription that has been derived from the "Jiu Yuan Fang" formula and consists of three herbs: Huangqi (Astragalus membranaceus Bunge), Baizhu (Atractylodes rubra Dekker), and Fangfeng (Saposhnikovia divaricata (Turcz.) Schischk). This prescription is widely acclaimed for its exceptional pharmacological properties, including potent antioxidant effects, hormone regulation, and immune modulation effects. AIM OF THE STUDY: Previous research provides evidence suggesting that YPF may have therapeutic effects on pulmonary fibrosis. Further exploration is essential to confirm its effectiveness and elucidate the fundamental processes. MATERIALS AND METHODS: First, the active components and target genes of YPF were extracted from the Traditional Chinese Medicine Systems Pharmacology (TCMSP) database. Next, the GSE53845 dataset, which contains information on pulmonary fibrosis, was downloaded from the GEO database. Network informatics methods was then be utilized to identify target genes associated with pulmonary fibrosis. A YPF-based network of protein-protein interactions was constructed to pinpoint possible target genes for pulmonary fibrosis treatment. Additionally, an in vitro model of pulmonary fibrosis induced by bleomycin (BLM) was established to further investigate and validate the possible mechanisms underlying the effectiveness of YPF. RESULTS: In this study, a total of 24 active ingredients of YPF, along with 178 target genes associated with the treatment, were identified. Additionally, 615 target genes related to pulmonary fibrosis were identified. Functional enrichment analysis revealed that 18 candidate genes (CGs) exhibited significant responses to tumor necrosis factor, NF-kB survival signaling, and positive regulation of apoptosis processes. Among these CGs, CAV1, VCAM1, and TP63 were identified as key target genes. Furthermore, cell experiments confirmed that the expression of CAV1 protein and RNA expression was increased in pulmonary fibrosis, but significantly decreased after treatment with YPF. Additionally, the expression of pSmad2, α-SMA, TGF-ß1, and TNF-α was also decreased following YPF treatment. CONCLUSIONS: Network pharmacology analysis revealed that YPF exhibits significant potential as a therapeutic intervention for pulmonary fibrosis by targeting various compounds and pathways. This study emphasizes that the efficacy of YPF in treating pulmonary fibrosis may be attributed to its ability to up-regulate CAV1 expression and inhibiting pulmonary fibrosis via modulation of the TGF-ß1/Smad2 signaling pathway. These findings underscore the promising role of YPF and its ability to potentially alleviate pulmonary fibrosis.

STARD12/14 are diagnostic and prognostic biomarkers of lung adenocarcinoma associated with epigenetic regulation, immune infiltration and ferroptosis.

Background: Metabolic reprogramming plays an important role in tumor progression and antitumor immunity. START domain-containing proteins (STARDs) are responsible for lipid metabolism. However, the underlying functions of STARDs in lung adenocarcinoma (LUAD) have not been clarified yet. Methods: Oncomine, UALCAN, TCGA and CPTAC were used to explore the expression landscape and clinicopathological characteristics of STARDs in LUAD. Diagnostic and prognostic values were assessed by Kaplan-Meier Plotter, Cox regression analysis, and ROC curve. GeneMANIA, GO, KEGG and GSEA were applied for exploring the potential biological functions. Epigenetic process, including mutation and m6A modification were analyzed by cBioPortal and TCGA. TIMER, TISIDB and TCGA cohort provided an immune signature. The correlation between STARDs expression and ferroptosis was analyzed by TCGA. Finally, the STARDs expression were confirmed by RT-qPCR and western blot. Results: STARD5/10/14 were overexpressed in LUAD compared with normal, while STARD4/7/8/11/12/13 were relatively low. STARD5/12/14 levels were positively related to clinical and lymph node stage. Survival analysis showed high STARD12 expression was associated with favorable overall survival, disease special survival as well as disease free survival, while STARD14 showed the opposite. GSEA analysis found STARD12 and STARD14 were associated with glycolysis, oxidative phosphorylation and tumor related signaling pathways. STARD12 co-expressed genes participated in cell cycle and DNA replication, and STARD14 were enriched in ECM-receptor interaction. Both STARD12 and STARD14 were corelated with epigenetic regulation, especially TP53 mutation and m6A modification. STARD12 expression was positively correlated with TMB level. The level of STARD12 was significantly associated with the abundance of infiltrating immune cells, including B cells, CD8+T cells, macrophages, dendritic cells, and chemokine, receptor, MHC, immunostimulatory related genes. STARD14 was negatively associated with the infiltration of CD8+T cells, while positively with CCL28 and immune checkpoints, including CTLA4 as well as PD-L2. In addition, STARD12/14 could regulate the ferroptosis related genes. Conclusion: STARD12 and STARD14 were expected to be potential biomarkers for LUAD, which were associated with epigenetic regulation, immune infiltration and ferroptosis.

