RESUMEN

Time-restricted feeding (TRF) has the potential to modulate circadian rhythm and widely studied in humans and laboratory mice. However, less is known about the physiological responses to TRF in wild mammals. Here, we used Mongolian gerbils, Meriones unguiculatus, to explore the effect of 6-week TRF on gene expression related with circadian rhythm and inflammation. The TRF gerbils had higher cumulative food intake than the ad libitum (AL) group, but body mass, feeding frequency/time and metabolic rate did not differ between groups. In the hypothalamus, downregulation of rhythm-related genes Per3, Cry1 and Dbp was detected in the daytime-restricted feeding (DRF) group and Cry1 was downregulated in the nighttime-restricted feeding (NRF) group. In the liver, the expression of Per1/3, Rev-erbα/ß and Dbp was lower, and Bmal1 was higher in the DRF than in AL group, while NRF gerbils showed no changes. In the colon, the expression of Bmal1 and Cry1 was higher but Per3, Rev-erbα/ß and Dbp were lower in the DRF than in AL group. Further, the expression of inflammation-related genes such as NF-κB, IL-1ß, IL-18 and Nlrp3 was lower in the liver of DRF gerbils, and IL-1ß was lower both in the hypothalamus and liver of NRF gerbils. Moreover, the genes related with inflammation such as NF-κB, Nlrp3, IL-10/18/1ß and Tnf-α were positively or negatively correlated with multiple rhythm-related genes in the central and peripheral organs. In conclusion, TRF, particularly DRF, could modulate rhythm-related genes in the central and peripheral tissues and reduce hepatic expression of inflammation-related genes in gerbils.

RESUMEN

AIMS: Prior evidence has shown a significant link between inflammation and the development of myocarditis. This study aimed to investigate the causal relationship between inflammation-related genes (IRGs) and myocarditis. METHODS AND RESULTS: In this study, the causal relationship between 167 IRGs and myocarditis were investigated using datasets from the Gene Set Enrichment Analysis and Integrative Epidemiology Unit open genome-wide association study (IEU OpenGWAS) databases. The GWAS data (finn-b-I9 MYOCARD) contained single nucleotide polymorphisms (SNPs) data from 117 755 myocarditis samples (16 379 455 SNPs, 829 cases vs. 116 926 controls). Five algorithms [MR-Egger, weighted median, inverse variance weighted (IVW), simple mode, and weighted mode regression] were employed for the MR analysis, with IVW as the primary method, and sensitivity analysis was conducted. Subcellular localization and protein-protein interaction (PPI) network analyses were performed for selected biomarkers. Results were verified in ebi-a-GCST90018882 (24 180 570 SNPs, 633 cases vs. 427 278 controls) and finn-b-I9 MYOCARD EXNONE (16 380 466 SNPs, 829 cases vs. 217 963 controls) to enhance reliability. RESULTS: IRF7 and ADORA2B were shown to be two exposure factors after screening. Univariable MR (UVMR) analysis revealed that IRF7 was a risk factor for myocarditis [IVW: odd ratio (OR) = 1.041, 95% confidence interval (CI) = 1.018-1.955, P = 0.039], while ADORA2B was a protective factors for myocarditis (IVW: OR = 0.799, 95% CI = 0.640-0.997, P = 0.047). Sensitivity analysis confirmed the robustness of these findings. Multivariable MR (MVMR) analysis further demonstrated a direct causal role of ADORA2B in preventing myocarditis. Subcellular localization analysis indicated predominant cytoplasmic expression and limited mitochondrial expression for both genes. The results of PPI analysis showed that 20 genes were predicted to be associated with IRF7 function, such as response to type I interferon, pattern recognition receptor signalling pathway, and toll-like receptor signalling pathway. The results in finn-b-I9 MYOCARD EXNONE were consistent with MR analysis. CONCLUSIONS: The findings indicated there was a causal connection between IRGs (IRF7 and ADORA2B) and myocarditis, which offered a crucial point of reference and guidance for future studies and myocarditis treatment.

