Effect of human heart valve-derived ECM and NP/PCL electrospun nanofibrous sheet on mice bone marrow mononuclear cells and cardiac repair.

Background: Biomaterials can improve cardiac repair combined with transplantation of bone marrow mononuclear cells (BMMNCs). In this study, we compared the phenotype and cardiac repair between human heart valve-derived scaffold (hHVS) and natural protein/polycaprolactone (NP/PCL) anchored BMNNCs. Methods and results: BMMNCs were obtained from mice five days following myocardial infarction. Subsequently, BMMNCs were separately cultured on hHVS and PCL. Proliferation and cardiomyogenic differentiation were detected in vitro. Cardiac function was measured after transplantation of cell-seeded cardiac patch on MI mice. After that, the BMMNCs were collected for mRNA sequencing after culturing on the scaffolds. Upon anchoring onto hHVS or PCL, BMMNCs exhibited an increased capacity for proliferation in vitro, however, the cells on hHVS exhibited superior cardiomyogenic differentiation ability. Moreover, both BMMNCs-seeded biomaterials effectively improved cardiac function after 4 weeks of transplantation, with reduced infarction area and restricted LV remodeling. Cell-seeded hHVS was superior to cell-seeded PCL. Conclusion: BMMNCs on hHVS showed better capacity in both cell cardiac repairing and improvement for cardiac function than on PCL. Compared with seeded onto PCL, BMMNCs on hHVS had 253 genes up regulated and 189 genes down regulated. The reason for hHVS' better performance than PCL as a scaffold for BMMNCs might be due to the fact that optimized method of decellularization let more cytokines in ECM retained.

Identification of lysosomal genes associated with prognosis in lung adenocarcinoma.

Background: Lung adenocarcinoma (LUAD) is the most common subtype of lung cancer, representing 40% of all cases of this tumor. Despite immense improvements in understanding the molecular basis, diagnosis, and treatment of LUAD, its recurrence rate is still high. Methods: RNA-seq data from The Cancer Genome Atlas (TCGA) LUAD cohort were download from Genomic Data Commons Portal. The GSE13213 dataset from Gene Expression Omnibus (GEO) was used for external validation. Differential prognostic lysosome-related genes (LRGs) were identified by overlapping survival-related genes obtained via univariate Cox regression analysis with differentially expressed genes (DEGs). The prognostic model was built using Kaplan-Meier curves and least absolute shrinkage and selection operator (LASSO) analyses. In addition, univariate and multivariate Cox analyses were employed to identify independent prognostic factors. The responses of patients to immune checkpoint inhibitors (ICIs) were further predicted. The pRRophetic package and rank-sum test were used to compute the half maximal inhibitory concentrations (IC50) of 56 chemotherapeutic drugs and their differential effects in the low- and high-risk groups. Moreover, quantitative real-time polymerase chain reaction, Western blot, and human protein atlas (HPA) database were used to verify the expression of the four prognostic biomarkers in LUAD. Results: Of the nine candidate differential prognostic LRGs, GATA2, TFAP2A, LMBRD1, and KRT8 were selected as prognostic biomarkers. The prediction of the risk model was validated to be reliable. Cox independent prognostic analysis revealed that risk score and stage were independent prognostic factors in LUAD. Furthermore, the nomogram and calibration curves of the independent prognostic factors performed well. Differential analysis of ICIs revealed CD276, ICOS, PDCD1LG2, CD27, TNFRSF18, TNFSF9, ENTPD1, and NT5E to be expressed differently in the low- and high-risk groups. The IC50 values of 12 chemotherapeutic drugs, including epothilone.B, JNK.inhibitor.VIII, and AKT.inhibitor.VIII, significantly differed between the two risk groups. KRT8 and TFAP2A were highly expressed, while GATA2 and LMBRD1 were poorly expressed in LUAD cell lines. In addition, KRT8 and TFAP2A were highly expressed, while GATA2 and LMBRD1 were poorly expressed in tumor tissues. Conclusions: Four key prognostic biomarkers-GATA2, TFAP2A, LMBRD1, and KRT8-were used to construct a significant prognostic model for LUAD patients.

