An Oxidative Stress-Related Gene Pair (CCNB1/PKD1), Competitive Endogenous RNAs, and Immune-Infiltration Patterns Potentially Regulate Intervertebral Disc Degeneration Development

A diagnostic signatures for intervertebral disc degeneration using TNFAIP6 and COL6A2 based on single-cell RNA-seq and bulk RNA-seq analyses

OBJECTIVES

Intervertebral disc degeneration (IVDD) is a prevalent degenerative condition associated with a high incidence rate of low back pain and disability. This study aimed to identify potential biomarkers and signaling pathways associated with IVDD.

METHODS

Biomarkers were discerned through bulk-RNA and single-cell RNA sequencing (scRNA-Seq) investigations of IVDD cases from the Gene Expression Omnibus (GEO) database. Following this, two central genes were identified. Furthermore, gene set enrichment analysis (GSEA) and receiver operating characteristic (ROC) curve analysis were conducted. The transcriptional factor (TF) derived from nucleus pulposus (NP) cells was examined through the DoRothEA R package. RT-qPCR and IHC techniques were employed to confirm the expression of the two hub genes and their associated genes in tissue samples.

RESULTS

The proteins Tumor necrosis factor-inducible gene 6 protein (TNFAIP6) and collagen VI-α2 (COL6A2) were frequently analyzed using a combination of DEGs from datasets GSE70362, GSE124272, and scRNA-seq. Examination of gene expression across multiple datasets indicated significant differences in TNFAIP6 and COL6A2 levels in IVDD compared to control or normal groups (p < 0.05). These two central genes demonstrated strong diagnostic utility in the training cohort and reliable predictive value in the validation datasets. Our study verified the potential role of ZEB2 as a TF in regulating two key genes associated with IVDD. Furthermore, qPCR and IHC confirmed elevated expression levels of the hub genes and transcription factor.

CONCLUSION

We identified biomarkers, specifically TNFAIP6 and COL6A2, that have the potential to predict disease activity and aid in the diagnosis of IVDD.

Association between the composite dietary antioxidant index and all-cause mortality in individuals with osteoarthritis via NHANES data

The impact of antioxidant intake on the prognosis of osteoarthritis (OA) patients remains unclear. The aim of this study was to investigate the relationship between the composite dietary antioxidant index (CDAI) and all-cause mortality in OA patients. A total of 35,590 participants with OA from the National Health and Nutrition Examination Survey (1999-2020) were included in this study. We analysed the associations between the CDAI and the risk of all-cause mortality in OA patients via a multivariate Cox regression model. Restricted cubic spline regression was used to investigate the dose-response associations between the CDAI and mortality. We also conducted stratified analyses and interaction tests to explore underlying effect modification. After multivariable adjustment, each one-unit increase in the CDAI was associated with a 2.1% reduction in the risk of mortality. Compared with those in the low CDAI group, the multivariate-adjusted hazard ratios (HRs) for mortality for patients in the high CDAI group were lower [Model 1 (HR 0.648, 95% CI 0.557-0.754), Model 2 (HR 0.739, 95% CI 0.627-0.871), and Model 3 (HR 0.788, 95% CI 0.661-0.941)]. We observed a negative nonlinear relationship between the CDAI and all-cause mortality (P < 0.05). Stratification analyses and interaction tests confirmed the robustness of the results. We found a negative nonlinear relationship between the CDAI and all-cause mortality in OA patients. A higher CDAI was significantly associated with a lower risk of mortality. These results highlight the potential advantages of monitoring and evaluating the CDAI status in preventing mortality among patients with OA.

Machine learning-based diagnostic model of lymphatics-associated genes for new therapeutic target analysis in intervertebral disc degeneration

Background

Low back pain resulting from intervertebral disc degeneration (IVDD) represents a significant global social problem. There are notable differences in the distribution of lymphatic vessels (LV) in normal and pathological intervertebral discs. Nevertheless, the molecular mechanisms of lymphatics-associated genes (LAGs) in the development of IVDD remain unclear. An in-depth exploration of this area will help to reveal the biological and clinical significance of LAGs in IVDD and may lead to the search for new therapeutic targets for IVDD.

Methods

Data sets were obtained from the Gene Expression Omnibus (GEO) database. Following quality control and normalization, the datasets (GSE153761, GSE147383, and GSE124272) were merged to form the training set, with GSE150408 serving as the validation set. LAGs from GeneCards, MSigDB, Gene Ontology, and KEGG database. The Venn diagram was employed to identify differentially expressed lymphatic-associated genes (DELAGs) that were differentially expressed in the normal and IVDD groups. Subsequently, four machine learning algorithms (SVM-RFE, Random Forest, XGB, and GLM) were used to select the method to construct the diagnostic model. The receiver operating characteristic (ROC) curve, nomogram, and Decision Curve Analysis (DCA) were used to evaluate the model effect. In addition, we constructed a potential drug regulatory network and competitive endogenous RNA (ceRNA) network for key LAGs.

