Cathepsin G promotes arteriovenous fistula maturation by positively regulating the MMP2/MMP9 pathway

BACKGROUND

Arteriovenous fistula (AVF) is currently the preferred vascular access for hemodialysis patients. However, the low maturation rate of AVF severely affects its use in patients. A more comprehensive understanding and study of the mechanisms of AVF maturation is urgently needed.

METHODS AND RESULTS

In this study, we downloaded the publicly available datasets (GSE119296 and GSE220796) from the Gene Expression Omnibus (GEO) and merged them for subsequent analysis. We screened 84 differentially expressed genes (DEGs) and performed the functional enrichment analysis. Next, we integrated the results obtained from the degree algorithm provided by the Cytohubba plug-in, Molecular complex detection (MCODE) plug-in, weighted gene correlation network analysis (WGCNA), and Least absolute shrinkage and selection operator (LASSO) logistic regression. This integration allowed us to identify CTSG as a hub gene associated with AVF maturation. Through the literature search and Pearson's correlation analysis, the genes matrix metalloproteinase 2 (MMP2) and MMP9 were identified as potential downstream effectors of CTSG. We then collected three immature clinical AVF vein samples and three mature samples and validated the expression of CTSG using immunohistochemistry (IHC) and double-immunofluorescence staining. The IHC results demonstrated a significant decrease in CTSG expression levels in the immature AVF vein samples compared to the mature samples. The results of double-immunofluorescence staining revealed that CTSG was expressed in both the intima and media of AVF veins. Moreover, the expression of CTSG in vascular smooth muscle cells (VSMCs) was significantly higher in the mature samples compared to the immature samples. The results of Masson's trichrome and collagen I IHC staining demonstrated a higher extent of collagen deposition in the media of immature AVF veins compared to the mature. By constructing an in vitro CTSG overexpression model in VSMCs, we found that CTSG upregulated the expression of MMP2 and MMP9 while downregulating the expression of collagen I and collagen III. Furthermore, CTSG was found to inhibit VSMC migration.

CONCLUSIONS

CTSG may promote AVF maturation by stimulating the secretion of MMP2 and MMP9 from VSMCs and reducing the extent of medial fibrosis in AVF veins by inhibiting the secretion of collagen I and collagen III.

Analysis and experimental validation of necroptosis-related molecular classification, immune signature and feature genes in Alzheimer's disease

Necroptosis, a programmed cell death pathway, has been demonstrated to be activated in Alzheimer's disease (AD). However, the precise role of necroptosis and its correlation with immune cell infiltration in AD remains unclear. In this study, we conducted non-negative matrix factorization clustering analysis to identify three subtypes of AD based on necroptosis-relevant genes. Notably, these subtypes exhibited varying necroptosis scores, clinical characteristics and immune infiltration signatures. Cluster B, characterized by high necroptosis scores, showed higher immune cell infiltration and was associated with a more severe pathology, potentially representing a high-risk subgroup. To identify potential biomarkers for AD within cluster B, we employed two machine learning algorithms: the least absolute shrinkage and selection operator regression and Random Forest. Subsequently, we identified eight feature genes (CARTPT, KLHL35, NRN1, NT5DC3, PCYOX1L, RHOQ, SLC6A12, and SLC38A2) that were utilized to develop a diagnosis model with remarkable predictive capacity for AD. Moreover, we conducted validation using bulk RNA-seq, single-nucleus RNA-seq, and in vivo experiments to confirm the expression of these feature genes. In summary, our study identified a novel necroptosis-related subtype of AD and eight diagnostic biomarkers, explored the roles of necroptosis in AD progression and shed new light for the clinical diagnosis and treatment of this disease.

Inhibition of RAC attenuates Adriamycin-induced podocyte injury

Minimal Change Disease (MCD), which is associated with podocyte injury, is the leading cause of nephrotic syndrome in children. A considerable number of patients experience relapses and require prolonged use of prednisone and immunosuppressants. Multi-drug resistance and frequent relapses can lead to disease progression to focal and segmental glomerulosclerosis (FSGS). To identify potential targets for therapy of podocyte injury, we examined microarray data of mRNAs in glomerular samples from both MCD patients and healthy donors, obtained from the GEO database. Differentially expressed genes (DEGs) were used to construct the protein-protein interactions (PPI) network through the application of the search tool for the retrieval of interacting genes (STRING) tool. The most connected genes in the network were ranked using cytoHubba. 16 hub genes were selected and validated by qRT-PCR. RAC2 was identified as a potential therapeutic target for further investigation. By downregulating RAC2, Adriamycin (ADR)-induced human podocytes (HPCs) injury was attenuated. EHT-1864, a small molecule inhibitor that targets the RAC (RAC1, RAC2, RAC3) family, proved to be more effective than RAC2 silencing in reducing HPCs injury. In conclusion, our research suggests that EHT-1864 may be a promising new molecular drug candidate for patients with MCD and FSGS.

Integrative experimental validation of concomitant miRNAs and transcription factors with differentially expressed genes in acute myocardial infarction

Identification of concomitant miRNAs and transcription factors (TFs) with differential expression (DEGs) in MI is crucial for understanding holistic gene regulation, identifying key regulators, and precision in biomarker and therapeutic target discovery. We performed a comprehensive analysis using Affymetrix microarray data, advanced bioinformatic tools, and experimental validation to explore potential biomarkers associated with human pathology. The search strategy includes the identification of the GSE83500 dataset, comprising gene expression profiles from aortic wall punch biopsies of MI and non-MI patients, which were used in the present study. The analysis identified nine distinct genes exhibiting DEGs within the realm of MI. miRNA-gene/TF and TF-gene/miRNA regulatory relations were mapped to retrieve interacting hub genes to acquire an MI miRNA-TF co-regulatory network. Furthermore, an animal model of I/R-induced MI confirmed the involved gene based on quantitative RT-PCR and Western blot analysis. The consequences of the bioinformatic tool substantiate the inference regarding the presence of three key hub genes (UBE2N, TMEM106B, and CXADR), a central miRNA (hsa-miR-124-3p), and sixteen TFs. Animal studies support the involvement of predicted genes in the I/R-induced myocardial infarction assessed by RT-PCR and Western blotting. Thus, the final consequences suggest the involvement of promising molecular pathways regulated by TF (p53/NF-κB1), miRNA (hsa-miR-124-3p), and hub gene (UBE2N), which may play a key role in the pathogenesis of MI.

Regulatory role of PDK1 via integrated gene analysis of mitochondria-immune response in periodontitis

AIMS

To investigate the association between mitochondrial events and immune response in periodontitis and related regulatory genes.

MAIN METHODS

Gene expression profiles in gingival tissues were retrieved from the Gene Expression Omnibus. Mitochondria-immune response-related differentially expressed genes (MIR-DEGs) between the healthy and periodontitis samples were determined. WGCNA, GO, and KEGG were used to investigate the function and the enriched pathways of MIR-DEGs. The correlation between MIR-DEGs expression and clinical probing pocket depth was analyzed. The MIR-DEGs were further identified and verified in animal samples. A periodontitis model was established in C57BL/6 mice with silk ligation. Micro-computed tomography was used to assess alveolar bone loss. Western blot, quantitative real-time polymerase chain reaction, and immunohistochemical analyses further validated the differential expression of the MIR-DEGs.

KEY FINDINGS

A total of ten MIR-DEGs (CYP24A1, PRDX4, GLDC, PDK1, BCL2A1, CBR3, ARMCX3, BNIP3, IFI27, and UNG) were identified, the expression of which could effectively distinguish patients with periodontitis from the healthy controls. Enhanced immune response was detected in the periodontitis group with that in the healthy controls, especially in B cells. PDK1 was a critical MIR-DEG correlated with B cell immune response and clinical periodontal probing pocket depth. Both animal and clinical periodontal samples presented higher gene and protein expression of PDK1 than the control samples. Additionally, PDK1 colocalized with B cells in both animal and clinical periodontal tissues.

SIGNIFICANCE

Mitochondria participate in the regulation of the immune response in periodontitis. PDK1 may be the key mitochondria-related gene regulating B-cell immune response in periodontitis.

MGP+ and IDO1+ tumor-associated macrophages facilitate immunoresistance in breast cancer revealed by single-cell RNA sequencing

Immunotherapy is widely applied for the treatment of breast cancer, but to which some patients respond poorly or develop resistance. Therefore, the mechanism needs to be further studied. Transcriptomic data of 31 breast cancer patients treated with anti-programmed death receptor 1 (PD-1) was downloaded from the VIB-KULeuven Center for Cancer Biology to analyze the changes in myeloid cells in tumor tissues before and after immunotherapy. And 24 cell populations that may be immune-related were further identified. Representative cell populations were also screened and validated through cellular and animal experiments to evaluate the relevant molecular expression and pathways of tumor-associated macrophages (TAMs) in the tumor microenvironment. The results demonstrated that MGP+ TAMs and IDO1+ TAMs influenced the efficacy of immunotherapy in breast cancer patients. After anti-PD-1 treatment, Increased numbers of MGP+ TAMs and IDO1+ TAMs in breast cancer patients upregulated pro-tumorigenic factors associated with resistance to immunosuppressive therapy. This study provides new biomarkers for immunotherapy to predict therapeutic responses and overcome potential resistance to immunotherapy. It is an important complement to the immunosuppression caused by TAMs after immunotherapy for breast cancer.

Identification of novel endoplasmic reticulum-related genes and their association with immune cell infiltration in major depressive disorder

BACKGROUND

Several lines of evidence point to an interaction between genetic predisposition and environmental factors in the onset of major depressive disorder (MDD). This study is aimed to investigate the pathogenesis of MDD by identifying key biomarkers, associated immune infiltration using bioinformatic analysis and human postmortem sample.

METHODS

The Gene Expression Omnibus (GEO) database of GSE98793 was adopted to identify hub genes linked to endoplasmic reticulum (ER) stress-related genes (ERGs) in MDD. Another GEO database of GSE76826 was employed to validate the novel target associated with ERGs and immune infiltration in MDD. Moreover, human postmortem sample from MDD patients was utilized to confirm the differential expression analysis of hub genes.