RESUMEN

AIM: Twenty to thirty percent of non-small cell lung cancers (NSCLC) are caused by lung squamous cell carcinoma (LUSC), especially in smokers and there has been limited study previously evaluating the situation in terms of the genome and gene expression profile, which demonstrates the relationship among DEL-1, leucocyte recruitment, and pro-inflammatory cytokines in LUSC. MATERIAL AND METHODS: In the current study, the m-RNA expression patterns and mutation profiles of our target genes, such as, pro-inflammatory cytokines, chemoattractant molecules, and DEL-1 genes, in 511 LUSC patients. To find the harmful mutations, the PolyPhen-2 and SNAP programs were employed. Not only gene expression was detected, but also survival analysis and correlation between DEL-1 and other target genes' expression levels were explored too. RESULTS: Target genes such as, DEL-1, TNF, IL-18, IL-1, CXCL8, CXCL13, and IL-6 were found to have a total genetic anomaly carrying rate of 16.4%. Seven mutations were found, and two of those mutations have a pathogenic aspect. Deep deletion and gene amplification of the genetic anomalies were also observed. According to gene expression analysis results in the LUSC patient group; DEL-1 and IL-6 levels were significantly lower than those of the control group, whereas the CXCL13 level was found to be higher. CONCLUSION: Findings of the current study revealed that, there is a significant role of DEL-1 in LUSC pathogenesis. Since present study is an in silico-centered study, this approach can give more insight on experimental studies. These events may support that one of the cancer improvement mechanisms depending on DEL-1 gene at the molecular level.

Asunto(s)

RESUMEN

Background: This study aims to screen inflammation-related genes closely associated with the prognosis of hepatocellular carcinoma (HCC) to accurately forecast the prognosis of HCC patients. Methods: Gene expression matrices and clinical information for liver cancer samples were obtained from the Cancer Genome Atlas (TCGA) and the International Cancer Genome Consortium (ICGC). An intersection of differentially expressed genes of HCC and normal and GeneCards yielded inflammation-related genes associated with HCC. Cox regression and the minor absolute shrinkage and selection operator (LASSO) regression analysis to filter genes associated with HCC prognosis. The prognostic value of the model was confirmed by drawing Kaplan-Meier and ROC curves. Select differentially expressed genes between the high-risk and low-risk groups and perform GO and KEGG pathways analyses. CIBERSORT analysis was conducted to assess associations of risk models with immune cells and verified using real-time qPCR. Results: A total of six hub genes (C3, CTNNB1, CYBC1, DNASE1L3, IRAK1, and SERPINE1) were selected using multivariate Cox regression to construct a prognostic model. The validation evaluation of the prognostic model showed that it has an excellent ability to predict prognosis. A line plot was drawn to indicate the HCC patients' survival, and the calibration curve revealed satisfactory predictability. Among the six hub genes, C3 and DNASE1L3 are relatively low expressed in HCCLM3 and 97H liver cancer cell lines, while CTNNB1, CYBC1, IRAK1, and SERPINE1 are relatively overexpressed in liver cancer cell lines. Conclusion: One new inflammatory factor-associated prognostic model was constructed in this study. The risk score can be an independent predictor for judging the prognosis of HCC patients' survival.

RESUMEN

Background: Cervical cancer (CC) is the fourth most common cancer among women worldwide. As part of the brisk cross-talk between the host and the tumor, prognosis can be affected through inflammatory responses or the tumor microenvironment. However, further exploration of the inflammatory response-related genes that have prognostic value, microenvironment infiltration, and chemotherapeutic therapies in CC is needed. Methods: The clinical data and mRNA expression profiles of CC patients were downloaded from a public database for this study. In the TCGA cohort, a multigene prognostic signature was constructed by least absolute shrinkage and selection operator (LASSO) and Cox analyses. CC patients from the GEO cohort were used for validation. K‒M analysis was used to compare overall survival (OS) between the high- and low-risk groups. Univariate and multivariate Cox analyses were applied to determine the independent predictors of OS. The immune cell infiltration and immune-related functional score were calculated by single-sample gene set enrichment analysis (GSEA). Immunohistochemistry was utilized to validate the protein expression of prognostic genes in CC tissues. Results: A genetic signature model associated with the inflammatory response was built by LASSO Cox regression analysis. Patients in the high-risk group had a significantly lower OS rate. The predictive ability of the prognostic genes was evaluated by means of receiver operating characteristic (ROC) curve analysis. The risk score was confirmed to be an independent predictor of OS by univariate and multivariate Cox analyses. The immune status differed between the high-risk and low-risk groups, and the cancer-related pathways were enriched in the high-risk group according to functional analysis. The risk score was significantly related to tumor stage and immune infiltration type. The expression levels of five prognostic genes (LCK, GCH1, TNFRSF9, ITGA5, and SLC7A1) were positively related to sensitivity to antitumor drugs. Additionally, the expression of prognostic genes was significantly different between CC tissues and myoma patient cervix (non-tumorous) tissues in the separate sample cohort. Conclusion: A model consisting of 5 inflammation-related genes can be used to predict prognosis and influence immune status in CC patients. Furthermore, the inhibition or enhancement of these genes may become a novel alternative therapy.