Results

A total of 15 differentially expressed LAGs were identified. By comparing four machine learning methods, the top five genes of importance in the XGB model (MET, HHIP, SPRY1, CSF1, TOX) were identified as lymphatics-associated gene diagnostic signatures. This signature was used to predict the diagnosis of IVDD with strong accuracy and an area under curve (AUC) value of 0.938. Furthermore, the diagnostic model was validated in an external dataset (GSE150408), with an AUC value of 0.772. The nomogram and DCA further prove that the diagnosis model has good performance and predictive value. Additionally, drug regulatory networks and ceRNA networks were constructed, revealing potential therapeutic drugs and post-transcriptional regulatory mechanisms.

Conclusion

We developed and validated a lymphatics-associated genes diagnostic model by machine learning algorithms that effectively identify IVDD patients. These five key LAGs may be potential therapeutic targets for IVDD patients.

New perspectives on YTHDF2 O-GlcNAc modification in the pathogenesis of intervertebral disc degeneration

This study investigates the potential molecular mechanisms by which O-GlcNAc modification of YTHDF2 regulates the cell cycle and participates in intervertebral disc degeneration (IDD). We employed transcriptome sequencing to identify genes involved in IDD and utilized bioinformatics analysis to predict key disease-related genes. In vitro mechanistic validation was performed using mouse nucleus pulposus (NP) cells. Changes in reactive oxygen species (ROS) and cell cycle were assessed through flow cytometry and CCK-8 assays. An IDD mouse model was also established for in vivo mechanistic validation, with changes in IDD severity measured using X-rays and immunohistochemical staining. Bioinformatics analysis revealed differential expression of YTHDF2 in NP cells of normal and IDD mice, suggesting its potential as a diagnostic gene for IDD. In vitro cell experiments demonstrated that YTHDF2 expression and O-GlcNAcylation were reduced in NP cells under H2O2 induction, leading to inhibition of the cell cycle through decreased stability of CCNE1 mRNA. Further, in vivo animal experiments confirmed a decrease in YTHDF2 expression and O-GlcNAcylation in IDD mice, while overexpression or increased O-GlcNAcylation of YTHDF2 promoted CCNE1 protein expression, thereby alleviating IDD pathology. YTHDF2 inhibits its degradation through O-GlcNAc modification, promoting the stability of CCNE1 mRNA and the cell cycle to prevent IDD formation.

Cyclin B1: A potential prognostic and immunological biomarker in pan-cancer

Cyclin B1 (CCNB1) encodes a regulatory protein essential for the regulation of cell mitosis, particularly in controlling the G2/M transition phase of the cell cycle. Current research has implicated CCNB1 in the progression of various types of cancer, including gastric cancer, breast cancer, and non-small cell lung cancer. In this study, we conducted a pan-cancer analysis of CCNB1 to investigate its prognostic significance and immunological aspects. Our comprehensive investigation covered a wide range of analyses, including gene expression, promoter methylation, genetic alterations, immune infiltration, immune regulators, and enrichment studies. We utilized multiple databases and tools for this purpose, such as The Cancer Genome Atlas (TCGA), the Genotype-Tissue Expression (GTEx) project, the Human Protein Atlas (HPA), the University of Alabama at Birmingham CANcer data analysis Portal (UALCAN), the Gene Expression Profiling Interactive Analysis (GEPIA), the DNA Methylation Interactive Visualization Database (DNMIVD), the Search Tool for the Retrieval of Interacting Genes/Proteins (STRING), Sangerbox, and cBioPortal. Data analyses were executed using GraphPad Prism software, R software, and various online tools. Our findings demonstrated a significant increase in CCNB1 expression across 28 cancer types. Elevated CCNB1 expression correlated with decreased overall survival (OS) in 11 cancer types and disease-free survival (DFS) in 12 cancer types. Additionally, DNA promoter methylation levels were significantly decreased in 14 cancer types. Furthermore, the study verified a significant association between CCNB1 expression and immune infiltration, immune modulators, microsatellite instability (MSI), and tumor mutational burden (TMB). Enrichment analysis indicated that CCNB1 is involved in multiple cellular pathways. Collectively, our results suggested that CCNB1 has the potential to serve as a valuable prognostic biomarker and may be a promising target for immunotherapy in various cancer types.