RESULTS

We discovered 12 ER stress-related differentially expressed genes (ERDEGs). A LASSO Cox regression analysis helped construct a diagnostic model for these ERDEGs, incorporating immune infiltration analysis revealed that three hub genes (ERLIN1, SEC61B, and USP13) show the significant and consistent expression differences between the two groups. Western blot analysis of postmortem brain samples indicated notably higher expression levels of ERLIN1 and SEC61B in the MDD group, with USP13 also tending to increase compared to control group.

LIMITATIONS

The utilization of the MDD gene chip in this analysis was sourced from the GEO database, which possesses a restricted number of pertinent gene chip samples.

CONCLUSIONS

These findings indicate that ERDEGs especially including ERLIN1, SEC61B, and USP13 associated the infiltration of immune cells may be potential diagnostic indicators for MDD.

Identification of fibronectin type III domain containing 3B as a potential prognostic and therapeutic target for pancreatic cancer: a preliminary analysis

BACKGROUND

Fibronectin type III domain containing 3B (FNDC3B), a member of the fibronectin type III domain-containing protein family, has been indicated in various malignancies. However, the precise role of FNDC3B in the progression of pancreatic cancer (PC) still remains to be elucidated.

METHODS

In this study, we integrated data from the National Center for Biotechnology Information, the Cancer Genome Atlas, Genotype-Tissue Expression database, and Gene Expression Omnibus datasets to analyze FNDC3B expression and its association with various clinicopathological parameters. Subsequently, Gene Ontology and Kyoto Encyclopedia of Genes and Genomes, along with Gene Set Enrichment Analysis (GSEA), single sample Gene Set Enrichment Analysis (ssGSEA) and estimate analysis were recruited to delve into the biological function and immune infiltration based on FNDC3B expression. Additionally, the prognostic estimation was conducted using Cox analysis and Kaplan-Meier analysis. Subsequently, a nomogram was constructed according to the result of Cox analysis to enhance the prognostic ability of FNDC3B. Finally, the preliminary biological function of FNDC3B in PC cells was explored.

RESULTS

The study demonstrated a significantly higher expression of FNDC3B in tumor tissues compared to normal pancreatic tissues, and this expression was significantly associated with various clinicopathological parameters. GSEA revealed the involvement of FNDC3B in biological processes and signaling pathways related to integrin signaling pathway and cell adhesion. Additionally, ssGSEA analysis indicated a positive correlation between FNDC3B expression and infiltration of Th2 cells and neutrophils, while showing a negative correlation with plasmacytoid dendritic cells and Th17 cells infiltration. Kaplan-Meier analysis further supported that high FNDC3B expression in PC patients was linked to shorter overall survival, disease-specific survival, and progression-free interval. However, although univariate analysis demonstrated a significant correlation between FNDC3B expression and prognosis in PC patients, this association did not hold true in multivariate analysis. Finally, our findings highlight the crucial role of FNDC3B expression in regulating proliferation, migration, and invasion abilities of PC cells.

CONCLUSION

Despite limitations, the findings of this study underscored the potential of FNDC3B as a prognostic biomarker and its pivotal role in driving the progression of PC, particularly in orchestrating immune responses.

Bioinformatic Analysis Identifies Potential Extracellular Matrix Related Genes in the Pathogenesis of Early Onset Preeclampsia

Early-onset preeclampsia (EOPE) is a complex pregnancy complication that poses significant risks to the health of both mothers and fetuses, and research on its pathogenesis and pathophysiology remains insuffcient. This study aims to explore the role of candidate genes and their potential interaction mechanisms in EOPE through bioinformatics analysis techniques. Two gene expression datasets, GSE44711 and GSE74341, were obtained from the Gene Expression Omnibus (GEO) to identify differentially expressed genes (DEGs) between EOPE and gestational age-matched preterm control samples. Functional enrichment analysis was performed utilizing the kyoto encyclopedia of genes and genomes (KEGG), gene ontology (GO), and gene set enrichment analysis (GSEA). A protein-protein interaction (PPI) network was constructed using the STRING database, and hub DEGs were identified through Cytoscape software and comparative toxicogenomics database (CTD) analysis. Furthermore, a diagnostic logistic model was established using these hub genes, which were confirmed through reverse transcription polymerase chain reaction (RT-PCR). Finally, immune cell infiltration was analyzed using CIBERSORT. In total, 807 DEGs were identified in the GSE44711 dataset (451 upregulated genes and 356 downregulated genes), and 787 DEGs were identified in the GSE74341 dataset (446 upregulated genes and 341 downregulated genes). These DEGs were significantly enriched in various molecular functions such as extracellular matrix structural constituent, receptor-ligand activity binding, cytokine activity, and platelet-derived growth factor. KEGG and GSEA annotation revealed significant enrichment in pathways related to ECM-receptor interaction, PI3K-AKT signaling, and focal adhesion. Ten hub genes were identified through the CytoHubba plugin in Cytoscape. Among these hub genes, three key DEGs (COL1A1, SPP1, and THY1) were selected using CTD analysis and various topological methods in Cytoscape. The diagnostic logistic model based on these three genes exhibited high efficiency in predicting EOPE (AUC = 0.922). RT-PCR analysis confirmed the downregulation of these genes in EOPE, and immune cell infiltration analysis suggested the significant role of M1 and M2 macrophages in EOPE. In conclusion, this study highlights the association of three key genes (COL1A1, SPP1, and THY1) with EOPE and their contribution to high diagnostic efficiency in the logistic model. Additionally, it provides new insights for future research on EOPE and emphasizes the diagnostic value of these identified genes. More research is needed to explore their functional and diagnostic significance in EOPE.

Identification of Y‒linked biomarkers and exploration of immune infiltration of normal-appearing gray matter in multiple sclerosis by bioinformatic analysis

Background

The knowledge of normal‒appearing cortical gray matter (NAGM) in multiple sclerosis (MS) remains unclear. In this study, we aimed to identify diagnostic biomarkers and explore the immune infiltration characteristics of NAGM in MS through bioinformatic analysis and validation in vivo.

Methods

Differentially expressed genes (DEGs) were analyzed. Subsequently, the functional pathways of the DEGs were determined. After screening the overlapping DEGs of MS with two machine learning methods, the biomarkers' efficacy and the expression levels of overlapping DEGs were calculated. Quantitative reverse transcription polymerase chain reaction (qRT‒PCR) identified the robust diagnostic biomarkers. Additionally, infiltrating immune cell populations were estimated and correlated with the biomarkers. Finally, the characteristics of immune infiltration of NAGM from MS were evaluated.

Results

A total of 98 DEGs were identified. They participated in sensory transduction of the olfactory system, synaptic signaling, and immune responses. Nine overlapping genes were screened by machine learning methods. After verified by ROC curve, four genes, namely HLA‒DRB1, RPS4Y1, EIF1AY and USP9Y, were screened as candidate biomarkers. The mRNA expression of RPS4Y1 and USP9Y was significantly lower in MS patients than that in the controls. They were selected as the robust diagnostic biomarkers for male MS patients. RPS4Y1 and USP9Y were both positively correlated with memory B cells. Moreover, naive CD4+ T cells and monocytes were increased in the NAGM of MS patients compared with those in controls.

Conclusions

Low expressed Y‒linked genes, RPS4Y1 and USP9Y, were identified as diagnostic biomarkers for MS in male patients. The inhomogeneity of immune cells in NAGM might exacerbate intricate interplay between the CNS and the immune system in the MS.

Novel biomarkers related to oxidative stress and immunity in chronic kidney disease

Introduction

The incidence of chronic kidney disease (CKD) has been increasing in recent years, gradually becoming a global health crisis. Due to limited treatment options, novel molecular pathways are urgently required to advance the treatment and diagnosis of CKD.

Materials and methods

The characteristics of differentially expressed genes (DEGs) in CKD patients were analyzed using Gene Expression Omnibus (GEO) database, and genes related to oxidative stress were retrieved from the Genecard database. Subsequently, a comprehensive approach was applied, including immune infiltration analysis, weighted gene co-expression network analysis (WGCNA) and protein-protein interaction (PPI) network analysis, to identify hub genes among differentially expressed immune-related oxidative stress genes (DEIOSGs). Validation of hub genes was performed using an external data set, and diagnostic potential capability was evaluated through receiver operating curve (ROC) analysis. In animal experiments, the expression of hub genes in CKD was confirmed by inducing a CKD model through a 5/6 nephrectomy procedure. Finally, the relationship between these hub genes and clinical characteristics were assessed using the Nephroseq v5 database.

Results

29 DEIOSGs were identified by comprehensive bioinformatics analysis. PPI analysis screened the hub genes NCF2, S100A9, and SELL. ROC analysis demonstrated excellent diagnostic efficacy. Further validation from other databases and animal experiments confirmed a substantial upregulation in the expression of hub genes in CKD. Additionally, clinical correlation analysis established a clear link between hub gene expression and renal function deterioration.

Conclusions

Our study confirms NCF2, S100A9, and SELL as diagnostic biomarkers associated with immune response and oxidative stress in CKD, suggesting their potential as novel targets for CKD diagnosis and treatment.

LncRNA and mRNA expression characteristic and bioinformatic analysis in myocardium of diabetic cardiomyopathy mice

BACKGROUND

Diabetic cardiomyopathy (DCM) is becoming a very well-known clinical entity and leads to increased heart failure in diabetic patients. Long non-coding RNAs (LncRNAs) play an important role in the pathogenesis of DCM. In the present study, the expression profiles of lncRNAs and mRNAs were illuminated in myocardium from DCM mice, with purpose of exploring probable pathological processes of DCM involved by differentially expressed genes in order to provide a new direction for the future researches of DCM.