SYT7 is a key player in increasing exosome secretion and promoting angiogenesis in non-small-cell lung cancer.

Lung cancer is the leading cause of cancer-related mortality, and non-small cell lung cancer (NSCLC) accounts for approximately 85% of all lung cancer cases. Our previous study confirmed that synaptotagmin 7 (SYT7) promoted NSCLC metastasis in vivo and in vitro. Studies have shown that SYT7 is an important regulatory molecule of exocytosis in various cells. However, the characteristics of SYT7 across cancers and the function of SYT7 in tumor exosome secretion remain unclear. In this study, we conducted systematic pancancer analyses of SYT7, namely, analyses of expression patterns, diagnostic and prognostic values, genetic alterations, methylation, immune infiltration, and potential biological pathways. Furthermore, we demonstrated that SYT7 increased the secretion of exosomes from A549 and H1299 cells, promoting the migration, proliferation, and tube formation of human umbilical vein endothelial cells (HUVECs). Notably, SYT7 promoted angiogenesis by transferring exosomes containing the molecule centrosomal protein of 55 kDa (CEP55) protein to HUVECs. The CEP55 protein levels was downregulated in STAT1 inhibitor-treating SYT7-overexpresion NSCLC cells. We further found that SYT7 activated the mTOR signaling pathway through the downstream molecule CEP55, thereby promoting the invasion and metastasis of NSCLC cells. SYT7 promoted exosome secretion by NSCLC cells through upregulating syntaxin-1a and syntaxin-3. In vivo, SYT7 promoted the tumorigenesis, angiogenesis and metastasis of A549 cells through the exosome pathway. Our study is of great importance for understanding the mechanism of tumor exosome secretion and the role of exosomes in tumor progression.

Giant pulmonary sclerosing pneumocytoma with potentially malignant biological behavior: a case report and literature review.

Background: Pulmonary sclerosing pneumocytoma (PSP) is a rare benign lung tumor which generally presents as a solitary pulmonary nodule in middle-aged females. However, the PSP in some patients exhibits potentially malignant biological behavior, with recurrence and lymphatic or distant metastasis being observed. Case Description: We encountered a case of a 46-year-old female with an inordinately massive tumor 9.5 cm in diameter and a relatively high Ki-67 proliferation rate. Fine needle aspiration (FNA) played a significant but limited role in the preoperative diagnosis: the computed tomography (CT)-guided lung puncture biopsy was consistent with the typical pathology of PSP; however, endobronchial ultrasound-guided transbronchial lung biopsy (EBUS-TBLB) could not provide a definitive diagnosis. The patient ultimately underwent thoracoscopic resection and mediastinal lymph node dissection. Here, we provide a review of the literature on patients with PSP with malignant biological behavior to raise awareness of the malignant potential of PSP and describe our experience to inform future management. Conclusions: PSP lacks specificity in its clinical and radiological characteristics and has complex pathological manifestations. FNA is valuable in the diagnosis and differential diagnosis of PSP but involves the risk of misdiagnosis or missed diagnosis. Additionally, we believe that the accepted benign features of PSP need to be updated and that the potential malignant features of PSP should be carefully monitored. Surgical resection is curative but strict follow-up is crucial.