Bioinformatics Research and qRT-PCR Verify Hub Genes and a Transcription Factor-MicroRNA Feedback Network in Intervertebral Disc Degeneration

The present study explores the potentials of bioinformatics analysis to identify hub genes linked to intervertebral disc degeneration (IDD) and explored the potential molecular mechanism of transcription factor-microRNA regulatory network. Furthermore, the hub genes were identified through quantitative reverse transcriptase PCR (qRT-PCR). GEO database expression profile datasets for candidate genes (GSE124272) were downloaded. Genes that were differentially expressed (DEGs) were detected utilizing limma technique in the R programming language. Search Tool for the Retrieval of Interacting Genes/Proteins and NetworkAnalyst software identified hub genes. The Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis as well as Gene Ontology annotation of the DEGs were performed using Metascape. Using Bioinformatics data from the TRRUST, StarBase, and TransmiR databases, a TF-miRNA-hub genes network was constructed. qRT-PCR was utilized to confirm the result. As compared to healthy persons, 521 DEGs, comprising 203 down-regulated and 318 up-regulated genes, as well as 7 core genes, were found in people with IDD. Analysis revealed that all seven essential genes were under-expressed. qRT-PCR further confirmed the low expression of these seven important genes. Based on the TRRUST database, 16 TFs that could target five junction genes were then predicted. According to the StarBase database, four miRNAs were linked to crucial genes, while the TransmiR database predicted regulatory connections between four miRNAs and five TFs. The expression of the TP53-(hsa-miR-183-5p)-CCNB1 TF-miRNA-mRNA interaction network was discovered to be correlated with IDD. Throughout this investigation, a network of TF-miRNA-mRNA connections was built for investigation of the probable molecular mechanisms responsible for IDD. The identification of hub genes associated with IDD may reveal promising IDD treatment strategies.

Integrated analysis and validation of ferroptosis-related genes and immune infiltration in acute myocardial infarction

BACKGROUND

Acute myocardial infarction (AMI) is indeed a significant cause of mortality and morbidity in individuals with coronary heart disease. Ferroptosis, an iron-dependent cell death, is characterized by the accumulation of intracellular lipid peroxides, which is implicated in cardiomyocyte injury. This study aims to identify biomarkers that are indicative of ferroptosis in the context of AMI, and to examine their potential roles in immune infiltration.

METHODS

Firstly, the GSE59867 dataset was used to identify differentially expressed ferroptosis-related genes (DE-FRGs) in AMI. We then performed gene ontology (GO) and functional enrichment analysis on these DE-FRGs. Secondly, we analyzed the GSE76591 dataset and used bioinformatic methods to build ceRNA networks. Thirdly, we identified hub genes in protein-protein interaction (PPI) network. After obtaining the key DE-FRGs through the junction of hub genes with ceRNA and least absolute shrinkage and selection operator (LASSO). ImmucellAI was applied to estimate the immune cell infiltration in each sample and examine the relationship between key DE-FRGs and 24 immunocyte subsets. The diagnostic performance of these genes was further evaluated using the receiver operating characteristic (ROC) curve analysis. Ultimately, we identified an immune-related ceRNA regulatory axis linked to ferroptosis in AMI.

RESULTS

Among 56 DE-FRGs identified in AMI, 41 of them were integrated into the construction of competitive endogenous RNA (ceRNA) networks. TLR4 and PIK3CA were identified as key DE-FRGs and PIK3CA was confirmed as a diagnostic biomarker for AMI. Moreover, CD4_native cells, nTreg cells, Th2 cells, Th17 cells, central-memory cells, effector-memory cells, and CD8_T cells had higher infiltrates in AMI samples compared to control samples. In contrast, exhausted cells, iTreg cells, and Tfh cells had lower infiltrates in AMI samples. Spearman analysis confirmed the correlation between 24 immune cells and PIK3CA/TLR4. Ultimately, we constructed an immune-related regulatory axis involving XIST and OIP5-AS1/miR-216a/PIK3CA.

CONCLUSION

Our comprehensive analysis has identified PIK3CA as a robust and promising biomarker for this condition. Moreover, we have also identified an immune-related regulatory axis involving XIST and OIP5-AS1/miR-216a/PIK3CA, which may play a key role in regulating ferroptosis during AMI progression.

Investigating the ID3/SLC22A4 as immune-related signatures in ischemic stroke

BACKGROUND

Ischemic stroke (IS) is a fearful disease that can cause a variety of immune events. Nevertheless, precise immune-related mechanisms have yet to be systematically elucidated. This study aimed to identify immune-related signatures using machine learning and to validate them with animal experiments and single cell analysis.

METHODS

In this study, we screened 24 differentially expressed genes (DEGs) while identifying immune-related signatures that may play a key role in IS development through a comprehensive strategy between least absolute shrinkage and selection operation (LASSO) regression, support vector machine (SVM) and immune-related genes. In addition, we explored immune infiltration using the CIBERSORT algorithm. Finally, we performed validation in mouse brain tissue and single cell analysis.