RESULTS

The results showed that a total of 93 differentially expressed lncRNA transcripts and 881 mRNA transcripts were aberrantly expressed in db/db mice compared with the controls. The top 6 differentially expressed lncRNAs like up-regulated Hmga1b, Gm8909, Gm50252 and down-regulated Msantd4, 4933413J09Rik, Gm41414 have not yet been reported in DCM. The lncRNAs-mRNAs co-expression network analysis showed that LncRNA 2610507I01Rik, 2310015A16Rik, Gm10503, A930015D03Rik and Gm48483 were the most relevant to differentially expressed mRNAs.

CONCLUSION

Our results showed that db/db DCM mice exist differentially expressed lncRNAs and mRNAs in hearts. These differentially expressed lncRNAs may be involved in the pathological process of cardiomyocyte apoptosis and fibrosis in DCM.

Identification of Anoikis-Related Genes in Spinal Cord Injury: Bioinformatics and Experimental Validation

Spinal cord injury (SCI) is a serious disease without effective therapeutic strategies. To identify the potential treatments for SCI, it is extremely important to explore the underlying mechanism. Current studies demonstrate that anoikis might play an important role in SCI. In this study, we aimed to identify the key anoikis-related genes (ARGs) providing therapeutic targets for SCI. The mRNA expression matrix of GSE45006 was downloaded from the Gene Expression Omnibus (GEO) database, and the ARGs were downloaded from the Molecular Signatures Database (MSigDB database). Then, the potential differentially expressed ARGs were identified. Next, correlation analysis, gene ontology (GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis, and protein-protein interaction (PPI) analysis were employed for the differentially expressed ARGs. Moreover, miRNA-gene networks were constructed by the hub ARGs. Finally, RNA expression of the top ten hub ARGs was validated in the SCI cell model and rat SCI model. A total of 27 common differentially expressed ARGs were identified at different time points (1, 3, 7, and 14 days) following SCI. The GO and KEGG enrichment analysis of these ARGs indicated several enriched terms related to proliferation, cell cycle, and apoptotic process. The PPI results revealed that most of the ARGs interacted with each other. Ten hub ARGs were further screened, and all the 10 genes were validated in the SCI cell model. In the rat model, only seven genes were validated eventually. We identified 27 differentially expressed ARGs of the SCI through bioinformatic analysis. Seven real hub ARGs (CCND1, FN1, IGF1, MYC, STAT3, TGFB1, and TP53) were identified eventually. These results may expand our understanding of SCI and contribute to the exploration of potential SCI targets.

m6A methylation modification and immune infiltration analysis in osteonecrosis of the femoral head

Osteonecrosis of the femoral head (ONFH) is a elaborate hip disease characterized by collapse of femoral head and osteoarthritis. RNA N6-methyladenosine (m6A) plays a crucial role in a lot of biological processes within eukaryotic cells. However, the role of m6A in the regulation of ONFH remains unclear. In this study, we identified the m6A regulators in ONFH and performed subtype classification. We identified 7 significantly differentially expressed m6A regulators through the analysis of differences between ONFH and normal samples in the Gene Expression Omnibus (GEO) database. A random forest algorithm was employed to monitor these regulators to assess the risk of developing ONFH. We constructed a nomogram based on these 7 regulators. The decision curve analysis suggested that patients can benefit from the nomogram model. We classified the ONFH samples into two m6A models according to these 7 regulators through consensus clustering algorithm. After that, we evaluated those two m6A patterns using principal component analysis. We assessed the scores of those two m6A patterns and their relationship with immune infiltration. We observed a higher m6A score of type A than that of type B. Finally, we performed a cross-validation of crucial m6A regulatory factors in ONFH using external datasets and femoral head bone samples. In conclusion, we believed that the m6A pattern could provide a novel diagnostic strategy and offer new insights for molecularly targeted therapy of ONFH.

Diagnostic signatures and immune cell infiltration characteristics in anti-GABABR encephalitis

PURPOSE

Anti-gamma-aminobutyric acid B receptor (GABABR) encephalitis is an uncommon form of autoimmune encephalitis associated with a poor prognosis and a high fatality rate. We aim to find diagnostic markers for anti- GABABR encephalitis as well as the effects of immune cell infiltration on this pathology.

METHODS

For quantitative proteomic analysis, isobaric tags for relative and absolute quantitation were used in conjunction with LC-MS/MS analysis. To conduct functional correlation analyses, differentially expressed proteins (DEPs) were identified. Following that, we used bioinformatics analysis to screen for and determine the diagnostic signatures of anti- GABABR encephalitis. ROC curves were used to evaluate the diagnostic values. To assess the inflammatory status of anti- GABABR encephalitis, we used cell-type identification by estimating relative subsets of the RNA transcript (CIBERSORT) and explored the link between diagnostic markers and infiltrating immune cells.

RESULTS

Overall, 108 robust DEPs (47 upregulated and 61 downregulated) were identified, of which 11 were immune related. The most impressively enriched pathways were complemented and coagulation cascades, actin cytoskeleton regulation, and cholesterol metabolism; GSEA revealed that the enriched pathways were considerably differentially connected to immune modulation. Eleven immune-related DEPs were chosen for further investigation. We developed a novel diagnostic model based on CSF1R and AZGP1 serum levels using ROC analysis (area under the ROC curve = 1). M1 macrophages and activated natural killer cells are likely to play a role in course of anti- GABABR encephalitis.

CONCLUSION

We identified CSF1R and AZGP1 are possible anti-GABABR encephalitis diagnostic indicators, and immune cell infiltration may have a significant impact on the development and occurrence of anti- GABABR encephalitis.

Statistical and network analyses reveal mechanisms for the enhancement of macrophage immunity by manganese in Mycobacterium tuberculosis infection

Tuberculosis is a significant infectious disease that poses a serious risk to human health. Our previous research has indicated that manganese ions reduce the bacterial load of Mycobacterium tuberculosis in macrophages, but the exact immune defense mechanism remains unknown. Several critical proteins and pathways involved in the host's immune response during this process are still unidentified. Our research aims to identify these proteins and pathways and provide a rationale for the use of manganese ions in the adjuvant treatment of tuberculosis. We downloaded GSE211666 data from the GEO database and selected the RM (Post-infection manganese ion treatment group) and Ra (single-infection group) groups for comparison and analysis to identify differential genes. These differential genes were then enriched and analyzed using STRING, Cytoscape, and NDEx tools to identify the two most relevant pathways of the "Host Response Signature Network." After conducting an in-depth analysis of these two pathways, we found that manganese ions mainly mediate (1) the interferon -gamma (IFN-γ) and its receptor IFNGR and the downstream JAK-STAT pathway and (2) the NFκB pathway to enhance macrophage response to interferon, autophagy, polarization, and cytokine release. Using qPCR experiments, we verified the increased expression of CXCL10, MHCII, IFNγ, CSF2, and IL12, all of which are cytokines that play a key role in resistance to Mycobacterium tuberculosis infection, suggesting that macrophages enter a state of pro-inflammatory and activation after the addition of manganese ions, which enhances their immunosuppressive effect against Mycobacterium tuberculosis. We conclude that our study provides evidence of manganese ion's ability to treat tuberculosis adjuvantly.

Exploration of potential biomarkers and therapeutic targets for trauma-related acute kidney injury

PURPOSE

Acute kidney injury (AKI) is one of the most common functional injuries observed in trauma patients. However, certain trauma medications may exacerbate renal injury. Therefore, the early detection of trauma-related AKI holds paramount importance in improving trauma prognosis.

METHODS

Qualified datasets were selected from public databases, and common differentially expressed genes related to trauma-induced AKI and hub genes were identified through enrichment analysis and the establishment of protein-protein interaction (PPI) networks. Additionally, the specificity of these hub genes was investigated using the sepsis dataset and conducted a comprehensive literature review to assess their plausibility. The raw data from both datasets were downloaded using R software (version 4.2.1) and processed with the "affy" package19 for correction and normalization.

RESULTS

Our analysis revealed 585 upregulated and 629 downregulated differentially expressed genes in the AKI dataset, along with 586 upregulated and 948 downregulated differentially expressed genes in the trauma dataset. Concurrently, the establishment of the PPI network and subsequent topological analysis highlighted key hub genes, including CD44, CD163, TIMP metallopeptidase inhibitor 1, cytochrome b-245 beta chain, versican, membrane spanning 4-domains A4A, mitogen-activated protein kinase 14, and early growth response 1. Notably, their receiver operating characteristic curves displayed areas exceeding 75%, indicating good diagnostic performance. Moreover, our findings postulated a unique molecular mechanism underlying trauma-related AKI.

CONCLUSION

This study presents an alternative strategy for the early diagnosis and treatment of trauma-related AKI, based on the identification of potential biomarkers and therapeutic targets. Additionally, this study provides theoretical references for elucidating the mechanisms of trauma-related AKI.

ATG9A as a potential diagnostic marker of intervertebral disc degeneration: Inferences from experiments and bioinformatics analysis incorporating sc-RNA-seq data

BACKGROUND

Disfunctional autophagy plays a pivotal role in Intervertebral Disc Degeneration (IDD) progression. however, the connection between Autophagy-related gene 9A (ATG9A) and IDD has not been reported.

METHODS

Firstly, transcriptome datasets from the GEO and Autophagy-related genes (ARGs) from GeneCards were carried out using R. Following this, IDD-specific signature genes were identified through methods such as least absolute shrinkage and selection operator (LASSO), random forest (RF), and support vector machine (SVM) analyses. Validation of these findings proceeded through in vitro experiments, evaluation of independent datasets, and analysis of receiver operating characteristic (ROC) curves. Subsequent steps incorporated co-expression analysis, Gene Ontology (GO) analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis, Gene Set Enrichment Analysis (GSEA), and construction of competing endogenous RNA (ceRNA) network. The final section established the correlation between immune cell infiltration, ATG9A, and IDD utilizing the CIBERSORT algorithm and single-cell RNA (scRNA) sequencing data.

RESULTS

Research identified 87 differentially expressed genes, with only ATG9A noted as an IDD signature gene. Analysis of in vitro experiments and independent datasets uncovered a decrease in ATG9A expression within the degeneration group. The area under the curve (AUC) of ATG9A exceeded 0.8 following ROC analysis. Furthermore, immune cell infiltration and scRNA sequencing data analysis elucidated the substantial role of immune cells in IDD progression. A ceRNA network was constructed, centered around ATG9A, included 4 miRNAs and 22 lncRNAs.