Autophagy-related tumor subtypes associated with significant gene expression profiles and immune cell infiltration signatures to reveal the prognosis of non-small cell lung cancer.

Autophagy plays an important role in non-small cell lung cancer (NSCLC). We aimed to establish novel autophagy-related tumor subtypes to distinguish the prognosis of NSCLC. In this study, gene expression profiles, mutation data and clinical information obtained from the Cancer Genome Atlas. Kaplan Meier-plotter could evaluate prognostic value of autophagy-related genes. Consensus clustering revealed autophagy-related tumor subtypes. Gene expression profiles, mutation data and immune infiltration signatures were identified, oncogenic pathways and gene-drug interactions were performed according to the clusters. Finally, a total of 23 prognostic genes were screened and consensus clustering analysis divided the NSCLC into 2 clusters. The mutation signature showed that 6 genes are special. Immune infiltration signatures showed that higher fraction of immune cells was associated with cluster 1. The oncogenic pathways and gene-drug interactions also showed different patterns. In conclusion, autophagy-related tumor subtypes have different prognosis. Understanding the subtypes of NSCLC are helpful to accurately identify the NSCLC and personalized treatment.

IDO1 Promotes the Progression of NSCLC by Regulating the Polarization of M2 Macrophages.

Purpose: 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.

The role of autophagy in idiopathic pulmonary fibrosis: from mechanisms to therapies.

Idiopathic pulmonary fibrosis (IPF) is an interstitial pulmonary disease with an extremely poor prognosis. Autophagy is a fundamental intracellular process involved in maintaining cellular homeostasis and regulating cell survival. Autophagy deficiency has been shown to play an important role in the progression of pulmonary fibrosis. This review focused on the six steps of autophagy, as well as the interplay between autophagy and other seven pulmonary fibrosis related mechanisms, which include extracellular matrix deposition, myofibroblast differentiation, epithelial-mesenchymal transition, pulmonary epithelial cell dysfunction, apoptosis, TGF-ß1 pathway, and the renin-angiotensin system. In addition, this review also summarized autophagy-related signaling pathways such as mTOR, MAPK, JAK2/STAT3 signaling, p65, and Keap1/Nrf2 signaling during the development of IPF. Furthermore, this review also illustrated the commonly used autophagy detection methods, the currently approved antifibrotic drugs pirfenidone and nintedanib, and several prospective compounds targeting autophagy for the treatment of IPF.

FOXP family DNA methylation correlates with immune infiltration and prognostic value in NSCLC.

Background: Forkhead box P (FOXP) family was introduced as a double-edged sword in tumorigenesis and influenced immunotherapy response by modulating host immunity. This study aimed to summarize the involvement of the FOXP family in non-small cell lung cancer (NSCLC). Methods: The UALCAN, Gene Expression Profiling Interactive Analysis (GEPIA), and Reverse transcription-quantitative polymerase chain reaction (RT‒qPCR) were used to analyse the expression levels of the FOXP family in NSCLC. The prognostic impact was evaluated using Kaplan-Meier Plotter. MethSurv, UALCAN, and cBioPortal were applied to analyse the DNA methylation and mutation status of the FOXP family respectively. COEXPEDIA, STRING, and GeneMANIA were used to explore the interaction mechanism. Finally, TISIDB was used to investigate all of the immune-related characteristics regulated by the FOXP family. Results: The expression levels of FOXP1/3/4 were dysregulated in NSCLC tissues than that in normal tissues. Groups with low expression levels of FOXP1/4 and high expression levels of FOXP2/3 were associated with poor prognosis in NSCLC. The transcriptional levels of FOXP2/3/4 were correlated with DNA methylation in NSCLC. FOXP1/3/4 DNA methylation were correlated with prognosis. Pathway enrichment analysis indicated the FOXP family was mainly related to immune-related pathways. After DNA methylation, the correlations between FOXP family and immune factors were opposite to that before alteration in NSCLC. Conclusion: This study elucidated FOXP family could serve as vital diagnostic and prognostic biomarkers in NSCLC. Our study highlighted novel potential functions of FOXP family DNA methylation in regulation of immune-related signatures in NSCLC.