RESULTS

We identified 24 DEGs for follow-up analysis. ID3 and SLC22A4 were finally identified as the better immune-related signatures through a comprehensive strategy among DEGs, LASSO, SVM and immune-related genes. RT-qPCR, western blot, and immunofluorescence revealed a significant decrease in ID3 and a significant increase in SLC22A4 in the middle cerebral artery occlusion group. Single cell analysis revealed that ID3 was mainly concentrated in endothelial_2 cells and SLC22A4 in astrocytes in the MCAO group. A CIBERSORT finds significantly altered levels of immune infiltration in IS patients.

CONCLUSIONS

This study focused on immune-related signatures after stroke and ID3 and SLC22A4 may be new therapeutic targets to promote functional recovery after stroke. Furthermore, the association of ID3 and SLC22A4 with immune cells may be a new direction for post-stroke immunotherapy.

Mitochondrial Lipid Metabolism Genes as Diagnostic and Prognostic Indicators in Hepatocellular Carcinoma

Background

Due to the heterogeneity of Hepatocellular carcinoma (HCC), there is an urgent need for reliable diagnosis and prognosis. Mitochondria-mediated abnormal lipid metabolism affects the occurrence and progression of HCC.

Objective

This study aims to investigate the potential of mitochondrial lipid metabolism (MTLM) genes as diagnostic and independent prognostic biomarkers for HCC.

Methods

MTLM genes were screened from the Gene Expression Omnibus (GEO) and Gene Set Enrichment Analysis (GSEA) databases, followed by an evaluation of their diagnostic values in both The Cancer Genome Atlas Program (TCGA) and the Affiliated Cancer Hospital of Guangxi Medical University (GXMU) cohort. The TCGA dataset was utilized to construct a gene signature and investigate the prognostic significance, immune infiltration, and copy number alterations. The validity of the prognostic signature was confirmed through GEO, International Cancer Genome Consortium (ICGC), and GXMU cohorts.

Results

The diagnostic receiver operating characteristic (ROC) curve revealed that eight MTLM genes have excellent diagnostic of HCC. A prognostic signature comprising 5 MTLM genes with robust predictive value was constructed using the lasso regression algorithm based on TCGA data. The results of the Stepwise regression model showed that the combination of signature and routine clinical parameters had a higher area under the curve (AUC) compared to a single risk score. Further, a nomogram was constructed to predict the survival probability of HCC, and the calibration curves demonstrated a perfect predictive ability. Finally, the risk score also unveiled the different immune and mutation statuses between the two different risk groups.

Conclusion

MTLT-related genes may serve as diagnostic and prognostic biomarkers for HCC as well as novel therapeutic targets, which may be beneficial for facilitating further understanding the molecular pathogenesis and providing potential therapeutic strategies for HCC.

GREM1, LRPPRC and SLC39A4 as potential biomarkers of intervertebral disc degeneration: a bioinformatics analysis based on multiple microarray and single-cell sequencing data

BACKGROUND

Low back pain (LBP) has drawn much widespread attention and is a major global health concern. In this field, intervertebral disc degeneration (IVDD) is frequently the focus of classic studies. However, the mechanistic foundation of IVDD is unclear and has led to conflicting outcomes.

METHODS

Gene expression profiles (GSE34095, GSE147383) of IVDD patients alongside control groups were analyzed to identify differentially expressed genes (DEGs) in the GEO database. GSE23130 and GSE70362 were applied to validate the yielded key genes from DEGs by means of a best subset selection regression. Four machine-learning models were established to assess their predictive ability. Single-sample gene set enrichment analysis (ssGSEA) was used to profile the correlation between overall immune infiltration levels with Thompson grades and key genes. The upstream targeting miRNAs of key genes (GSE63492) were also analyzed. A single-cell transcriptome sequencing data (GSE160756) was used to define several cell clusters of nucleus pulposus (NP), annulus fibrosus (AF), and cartilaginous endplate (CEP) of human intervertebral discs and the distribution of key genes in different cell clusters was yielded.

RESULTS

By developing appropriate p-values and logFC values, a total of 6 DEGs was obtained. 3 key genes (LRPPRC, GREM1, and SLC39A4) were validated by an externally validated predictive modeling method. The ssGSEA results indicated that key genes were correlated with the infiltration abundance of multiple immune cells, such as dendritic cells and macrophages. Accordingly, these 4 key miRNAs (miR-103a-3p, miR-484, miR-665, miR-107) were identified as upstream regulators targeting key genes using the miRNet database and external GEO datasets. Finally, the spatial distribution of key genes in AF, CEP, and NP was plotted. Pseudo-time series and GSEA analysis indicated that the expression level of GREM1 and the differentiation trajectory of NP chondrocytes are generally consistent. GREM1 may mainly exacerbate the degeneration of NP cells in IVDD.

CONCLUSIONS

Our study gives a novel perspective for identifying reliable and effective gene therapy targets in IVDD.