Exploration of the shared genes and signaling pathways between lung adenocarcinoma and idiopathic pulmonary fibrosis.

Background: Idiopathic pulmonary fibrosis (IPF), a type of interstitial lung disease (ILD), is a chronic disease with an unknown etiology. The occurrence of lung cancer (LC) is one of the main causes of death in patients with IPF. However, the pathogenesis driving these malignant transformations remains unclear; therefore, this study aimed to identify the shared genes and functional pathways associated with both disease conditions. Methods: Data were downloaded from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. To identify overlapping genes in both diseases, the "limma" package in R software and weighted gene coexpression network analysis (WGCNA) were used. Venn diagrams were used to obtain the shared genes. The diagnostic value of the shared genes was assessed using receiver operating characteristic (ROC) curve analysis. Gene Ontology (GO) term enrichment was performed on the shared genes between lung adenocarcinoma (LUAD) and IPF, and the genes were also functionally enriched using Metascape. A protein-protein interaction (PPI) network was created using the Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) database. Finally, the link between shared genes and common antineoplastic medicines was investigated using the CellMiner database. Results: The coexpression modules associated with LUAD and IPF were discovered using WGCNA, and 148 genes were found to overlap. In addition, 74 upregulated and 130 downregulated overlapping genes were obtained via differential gene analysis. Functional analysis of the genes revealed that these genes are primarily engaged in extracellular matrix (ECM) pathways. Furthermore, COL1A2, POSTN, COL5A1, CXCL13, CYP24A1, CXCL14, and BMP2 were identified as potential biomarkers in patients with LUAD secondary to IPF showing good diagnostic values. Conclusions: ECM-related mechanisms may be the underlying link between LC and IPF. A total of 7 shared genes were identified as potential diagnostic markers and therapeutic targets for LUAD and IPF.

Identification of a polycomb group-related gene signature for predicting prognosis and immunotherapy efficacy in lung adenocarcinoma.

Background: Several studies have reported the role of polycomb group (PcG) genes in human cancers; however, their role in lung adenocarcinoma (LUAD) is unknown. Methods: Firstly, consensus clustering analysis was used to identify PcG patterns among the 633 LUAD samples in the training dataset. The PcG patterns were then compared in terms of the overall survival (OS), signaling pathway activation, and immune cell infiltration. The PcG-related gene score (PcGScore) was developed using Univariate Cox regression and the least absolute shrinkage and selection operator (LASSO) algorithm to estimate the prognostic value and treatment sensitivity of LUAD. Finally, the prognostic ability of the model was validated using a validation dataset. Results: Two PcG patterns were obtained by consensus clustering analysis, and the two patterns showed significant differences in prognosis, immune cell infiltration, and signaling pathways. Both the univariate and multivariate Cox regression analyses confirmed that the PcGScore was a reliable and independent predictor of LUAD (P<0.001). The high- and low-PCGScore groups showed significant differences in the prognosis, clinical outcomes, genetic variation, immune cell infiltration, and immunotherapeutic and chemotherapeutic effects. Lastly, the PcGScore demonstrated exceptional accuracy in predicting the OS of the LUAD patients in a validation dataset (P<0.001). Conclusions: The study indicated that the PcGScore could serve as a novel biomarker to predict prognosis, clinical outcomes, and treatment sensitivity for LUAD patients.

Sustainably released nanoparticle-based rhynchophylline limits pulmonary fibrosis by inhibiting the TEK-PI3K/AKT signaling pathway.