RESUMEN

Background: The relationship between inflammation-related genes (IRGs) and keloid disease (KD) is currently unclear. The aim of this study was to identify a new set of inflammation-related biomarkers in KD. Methods: GSE145725 and GSE7890 datasets were used in this study. A list of 3026 IRGs was obtained from the Molecular Signatures Database. Differentially expressed inflammation-related genes (DEGs) were obtained by taking the intersection of DEGs between KD and control samples and the list of IRGs. Candidate genes were selected using least absolute shrinkage and selection operator (LASSO) regression analysis. Candidate genes with consistent expression differences between KD and control in both GSE145725 and GSE7890 datasets were screened as biomarkers. An alignment diagram was constructed and validated, and in silico immune infiltration analysis and drug prediction were performed. Finally, RT-qPCR was performed on KD samples to analyze the expression of the identified biomarkers. Results: A total of 889 DEGs were identified from the GSE145725 dataset, 169 of which were IRGs. Three candidate genes (TRIM32, LPAR1 and FOXF1) were identified by the LASSO regression analysis, and expression validation analysis suggested that FOXF1 and LPAR1 were down-regulated in KD samples and TRIM32 was up-regulated. All three candidate genes had consistent changes in expression in both the GSE145725 and GSE7890 datasets. An alignment diagram was constructed to predict KD. Effector memory CD4 T cells, T follicular helper cell, Myeloid derived suppressor cell, activated dendritic cell, Immature dendritic cell and Monocyte were differentially expressed between the KD and control group. Sixty-seven compounds that may act on FOXF1, 108 compounds that may act on LPAR1 and 56 compounds that may act on TRIM32 were predicted. Finally, RT-qPCR showed that the expression of LPAR1 was significantly lower in KD samples compared to normal samples whereas TRIM32 was significantly higher, while there was no difference in the expression of FOXF1. Conclusion: This study provides a new perspective to study the relationship between IRGs and KD.

Asunto(s)

RESUMEN

Background: Cervical cancer (CC) is a highly malignant gynecological cancer with a direct causal link to inflammation, primarily resulting from persistent high-risk human papillomavirus (HPV) infection. Given the challenges in early detection and mid to late-stage treatment, our research aims to identify inflammation-associated immune biomarkers in CC. Methods: Using a bioinformatics approach combined with experimental validation, we integrated two CC datasets (GSE39001 and GSE63514) in the Gene Expression Omnibus (GEO) to eliminate batch effects. Immune-related inflammation differentially expressed genes (DGEs) were obtained by R language identification. Results: This analysis identified 37 inflammation-related DEGs. Subsequently, we discussed the different levels of immune infiltration between CC cases and controls. Weighted gene co-expression network analysis (WGCNA) identified seven immune infiltration-related modules in CC. We identified 15 immune DEGs associated with inflammation at the intersection of these findings. In addition, we constructed a protein interaction network using the String database and screened five hub genes using "CytoHubba": CXC chemokine ligand 8 (CXCL8), CXC chemokine ligand 10 (CXCL10), CX3C chemokine receptor 1 (CX3CR1), Fc gamma receptors 3B (FCGR3B), and SELL. The expression of these five genes in CC was determined by PCR experiments. In addition, we assessed their diagnostic value and further analyzed the association of immune cells with them. Conclusions: Five inflammation- and immune-related genes were identified, aiming to provide new directions for early diagnosis and mid to late-stage treatment of CC from multiple perspectives.