CONCLUSION

ATG9A was identified as a diagnostic gene for IDD, indicating its viability as a effective target for therapy disease.

Preconditioning exercise reduces brain damage of ischemic stroke in rats via PI3K-AKT pathway by bioinformatic analysis

Ischemic stroke is one of the most vital causes of high neurological morbidity and mortality in the world. Preconditioning exercise is considered as the primary prevention of stroke to resistance to subsequent injury. We tried to research the underlying biological mechanisms of this exercise. Forty-two SD rats were randomly divided into three groups: middle cerebral artery occlusion (MCAO) group, exercise group with MCAO (EX + MCAO) group, and sham group, with 14 rats in each group. The EX + MCAO group underwent exercise preconditioning for 3 weeks before occlusion, and the other two groups were fed and exercised normally. After 3 weeks, MCAO model was made by thread plug method in the EX + MCAO group and MCAO group. After successful modeling, the Longa scale was used to evaluate the neurological impairment of rats at day 0, day 1, and day 2. The rats in each group were killed on the third day after modeling. TTC staining measured the infarct volume of each group. The morphology and apoptosis of cortical cells were observed by HE and Tunel staining. Three rats in each group underwent high-throughput sequencing. Bioinformatic analysis was used to find the deferentially expressed genes (DEGs) and predict the transcription factor binding sites (TFBS) of the next-generation sequencing results. Gene enrichment (GSEA) was used to analyze potential functional genes and their corresponding signaling pathways. The Longa scale showed EX + MCAO group had the neurological function better than the modeling group (P < 0.001). TTC staining showed that the infarct size of EX + MCAO group was less than MCAO group (P < 0.05). HE and Tunel staining showed that the cells in the EX + MCAO group and the sham group had normal morphology and fewer apoptotic cells than MCAO group. A new gene named 7994 was discovered and TFBS of this gene was predicted, which could interact with key genes such as Foxd3, Foxa2, NR4A2, SP1, CEBPA, and SOX10. GSEA showed that EX + MCAO group could promote and regulate angiogenesis and apoptosis through PI3K-AKT pathway. Preconditioning exercise could improve nerve function and reduce infarct size in rats. The underlying mechanism is to regulate the PI3K-AKT pathway through several key genes, promote cerebral angiogenesis, and reduce apoptosis.

Insights into the molecular mechanisms and signalling pathways of epithelial to mesenchymal transition (EMT) in colorectal cancer: A systematic review and bioinformatic analysis of gene expression

Colorectal cancer (CRC) is ranked as the second leading cause of mortality worldwide, mainly due to metastasis. Epithelial to mesenchymal transition (EMT) is a complex cellular process that drives CRC metastasis, regulated by changes in EMT-associated gene expression. However, while numerous genes have been identified as EMT regulators through various in vivo and in vitro studies, little is known about the genes that are differentially expressed in CRC tumour tissue and their signalling pathway in regulating EMT. Using an integration of systematic search and bioinformatic analysis, gene expression profiles of CRC tumour tissues were compared to non-tumour adjacent tissues to identify differentially expressed genes (DEGs), followed by performing systematic review on common identified DEGs. Fifty-eight common DEGs were identified from the analysis of 82 tumour tissue samples obtained from four gene expression datasets (NCBI GEO). These DEGS were then systematically searched for their roles in modulating EMT in CRC based on previously published studies. Following this, 10 common DEGs (CXCL1, CXCL8, MMP1, MMP3, MMP7, TACSTD2, VIP, HPGD, ABCG2, CLCA4) were included in this study and subsequently subjected to further bioinformatic analysis. Their roles and functions in modulating EMT in CRC were discussed in this review. This study enhances our understanding of the molecular mechanisms underlying EMT and uncovers potential candidate genes and pathways that could be targeted in CRC.

Genome-wide analysis of the switchgrass YABBY family and functional characterization of PvYABBY14 in response to ABA and GA stress in Arabidopsis

BACKGROUND

The small YABBY plant-specific transcription factor has a prominent role in regulating plant growth progress and responding to abiotic stress.

RESULTS

Here, a total of 16 PvYABBYs from switchgrass (Panicum virgatum L.) were identified and classified into four distinct subgroups. Proteins within the same subgroup exhibited similar conserved motifs and gene structures. Synteny analyses indicated that segmental duplication contributed to the expansion of the YABBY gene family in switchgrass and that complex duplication events occurred in rice, maize, soybean, and sorghum. Promoter regions of PvYABBY genes contained numerous cis-elements related to stress responsiveness and plant hormones. Expression profile analysis indicated higher expression levels of many PvYABBY genes during inflorescence development and seed maturation, with lower expression levels during root growth. Real-time quantitative PCR analysis demonstrated the sensitivity of multiple YABBY genes to PEG, NaCl, ABA, and GA treatments. The overexpression of PvYABBY14 in Arabidopsis resulted in increased root length after treatment with GA and ABA compared to wild-type plants.

CONCLUSIONS

Taken together, our study provides the first genome-wide overview of the YABBY transcription factor family, laying the groundwork for understanding the molecular basis and regulatory mechanisms of PvYABBY14 in response to ABA and GA responses in switchgrass.

Bioinformatic analysis reveals prognostic value and immunotherapy potential of Siglec-15 in laryngeal squamous cell carcinoma

Background

Laryngeal squamous cell carcinoma (LSCC) is the ultimate common malignant head and neck cancer with dismal prognosis. The expression pattern and clinical significance of Siglec-15 (Sialic acid-binding immunoglobulin-like lectin 15) in LSCC are poorly understood. In order to lay the groundwork for future immune-related research on Siglec-15 in LSCC, we set out to study its expression and prognostic importance in the disease, as well as to use bioinformatics to investigate the immune features modulated by Siglec-15 in LSCC.

Methods

① In order to get the gene expression profile and clinical data for TCGA head and neck cancer (TCGA-HNSC), you may access the relevant data from UCSC xena and use 110 cases of laryngeal cancer as a training set. Two datasets, GSE27020 and GSE25727, were obtained from the GEO databank and utilized as validation sets. These datasets include expression profiles and clinical information. The Siglec-15 gene and immune characteristics were analyzed by bioinformatics methods. ② Retrospectively collected routine paraffin specimens from patients with pathological diagnosis of squamous cell carcinoma from December 2012 to November 2015 in Sun Yat-sen Memorial Hospital and fresh frozen tissue of patients from June 2021 to March 2022. Immunohistochemistry method, immunofluorescence technique and real-time quantitative PCR was used to examine the difference of Siglec-15 appearance in LSCC tissue and adjacent tissue, and its correlation of prognosis, clinic pathological characteristics and CD8+T lymphocyte infiltration. Using human laryngeal cancer cell line (LCC), we studied the influence of Siglec-15 in cell proliferation and invasion.

Results

We identified Siglec-15 was upregulated in LSCC. The patients in Siglec-15 high expression group had a poor overall survival (OS) based on the clinical information from TGCA and 111 LSCC patients that hospitalized in Sun Yat-sen Memorial Hospital. The COX regression analysis indicated Siglec-15 as an independent predictor for poor prognosis of LSCC. Bioinformatic analysis suggested that the high expression of Siglec-15 shape an immune suppressive tumor microenvironment (TEM), leading to poor response to immunotherapy in LSCC. Siglec-15 enhanced cell invasion and proliferation, as we showed in vitro.

Conclusion

Our study support Siglec-15 as a potential predictor for LSCC prognosis and an attractive target for LSCC immunotherapy.

Pan-cancer analysis reveals potential immunological and prognostic roles of METTL7A in human cancers

Methyltransferase-like protein 7A (METTL7A) is an m6A RNA methyltransferase that has been linked to cancer prognosis and drug resistance. However, a comprehensive analysis of METTL7A is lacking. The expression of METTL7A, prognostic performance, correlation with microsatellite instability (MSI), tumor mutational burden (TMB), and immune infiltration was investigated in The Cancer Genome Atlas (TCGA). Immunohistochemistry staining was applied to detect METTL7A in 6 tumors. METTL7A was significantly decreased in 19 cancers in TCGA including LUAD. Alterations of METTL7A include amplification and mutation, and epigenetic alterations revealed increased promoter methylation may result in down-regulation of METTL7A in LUAD. We also found that METTL7A was linked to both TMB and MSI in LUAD. METTL7A was increasingly correlated with invasive immune cells, while being negatively associated with Macrophages M0, Mast cells activated, activated memory CD4 T cells, CD8 T cells, and follicular helper T cells in several tumors. Additionally, METTL7A showed similar correlation with immune therapy-related genes across cancers. Our biological validation found that the protein levels of METTL7A were down-regulated in breast cancer (BRCA), endometrioid cancer (UCEC), colon cancer (COAD), prostate cancer (PRAD), and kidney clear cell carcinoma (KIRC), as detected by immunohistochemistry staining. Overall, our work indicates that METTL7A may serve as promising diagnostic and prognostic indicator of LUAD, and our work sheds light on the potential immunological and prognostic roles of METTL7A in human cancers.

Loss of helicase C-terminal domain of SMARCAL1 protein associated with severe Schimke immuno-osseous dysplasia

Schimke immuno-osseous dysplasia (SIOD) is a rare multi-system condition caused by biallelic loss-of-function mutations in the SMARCAL1 gene. This disorder is characterized by disproportionate growth failure, T-cell deficiency, and renal dysfunction. Pathogenic variants in the SMARCAL1 gene have been reported in only approximately half of SIOD-affected individuals. Among these alterations, nonsense and frameshift mutations generally lead to a severe phenotype with early onset. In this study, we identified novel mutations in an Iranian patient with SIOD. A 4-year-old girl with developmental delay and facial dysmorphism was referred to our center for molecular diagnosis. We applied whole-exome and Sanger sequencing for co-segregation analysis. Subsequently, bioinformatic analysis was performed to assess the pathogenic effects of the variants and their post-transcriptional effects. We discovered two novel mutations (c.2281delT and c.2283delA) in exon 15 of the SMARCAL1 gene, resulting in a truncated protein with a loss of 193 amino acids (p.S761Rfs*1). Variant effect predictors indicated that these variants are pathogenic, and multi-sequence alignments revealed high conservation of this region among different species. Given that our patient exhibited severe a phenotype and passed away soon after receiving a definitive molecular diagnosis, we propose that the loss of the helicase C-terminal domain in the deleted part of SMARCAL1 may lead to the severe form of SIOD. Besides, the combination of growth retardation and bone abnormalities also plays a crucial role in the early diagnosis of the disease.