Background: Pulmonary fibrosis (PF) is a rapidly progressing and irreversible disease, and the currently available types of clinical drugs are limited and inefficient. In our previous study, we observed that Rhynchophylline (Rhy) hindered tendon adhesion and stimulated the healing of injured tendon structures. Considering the similar mechanisms between adhesion formation and PF, we explored the roles of Rhy in PF. Methods: The cytotoxicity of Rhy was tested by a Cell Counting Kit-8 (CCK-8) assay. The degree of PF was evaluated by Western blot (WB), Masson and hematoxylin-eosin (HE) staining, and hydroxyproline quantification. The Rhy-loaded nanoparticles were prepared through an emulsification sonication technique and characterized by transmission electron microscopy (TEM) and scanning electron microscopy (SEM). The release of the Rhy-loaded nanoparticles was tested using the absorbance value of the supernatant. Transcriptome sequencing was performed to determine the downstream target and pathway of Rhy, which was then verified by WB. Results: In vitro, Rhy decreased Transforming Growth Factor Beta 1 (TGF-ß1)-induced abnormal overexpression of fibronectin (FN), collagen I (Col I), α-smooth muscle actin (α-SMA) in a dose-dependent manner in human lung fibroblast (HFL1) cells. In vivo, we confirmed (through Masson staining) that the intraperitoneal injection of Rhy reduced collagen deposition and the fibrotic area in a dose-dependent manner. Our results indicated that the Rhy-loaded nanoparticles intratracheal spray intuitively narrowed collagen deposition, shrank collagen deposition and the fibrotic area (Masson and HE staining), and reduced the expression of fibrosis-related markers (WB). Meanwhile, the lung index value and hydroxyproline content were markedly lower than the bleomycin (BLM)-treated group. By transcriptional sequencing analysis, we identified Receptor Tyrosine Kinase (TEK)-Phosphatidylinositol 3-Kinase/Protein Kinase B (PI3K/AKT) as the downstream target and pathway of Rhy. It was also observed that Rhy could reverse the TGF-ß1-induced TEK and phosphorylated AKT (p-AKT) elevated expression. Conclusions: Our findings indicate that Rhy constrained PF progression by inhibiting TEK-PI3K/AKT signaling pathway. Hence, this sustainable release system of Rhy is a highly effective therapy to limit PF and should be developed.

Analysis of prognostic model based on immunotherapy related genes in lung adenocarcinoma.

Lung cancer is one of the most common malignant tumors, and ranks high in the list of mortality due to cancers. Lung adenocarcinoma (LUAD) is the most common subtype of lung cancer. Despite progress in the diagnosis and treatment of lung cancer, the prognosis of these patients remains dismal. Therefore, it is crucial to identify the predictors and treatment targets of lung cancer to provide appropriate treatments and improve patient prognosis. In this study, the gene modules related to immunotherapy were screened by weighted gene co-expression network analysis (WGCNA). Using unsupervised clustering, patients in The Cancer Genome Atlas (TCGA) were divided into three clusters based on the gene expression. Next, gene clustering was performed on the prognosis-related differential genes, and a six-gene prognosis model (comprising PLK1, HMMR, ANLN, SLC2A1, SFTPB, and CYP4B1) was constructed using least absolute shrinkage and selection operator (LASSO) analysis. Patients with LUAD were divided into two groups: high-risk and low-risk. Significant differences were found in the survival, immune cell infiltration, Tumor mutational burden (TMB), immune checkpoints, and immune microenvironment between the high- and low-risk groups. Finally, the accuracy of the prognostic model was verified in the Gene Expression Omnibus (GEO) dataset in patients with LUAD (GSE30219, GSE31210, GSE50081, GSE72094).

Chitosan degradation products promote healing of burn wounds of rat skin.

Burns can impair the barrier function of the skin, and small burns can also cause high mortality. The WHO has described that over 180,000 people die of burns worldwide each year. Thus, the treatment of burn wounds is a major clinical challenge. Chitooligosaccharides (COS) are alkaline amino oligosaccharides with small molecular weights obtained by enzyme or chemical degradation of chitosan. With the characteristics of biocompatibility, water solubility and degradability, it has attracted increasing attention in the fields of biomedicine. In the present study, we used COS to treat deep second-degree burn wounds of rat skin and found that COS was able to promote wound healing. We also revealed that COS could promote fibroblast proliferation. Transcriptome sequencing analysis was performed on COS-treated fibroblasts to identify the underlying mechanisms. The results showed that COS was able to promote wound healing through regulation of the mitogen-activated protein kinase (MAPK) pathway and growth factor Hepatocyte Growth Factor (HGF). Our results provide a potential drug for burn wound therapy and the related molecular mechanism.