MAPK8 and CAPN1 as potential biomarkers of intervertebral disc degeneration overlapping immune infiltration, autophagy, and ceRNA

Background

Intervertebral disc degeneration (IDD) is one of the most common health problems in the elderly and a major causative factor in low back pain (LBP). An increasing number of studies have shown that IDD is closely associated with autophagy and immune dysregulation. Therefore, the aim of this study was to identify autophagy-related biomarkers and gene regulatory networks in IDD and potential therapeutic targets.

Methods

We obtained the gene expression profiles of IDD by downloading the datasets GSE176205 and GSE167931 from the Gene Expression Omnibus (GEO) public database. Subsequently, differentially expressed genes (DEGs) analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis, gene ontology (GO), and gene set enrichment analysis (GSEA) were performed to explore the biological functions of DEGs. Differentially expressed autophagy-related genes (DE-ARGs) were then crossed with the autophagy gene database. The hub genes were screened using the DE-ARGs protein-protein interaction (PPI) network. The correlation between the hub genes and immune infiltration and the construction of the gene regulatory network of the hub genes were confirmed. Finally, quantitative PCR (qPCR) was used to validate the correlation of hub genes in a rat IDD model.

Results

We obtained 636 DEGs enriched in the autophagy pathway. Our analysis revealed 30 DE-ARGs, of which six hub genes (MAPK8, CTSB, PRKCD, SNCA, CAPN1, and EGFR) were identified using the MCODE plugin. Immune cell infiltration analysis revealed that there was an increased proportion of CD8+ T cells and M0 macrophages in IDD, whereas CD4+ memory T cells, neutrophils, resting dendritic cells, follicular helper T cells, and monocytes were much less abundant. Subsequently, the competitive endogenous RNA (ceRNA) network was constructed using 15 long non-coding RNAs (lncRNAs) and 21 microRNAs (miRNAs). In quantitative PCR (qPCR) validation, two hub genes, MAPK8 and CAPN1, were shown to be consistent with the bioinformatic analysis results.

Conclusion

Our study identified MAPK8 and CAPN1 as key biomarkers of IDD. These key hub genes may be potential therapeutic targets for IDD.

Glutathione peroxidase 3 is a novel clinical diagnostic biomarker and potential therapeutic target for neutrophils in rheumatoid arthritis

BACKGROUND

Neutrophils have a critical role in the pathogenesis of rheumatoid arthritis (RA) with immune system dysfunction. However, the molecular mechanisms of this process mediated by neutrophils still remain elusive. The purpose of the present study is to identify hub genes in neutrophils for diagnosis and treatment of RA utilizing publicly available datasets.

METHODS

Gene expression profiles were downloaded from the Gene Expression Omnibus, and batch-corrected and normalized expression data were obtained using the ComBat package. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analysis were used to conduct significantly functional analysis and crucial pathways. The resulting co-expression genes modules and hub genes were generated based on the weighted gene co-expression network analysis and visualization by Cytoscape. Flow cytometry was conducted to detect reactive oxygen species (ROS) levels in neutrophils.

RESULTS

Neutrophils underwent transcriptional changes in synovial fluid (SF) of RA patients, different from peripheral blood of healthy controls or patients with RA. Especially, glycolysis, HIF-1 signaling, NADH metabolism, and oxidative stress were affected. These hub genes were strongly linked with classical glycolysis-related genes (ENO1, GAPDH, and PKM) responsible for ROS production. The antioxidant enzyme glutathione peroxidase 3 (GPX3), a ROS scavenger, was first identified as a hub gene in RA neutrophils. Neutrophils from patients with autoinflammatory and autoimmune diseases had markedly enhanced ROS levels, most notably in RA SF.

CONCLUSION

This research recognized hub genes and explored the characteristics of neutrophils in RA. Our findings suggest that the novel hub gene GPX3 is involved in the neutrophil-driven oxidative stress-mediated pathogenesis of RA. It has the potency to be a target for neutrophil-directed RA therapy.

Tempol modulates lncRNA-miRNA-mRNA ceRNA networks in ovaries of DHEA induced PCOS rats

Polycystic ovary syndrome (PCOS) is one of the most common endocrine and metabolic disorders in reproductive age women. Our previous results demonstrated that tempol was able to ameliorate PCOS phenotype in rats. However, the exact pathophysiological effect of tempol on PCOS remains largely unknown. To extend this research, deep RNA-sequencing was performed to investigate the long noncoding RNA (lncRNA) associated ceRNA mechanisms in the ovarian tissues of control rats, dehydropiandrosterone (DHEA) induced PCOS rats and tempol treated PCOS rats. Our results identified total 164, 79, and 914 significantly dysregulated lncRNAs, miRNAs, and mRNAs in three groups, respectively. The total of 7 lncRNAs, 8 mRNAs and 5 miRNAs were involved in lncRNA-associated ceRNA networks were constructed. Among them, mRNAs including C1qtnf1, Dipk2a, IL4r and lncRNAs including MSTRG.16751.2, MSTRG.8065.2 had high RNA connectivity in the ceRNA network, which also showed significant alterations in these three groups by using qPCR validation. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses revealed that the involvement of the identified ceRNA networks in regulating the development of PCOS from distinct origins, such as metabolic pathway, immune cell differentiation. The study presents the first systematic dissection of lncRNA-associated ceRNA profiles in tempol treated PCOS rats. The identified ceRNA networks could provide insights that help facilitate PCOS diagnosis and treatment.

