Identification of inflammation-related biomarkers in keloids
Ontology highlight
ABSTRACT:
SUBMITTER: Wang X
PROVIDER: S-EPMC10912164 | biostudies-literature | 2024 Jan
REPOSITORIES: biostudies-literature
Similar Datasets
Project description:The long non-coding RNAs (lncRNAs) regulating encoding transcripts/genes involved in Wnt signalling pathway in keloids is largely unclear. We used a pathway-focused lncRNA microarray to detect the differentiated expression profiles of both lncRNAs and genes involved in Wnt pathway, thus a total of 116 Wnt-targeted genes and 69 Wnt-related lncRNAs aberrantly expressed in keloids were initially identified. A stepwise bioinformatics was further performed to find skin-related lncRNA/gene pairs in Wnt pathway in keloids. Firstly, an lncRNA/gene co-expression network with clustered functional modules was constructed; simultaneously, 114 Wnt-genes regarding to dermis were online enriched using Phenotype Enrichment. Secondly, 17 skin-related keloid-aberrant Wnt-genes were acquired by overlapping the 114 skin-related Wnt-genes with the 116 keloid-aberrant Wnt-genes. Thirdly, after co-expression coefficient of each lncRNA/gene profile being ranked respectively, 11 top co-expressed lncRNAs characterized with the highest co-expression coefficients to the 17 genes were identified. Fourthly, seven of the 11 top co-expressed lncRNAs exhibiting array-detected aberrant expression in keloids, together with their 12 most interactive Wnt-genes, were selected to undergo in-pair intracellularly quantitative PCR validation in keloids. As a result, four lncRNAs including CACNA1G-AS1, HOXA11-AS, LINC00312 and RP11-91I11.1 with their six paired Wnt-genes undergoing both array-and-qPCR as well as lncRNA-and-gene double validation were finally identified as skin-related lncRNA/gene pairs that involved in Wnt signalling pathway in keloids. In conclusion, in-depth exploration on these easily-accessible lncRNAs in keloids might aid to find the novel target on how to maintain highly recurrent tumours benign via Wnt-involved network regulation.
| S-EPMC5470963 | biostudies-literature
Project description:BackgroundStudies have revealed that inflammatory response is relevant to the tetralogy of Fallot (TOF). However, there are no studies to systematically explore the role of the inflammation-related genes (IRGs) in TOF. Therefore, based on bioinformatics, we explored the biomarkers related to inflammation in TOF, laying a theoretical foundation for its in-depth study.MethodsTOF-related datasets (GSE36761 and GSE35776) were downloaded from the Gene Expression Omnibus (GEO) database. The differentially expressed genes (DEGs) between TOF and control groups were identified in GSE36761. And DEGs between TOF and control groups were intersected with IRGs to obtain differentially expressed IRGs (DE-IRGs). Afterwards, the least absolute shrinkage and selection operator (LASSO) and random forest (RF) were utilized to identify the biomarkers. Next, immune analysis was carried out. The transcription factor (TF)-mRNA, lncRNA-miRNA-mRNA, and miRNA-single nucleotide polymorphism (SNP)-mRNA networks were created. Finally, the potential drugs targeting the biomarkers were predicted.ResultsThere were 971 DEGs between TOF and control groups, and 29 DE-IRGs were gained through the intersection between DEGs and IRGs. Next, a total of five biomarkers (MARCO, CXCL6, F3, SLC7A2, and SLC7A1) were acquired via two machine learning algorithms. Infiltrating abundance of 18 immune cells was significantly different between TOF and control groups, such as activated B cells, neutrophil, CD56dim natural killer cells, etc. The TF-mRNA network contained 4 mRNAs, 31 TFs, and 33 edges, for instance, ELF1-CXCL6, CBX8-SLC7A2, ZNF423-SLC7A1, ZNF71-F3. The lncRNA-miRNA-mRNA network was created, containing 4 mRNAs, 4 miRNAs, and 228 lncRNAs. Afterwards, nine SNPs locations were identified in the miRNA-SNP-mRNA network. A total of 21 drugs were predicted, such as ornithine, lysine, arginine, etc.ConclusionsOur findings detected five inflammation-related biomarkers (MARCO, CXCL6, F3, SLC7A2, and SLC7A1) for TOF, providing a scientific reference for further studies of TOF.
| S-EPMC11320004 | biostudies-literature
Project description:ObjectiveInflammation 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 methodsThe 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).Results64 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.ConclusionSERPINA3, 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.