RESUMEN

Inflammation and DNA methylation have been reported to play key roles in intracerebral hemorrhage (ICH). This study aimed to investigate new diagnostic biomarkers associated with inflammation and DNA methylation using a comprehensive bioinformatics approaches. GSE179759 and GSE125512 were collected from the Gene Expression Omnibus database, and 3222 inflammation-related genes (IFRGs) were downloaded from the Molecular Signatures Database. Key differentially expressed methylation-regulated and inflammation-related genes (DE-MIRGs) were identified by overlapping methylation-regulated differentially expressed genes (MeDEGs) between patients with ICH and control samples, module genes from weighted correlation network analysis, and IFRGs. Functional annotation of DE-MIRGs was performed using Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG). A protein-protein interaction (PPI) network was constructed to clarify the interrelationships between different DE-MIRGs. The key genes were categorized by least absolute shrinkage selection operator (LASSO) and support vector machine-recursive feature elimination (SVM-RFE), and gene set enrichment analysis (GSEA). A total of 22 DE-MIRGs were acquired from 451 MeDEGs, 3222 IFRGs, and 302 module genes, and were mainly enriched in the GO terms of wound healing, blood coagulation, and hemostasis; and the KEGG pathways of PI3K/Akt signaling, focal adhesion, and regulation of actin cytoskeleton. A PPI network with 22 nodes and 87 edges was constructed based on the 22 DE-MIRGs, 11 of which were selected for key gene selection. Two 2 key genes (SELP and S100A4) were identified using LASSO and SVM-RFE. Finally, SELP was mainly enriched in cell morphogenesis involved in differentiation, cytoplasmic translation, and actin binding of GO terms, and the KEGG pathway including endocytosis, focal adhesion, and platelet activation. S100A4 was mainly enriched in GO terms including mitochondrial inner membrane; mitochondrial respirasome and lysosomal membrane; and the KEGG pathway of oxidative phosphorylation, regulation of actin cytoskeleton, and chemical carcinogenesis-reactive oxygen species. Twenty-two DE-MIRGs-associated inflammation and DNA methylation were identified between patients with ICH and normal controls, and two key genes (SELP and S100A4) were identified and regarded as biomarkers for ICH, which could provide the research foundation for further investigation of the pathological mechanism of ICH.

Asunto(s)

RESUMEN

BACKGROUND: Epilepsy is the second most prevalent neurological disease. Although there are many antiseizure drugs, approximately 30% of cases are refractory to treatment. Temporal lobe epilepsy (TLE) is the most common epilepsy subtype, and previous studies have reported that hippocampal inflammation is an important mechanism associated with the occurrence and development of TLE. However, the inflammatory biomarkers associated with TLE are not well defined. METHODS: In our study, we merged human hippocampus datasets (GSE48350 and GSE63808) through batch correction and generally verified the diagnostic roles of inflammation-related genes (IRGs) and subtype classification according to IRGs in epilepsy through differential expression, random forest, support vector machine, nomogram, subtype classification, enrichment, protein‒protein interaction, immune cell infiltration, and immune function analyses. Finally, we detected the location and expression of inhibitor of metalloproteinase-1 (TIMP1) in epileptic patients and kainic acid-induced epileptic mice. RESULTS: According to the bioinformatics analysis, we identified TIMP1 as the most significant IRG associated with TLE, and we found that TIMP1 was mainly located in cortical neurons and scantly expressed in cortical gliocytes by immunofluorescence staining. We detected decreased expression of TIMP1 by quantitative real-time polymerase chain reaction and western blotting. CONCLUSION: TIMP1, the most significant IRG associated with TLE, might be a novel and promising biomarker to study the mechanism of epilepsy and guide the discovery of new drugs for its treatment.

Asunto(s)