Identification of common core ion channel genes in epilepsy and Alzheimer's disease

BACKGROUND

Although available literature indicates that the incidence of dementia in the epilepsy population and the risk of seizures in the Alzheimer's disease (AD) population are high, the specific genetic risk factors and the interaction mechanism are unclear, rendering rational genetic interpretation rather challenging.

AIMS

Our work aims to identify the common core ion channel genes in epilepsy and AD.

METHODS

In this study, we first integrated gene expression omnibus datasets (GSE48350 and GSE6834) on AD and epilepsy to identify differentially expressed genes (DEGs), performing Gene Ontology function and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis of DEGs. The related protein-protein interaction (PPI) network was constructed for DEGs, and the hub gene was evaluated.

RESULTS

A total of 2800 and 35 genes were identified in GSE48350 and GSE6834, and 12 DEGs were significantly differentially expressed between the datasets. KEGG pathway analysis showed that DEGs were primarily enriched in glutamatergic synapse and dopaminergic synapse pathways. SCN2A, GRIA1, and KCNJ9 were the hub genes with high connectivity.

CONCLUSIONS

The findings suggest that the three genes, SCN2A, GRIA1, and KCNJ9, may serve as potential targets for treating AD comorbid with epilepsy.

Global analysis of iron metabolism-related genes identifies potential mechanisms of gliomagenesis and reveals novel targets

AIMS

This study aimed to investigate key regulators of aberrant iron metabolism in gliomas, and evaluate their effect on biological functions and clinical translational relevance.

METHODS

We used transcriptomic data from multiple cross-platform glioma cohorts to identify key iron metabolism-related genes (IMRGs) based on a series of bioinformatic and machine learning methods. The associations between IMRGs and prognosis, mesenchymal phenotype, and genomic alterations were analyzed in silico. The performance of the IMRGs-based signature in predicting temozolomide (TMZ) treatment sensitivity was evaluated. In vitro and in vivo experiments were used to explore the biological functions of these key IMRGs.

RESULTS

HMOX1, LTF, and STEAP3 were identified as the most essential IMRGs in gliomas. The expression levels of these genes were strongly related to clinicopathological and molecular features. The robust IMRG-based gene signature could be used for prognosis prediction. These genes facilitate mesenchymal transformation, driver gene mutations, and oncogenic alterations in gliomas. The gene signature was also associated with TMZ resistance. HMOX1, LTF, and STEAP3 knockdown in glioma cells significantly reduced cell proliferation, colony formation, migration, and malignant invasion.

CONCLUSION

The study presented a comprehensive view of key regulators underpinning iron metabolism in gliomas and provided new insights into novel therapeutic approaches.

Insight into the role of mitochondrion-related gene anchor signature in mitochondrial dysfunction of neutrophilic asthma

OBJECTIVE

At present, targeting molecular-pharmacological therapy is still difficult in neutrophilic asthma. The investigation aims to identify and validate mitochondrion-related gene signatures for diagnosis and specific targeting therapeutics in neutrophilic asthma.

METHODS

Bronchial biopsy samples of neutrophilic asthma and healthy people were identified from GSE143304 dataset and then matched with human mitochondrial gene data to obtain mitochondria-related differential genes (MitoDEGs). Signature mitochondria-related diagnostic markers were jointly screened by support vector machine (SVM) analysis, least absolute shrinkage, and selection operator (LASSO) regression. The expression of marker MitoDEGs was evaluated by validation datasets GSE147878 and GSE43696. The diagnostic value was evaluated by receiver operating characteristic (ROC) curve analysis. Meanwhile, the infiltrating immune cells were analyzed by the CIBERSORT. Finally, oxidative stress level and mitochondrial functional morphology for asthmatic mice and BEAS-2B cells were evaluated. The expression of signature MitoDEGs was verified by qPCR.

RESULTS

67 MitoDEGs were identified. Five signature MitoDEGs (SOD2, MTHFD2, PPTC7, NME6, and SLC25A18) were further screened out. The area under the curve (AUC) of signature MitoDEGs presented a good diagnostic performance (more than 0.9). There were significant differences in the expression of signature MitoDEGs between neutrophilic asthma and non-neutrophilic asthma. In addition, the basic features of mitochondrial dysfunction were demonstrated by in vitro and in vivo experiments. The expression of signature MitoDEGs in the neutrophilic asthma mice presented a significant difference from the control group.

CONCLUSIONS

These MitoDEGs signatures in neutrophilic asthma may hold potential as anchor diagnostic and therapeutic targets in neutrophilic asthma.

Unveiling promising breast cancer biomarkers: an integrative approach combining bioinformatics analysis and experimental verification

BACKGROUND

Breast cancer remains a significant health challenge worldwide, necessitating the identification of reliable biomarkers for early detection, accurate prognosis, and targeted therapy.

MATERIALS AND METHODS

Breast cancer RNA expression data from the TCGA database were analyzed to identify differentially expressed genes (DEGs). The top 500 up-regulated DEGs were selected for further investigation using random forest analysis to identify important genes. These genes were evaluated based on their potential as diagnostic biomarkers, their overexpression in breast cancer tissues, and their low median expression in normal female tissues. Various validation methods, including online tools and quantitative Real-Time PCR (qRT-PCR), were used to confirm the potential of the identified genes as breast cancer biomarkers.

RESULTS

The study identified four overexpressed genes (CACNG4, PKMYT1, EPYC, and CHRNA6) among 100 genes with higher importance scores. qRT-PCR analysis confirmed the significant upregulation of these genes in breast cancer patients compared to normal samples.

CONCLUSIONS

These findings suggest that CACNG4, PKMYT1, EPYC, and CHRNA6 may serve as valuable biomarkers for breast cancer diagnosis, and PKMYT1 may also have prognostic significance. Furthermore, CACNG4, CHRNA6, and PKMYT1 show promise as potential therapeutic targets. These findings have the potential to advance diagnostic methods and therapeutic approaches for breast cancer.

Identifying hub genes of sepsis-associated and hepatic encephalopathies based on bioinformatic analysis-focus on the two common encephalopathies of septic cirrhotic patients in ICU

BACKGROUND

In the ICU ward, septic cirrhotic patients are susceptible to suffering from sepsis-associated encephalopathy and/or hepatic encephalopathy, which are two common neurological complications in such patients. However, the mutual pathogenesis between sepsis-associated and hepatic encephalopathies remains unclear. We aimed to identify the mutual hub genes, explore effective diagnostic biomarkers and therapeutic targets for the two common encephalopathies and provide novel, promising insights into the clinical management of such septic cirrhotic patients.

METHODS

The precious human post-mortem cerebral tissues were deprived of the GSE135838, GSE57193, and GSE41919 datasets, downloaded from the Gene Expression Omnibus database. Furthermore, we identified differentially expressed genes and screened hub genes with weighted gene co-expression network analysis. The hub genes were then subjected to Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway functional enrichment analyses, and protein-protein interaction networks were constructed. Receiver operating characteristic curves and correlation analyses were set up for the hub genes. Finally, we explored principal and common signaling pathways by using Gene Set Enrichment Analysis and the association between the hub genes and immune cell subtype distribution by using CIBERSORT algorithm.

RESULTS

We identified seven hub genes-GPR4, SOCS3, BAG3, ZFP36, CDKN1A, ADAMTS9, and GADD45B-by using differentially expressed gene analysis and weighted gene co-expression network analysis method. The AUCs of these genes were all greater than 0.7 in the receiver operating characteristic curves analysis. The Gene Set Enrichment Analysis results demonstrated that mutual signaling pathways were mainly enriched in hypoxia and inflammatory response. CIBERSORT indicated that these seven hub genes were closely related to innate and adaptive immune cells.

CONCLUSIONS

We identified seven hub genes with promising diagnostic value and therapeutic targets in septic cirrhotic patients with sepsis-associated encephalopathy and/or hepatic encephalopathy. Hypoxia, inflammatory, and immunoreaction responses may share the common downstream pathways of the two common encephalopathies, for which earlier recognition and timely intervention are crucial for management of such septic cirrhotic patients in ICU.

Identification of potential biomarkers and therapeutic targets related to post-traumatic stress disorder due to traumatic brain injury

BACKGROUND

Post-traumatic stress disorder (PTSD), a disease state that has an unclear pathogenesis, imposes a substantial burden on individuals and society. Traumatic brain injury (TBI) is one of the most significant triggers of PTSD. Identifying biomarkers associated with TBI-related PTSD will help researchers to uncover the underlying mechanism that drives disease development. Furthermore, it remains to be confirmed whether different types of traumas share a common mechanism of action.

METHODS

For this study, we screened the eligible data sets from the Gene Expression Omnibus (GEO) database, obtained differentially expressed genes (DEGs) through analysis, conducted functional enrichment analysis on the DEGs in order to understand their molecular mechanisms, constructed a PPI network, used various algorithms to obtain hub genes, and finally evaluated, validated, and analyzed the diagnostic performance of the hub genes.