| S-EPMC9445158 | biostudies-literature
Project description:Malaria is one of the most prevalent infectious diseases worldwide with more than 250 million cases and one million deaths each year. One of the well-characterized malarial-related molecules is hemozoin (HZ), which is a dark-brown crystal formed by the parasite and released into the host during the burst of infected red blood cells. HZ has a stimulatory effect on the host immune system such as its ability to induce pro-inflammatory mediators responsible for some of the malaria related clinical symptoms such as fever. However, the host serum proteins interacting with malarial HZ as well as how this interaction modifies its recognition by phagocytes remained elusive. In the actual study, using proteomic liquid chromatographic mass spectrometry (LC-MS/MS) and immunochemical approaches, we compared the serum protein profiles of malaria patients and healthy individuals. Particularly, we utilized the malarial HZ itself to capture serum proteins capable to bind to HZ, enabling us to identify several proteins such as apolipoprotein E (ApoE), serum amyloid A (SAA), gelsolin, complement factor H and fibrinogen that were found to differ among healthy and malaria individual. Of particular interest is LPS binding protein (LBP), which is reported herein for the first time in the context of malaria. LBP is usually produced during innate inflammatory response to gram-negative bacterial infections. The exact role of these biomarkers and acute phase responses in malaria in general and HZ in particular remains to be investigated. The identification of these inflammation-related biomarkers in malaria paves the way to potentially utilize them as diagnostic and therapeutic targets.
| S-EPMC3197653 | biostudies-literature
Project description:BackgroundMembranous nephropathy (MN) is an autoimmune glomerular disease that is predominantly mediated by immune complex deposition and complement activation. The aim of this study was to identify key biomarkers of MN and investigate their association with immune-related mechanisms, inflammatory cytokines, chemokines and chemokine receptors (CCRs).MethodsMN cohort microarray expression data were downloaded from the GEO database. Differentially expressed genes (DEGs) in MN were identified, and hub genes were determined using a protein-protein interaction (PPI) network. The relationships between immune-related hub genes, immune cells, CCRs, and inflammatory cytokines were examined using immune infiltration analysis, gene set enrichment analysis (GSEA), and weighted gene co-expression network analysis (WGCNA). Finally, the immune-related hub genes in MN were validated using ELISA.ResultsIn total, 501 DEGs were identified. Enrichment analysis revealed the involvement of immune- and cytokine-related pathways in MN progression. Using WGCNA and immune infiltration analysis, 2 immune-related hub genes (CYBB and CSF1R) were identified. These genes exhibited significant correlations with a wide range of immune cells and were found to participate in B cell/T cell receptor and chemokine signaling pathways. In addition, the expressions of 2 immune-related hub genes were positively correlated with the expression of CCR1, CX3CR1, IL1B, CCL4, TNF, and CCR2.ConclusionOur study identified CSF1 and CYBB as immune-related hub genes that potentially influence the expression of CCRs and pro-inflammatory cytokines (CCR1, CX3CR1, IL1B, CCL4, TNF, and CCR2). CSF1 and CYBB may be potential biomarkers for MN progression, providing a perspective for diagnostic and immunotherapeutic targets of MN.
| S-EPMC10590909 | biostudies-literature
Project description:Evidence from past research has shown that DNA methylation plays a key role in the pathogenesis of periodontitis, regulating gene expression levels and thereby affecting the occurrence of various diseases. Three sample sets of methylation data and gene expression data were downloaded from Gene Expression Omnibus (GEO) database. A diagnostic classifier is established based on gene expression data and CpG methylation data. Abnormal expression of immune-related pathways and methyltransferase-related genes in patients with periodontitis was detected. A total of 8,029 differentially expressed CpG (DMP) was annotated to the promoter region of 4,940 genes, of which 295 immune genes were significantly enriched. The CpG sites of 23 differentially co-expressed immune gene promoter regions were identified, and 13 CpG were generally hypermethylated in healthy group samples, while some were methylated in most patients. Five CpGs were screened as robust periodontitis biomarkers. The accuracy in the training data set, the two external verification data sets, and in the transcriptome was 95.5%, 80% and 78.3%, and 82.6%, respectively. This study provided new features for the diagnosis of periodontitis, and contributed to the personalized treatment of periodontitis.
| S-EPMC8386560 | biostudies-literature
Project description:Systems vaccinology approaches have been used successfully to define early signatures of the vaccine-induced immune response. However, the possibility that transcriptomics can also identify a correlate or surrogate for vaccine inflammation has not been fully explored. We have compared four licensed vaccines with known safety profiles, as well as three agonists of Toll-like receptors (TLRs) with known inflammatory potential, to elucidate the transcriptomic profile of an acceptable response to vaccination versus that of an inflammatory reaction. In mice, we looked at the transcriptomic changes in muscle at the injection site, the lymph node that drained the muscle, and the peripheral blood mononuclear cells (PBMCs)isolated from the circulating blood from 4 hr after injection and over the next week. A detailed examination and comparative analysis of these transcriptomes revealed a set of novel biomarkers that are reflective of inflammation after vaccination. These biomarkers are readily measurable in the peripheral blood, providing useful surrogates of inflammation, and provide a way to select candidates with acceptable safety profiles.