RESUMEN

Background: Aortic dissection (AD) is a life-threatening cardiovascular disease. Pathophysiologically, it has been shown that aortic wall inflammation promotes the occurrence and development of aortic dissection. Thus, the aim of the current research was to determine the inflammation-related biomarkers in AD. Methods: In this study, we conducted differentially expressed genes (DEGs) analysis using the GSE153434 dataset containing 10 type A aortic dissection (TAAD) and 10 normal samples downloaded from the Gene Expression Omnibus (GEO) database. The intersection of DEGs and inflammation-related genes was identified as differential expressed inflammation-related genes (DEIRGs). Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were performed for DEIRGs. We then constructed the protein-protein interaction (PPI) network using the Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) database and identified hub genes using the Cytoscape plugin MCODE. Finally, least absolute shrinkage and selection operator (LASSO) logistic regression was used to construct a diagnostic model. Results: A total of 1728 DEGs were identified between the TAAD and normal samples. Thereafter, 61 DEIRGs are obtained by taking the intersection of DEGs and inflammation-related genes. The GO indicated that DEIRGs were mainly enriched in response to lipopolysaccharide, in response to molecules of bacterial origin, secretory granule membrane, external side of plasma, receptor ligand activity, and signaling receptor activator activity. KEGG analysis indicated that DEIRGs were mainly enriched in cytokine-cytokine receptor interaction, TNF signaling pathway, and proteoglycans in cancer. We identified MYC, SELL, HIF1A, EDN1, SERPINE1, CCL20, IL1R1, NOD2, TLR2, CD69, PLAUR, MMP14, and HBEGF as hub genes using the MCODE plug-in. The ROC indicated these genes had a good diagnostic performance for TAAD. Conclusion: In conclusion, our study identified 13 hub genes in the TAAD. This study will be of significance for the future development of a preventive therapy of TAAD.

RESUMEN

Inflammation is a critical component of tumor progression, and it modifies the tumor microenvironment by various mechanisms. Here, we explore the effect of the inflammatory response on the tumor microenvironment in colorectal cancer (CRC). A prognostic signature consisting of inflammation-related genes (IRGs) was constructed and verified based on the inflammatory response by bioinformatics analysis. IRG risk model was identified as an independent prognostic factor in CRC, and was related to biological processes of extracellular matrix, cell adhesion and angiogenesis. The IRG risk score predicted the clinical benefit of ipilimumab. Weighted correlation network analysis identified TIMP1 as the hub gene of the inflammatory response in the IRG risk model. Coculture experiments with macrophages and CRC cells revealed that TIMP1 promoted macrophage migration, inhibited the expression of M1 markers (CD11C and CD80), and promoted the expression of M2 markers (ARG1 and CD163). TIMP1 promoted the expression of ICAM1 and CCL2 by activating the ERK1/2 signaling pathway to promote macrophage migration and M2-like polarization. These IRGs in the risk model regulated stromal and immune components in the tumor microenvironment and could serve as potential therapeutic targets in CRC. TIMP1 promoted macrophage migration and meditated macrophage M2 polarization by activating ERK1/2/CLAM1 and CCL2.

Asunto(s)

RESUMEN

Background: Coronavirus disease 2019 (COVID-19) and inflammatory bowel disease (IBD) are both caused by a disordered immune response and have direct and profound impacts on health care services. In this study, we implemented transcriptomic and single-cell analysis to detect common molecular and cellular intersections between COVID-19 and IBD that help understand the linkage of COVID-19 to the IBD patients. Methods: Four RNA-sequencing datasets (GSE147507, GSE126124, GSE9686 and GSE36807) from Gene Expression Omnibus (GEO) database are extracted to detect mutual differentially expressed genes (DEGs) for IBD patients with the infection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) to find shared pathways, candidate drugs, hub genes and regulatory networks. Two single-cell RNA sequencing (scRNA-eq) datasets (GSE150728, PRJCA003980) are used to analyze the immune characteristics of hub genes and the proportion of immune cell types, so as to find common immune responses between COVID-19 and IBD. Results: A total of 121 common DEGs were identified among four RNA-seq datasets, and were all involved in the functional enrichment analysis related to inflammation and immune response. Transcription factors-DEGs interactions, miRNAs-DEGs coregulatory networks, and protein-drug interactions were identified based on these datasets. Protein-protein interactions (PPIs) was built and 59 hub genes were identified. Moreover, scRNA-seq of peripheral blood monocyte cells (PBMCs) from COVID-19 patients revealed a significant increase in the proportion of CD14+ monocytes, in which 38 of 59 hub genes were highly enriched. These genes, encoding inflammatory cytokines, were also highly expressed in inflammatory macrophages (IMacrophage) of intestinal tissues of IBD patients. Conclusions: We conclude that COVID-19 may promote the progression of IBD through cytokine storms. The candidate drugs and DEGs-regulated networks may suggest effective therapeutic methods for both COVID-19 and IBD.