RESULTS

A total of 430 upregulated and 992 down-regulated differentially expressed genes were extracted from the TBI data set. A total of 1919 upregulated and 851 down-regulated differentially expressed genes were extracted from the PTSD data set. Functional enrichment analysis revealed that the differentially expressed genes had biological functions linked to molecular regulation, cell signaling transduction, cell metabolic regulation, and immune response. After constructing a PPI network and introducing algorithm analysis, the upregulated hub genes were identified as VNN1, SERPINB2, and ETFDH, and the down-regulated hub genes were identified as FLT3LG, DYRK1A, DCN, and FKBP8. In addition, by comparing the data with patients with other types of trauma, it was revealed that PTSD showed different molecular processes that are under the influence of different trauma characteristics and responses.

CONCLUSIONS

By exploring the role of different types of traumas during the pathogenesis of PTSD, its possible molecular mechanisms have been revealed, providing vital information for understanding the complex pathways associated with TBI-related PTSD. The data in this study has important implications for the design and development of new diagnostic and therapeutic methods needed to treat and manage PTSD.

Identification of biomarkers and potential therapeutic targets of kidney stone disease using bioinformatics

PURPOSE

Kidney stone disease (KSD) is a common urological disease, but its pathogenesis remains unclear. In this study, we screened KSD-related hub genes using bioinformatic methods and predicted the related pathways and potential drug targets.

METHODS

The GSE75542 and GSE18160 datasets in the Gene Expression Omnibus (GEO) were selected to identify common differentially expressed genes (DEGs). We conducted Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses to identify enriched pathways. Finally, we constructed a hub gene-miRNA network and drug-DEG interaction network.

RESULTS

In total, 44 upregulated DEGs and 1 downregulated DEG were selected from the GEO datasets. Signaling pathways, such as leukocyte migration, chemokine activity, NF-κB, TNF, and IL-17, were identified in GO and KEGG. We identified 10 hub genes using Cytohubba. In addition, 21 miRNAs were predicted to regulate 4 or more hub genes, and 10 drugs targeted 2 or more DEGs. LCN2 expression was significantly different between the GEO datasets. Quantitative real-time polymerase chain reaction (qRT-PCR) analyses showed that seven hub gene expressions in HK-2 cells with CaOx treatment were significantly higher than those in the control group.

CONCLUSION

The 10 hub genes identified, especially LCN2, may be involved in kidney stone occurrence and development, and may provide new research targets for KSD diagnosis. Furthermore, KSD-related miRNAs may be targeted for the development of novel drugs for KSD treatment.

GL13K-modified titanium regulates osteogenic differentiation via the NF-κB pathway

The osteoimmune response plays a crucial regulatory role in the osseointegration of dental implants. Previous studies found the antimicrobial peptide coating (GL13K) could activate the immunomodulatory potential of macrophages (Raw 264.7) and promote osteogenic differentiation of bone marrow mesenchymal stem cells (BMSCs). To further investigate the mechanism of interaction between immunomodulation and differentiation, a co-culture model of the representative cells (Raw 264.7 and BMSCs) was constructed to mimic the immune microenvironment. In this system, GL13K coating of titanium implant effectively inhibited the polarization of the inflammatory M1 type and promoted the polarization of the anti-inflammatory M2 type. Furthermore, the inhibited NF-κB signaling pathway and Mip-2 gene expression were found and validated by bioinformatics analysis and virus-induced gene silencing, which significantly affected the tissue repair process. It can be concluded that the GL13K coating had the potential to establish a localized immune microenvironment conducive to osteogenic differentiation through cellular interactions. Subsequent investigations would be dedicated to a thorough examination of the osseointegration effects of GL13K coating.

Epidemiological and genetic characteristics of foot-and-mouth disease virus in China from 2010 to 2022

Foot-and-mouth disease virus (FMDV) is a highly contagious picornavirus that can infect cloven-hoofed animals of significant agricultural importance. In China, foot-and-mouth disease (FMD) epidemics occur annually, resulting in localized outbreaks or sporadic epidemics that cause significant economic losses. This study summarized 123 cases of FMD reported in China between 2010 and 2022, using data from the official website of the Chinese Center for Animal Disease Control and Prevention. The epidemic situation and genetic characteristics of FMDV in China were studied through phylogenetic analysis, amino acid variation analysis of antigenic epitopes, and genetic recombination analysis. The findings provide important references for predicting the FMDV epidemic situation in China, developing vaccines, and effectively preventing and controlling FMD.

Bulk RNA-seq Assessment of Murine Spleen Using a Portable MinION Sequencing Device

Comprehensive profiling of the transcriptome reflects the dynamic changes in complex regulator interactions between genes and proteins in the pathological processes of autoimmune disease. To enable real-time adaptive sampling and run rapid sequencing with maximal expected readings of 50 Gb of data with accessibility to clinicians, basic researchers, and even students, a portable and affordable sequencing device, MinION, was employed in our laboratory for both basic and clinical studies. Here, the workflow of bulk RNA-seq in murine spleen using MinION is introduced. The methodology of both laboratory library preparation and the establishment of a bioinformatic pipeline are included in this chapter.

Identification of novel candidate genes associated with non-syndromic tooth agenesis in Mongolian families

OBJECTIVES

This study aimed to identify genetic variants associated with non-syndromic tooth agenesis (TA) in nine families from Mongolia using whole-exome sequencing (WES) and bioinformatics analysis.

MATERIAL AND METHODS

The study enrolled 41 participants, including three inherited and six non-inherited families. WES analysis was performed on 14 saliva samples from individuals with non-syndromic TA. The potential candidate genes were identified through variant filtering and segregation analysis. The filtered variants were then analyzed in silico mutation impact analysis.

RESULTS

WES analysis identified 21 variants associated with TA, and 5 of these variants met all filtering criteria. These variants were located in the exome region of MAST4, ITGA6, PITX2, CACNA1S, and CDON genes. The variant in PITX2 was found in eight participants from inherited and non-inherited families, while the MAST4 variant was identified in 6 participants from inherited families.

CONCLUSIONS

The study identified various genetic variant candidates associated with TA in different family groups, with PITX2 being the most commonly identified. Our findings suggest that MAST4 may also be a novel candidate gene for TA due to its association with the Wnt signaling pathway. Additionally, we found that five candidate genes related to focal adhesion and calcium channel complex were significant and essential in tooth development.

CLINICAL RELEVANCE

Identifying new pathogenic genes associated with TA can improve our understanding of the molecular mechanisms underlying the disease, leading to better diagnosis, prevention, and treatment. Early detection of TA based on biomarkers can improve dental management and facilitate orthodontic and prosthetic treatment.

Identification of ACBD3 as a new molecular biomarker in pan-cancers through bioinformatic analysis: a preclinical study

BACKGROUND

Acyl-CoA-binding domain-containing 3 (ACBD3) is a multifunctional protein, that plays essential roles in cellular signaling and membrane domain organization. Although the precise roles of ACBD3 in various cancers remain unclear. Thus, we aimed to determine the diverse roles of ACBD3 in pan-cancers.

METHODS

Relevant clinical and RNA-sequencing data for normal tissues and 33 tumors from The Cancer Genome Atlas (TCGA) database, the Human Protein Atlas, and other databases were applied to investigate ACBD3 expression in various cancers. ACBD3-binding and ACBD3-related target genes were obtained from the STRING and GEPIA2 databases. The possible functions of ACBD3-binding genes were explored using Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses. We also applied the diagnostic value and survival prognosis analysis of ACBD3 in pan-cancers using R language. The mutational features of ACBD3 in various TCGA cancers were obtained from the cBioPortal database.

RESULTS

When compared with normal tissues, ACBD3 expression was statistically upregulated in eleven cancers and downregulated in three cancers. ACBD3 expression was remarkably different among various pathological stages of tumors, immune and molecular subtypes of cancers, cancer phosphorylation levels, and immune cell infiltration. The survival of four tumors was correlated with the expression level of ACBD3, including pancreatic adenocarcinoma, adrenocortical carcinoma, sarcoma, and glioma. The high accuracy in diagnosing multiple tumors and its correlation with prognosis indicated that ACBD3 may be a potential biomarker of pan-cancers.

CONCLUSION

According to our pan-cancer analysis, ACBD3 may serve as a remarkable prognostic and diagnostic biomarker of pan-cancers as well as contribute to tumor development. ACBD3 may also provide new directions for cancer treatment targets in the future.

Predictive value of CCL2 in the prognosis and immunotherapy response of glioblastoma multiforme

BACKGROUND

Glioblastoma multiforme (GBM) is the most common and lethal primary brain tumor with a poor prognosis. The C-C motif chemokine ligand 2 (CCL2) has shown abnormal expression associated with progression of multiple malignancies, however, its role in predicting the prognosis and immunotherapy response of GBM remains poorly understood.

RESULTS

CCL2 was highly expressed in GBM as analyzed by integrating CGGA, GEPIA and UALCAN online platforms, and further verified by histologic examinations, qRT-PCR analysis, and independent GEO datasets. CCL2 could serve as an independent prognostic factor for both the poor overall survival and progression-free survival of GBM patients based on TCGA data, univariate and multivariate cox analyses. Functional enrichment analysis revealed that CCL2 mainly participated in the regulation of chemokine signaling pathway and inflammatory response. Further, CCL2 expression was positively correlated with CD4 T cells, macrophages, neutrophils and myeloid dendritic cells infiltrating GBM as calculated by the TIMER2.0 algorithm. Importantly, the tumor immune dysfunction and exclusion (TIDE) algorithm showed that in CCL2-high GBM group, the expression of CD274, CTLA4, HAVCR2 and other immune checkpoints were significantly increased, and the immune checkpoint blockade (ICB) therapy was accordingly more responsive.

CONCLUSIONS

CCL2 can be used as a predictor of prognosis as well as immunotherapy response in GBM, offering potential clinical implications.