| S-EPMC6555592 | biostudies-literature
Project description:Keloids result from abnormal proliferative scar formation with scar tissue expanding beyond the margin of the original wound and are mostly found in individuals of sub-Saharan African descent. The etiology of keloids has not been resolved but previous studies suggest that keloids are a genetically heterogeneous disorder. Although possible candidate genes have been suggested by genome-wide association studies using common variants, by upregulation in keloids or their involvement in syndromes that include keloid formation, rare coding variants that contribute to susceptibility in non-syndromic keloid formation have not been previously identified. Through analysis of whole-genome data we mapped a locus to chromosome 8p23.3-p21.3 with a statistically significant maximum multipoint LOD score of 4.48. This finding was followed up using exome sequencing and led to the identification of a c.1202T>C (p.(Leu401Pro)) variant in the N-acylsphingosine amidohydrolase (ASAH1) gene that co-segregates with the keloid phenotype in a large Yoruba family. ASAH1 is an acid ceramidase known to be involved in tumor formation by controlling the ratio of ceramide and sphingosine. ASAH1 is also involved in cell proliferation and inflammation, and may affect the development of keloids via multiple mechanisms. Functional studies need to clarify the role of the ASAH1 variant in wound healing.
| S-EPMC5602022 | biostudies-literature
Project description:Effective biomarkers for multiple sclerosis diagnosis, assessment of prognosis, and treatment responses, in particular those measurable in blood, are largely lacking. We have investigated a broad set of protein biomarkers in cerebrospinal fluid (CSF) and plasma using a highly sensitive proteomic immunoassay. Cases from two independent cohorts were compared with healthy controls and patients with other neurological diseases. We identified and replicated 10 cerebrospinal fluid proteins including IL-12B, CD5, MIP-1a, and CXCL9 which had a combined diagnostic efficacy similar to immunoglobulin G (IgG) index and neurofilament light chain (area under the curve [AUC] = 0.95). Two plasma proteins, OSM and HGF, were also associated with multiple sclerosis in comparison to healthy controls. Sensitivity and specificity of combined CSF and plasma markers for multiple sclerosis were 85.7% and 73.5%, respectively. In the discovery cohort, eotaxin-1 (CCL11) was associated with disease duration particularly in patients who had secondary progressive disease (P CSF < 4 × 10-5, P plasma < 4 × 10-5), and plasma CCL20 was associated with disease severity (P = 4 × 10-5), although both require further validation. Treatment with natalizumab and fingolimod showed different compartmental changes in protein levels of CSF and peripheral blood, respectively, including many disease-associated markers (e.g., IL12B, CD5) showing potential application for both diagnosing disease and monitoring treatment efficacy. We report a number of multiple sclerosis biomarkers in CSF and plasma for early disease detection and potential indicators for disease activity. Of particular importance is the set of markers discovered in blood, where validated biomarkers are lacking.
| S-EPMC7293699 | biostudies-literature
Project description:BackgroundThe pathophysiology of keloids is complex, and the treatment for keloids is still an unmet medical need. Our study is aimed at identifying the hub genes among the differentially expressed genes (DEGs) between normal skin tissue and keloids and key pathways in the development of keloids.Materials and methodsWe downloaded the GSE92566 and GSE90051 microarray data, which contain normal skin tissue and keloid gene expression data. GSE92566 was treated as a discovery dataset for summarizing the significantly DEGs, and GSE90051 served as a validation dataset. Gene Ontology, Kyoto Encyclopedia of Genes and Genomes pathway, Reactome enrichment analysis, gene set enrichment analysis, and gene set variation analysis were performed for the key functions and pathways enriched in DEGs. Moreover, we also validated the hub genes identified from the protein-protein interaction network and predicted miRNA-hub gene interactions.Results117 downregulated DEGs and 204 upregulated DEGs in GSE92566 were identified. Extracellular and collagen-related pathways were prominent in upregulated DEGs, while the keratinization-related pathway was associated with downregulated DEGs. The hub genes included COL5A1, COL5A2, and SERPINH1, which were also validated in GSE90051.ConclusionThis study identified several hub genes and provided insights for the underlying pathways and miRNA-hub gene interactions for keloid development through bioinformatic analysis of two microarray datasets. Additionally, our results would support the development of future therapeutic strategies.
| S-EPMC8009712 | biostudies-literature