Identification and Validation of CDKN1A and HDAC1 as Senescence-Related Hub Genes in Chronic Obstructive Pulmonary Disease.

Purpose: 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.

Erratum: Targeting cysteine-rich angiogenic inducer-61 by antibody immunotherapy suppresses growth and migration of non-small cell lung cancer.

[This corrects the article DOI: 10.3892/etm.2018.6274.].

Downregulation of hsa-miR-30b-3p Inhibits the Oncogenicity of Lung Adenocarcinoma by Targeting the METTL7B Gene.

Objective: Lung adenocarcinoma (LUAD) is one of the malignant tumors with the highest morbidity and mortality rates worldwide. Although surgery-based combination therapy can greatly improve the prognosis of LUAD patients, the overall outcome is still poor, and there is an urgent need to develop new and effective treatment alternatives for LUAD. The microRNA (miRNA) miR-30b-3p is a typical multifunctional miRNA that has been reported to promote the development of various malignancies. In this study, we investigated the effects of miR-30b-3p on the biological properties of LUAD and the possible mechanisms involved to provide new ideas for the development of more effective treatment options for LUAD. Methods: Fluorescence quantitative real-time polymerase chain reaction (qRT-PCR) was used to measure the expression of miR-30b-3p and its target METTL7B gene in tumor tissues and adjacent noncancerous lung tissues of LUAD patients and to determine their correlation. The effect of miR-30b-3p on the biological properties of LUAD was investigated, after transfection of miR-30b-3p mimics or scramble miRNA (negative control) in LUAD cells, using various approaches, including by measuring cell proliferation using CCK-8 and Edu assays, cell invasion by Transwell assay, and apoptosis and cell cycle distribution by flow cytometry. Additionally, rescue assays were performed to verify the effect of METTL7B on miR-30b-3p function. Results: In LUAD patients, low expression of miR-30b-3p and high expression of METTL7B in tumor tissues were significantly and negatively correlated with those in adjacent noncancerous lung tissues of the LUAD patients. It was also found that miR-30b-3p inhibits the proliferation and invasion of LUAD cells, promotes apoptosis, and changes the cell cycle distribution. METTL7B is a target gene of miR-30b-3p. METTL7B overexpression significantly reversed the biological effects of miR-30b-3p overexpression, including inhibition of cell proliferation and invasion, promotion of apoptosis, and alteration of the cell cycle distribution. Conclusions: The miR-30b-3p alters the biology of LUAD by negatively regulating METTL7B expression, indicating the importance of the miR-30b-3p/METTL7B pathway in the development of LUAD.

Junctional adhesion molecule-like protein promotes tumor progression via the Wnt/ß-catenin signaling pathway in lung adenocarcinoma.

BACKGROUND: Lung adenocarcinoma (LUAD) is a heavy social burden worldwide. Because the mechanisms involved in LUAD remain unclear, the prognosis of LUAD remains poor. Consequently, it is urgent to investigate the potential mechanisms of LUAD. Junctional adhesion molecule-like protein (JAML), is recognized as a tumorigenesis molecule in gastric cancer. However, the role of JAML in LUAD is still unclear. Here we aimed to evaluate the role of JAML in LUAD. METHODS: qRT-PCR, Western blotting and immunohistochemistry were conducted to investigate the expression of JAML in LUAD tissues. JAML was knocked down and overexpressed in LUAD cells using transient transfection by siRNA and plasmids or stable transfection by lentivirus. Proliferation potential of LUAD cells were detected by Cell Counting Kit-8, EdU incorporation and Colony formation assay. Migration and invasion abilities of LUAD cells were determined by wound healing, transwell migration and invasion assays. Cell cycle and cell apoptosis were detected by flow cytometry. The effects of JAML in vivo were studied in xenograft tumor models. Western blotting was used to explore the molecular mechanisms of JAML function. In addition, rescue experiments were performed to verify the possible mechanisms. RESULTS: JAML expression was elevated in LUAD tissues compared with peritumor tissues, and this upregulation was positively related to pT and pTNM. Furthermore, both in vitro and in vivo, JAML silencing markedly repressed malignant behaviors of LUAD cells and vice versa. Knockdown of JAML also mediated cell cycle arrest at G0/G1 phase and promoted apoptosis in LUAD cells. Mechanistically, silencing JAML repressed the process of epithelial-mesenchymal transition by inactivating the Wnt/ß-catenin pathway in LUAD cells. Effects of JAML can be rescued by Wnt/ß-catenin pathway activator in A549 cells. CONCLUSIONS: Our data reveal the oncogenic role of JAML in LUAD, indicating that JAML may be a predictive biomarker and novel therapeutic target for LUAD.