A Cellular Senescence-Related Signature Predicts Cervical Cancer Patient Outcome and Immunotherapy Sensitivity

Cervical cancer (CC) is one of the most prevalent gynecological malignancies. The rate of mortality and morbidity among patients with CC is high. Cellular senescence is involved in tumorigenesis as well as in the cancer progression. However, the involvement of cellular senescence in CC development is still unclear and requires further investigation. In this study, we retrieved data on cellular senescence-related genes (CSRGs) from the "CellAge" Database. We used the TCGA-CESC and CGCI-HTMCP-CC datasets as the training and validation sets, respectively. Finally, a signature was constructed using "univariate" and "Least Absolute Shrinkage and Selection Operator" (LASSO) Cox regression analysis, which contains eight CSRGs. Using this signature, we calculated the risk scores of all patients in the training and validation cohorts and categorized them into the low-risk group (LR-G) and the high-risk group (HR-G). Results showed that, compared to patients in the HR-G, those in the LR-G demonstrated a more positive clinical prognosis, more abundant immune cell infiltrations, and a more active immune response. The signature could also modulate the expression of SASP factors. In vitro studies showed an increased expression of SERPINE1 and IL-1α genes included in the signature in CC cells and tissues. Our findings help to deepen our insights into the etiology of CC, which could be beneficial for prognostic prediction and immunotherapy in clinical practice.

Identification of Molecular Markers Predicting the Outcome of Anti-thrombotic Therapy After Percutaneous Coronary Intervention in Patients with Acute Coronary Syndrome and Atrial fibrillation: Evidence from a Meta-analysis and Experimental Study

Acute coronary syndrome (ACS) and atrial fibrillation (AF) often coexist in clinical practice, and patients with these conditions often have a critical illness with high risk of both ischemia and bleeding. This study aims to report potential molecular markers for predicting the efficacy based on a meta-analysis of microarray data from the GEO database. In 40 patients with acute coronary syndrome (ACS) and atrial fibrillation (AF) treated with PCI, P2RX1's effects on platelet aggregation, medication resistance, and predictive value were examined. Twenty up-regulated genes in peripheral blood samples of ACS and AF patients were down-regulated after PCI, while 7 down-regulated genes were up-regulated. ACS affected eight potential genes. P2RX1, one of the four LASSO analysis-retrieved disease characteristic genes, accurately predicted AF patients' thrombosis risk and PCI's anti-thrombotic impact. Therefore, P2RX1 may be a molecular marker to predict the effect of anti-thrombotic therapy in patients with ACS and AF after PCI.

Integrative human and murine multi-omics: Highlighting shared biomarkers in the neuronal ceroid lipofuscinoses

Neuronal ceroid lipofuscinosis (NCL) is a group of neurodegenerative disorders whose molecular mechanisms remain largely unknown. Omics approaches are among the methods that generate new information on modifying factors and molecular signatures. Moreover, omics data integration can address the need to progressively expand knowledge around the disease and pinpoint specific proteins to promote as candidate biomarkers. In this work, we integrated a total of 62 proteomic and transcriptomic datasets originating from humans and mice, employing a new approach able to define dysregulated processes across species, stages and NCL forms. Moreover, we selected a pool of differentially expressed proteins and genes as species- and form-related biomarkers of disease status/progression and evaluated local and spatial differences in most affected brain regions. Our results offer promising targets for potential new therapeutic strategies and reinforce the hypothesis of a connection between NCLs and other forms of dementia, particularly Alzheimer's disease.

Effects of miR-143 regulation on cardiomyocytes apoptosis in doxorubicin cardiotoxicity based on integrated bioinformatics analysis

This study aimed to investigate the effect of miRNAs involving oxidative stress response in doxorubicin (DOX)-induced cardiotoxicity based on the data from Gene Expression Omnibus (GEO) database and experimental results via integrated bioinformatics analysis. MiRNA expression profiles of DOX-induced cardiotoxicity in rat myocardial tissues and adult rat cardiomyocytes (ARC) were extracted from GEO datasets (GSE36239). Differential expression miRNA (DEMs) were separately captured in rat myocardial tissues and in ARC, and intersected between rat myocardial tissues and ARC via Venny 2.1. Subsequently, Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes pathway (KEGG) analyzed 46 target genes of miR-143, one of 6 DEMs, and HIF-1 and PI3K-Akt signaling pathway were significantly enriched. Further experimental results showed DOX-induced oxidative stress downregulated the expression of miR-143, and then promoted target gene Bbc3 expression and H9c2 apoptosis, the intervention of phosphocreatine (PCr) or N-acetyl-L-cystine (NAC) alleviated oxidative stress, apoptosis and Bbc3 expression, upregulated miR-143 in DOX-induced cardiotoxicity in vivo and in vitro. Our findings elucidated the regulatory network between miR-143 and oxidative stress in DOX-induced cardiotoxicity, and might unveiled a potential biomarker and molecular mechanisms, which could be helpful to the diagnosis and treatment of DOX-induced cardiotoxicity.

Mapping the immunological battlefield in gastric cancer: prognostic implications of an immune gene expression signature

BACKGROUND

Gastric cancer (GC) is a heterogeneous malignancy with variable clinical outcomes. The immune system has been implicated in GC development and progression, highlighting the importance of immune-related gene expression patterns and their prognostic significance.

OBJECTIVE

This study aimed to identify differentially expressed immune-related genes (DEIRGs) and establish a prognostic index for GC patients using comprehensive bioinformatic analyses.

METHODS

We integrated RNA sequencing data from multiple databases and identified DEIRGs by overlapping differentially expressed genes with immune-related genes. Functional enrichment analysis was performed to uncover the biological processes and signaling pathways associated with DEIRGs. We conducted a Weighted Gene Co-expression Network Analysis (WGCNA) to identify key gene modules related to with GC. Cox regression analysis was conducted to determine independent prognostic DEIRGs for overall survival prediction. Based on these findings, we developed an immune-related gene prognostic index (IRGPI) based on these findings. The prognostic value of the IRGPI was validated using survival analysis and an independent validation cohort. Functional enrichment analysis, gene mutation analysis, and immune cell profiling were performed to gain insights into the biological functions and immune characteristics associated with the IRGPI-based subgroups.

RESULTS

We identified 493 DEIRGs significantly enriched in immune-related biological processes and signaling pathways associated with GC. WGCNA analysis revealed a significant module (turquoise module) associated with GC, revealing potential therapeutic targets. Cox regression analysis identified RNASE2, CGB5, CTLA4, and DUSP1 as independent prognostic DEIRGs. The IRGPI, incorporating the expression levels of these genes, demonstrated significant prognostic value in predicting overall survival. The IRGPI-based subgroups exhibited distinct biological functions, genetic alterations, and immune cell compositions.

CONCLUSION

Our study identified DEIRGs and established a prognostic index (IRGPI) for GC patients. The IRGPI exhibited promising prognostic potential and provided insights into GC tumor biology and immune characteristics. These findings have implications for guiding therapeutic strategies.

Classification of Colorectal Cancer Subtypes Based on Endoplasmic Reticulum Stress

INTRODUCTION

Endoplasmic reticulum stress (ERS) is associated with the occurrence and development of colorectal cancer (CRC).

METHODS

One thousand nine CRC samples and 3 ERS gene sets from GEO database were used to screen and validate genes related to stage and prognosis of CRC. Twenty thousand five hundred thirty samples from the TCGA database validated the ERS genes related to prognosis. PPI network construction and coexpression analysis were used to investigate the correlation of genes. ConsensusClusterPlus analysis was used to classify CRC subtypes. Cox regression and the LASSO algorithm were used to screen ERS genes related to prognosis. HE staining, immunohistochemical staining, and RT-qPCR of 50 owner-central samples were used to verify the genes. The ERscore model was constructed based on the ERS genes related to prognosis. The nomogram model was used to verify that different subtypes of CRC patients have different prognosis.

RESULTS

Fifty ERS differentially expressed genes related to CRC stage and 8 ERS model genes related to prognosis were screened. Three subtypes of CRC were classified based on the former 50 genes. The clinical characteristics were significantly different among the subtypes. The ERscore model was constructed based on the latter 8 genes, and its accuracy was verified by clinical samples. Finally, the nomogram was constructed based on ERscore, age, and CRC stage, and the accuracy of the nomogram prediction was verified.

CONCLUSION

ERS-related genes can be used as classification criteria for CRC, and the related clinical characteristics of different CRC subtypes are different.

Differential expression of miR-140-3p and its potential role during the development of the acute coronary syndrome

BACKGROUND

Acute coronary syndrome (ACS) is a category of cardiovascular disease with a high fatality rate.

AIMS

We searched the differential expressed miRNAs (DEmiRNAs) in ACS based on bioinformatic analysis and investigated the diagnostic value of plasma miR-140-3p in patients with ACS and its potential functional role in ACS.

METHODS

The miRNAs (GSE94605, GSE49823, and GSE185729) microarray datasets of ACS were downloaded from the GEO datasets. After integrating the miRNA and mRNA interaction, a protein-protein interaction (PPI) network was constructed with 36 overlapped target mRNAs using STRING database. The plasma levels of miR-140-3p were detected by RT-qPCR, and its clinical diagnostic value was evaluated using the ROC curve. The potential effects of the miR-140-3p/RHOA axis in ACS were explored using human coronary endothelial cells (HCAECs).

RESULTS

After overlapping the GEO datasets, miR-140-3p was identified in the microarray datasets of ACS. The plasma miR-140-3p expression levels were highly expressed in ACS patients than in healthy control and had diagnostic significance. The target mRNAs of miR-140-3p were predicted using TargetScan, miRWalk, TarBase, and miRDB databases. The PPI network identified ten hub genes. miR-140-3p could decrease the HCAECs' cell viability, while RHOA reversed the inhibition effect of miR-140-3p.

CONCLUSIONS

The plasma expression of miR-140-3p was upregulated in ACS patients. miR-140-3p could decrease the HCAECs' cell viability, while RHOA reversed the inhibition effect of miR-140-3p. The miR-140-3p may be a potential diagnostic biomarker for the early detection of ACS.

Identification of genes related to glucose metabolism and analysis of the immune characteristics in Alzheimer's disease

OBJECTIVE

Glucose metabolism plays a crucial role in the progression of Alzheimer's disease (AD). The purpose of this study is to identify genes related to glucose metabolism in AD by bioinformatics, construct an early AD prediction model from the perspective of glucose metabolism, and analyze the characteristics of immune cell infiltration.