Platelet-Membrane-Encapsulated Carvedilol with Improved Targeting Ability for Relieving Myocardial Ischemia-Reperfusion Injury.

In recent years, cell membrane drug delivery systems have received increasing attention. However, drug-loaded membrane delivery systems targeting therapy in myocardial ischemia-reperfusion injury (MIRI) have been relatively rarely studied. The purpose of this study was to explore the protective effect of platelet-membrane-encapsulated Carvedilol on MIRI. We extracted platelets from the blood of adult SD rats and prepared platelet membrane vesicles (PMVs). Carvedilol, a nonselective ß-blocker, was encapsulated into the PMVs. In order to determine the best encapsulation rate and drug-loading rate, three different concentrations of Carvedilol in low, medium, and high amounts were fused to the PMVs in different volume ratios (drugs/PMVs at 2:1, 1:1, 1:2, and 4:1) for determining the optimum concentration and volume ratio. By comparing other delivery methods, including abdominal injection and intravenous administration, the efficacy of PMVs-encapsulated drug-targeted delivery treatment was observed. The PMVs have the ability to target ischemic-damaged myocardial tissue, and the concentration and volume ratio at the optimum encapsulation rate and the drug-loading rate are 0.5 mg and 1:1. We verified that PMVs@Carvedilol had better therapeutic effects compared to other treatment groups, and immunofluorescence observation showed a significant improvement in the apoptosis indicators and infarction area of myocardial cells. Targeted administration of PMVs@Carvedilol may be a promising treatment for myocardial reperfusion injury, as it significantly improves postinjury cardiac function and increases drug utilization compared to other delivery methods.

PRKCB is relevant to prognosis of lung adenocarcinoma through methylation and immune infiltration.

BACKGROUND: Lung adenocarcinoma (LUAD) is one of the tumor-related diseases with high morbidity worldwide. Epigenetic modifications such as DNA methylation changes may involve in tumorigenesis. This study aimed to explore new biomarkers that have prognostic significance of LUAD. METHODS: First, we downloaded the gene expression and methylation data set from Gene Expression Omnibus. R software was then used to identify abnormally methylated differentially expressed genes (MDEGs). Next, R package Cluster Profiler was used to analyze the enrichment and pathway of the MDEGs. Analysis using STRING revealed the protein-protein interaction network. The result was then visualized by Cytoscape and obtained 10 hub genes. Afterward, they were further verified by The Cancer Genome Atlas to select candidate genes. Moreover, quantitative real-time polymerase chain reaction (qRT-PCR) and immunohistochemistry were used to verify the expression and prognostic value of candidate genes in LUAD patients. RESULTS: The results showed that the expressions of ADCY5 and PRKCB are indeed related to LUAD. The clinical relevance to PRKCB was confirmed by its clinical correlation analysis. Gene set enrichment analysis (GSEA) and tumor immune estimation resource (TIMER) tumor immune correlations showed that PRKCB is involved in the cancer-related Kyoto Encyclopedia of Genes and Genomes pathway and is involved in immune infiltration. It was also verified by qRT-PCR and immunohistochemistry that PRKCB was lowly expressed in LUAD patients and correlated with prognosis. CONCLUSIONS: PRKCB is relevant to prognosis of LUAD through methylation and immune infiltration.

SMOX expression predicts the prognosis of non-small cell lung cancer.