Asunto(s)

RESUMEN

BACKGROUND: Inflammation is known to have an intricate relationship with tumorigenesis and tumor progression while it is also closely related to tumor immune microenvironment. Whereas the role of inflammation-related genes (IRGs) in lung squamous carcinoma (LUSC) is barely understood. Herein, we recognized IRGs associated with overall survival (OS), built an IRGs signature for risk stratification and explored the impact of IRGs on immune infiltration landscape of LUSC patients. METHODS: The RNA-sequencing and clinicopathological data of LUSC patients were downloaded from The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) database, which were defined as training and validation cohorts. Cox regression and least absolute shrinkage and selection operator analyses were performed to build an IRG signature. CIBERSORT, microenvironment cell populations-counter and tumor immune dysfunction and rejection (TIDE) algorithm were used to perform immune infiltration analysis. RESULTS: A two-IRG signature consisting of KLF6 and SGMS2 was identified according to the training set, which could categorize patients into two different risk groups with distinct OS. Patients in the low-risk group had more anti-tumor immune cells infiltrated while patient with high-risk had lower TIDE score and higher levels of immune checkpoint molecules expressed. The IRG signature was further identified as an independent prognostic factor of OS. Subsequently, a prognostic nomogram including IRG signature, age, and cancer stage was constructed for predicting individualized OS, whose concordance index values were 0.610 (95% CI: 0.568-0.651) in the training set and 0.652 (95% CI: 0.580-0.724) in validation set. Time-dependent receiver operator characteristic curves revealed that the nomogram had higher prediction accuracy compared with the traditional tumor stage alone. CONCLUSION: The IRG signature was a predictor for patients with LUSC and might serve as a potential indicator of the efficacy of immunotherapy. The nomogram based on the IRG signature showed a relatively good predictive performance in survival.

Asunto(s)

RESUMEN

The occurrence of intestinal diseases such as colon cancer is closely related to the intestinal flora. Lactobacillus fermentum is a gut probiotic that plays an important role in chronic intestinal inflammation and colon cancer. In the current study, we investigated the effect of Lactobacillus fermentum ZS40 on NF-κB signaling pathway of azomethane-dextran sulfate sodium (AOM-DSS) -induced colon cancer in mice. Animals were divided into control group (NC), AOM-DSS-induced model group (CRC), AOM-DSS plus high-dose Lactobacillus fermentum ZS40 (ZS40-H), AOM-DSS plus low-dose Lactobacillus fermentum ZS40 (ZS40-L), AOM-DSS plus Lactobacillus bulgaricus (BLA), and AOM-DSS plus sulfasalazine (SD)-treated group. Observation of animal physiological activity (body weight and defecation), biochemical measurements, histopathological examination of colon tissue, qPCR to evaluate the expression of inflammation-related genes, immunohistochemical analysis of CD34 and CD117, and Western blot analysis of NF-κB signaling pathway were performed. Compared with the CRC group, the ZS40-H, ZS40-L, BLA, and SD groups had decreased levels of colon cancer marker proteins CD34 and CD117, and the number of abnormal colonic lesions observed by colon histology decreased, while the ZS40-H group showed excellent results. In addition, all probiotic interventions showed weight loss effects. The expression of inflammatory stimulators TNF-α and IL-1ß in the probiotic treatment group decreased; the expression of key proteins IκBα and p65 in the NF-κB signaling pathway also decreased, resulting in a decrease in the expression of the target protein Cox-2. Therefore, administration of Lactobacillus fermentum ZS40 as a probiotic can alleviate intestinal inflammation and prevent colon cancer in mice.

RESUMEN

Objective: Inflammation plays an important role in the pathophysiology of ischemic cardiomyopathy (ICM). We aimed to identify potential biomarkers of inflammation-related genes for ICM and build a model based on the potential biomarkers for the diagnosis of ICM. Materials and methods: The microarray datasets and RNA-Sequencing datasets of human ICM were downloaded from the Gene Expression Omnibus database. We integrated 8 microarray datasets via the SVA package to screen the differentially expressed genes (DEGs) between ICM and non-failing control samples, then the differentially expressed inflammation-related genes (DEIRGs) were identified. The least absolute shrinkage and selection operator, support vector machine recursive feature elimination, and random forest were utilized to screen the potential diagnostic biomarkers from the DEIRGs. The potential biomarkers were validated in the RNA-Sequencing datasets and the functional experiment of the ICM rat, respectively. A nomogram was established based on the potential biomarkers and evaluated via the area under the receiver operating characteristic curve (AUC), calibration curve, decision curve analysis (DCA), and Clinical impact curve (CIC). Results: 64 DEGs and 19 DEIRGs were identified, respectively. 5 potential biomarkers (SERPINA3, FCN3, PTN, CD163, and SCUBE2) were ultimately selected. The validation results showed that each of these five potential biomarkers showed good discriminant power for ICM, and their expression trends were consistent with the bioinformatics results. The results of AUC, calibration curve, DCA, and CIC showed that the nomogram demonstrated good performance, calibration, and clinical utility. Conclusion: SERPINA3, FCN3, PTN, CD163, and SCUBE2 were identified as potential biomarkers associated with the inflammatory response to ICM. The proposed nomogram could potentially provide clinicians with a helpful tool to the diagnosis and treatment of ICM from an inflammatory perspective.