Identification of Ferroptosis-Related Hub Genes and Their Association with Immune Infiltration in Chronic Obstructive Pulmonary Disease by Bioinformatics Analysis.

Purpose: 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.

Autophagy Induced by BCL2-Related ceRNA Network Participates in the Occurrence of COPD.

Purpose: 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.

Prognostic Value of Genomic Instability of m6A-Related lncRNAs in Lung Adenocarcinoma.

Background: Genomic instability of N6-methyladenosine (m6A)-related long noncoding RNAs (lncRNAs) plays a pivotal role in the tumorigenesis of lung adenocarcinoma (LUAD). Our study identified a signature of genomic instability of m6A-associated lncRNA signature and revealed its prognostic role in LUAD. Methods: We downloaded RNA-sequencing data and somatic mutation data for LUAD from The Cancer Genome Atlas (TCGA) and the GSE102287 dataset from the Gene Expression Omnibus (GEO) database. The "Limma" R package was used to identify a network of regulatory m6A-related lncRNAs. We used the Wilcoxon test method to identify genomic-instability-derived m6A-related lncRNAs. A competing endogenous RNA (ceRNA) network was constructed to identify the mechanism of the genomic instability of m6A-related lncRNAs. Univariate and multivariate Cox regression analyses were performed to construct a prognostic model for internal testing and validation of the prognostic m6A-related lncRNAs using the GEO dataset. Performance analysis was conducted to compare our prognostic model with the previously published lncRNA models. The CIBERSORT algorithm was used to explore the relationship of m6A-related lncRNAs and the immune microenvironment. Prognostic m6A-related lncRNAs in prognosis, the tumor microenvironment, stemness scores, and anticancer drug sensitivity were analyzed to explore the role of prognostic m6A-related lncRNAs in LUAD. Results: A total of 42 genomic instability-derived m6A-related lncRNAs were differentially expressed between the GS (genomic stable) and GU (genomic unstable) groups of LUAD patients. Four differentially expressed lncRNAs, 17 differentially expressed microRNAs, and 75 differentially expressed mRNAs were involved in the genomic-instability-derived m6A-related lncRNA-mediated ceRNA network. A prediction model based on 17 prognostic m6A-associated lncRNAs was constructed based on three TCGA datasets (all, training, and testing) and validated in the GSE102287 dataset. Performance comparison analysis showed that our prediction model (area under the curve [AUC] = 0.746) could better predict the survival of LUAD patients than the previously published lncRNA models (AUC = 0.577, AUC = 0.681). Prognostic m6A-related-lncRNAs have pivotal roles in the tumor microenvironment, stemness scores, and anticancer drug sensitivity of LUAD. Conclusion: A signature of genomic instability of m6A-associated lncRNAs to predict the survival of LUAD patients was validated. The prognostic, immune microenvironment and anticancer drug sensitivity analysis shed new light on the potential novel therapeutic targets in LUAD.

Identification of a Five Autophagy Subtype-Related Gene Expression Pattern for Improving the Prognosis of Lung Adenocarcinoma.

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.