BACKGROUND: The development of non-small cell lung cancer (NSCLC) is very rapid, and the effect of its treatment is often closely related to the diagnosis time of the disease. Therefore, simple and convenient tumor biomarkers are helpful for the timely diagnosis and prevention of NSCLC. METHODS: Through univariate and multivariate Cox regression analyses, SMOX was determined as an independent prognostic factor of GSE42127, GSE41271, GSE68465, and TCGA datasets. Furthermore, western blot, reverse transcription-polymerase chain reaction (RT-PCR), and immunohistochemical analysis were performed to confirm the predictive efficiency of SMOX expression in NSCLC. RESULTS: Patients were divided into high and low expression groups according to the median value of SMOX expression, and Kaplan-Meier curves of multiple datasets indicated that patients with low SMOX expression had a better survival rate. According to the analysis of immune infiltration, the immune microenvironment, and immune checkpoints, SMOX expression of the high and low groups showed differences in immunity in NSCLC. By comparing cancer and adjacent tissues using western blot analysis, RT-PCR and immunohistochemical analysis, we found that SMOX was highly expressed in tumor tissues and had low expression in adjacent tissues. Simultaneously, the Kaplan-Meier curve suggested that among the 155 NSCLC patients, those with low SMOX expression had better survival. CONCLUSIONS: SMOX can be used as an effective predictive target for NSCLC.

Low expression of IL6R predicts poor prognosis for lung adenocarcinoma.

BACKGROUND: Interleukin 6 (IL6) is both a pleiotropic cytokine and an immune-related gene. Interleukin 6 receptor (IL6R) is the receptor for IL6. It may be closely connected to the development of lung cancer. This research aims to explore the prognostic value of IL6R and prevent overtreatment of patients with lung adenocarcinoma (LUAD). METHODS: In this study, the expression of IL6R in tumor tissues and surrounding tissues was first analyzed by immunohistochemistry in the Affiliated Hospital of Nantong University (NTU) cohort. Secondly, we downloaded information from The Cancer Genome Atlas (TCGA) for the TCGA cohort and used this information to explore the messenger RNA (mRNA) level of IL6R. We then used Kaplan-Meier survival analyses, univariate and multivariate Cox analyses, nomogram models, and decision curve analyses to assess the prognostic value of IL6R. In addition, we also analyzed immune cell infiltration and the signaling pathways related to IL6R through Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and Gene Set Enrichment Analysis (GSEA). RESULTS: Through the data analysis of the NTU cohort and the TCGA cohort, it was found that the expression of IL6R in normal tissues around the tumor was higher than that in tumor tissue, and was positively correlated with the overall survival (OS) of LUAD patients. Additionally, low expression of IL6R was found to be an independent predictor of poor prognosis among the patients in these two research cohorts. Next, using GO, KEGG, and GSEA analyses, we found that partially infiltrated tumor immune cells might be related to earlier staging and better prognosis of patients with LUAD. Finally, the study of the 3-5-year survival rate of LUAD patients through the nomogram showed that the expression of IL6R could improve the accuracy of prediction to prevent the overtreatment of some LUAD patients. CONCLUSIONS: In summary, our study indicated that the low expression of IL6R was associated with poor prognosis among LUAD patients and that low expression of IL6R is a potential independent risk factor that could provide a basis for strengthening postoperative classification management of such patients.

Loss of IL-34 Expression Indicates Poor Prognosis in Patients With Lung Adenocarcinoma.