RESUMEN

ß-Carotene is converted into vitamin A in the body and can remove reactive oxygen species. However, it is still unclear whether ß-carotene alters the expression levels of inflammation-related genes in macrophages and how this is regulated. In the present study, we investigated whether the administration of ß-carotene under hyperglycemic conditions altered the expression level of inflammation-related genes and whether any observed differences were associated with changes in histone modifications in juvenile macrophage-like THP-1 cells. THP-1 cells (from a human monocytic leukemia cell line) were cultured in low glucose (5 mM), high glucose (25 mM), or high glucose (25 mM) + ß-carotene (5 µM) media for 1 day, and mRNA expression levels of genes related to oxidative stress and inflammation, and histone modifications were determined by mRNA microarray and qRT-PCR analyses, and chromatin immunoprecipitation assays, respectively. The expression of inflammation-related genes, such as IL31RA, CD38, and NCF1B, and inflammation-associated signaling pathway genes, such as ITGAL, PRAM1, and CSF3R, were upregulated by ß-carotene under high-glucose conditions. Under these conditions, histone H3 lysine 4 (K4) demethylation, H3K36 trimethylation, and H3K9 acetylation around the CD38, NCF1B, and ITGAL genes were higher in ß-carotene-treated cells than in untreated cells. Treatment of juvenile macrophage-like THP-1 cells with ß-carotene under these high glucose conditions induced the expression of inflammation-related genes, K9 acetylation, and K4 di- and K36 trimethylation of histone H3 around these genes.

RESUMEN

OBJECTIVE: To investigate the effect of inflammation-related genes on the prognosis of prostate cancer (PCa). METHODS: We downloaded PCa-related clinical data and mRNA sequencing data from the database Cancer Genome Atlas (TCGA) and inflammation-related pathway gene sets from MsigDB. Using univariate regression and LASSO regression analyses, we screened inflammation-related genes for the construction of a prognostic risk model and evaluated the performance of the model in predicting the prognosis of PCa by Kaplan-Meier and ROC analyses. Based on the nomogram, we calculated the risk scores of the patients, divided them into a high-risk and a low-risk group based on the median values of their risk scores, identified differentially expressed genes for enrichment analysis and verified the expression level of SPHK1 in the PCa tissue microarrays by immunohistochemical staining. RESULTS: Totally 19 inflammation-related genes were identified from 172 candidate genes for the construction of the prognostic risk model, including the risk genes CD14, PIK3R5, GABBR1, RELA, IRF7, SCARF1, MSR1, SPHK1, OSM and STAB1, and the protective genes AQP9, LPAR1, ATP2C1, NDP, CXCL6, P2RY2, DCBLD2, PCDH7, and IFNAR1. Kaplan-Meier analysis showed that the patients with high risk scores had a significantly lower recurrence-free survival and a worse prognosis than those with low risk scores. Differentially expressed genes were involved mainly in the activation of inflammatory response pathways. Immunohistochemical results indicated that the expression of SPHK1 was significantly higher in the tumorous than in the normal tissue and increased with the Gleason score. There was a correlation between the SPHK1 expression and envelope invasion. CONCLUSION: The prognostic risk model of inflammation-related genes constructed based on the TCGA database can effectively predict the prognosis of PCa.