A novel chromatin regulator signature predicts the prognosis, clinical features and immunotherapy of colon cancer

Aim: To elucidate the potential function and prognostic value of chromatin regulators (CRs) in colon cancer. Materials & methods: A comprehensive analysis of CR RNA expression data from public databases was conducted. Results: The authors successfully established and validated a 17 CR-based signature using public databases. Ten CRs of the signature were eventually verified at the protein level using the Human Protein Atlas database. Functional enrichment showed that CRs were significantly enriched in cancer-related pathways. This signature was remarkably relevant to immune cell infiltration, immune checkpoints, tumor immune dysfunction and exclusion (TIDE) score and drug sensitivity. Conclusion: The authors identified a novel, reliable prognostic signature for colon cancer. The study provided new insights into the function of CRs and has important clinical implications for immunotherapy for colon cancer.

Comprehensive analysis of potential ceRNA network and immune cell infiltration in intervertebral disc degeneration

Background

Intervertebral disc degeneration (IDD) has become a serious public health problem, the mechanism of which is complex and still unclear. We aimed to construct a ceRNA network related to IDD to explore its pathogenesis.

Methods

We downloaded the GSE67566, GSE63492, GSE116726 and GSE124272 datasets from GEO database, and obtained the differentially expressed RNAs. Then, we constructed a ceRNA network and the KEGG and GO enrichment analysis were performed. Finally, we performed immune cell infiltration analysis on the GSE124272 dataset and analysed the correlation between immune cell abundance and hub genes expression levels.

Results

The ceRNA network included three down-regulated circRNAs: hsa_circ_0074817, hsa_circ_0002702, hsa_circ_0003600, three up-regulated miRNAs: hsa-miR-4741, hsa-miR-3158-5p, hsa-miR-508-5p, and 57 down-regulated mRNAs, including six hub genes: IGF1, CHEK1, CCNB1, OIP5, BIRC5, AR. GO and KEGG analysis revealed that the network is involved in various biological functions. Immune infiltration analysis showed that IDD was closely related to immune cell infiltration, and hub genes could further affect the development of IDD by affecting immune cell infiltration.

Conclusion

This study identified the hsa_circ_0074817-hsa-miR-508-5p-IGF1/CHEK1/CCNB1, the hsa_circ_0003600-hsa-miR-4741-BIRC5/OIP5/AR and the hsa_circ_0002702-hsa-miR-3158-5p-IGF1/AR as important regulatory axis of IDD, which will help us gain further insight into the pathogenesis of IDD and determine potential therapeutic targets.

Non-coding RNAs as potential biomarkers and therapeutic targets in polycystic kidney disease

Polycystic kidney disease (PKD) is a significant cause of end-stage kidney failure and there are few effective drugs for treating this inherited condition. Numerous aberrantly expressed non-coding RNAs (ncRNAs), particularly microRNAs (miRNAs), may contribute to PKD pathogenesis by participating in multiple intracellular and intercellular functions through post-transcriptional regulation of protein-encoding genes. Insights into the mechanisms of miRNAs and other ncRNAs in the development of PKD may provide novel therapeutic strategies. In this review, we discuss the current knowledge about the roles of dysregulated miRNAs and other ncRNAs in PKD. These roles involve multiple aspects of cellular function including mitochondrial metabolism, proliferation, cell death, fibrosis and cell-to-cell communication. We also summarize the potential application of miRNAs as biomarkers or therapeutic targets in PKD, and briefly describe strategies to overcome the challenges of delivering RNA to the kidney, providing a better understanding of the fundamental advances in utilizing miRNAs and other non-coding RNAs to treat PKD.