Interleukin 34 (IL-34), an additional ligand of the colony-stimulating factor-1 receptor (CSF-1R), promotes the secretion of pro-inflammatory cytokines and stimulates NF-κB and JNK-related signaling pathways. However, the potential mechanism and prognostic value of IL-34 in lung adenocarcinoma (LUAD) remain obscure. In this study, IL-34 was found to be downregulated in LUAD tissues compared with para-carcinoma tissues, and loss of IL-34 expression was correlated with shorter overall survival (OS), which was validated by bioinformatics\ analysis in TCGA (The Cancer Genome Atlas) cohort and immunohistochemical analysis in the NTU (Nantong University) cohort, respectively. Subsequently, loss of IL-34 promotes negative regulation of the immune system and inhibits the infiltration of immune cells. Moreover, IL-34 deficiency was shown to be an independent adverse prognostic factor for patients with LUAD, and subgroup analysis indicated that IL-34 might contribute to the stratified management of patients with LUAD. IL-34-based nomogram model significantly improved the accuracy of prognostic predictions for OS of patients with LUAD, both in the TCGA cohort and the NTU cohort. Taken together, our data suggested that loss of IL-34 expression is associated with poor prognosis and negative regulation of the immune system of patients with LUAD, contributing to the stratified management of patients with LUAD.

Characteristic of molecular subtypes in lung adenocarcinoma based on m6A RNA methylation modification and immune microenvironment.

BACKGROUND: Lung adenocarcinoma (LUAD) is a major subtype of lung cancer and closely associated with poor prognosis. N6-methyladenosine (m6A), one of the most predominant modifications in mRNAs, is found to participate in tumorigenesis. However, the potential function of m6A RNA methylation in the tumor immune microenvironment is still murky. METHODS: The gene expression profile cohort and its corresponding clinical data of LUAD patients were downloaded from TCGA database and GEO database. Based on the expression of 21 m6A regulators, we identified two distinct subgroups by consensus clustering. The single-sample gene-set enrichment analysis (ssGSEA) algorithm was conducted to quantify the relative abundance of the fraction of 28 immune cell types. The prognostic model was constructed by Lasso Cox regression. Survival analysis and receiver operating characteristic (ROC) curves were used to evaluate the prognostic model. RESULT: Consensus classification separated the patients into two clusters (clusters 1 and 2). Those patients in cluster 1 showed a better prognosis and were related to higher immune scores and more immune cell infiltration. Subsequently, 457 differentially expressed genes (DEGs) between the two clusters were identified, and then a seven-gene prognostic model was constricted. The survival analysis showed poor prognosis in patients with high-risk score. The ROC curve confirmed the predictive accuracy of this prognostic risk signature. Besides, further analysis indicated that there were significant differences between the high-risk and low-risk groups in stages, status, clustering subtypes, and immunoscore. Low-risk group was related to higher immune score, more immune cell infiltration, and lower clinical stages. Moreover, multivariate analysis revealed that this prognostic model might be a powerful prognostic predictor for LUAD. Ultimately, the efficacy of this prognostic model was successfully validated in several external cohorts (GSE30219, GSE50081 and GSE72094). CONCLUSION: Our study provides a robust signature for predicting patients' prognosis, which might be helpful for therapeutic strategies discovery of LUAD.

Identification of Prognostic Risk Model Based on DNA Methylation-Driven Genes in Esophageal Adenocarcinoma.

BACKGROUND: DNA methylation is an important part of epigenetic modification, and its abnormality is closely related to esophageal adenocarcinoma (EAC). This study was aimed at using bioinformatics analysis to identify methylation-driven genes (MDGs) in EAC patients and establish a risk model as a biological indicator of EAC prognosis. METHOD: Downloaded EAC DNA methylation, transcriptome, and related clinical data from TCGA database. MethylMix was used to identify MDGs. R package clusterProfiler and the ConsensusPathDB online database were used to analyze the rich functions and pathways of these MDGs. The prognostic risk model was established by univariate Cox regression, Lasso regression, and multivariate Cox regression analysis. Finally each MDG in the model were carried out through the survival R package. RESULTS: A total of 273 MDGs were identified, which were enriched in transcriptional regulation and embryonic organ morphogenesis. Cox regression analysis established a risk model consisting of GPBAR1, OLFM4, FOXI2, and CASP10. In addition, further survival analysis revealed that OLFM4 and its two related sites were significantly related to the EAC patients' survival. CONCLUSION: In summary, this study used bioinformatics methods to identify EAC MDGs and established a reliable risk prognosis model. It provided potential biomarkers for the early treatment and prognosis evaluation of EAC.