METHODS

AD-related modules and genes were screened by weighted gene co-expression network analysis (WGCNA). The GO and KEEG enrichment analysis were used to explore the potential biological functions of glucose metabolism related genes (GMRGs) in AD. The Least Absolute Shrinkage Selection Operator (LASSO) method was used to construct an early AD prediction model based on GMRGs. Then, the receiver operating characteristic curve (ROC) and nomogram were introduced to evaluate the effectiveness of this model. Finally, CIBERSORT and single-cell analysis were applied for illustrating the immune characteristics in AD patients.

RESULTS

A total of 462 differential expressed genes (DEGs) were obtained between Non-Alzheimer's disease (ND,) and AD groups. The genes in the blue module had the highest correlation with AD by WGCNA analysis. We found 18 intersected genes among DEGs, blue model genes and GMRGs according to the Venn diagram. The GO and KEEG enrichment analysis showed that these 18 genes were mainly involved in the production of metabolites and energy, glycolysis, amino acid biosynthesis and so on. The early AD prediction model including ENO2, TPI1, AEBP1, HERC1, PCSK1, PREPL, SLC25A4, UQCRC2, CHST6, DDIT4, ACSS1 and SUCLA2 was constructed by LASSO analysis. The area under the curve (AUC) of this model in brain tissues was 0.942. Then, we draw the nomogram of this model and the C-index was 0.942. The model was further validated in blood samples and the AUC was 0.644. Immune cell infiltration analysis showed that the proportion of plasma cells, T cells follicular helper and activated NK cells in AD group were significantly lower than ND group, while the proportion of M1 macrophages, neutrophils, T cells CD4 naive and γ-δ T cells was significantly increased when compared with the ND group. Additionally, the specific GMRGs such as ENO2, DDIT4, and SUCLA2 are significantly correlated with certain immune cells such as plasma cells, follicular helper T cells, and M1 macrophages. Single-cell analysis results suggested that the increased macrophages in AD was associated with the up-regulation of AEBP1, DDIT4 and ACSS1.

CONCLUSIONS

The diagnosis model based on the twelve GMRGs has strong predictive ability and can be used as early diagnosis biomarkers for AD. In addition, these GMRGs closely associate with AD development by influencing the glucose metabolism of immune cells.

Identification of ferroptosis-related genes in acute phase of temporal lobe epilepsy based on bioinformatic analysis

BACKGROUND

Epilepsy is a prevalent neurological disorder, and while its precise mechanism remains elusive, a connection to ferroptosis has been established. This study investigates the potential clinical diagnostic significance of ferroptosis-related genes (FRGs) during the acute phase of temporal lobe epilepsy.

METHODS

To identify differentially expressed genes (DEGs), we accessed data from the GEO database and performed an intersection analysis with the FerrDB database to pinpoint FRGs. A protein-protein interaction (PPI) network was constructed. To assess the diagnostic utility of the discovered feature genes for the disease, ROC curve analysis was conducted. Subsequently, qRT-PCR was employed to validate the expression levels of these feature genes.

RESULTS

This study identified a total of 25 FRGs. PPI network analysis revealed six feature genes: IL6, PTGS2, HMOX1, NFE2L2, TLR4, and JUN. ROC curve analysis demonstrated that the combination of these six feature genes exhibited the highest diagnostic potential. qRT-PCR validation confirmed the expression of these feature genes.

CONCLUSION

We have identified six feature genes (IL6, PTGS2, HMOX1, NFE2L2, TLR4, and JUN) strongly associated with ferroptosis in epilepsy, suggesting their potential as biomarkers for the diagnosis of temporal lobe epilepsy.

In silico whole-transcriptome analysis reveals a potential hsa_circ_0000375-miR-424-5p-TPM2/SRPX/SRGAP1 regulatory network related to liver metastasis of colorectal cancer

Liver metastasis is the main lethal cause of colorectal cancer (CRC). The knowledge of role and mechanism of circular RNA (circRNA) in liver metastasis of CRC is still inadequate. In this study, whole-transcriptome analysis was performed using three datasets (GSE147597, GSE147602 and GSE147603). A total of 14 potential circRNAs were identified, after which their structural patterns and binding miRNAs were obtained. Next, 45 differentially expressed miRNAs (DEmiRNAs) between CRC without and with liver metastasis were acquired, consisting 38 upregulated and 7 downregulated miRNAs. After conducting intersection analysis, expression validation and correlation analysis, miR-761 and miR-424-5p were selected as the most potential miRNAs linked to liver metastasis of CRC. Subsequently, the target genes of miR-761 or miR-424-5p were predicted and differentially expressed genes (DEGs) between CRC without and with liver metastasis were obtained. 257 genes that were commonly appeared in predicted genes and DEGs were significantly enriched in "epithelial-to-mesenchymal transition" and "signaling by Robo receptor". Among these enriched genes, only TPM2, SRPX and SRGAP1 were significantly negatively correlated with miR-424-5p and were positively linked to hsa_circ_0000375 in CRC without or with liver metastasis. Collectively, the current findings elucidated a potential hsa_circ_0000375-miR-424-5p-TPM2/SRPX/SRGAP1 network contributing to liver metastasis of CRC.

An androgen receptor regulated gene score is associated with epithelial to mesenchymal transition features in triple negative breast cancers

BACKGROUND

Androgen receptor (AR) is considered a marker of better prognosis in hormone receptor positive breast cancers (BC), however, its role in triple negative breast cancer (TNBC) is controversial. This may be attributed to intrinsic molecular differences or scoring methods for AR positivity. We derived AR regulated gene score and examined its utility in BC subtypes.

METHODS

AR regulated genes were derived by applying a bioinformatic pipeline on publicly available microarray data sets of AR+ BC cell lines and gene score was calculated as average expression of six AR regulated genes. Tumors were divided into AR high and low based on gene score and associations with clinical parameters, circulating androgens, survival and epithelial to mesenchymal transition (EMT) markers were examined, further evaluated in invitro models and public datasets.

RESULTS

53% (133/249) tumors were classified as AR gene score high and were associated with significantly better clinical parameters, disease-free survival (86.13 vs 72.69 months, log rank p = 0.032) when compared to AR low tumors. 36% of TNBC (N = 66) were AR gene score high with higher expression of EMT markers (p = 0.024) and had high intratumoral levels of 5α-reductase, enzyme involved in intracrine androgen metabolism. In MDA-MB-453 treated with dihydrotestosterone, SLUG expression increased, E-cadherin decreased with increase in migration and these changes were reversed with bicalutamide. Similar results were obtained in public datasets.

CONCLUSION

Deciphering the role of AR in BC is difficult based on AR protein levels alone. Our results support the context dependent function of AR in driving better prognosis in ER positive tumors and EMT features in TNBC tumors.

Identification of the role of endoplasmic reticulum stress genes in endometrial cancer and their association with tumor immunity

BACKGROUND

Endometrial cancer (EC) is one of the worldwide gynecological malignancies. Endoplasmic reticulum (ER) stress is the cellular homeostasis disturbance that participates in cancer progression. However, the mechanisms of ER Stress on EC have not been fully elucidated.

METHOD

The ER Stress-related genes were obtained from Gene Set Enrichment Analysis (GSEA) and GeneCards, and the RNA-seq and clinical data were downloaded from The Cancer Genome Atlas (TCGA). The risk signature was constructed by the Cox regression and the least absolute shrinkage and selection operator (LASSO) analysis. The significance of the risk signature and clinical factors were tested by time-dependent receiver operating characteristic (ROC) curves, and the selected were to build a nomogram. The immunity correlation was particularly analyzed, including the related immune cells, pathways, and immune checkpoints. Functional enrichment, potential chemotherapies, and in vitro validation were also conducted.

RESULT

An ER Stress-based risk signature, consisting of TRIB3, CREB3L3, XBP1, and PPP1R15A was established. Patients were randomly divided into training and testing groups with 1:1 ratio for subsequent calculation and validation. Based on risk scores, high- and low-risk subgroups were classified, and low-risk subgroup demonstrated better prognosis. The Area Under Curve (AUC) demonstrated a reliable predictive capability of the risk signature. The majority of significantly different immune cells and pathways were enriched more in low-risk subgroup. Similarly, several typical immune checkpoints, expressed higher in low-risk subgroup. Patients of the two subgroups responded differently to chemotherapies.

CONCLUSION

We established an ER Stress-based risk signature that could effectively predict EC patients' prognosis and their immune correlation.

Potential molecular targets and drugs for basement membranes-related intervertebral disk degeneration through bioinformatics analysis and molecular docking

BACKGROUND

Through bioinformatics analysis to identify the hub genes of Intervertebral disc degeneration (IVDD) associated with basement membranes (BMs) and find out the potential molecular targets and drugs for BMs-related annulus fibrosus (AF) degeneration based on bioinformatic analysis and molecular approach.

METHODS

Intervertebral disc degeneration (IVDD) related targets were obtained from GeneCards, DisGenet and OMIM databases. BMs related genes were obtained from Basement membraneBASE database. The intersection targets were identified and subjected to protein-to-protein interaction (PPI) construction via STRING. Hub genes were identified and conducted Gene ontology (GO) and pathway enrichment analysis through MCODE and Clue GO in Cytospace respectively. DSigDB database was retrieved to predict therapeutic drugs and molecular docking was performed through PyMOL, AutoDock 1.5.6 to verify the binding energy between the drug and the different expressed hub genes. Finally, GSE70362 from GEO database was obtained to verify the different expression and correlation of each hub gene for AF degeneration.

RESULTS

We identified 41 intersection genes between 3 disease targets databases and Basement membraneBASE database. PPI network revealed 25 hub genes and they were mainly enriched in GO terms relating to glycosaminoglycan catabolic process, the TGF-β signaling pathway. 4 core targets were found to be significant via comparison of microarray samples and they showed strong correlation. The molecular docking results showed that the core targets have strong binding energy with predicting drugs including chitosamine and retinoic acid.

CONCLUSIONS

In this study, we identified hub genes, pathways, potential targets, and drugs for treatment in BMs-related AF degeneration and IVDD.