Asunto(s)

RESUMEN

Cyclooxygenase 2 (COX2) has been implicated in cancer development and metastasis. We have identified several COX2-regulated inflammation-related genes in human colorectal cancer cells and shown that some of them play important roles in tumor progression. In this work, we have studied the COX2-regulated genes in the mouse colorectal cancer cell line CT26, to find that many are also regulated by COX2 over-expression. On the other hand, we generated a CT26 cell line expressing Gfp and Luciferase, to study tumor growth and metastasis in immunocompetent Balb/c mice. We then collected solid tissue, and blood samples, from healthy and tumor-bearing mice. Using the Parsortix® cell separation system and taking advantage of the fact that the tumor cells expressed Gfp, we were able to identify circulating tumor cells (CTCs) in some of the mice. We compared the mRNA expression levels of Ptgs2 and effector genes in the samples obtained from tumor-bearing or healthy mice, namely, tumor or healthy colon, Ficoll purified buffy coat, and Parsortix-isolated cells to find different patterns between healthy, tumor-bearing mice with or without CTCs. Although for genes like Il15 we did not observe any difference between healthy and tumor-bearing mice in Ficoll or Parsortix samples; others, such as Egr1, Zc3h12a, Klf4, or Nfat5, allowed distinguishing for cancer or CTC presence. Gene expression analysis in Ficoll or Parsortix processed samples, after liquid biopsy, may offer valuable diagnostic and prognostic information and thus should be further studied.

RESUMEN

Microglia, resident myeloid cells of the central nervous system (CNS), act as immune sentinels that contribute to maintenance of physiological homeostasis and respond to any perturbation in CNS. Microglia could be polarized by various stimuli to perform dedicated functions and instigate inflammatory or pro-regenerative responses. Microglia and peripheral macrophages accumulate in glioblastomas (GBMs), malignant brain tumors, but instead of initiating antitumor responses, these cells are polarized to the pro-invasive and immunosuppressive phenotype which persists for a long time and contributes to a "cold" immune microenvironment of GBMs. Molecular mechanisms underlying this long-lasting "microglia memory" are unknown. We hypothesized that this state may rely on epigenetic silencing of inflammation-related genes. In this study, we show that cultured microglia pre-exposed to glioma-conditioned medium (GCM) acquire a "transcriptional memory" and display reduced expression of inflammatory genes after re-stimulation with lipopolysaccharide. Unstimulated microglia have unmethylated DNA and active histone marks at selected gene promoters indicating chromatin accessibility. Adding GCM increases expression and enzymatic activity of histone deacetylases (Hdac), leading to erasure of histone acetylation at tested genes. Later inflammatory genes acquire repressive histone marks (H3K27 trimethylation), which correlates with silencing of their expression. GCM induced genes acquire active histone marks. Hdac inhibitors block GCM-induced changes of histone modifications and restore microglia ability to initiate effective inflammatory responses. Altogether, we show a scenario of distinct histone modifications underlying polarization of microglia by glioma. We demonstrate contribution of epigenetic mechanisms to glioma-induced "transcriptional memory" in microglia resulting in the tumor-supportive phenotype.

Asunto(s)

RESUMEN

The aim of this study is to investigate the protective effect of green tea (GT) against the toxicity of nicotine. BALB/c mice were divided into four groups. Group I received food and water intake ad libidium, Group II received GT solution at a dose of 1 ml/kg body weight orally twice a day via gastric gavage, Group III was injected intraperitoneally with nicotine (2.5 mg/kg) once per day for 4 weeks, and Group IV received both nicotine and GT; GT was introduced using gastric gavage 1 hr before and 1 hr after the nicotine injection. The administration of nicotine altered the cellular antioxidant defense system by inducing inflammation and damage in the tissues of liver, lungs, and kidneys. In addition, nicotine treatment significantly enhanced the expression antioxidant- and inflammation-related genes. There were significant improvements when the nicotine-exposed mice treated with GT. PRACTICAL APPLICATIONS: In this study, it is revealed that the administration of nicotine altered the cellular antioxidant defense system by inducing inflammation manifested by the infiltration of inflammatory cells and damage seen in liver, lungs, and kidneys. GT contributed to the reduction of toxicity of nicotine, probably mediated by free radicals, through downregulation of nicotine-induced upregulated antioxidant- and inflammation-related genes. Never the less, further in depth investigation on characterization of the active constituents of GT responsible for their effect seen here and the mechanism that contributes to the effects seen in this reports is highly demanded. Furthermore, GT extract could be considered as a dietary supplement for the reduction of nicotine toxicity among cigarette smoker.

Asunto(s)