Experimental verification and validation of immune biomarkers based on chromatin regulators in ischemic stroke

Ischemic stroke (IS) is a disease characterized by rapid progression and high mortality and disability rates. Its pathophysiological process is inseparable from immune dysfunction. Recently, chromatin regulators (CRs) have been described as a class of enzymes that can recognize, form, and maintain the epigenetic state of an organism, and are closely associated with immune regulation. Nevertheless, the role of CR-related genes in IS has not been fully elucidated. In this study, seven CR-related immune biomarkers in the GSE58294 and GSE22255 datasets were identified by combining differential gene expression analysis, weighted correlation network analysis, and single sample gene set enrichment analysis. After experimental validation using quantitative polymerase chain reaction, four genes (DPF2, LMNB1, MLLT3, and JAK2) were screened as candidate immune biomarkers. These four biomarkers demonstrated good predictive power in the clinical risk model (area under the curve, 0.775). Molecular docking simulations revealed that mevastatin, WP1066, cladribine, trichostatin A, mequitazine, and zuclomiphene may be potential immunomodulatory drugs for IS. Overall, the results of this study contribute to the identification of CR-related immune therapeutics target in IS and provide an important reference for further research.

Macrophage polarization regulates intervertebral disc degeneration by modulating cell proliferation, inflammation mediator secretion, and extracellular matrix metabolism

Macrophage infiltration and polarization have been increasingly observed in intervertebral disc (IVD) degeneration (IDD). However, their biological roles in IDD are still unrevealed. We harvested conditioned media (CM) derived from a spectrum of macrophages induced from THP-1 cells, and examined how they affect nucleus pulposus cells (NPCs) in vitro, by studying cell proliferation, extracellular matrix (ECM) synthesis, and pro-inflammation expression; and in vivo by injection CM in a rat IDD model. Then, high-throughput sequencing was used to detect differentially expressed genes (DEGs). Gene Ontology (GO), the Kyoto Encyclopedia of Genes and Genomes (KEGG), and protein-protein interaction (PPI) networks were used to further analysis. Higher CCR7+ (M1 marker) and CD206+ (M2 marker) cell counts were found in the degenerated human IVD tissues as compared with the control. Furthermore, the cell co-culture model showed M1CM attenuated NPC proliferation, downregulated the expression of ECM anabolic genes encoding aggrecan and collagen IIα1, upregulated the expression of ECM catabolic genes encoding MMP-13, and inflammation-related genes encoding IL-1β, IL-6, and IL-12, while M2CM showed contrasting trends. In IDD model, higher histological scores and lower disc height index were found following M1CM treatment, while M2CM exhibited opposite results. M1CM injection decreased ECM anabolic and increased ECM catabolic, as well as the upregulation of inflammation-related genes after 8 weeks treatment, while M2CM slowed down these trends. Finally, a total of 637 upregulated and 655 downregulated genes were detected in M1CM treated NPCs, and 975 upregulated genes and 930 downregulated genes in the M2CM groups. The top 30 GO terms were shown and the most significant KEGG pathway was cell cycle in both groups. Based on the PPI analysis, the five most significant hub genes were PLK1, KIF20A, RRM2, CDC20, and UBE2C in the M1CM groups and RRM2, CCNB1, CDC20, PLK1, and UBE2C in the M2CM groups. In conclusion, macrophage polarization exhibited diverse roles in IDD progression, with M1CM exacerbating cell proliferation suppression and IVD degeneration, while M2CM attenuated IDD development. These findings may facilitate the further elucidation of the role of macrophage polarization in IDD, and provide novel insights into the therapeutic potential of macrophages.

Key LncRNAs Associated With Oxidative Stress Were Identified by GEO Database Data and Whole Blood Analysis of Intervertebral Disc Degeneration Patients

Background: Intervertebral disc degeneration (IDD) is a major cause of low back pain, but the onset and progression of IDD are unknown. Long non-coding RNA (lncRNA) has been validated to play a critical role in IDD, while an increasing number of studies have linked oxidative stress (OS) to the initiation and progression of IDD. We aim to investigate key lncRNAs in IDD through a comprehensive network of competing endogenous RNA (ceRNA) and to identify possible underlying mechanisms.

Methods: We downloaded IDD-related gene expression data from the Gene Expression Omnibus (GEO) database and obtained differentially expressed-lncRNAs (DE-lncRNA), -microRNAs (DE-miRNA), and -messenger RNAs (DE-mRNA) by bioinformatics analysis. The OS-related lncRNA-miRNA-mRNA ceRNA interaction axis was constructed and key lncRNAs were identified based on ceRNA theory. We performed gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses on mRNAs regulated by lncRNAs in the ceRNA network. Single sample gene set enrichment analysis (ssGSEA) was used to reveal the immune landscape. Expression of key lncRNAs in IDD was assessed by quantitative reverse transcription-polymerase chain reaction (qRT-PCR).

Results: In this study, 111 DE-mRNAs, 20 DE-lncRNAs, and 502 DE-miRNAs were identified between IDD patients and controls, and 16 OS-related DE-lncRNAs were also identified. The resulting lncRNA-miRNA-mRNA network consisted of eight OS-related DE-lncRNA nodes, 24 DE-miRNA nodes, 70 DE-mRNA nodes, and 183 edges. Functional enrichment analysis suggested that the ceRNA network may be involved in regulating biological processes related to cytokine secretion, lipid, and angiogenesis. We also identified four key lncRNAs, namely lncRNA GNAS-AS1, lncRNA MIR100HG, lncRNA LINC01359, and lncRNA LUCAT1, which were also found to be significantly associated with immune cells.