Characteristics of hypoxic tumor microenvironment in non-small cell lung cancer, involving molecular patterns and prognostic signature.

BACKGROUND: The mechanisms of hypoxia or immune microenvironment in cancer have been studied respectively, but the role of hypoxia immune microenvironment in non-small cell lung cancer (NSCLC) still needs further exploration. METHODS: By applying the K-means algorithm, 1,121 patients with NSCLC were divided into three categories. We evaluated the constructed signature in order to link it with the prognosis, which was constructed by univariate and least absolute shrinkage operator (LASSO) Cox regression analysis. RESULTS: A total of three clusters were obtained by clustering five Gene Expression Omnibus (GEO) data sets. Gene Set Variation Analysis (GSVA) and immune infiltration analysis were performed to explore the biological behavior. Cluster one presented an activated state of oncogenic pathways, and compared with the other two clusters, the median risk score was the highest, which was the reason for its poor survival. Cluster three showed that the immune pathway was active and the median risk score was the lowest, so the survival was the best. However, cluster two presented a state in which both immune and matrix pathways were activate. This was manifested as mutual antagonism, and its risk score was in the middle. Its survival was in the middle. CONCLUSIONS: This work revealed the role of hypoxia related genes (HRGs) modification in tumor microenvironment, which was conducive to our comprehensive analysis of the prognosis of NSCLC, and provided direction and guidance for clinical immunotherapy.

Integrated analysis of ceRNA network and tumor-infiltrating immune cells in esophageal cancer.

BACKGROUND: Esophageal cancer (ESCA) is one of the most commonly diagnosed cancers in the world. Tumor immune microenvironment is closely related to tumor prognosis. The present study aimed at analyzing the competing endogenous RNA (ceRNA) network and tumor-infiltrating immune cells in ESCA. METHODS: The expression profiles of mRNAs, lncRNAs, and miRNAs were downloaded from the Cancer Genome Atlas database. A ceRNA network was established based on the differentially expressed RNAs by Cytoscape. CIBERSORT was applied to estimate the proportion of immune cells in ESCA. Prognosis-associated genes and immune cells were applied to establish prognostic models basing on Lasso and multivariate Cox analyses. The survival curves were constructed with Kaplan-Meier method. The predictive efficacy of the prognostic models was evaluated by the receiver operating characteristic (ROC) curves. RESULTS: The differentially expressed mRNAs, lncRNAs, and miRNAs were identified. We constructed the ceRNA network including 23 lncRNAs, 19 miRNAs, and 147 mRNAs. Five key molecules (HMGB3, HOXC8, HSPA1B, KLHL15, and RUNX3) were identified from the ceRNA network and five significant immune cells (plasma cells, T cells follicular helper, monocytes, dendritic cells activated, and neutrophils) were selected via CIBERSORT. The ROC curves based on key genes and significant immune cells all showed good sensitivity (AUC of 3-year survival: 0.739, AUC of 5-year survival: 0.899, AUC of 3-year survival: 0.824, AUC of 5-year survival: 0.876). There was certain correlation between five immune cells and five key molecules. CONCLUSION: The present study provides an effective bioinformatics basis for exploring the potential biomarkers of ESCA and predicting its prognosis.

Prognostic signature of lung adenocarcinoma based on stem cell-related genes.

Lung adenocarcinoma (LUAD) is characterized by high infiltration and rapid growth. The function of the stem cell population is to control and maintain cell regeneration. Therefore, it is necessary to study the prognostic value of stem cell-related genes in LUAD. Signature genes were screened out from 166 stem cell-related genes according to the least absolute shrinkage operator (LASSO) and subsequently multivariate Cox regression analysis, and then established risk model. Immune infiltration and nomogram model were used to evaluate the clinical efficacy of signature. A signature consisting of 10 genes was used to dichotomize the LUAD patients into two groups (cutoff, 1.314), and then validated in GSE20319 and GSE42127. There was a significant correlation between signature and clinical characteristics. Patients with high-risk had a shorter overall survival. Furthermore, significant differences were found in multiple immune cells between the high-risk group and low-risk group. A high correlation was also reflected between signature and immune infiltration. What's more, the signature could effectively predict the efficacy of chemotherapy in patients with LUAD, and a nomogram based on signature might accurately predict the prognosis of patients with LUAD. The signature-based of stem cell-related genes might be contributed to predicting prognosis of patients with LUAD.

Phosphorylated nuclear factor erythroid 2-related factor 2 promotes the secretion of C-C motif chemokine ligand 2 and the recruitment of M2 macrophages.

BACKGROUND: Nuclear factor erythroid 2-related factor 2 (Nrf2) has been shown to ameliorate early ischemia-reperfusion (I/R) injury after activation by tertiary butylhydroquinone (TBHQ). However, despite macrophage-associated inflammation being a distinguishing feature of I/R injury, the precise roles and mechanisms of Nrf2 in macrophage-associated inflammation are still poorly understood. METHODS: I/R and hypoxia/reperfusion (H/R) models were constructed in vivo using rats and in vitro using the H9C2 rat cardiomyoblast cell line, respectively. The effects of TBHQ on myocardial damage under oxidative stress were assessed using apoptosis and cell cycle assays, as well as echocardiography. The Jaspar database was used to identify the C-C motif chemokine ligand 2 (Ccl2) gene promoter as a possible binding site for Nrf2. This interaction was validated by chromatin immunoprecipitation (ChIP) assays, enzyme-linked immunosorbent assay (ELISA), immunofluorescence staining, and western blot analysis. Transwell migration assays were used to examine the migration ability of the recruited macrophages. RESULTS: The Nrf2 activator, TBHQ, induced phosphorylation of Nrf2 and promoted the secretion of Ccl2 by myocardial microvascular endothelial cells. The secreted Ccl2 induced the chemotaxis of M2 macrophages into the injury site and triggered the secretion of anti-inflammatory factors including interleukin (IL)-10 and tumor growth factor (TGF)-ß1 by M2 macrophages, thereby reducing early myocardial ischemia reperfusion injury (MI/R). CONCLUSIONS: Activation of Nrf2 alleviated oxidative stress during myocardial ischemia and reperfusion by inducing the secretion of anti-inflammatory factors.

A robust signature associated with patient prognosis and tumor immune microenvironment based on immune-related genes in lung squamous cell carcinoma.

BACKGROUND: Lung squamous cell carcinoma (LUSC) is one common type of lung cancer. Immune-related genes (IRGs) are closely associated with cancer prognosis. This study aims to screen the key genes associated with LUSC and establish an immune-related prognostic model. METHODS: Based on the Cancer Genome Atlas (TCGA) database, we screened the differentially expressed genes (DEGs) between LUSC and normal samples. Intersecting the DEGs with the immune-related genes (IRGs), we obtained the differentially expressed IRGs (DEIRGs). Univariate as well as multivariate Cox regression analyses were performed to identify the survival-associated IRGs and establish an immune-related prognostic model. The relationship between the prognostic model and tumor-infiltrating immune cells was analyzed by TIMER and CIBERSORT. RESULTS: A total of 229 DEIRGs were screened, and 14 IRGs associated with survival were identified using univariate Cox analysis. Among the 14 IRGs, six genes were selected out using Lasso and multivariate Cox analyses, and they were used to build the prognostic model. Further analysis indicated that overall survival (OS) of high-risk groups was lower than that of low-risk groups. High risk score was independently related to worse OS. Moreover, the risk score was positively correlated with several immune infiltration cells. Finally, the efficacy of the prognostic model was validated by another independent cohort GSE73403. CONCLUSION: The DEIRGs described in the study may have the potential to be the prognostic molecular markers for LUSC. In addition, the risk score model could predict the OS and provides more information for the immunotherapy of patients with LUSC.