Conclusion: These results provide novel insights into the potential applications of OS-related lncRNAs in patients with IDD.

Investigating the AC079305/DUSP1 Axis as Oxidative Stress-Related Signatures and Immune Infiltration Characteristics in Ischemic Stroke

Background

Oxidative stress (OS) and immune inflammation play complex intersections in the pathophysiology of ischemic stroke (IS). However, a competing endogenous RNA- (ceRNA-) based mechanism linked to the intersections in IS has not been explored. We aimed to identify potential OS-related signatures and analyze immune infiltration characteristics in IS.

Methods

Three datasets (GSE22255, GSE110993, and GSE140275) from the GEO database were extracted. Differentially expressed long noncoding RNAs, microRNAs, and messenger RNAs (DElncRNAs, DEmiRNAs, and DEmRNAs) between IS patients and controls were identified. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis were explored. Moreover, a triple ceRNA network was constructed to reveal transcriptional regulation mechanisms. A comprehensive strategy among least absolute shrinkage and selection operator (LASSO) regression, DEmRNAs, uprelated DEmRNAs, and OS-related genes was adopted to select the best signature. Then, we evaluated and verified the discriminant ability of the signature via receiver operating characteristic (ROC) analysis. Immune infiltration characteristics were explored via the CIBERSORT algorithm. Moreover, the best signature was verified via qPCR and western blot methods in rat brain tissues and PC12 cells.

Results

11 DEmRNAs were identified totally. Enrichment analysis showed that the DEmRNAs were primarily concentrated in MAPK-associated biological processes and immune or inflammation-involved pathways. DUSP1 was identified as the best signature with an area under the ROC curve of 73.5% (95%CI = 57.02-89.98, sensitivity = 95%, and specificity = 60%) in GSE22255 and 100.0% (95%CI = 100.00-100.00, sensitivity = 100%, and specificity = 100%) in GSE140275. Importantly, we also identified the AC079305/DUSP1 axis in the ceRNA network. Immune infiltration showed that resting mast cells infiltrate less in IS patients compared with controls. And DUSP1 was negatively correlated with resting mast cells (r = −0.703, P < 0.01), whereas it was positively correlated with neutrophils (r = 0.339, P < 0.05). Both in vivo and in vitro models confirmed the upregulated expression of DUSP1 and the downregulated expression of miR-429.

Conclusion

This study identified the ceRNA-based AC079305/DUSP1 axis as a promising OS-related signature for IS. Immune infiltrating cells, especially mast cells, may exert a pivotal role in IS progression. Pharmacological agents targeting signatures, their receptors, or mast cells may shed a novel light on therapeutic targets for IS.

Identification of a ferroptosis-related gene pair biomarker with immune infiltration landscapes in ischemic stroke: a bioinformatics-based comprehensive study

Background

Ischemic stroke (IS) is a principal contributor to long-term disability in adults. A new cell death mediated by iron is ferroptosis, characterized by lethal aggregation of lipid peroxidation. However, a paucity of ferroptosis-related biomarkers early identify IS until now. This study investigated potential ferroptosis-related gene pair biomarkers in IS and explored their roles in immune infiltration.

Results

In total, we identified 6 differentially expressed ferroptosis-related genes (DEFRGs) in the metadata cohort. Of these genes, 4 DEFRGs were incorporated into the competitive endogenous RNA (ceRNA) network, including 78 lncRNA-miRNA and 16 miRNA-mRNA interactions. Based on relative expression values of DEFRGs, we constructed gene pairs. An integrated scheme consisting of machine learning algorithms, ceRNA network, and gene pair was proposed to screen the key DEFRG biomarkers. The receiver operating characteristic (ROC) curve witnessed that the diagnostic performance of DEFRG pair CDKN1A/JUN was superior to that of single gene. Moreover, the CIBERSORT algorithm exhibited immune infiltration landscapes: plasma cells, resting NK cells, and resting mast cells infiltrated less in IS samples than controls. Spearman correlation analysis confirmed a significant correlation between plasma cells and CDKN1A/JUN (CDKN1A: r = − 0.503, P < 0.001, JUN: r = − 0.330, P = 0.025).

Conclusions

Our findings suggested that CDKN1A/JUN could be a robust and promising gene-pair diagnostic biomarker for IS, regulating ferroptosis during IS progression via C9orf106/C9orf139-miR-22-3p-CDKN1A and GAS5-miR-139-5p/miR-429-JUN axes. Meanwhile, plasma cells might exert a vital interplay in IS immune microenvironment, providing an innovative insight for IS therapeutic target.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12864-022-08295-0.