Personalized immune subtypes based on machine learning predict response to checkpoint blockade in gastric cancer.

Immune checkpoint inhibitors (ICI) show high efficiency in a small fraction of advanced gastric cancer (GC). However, personalized immune subtypes have not been developed for the prediction of ICI efficiency in GC. Herein, we identified Pan-Immune Activation Module (PIAM), a curated gene expression profile (GEP) representing the co-infiltration of multiple immune cell types in tumor microenvironment of GC, which was associated with high expression of immunosuppressive molecules such as PD-1 and CTLA-4. We also identified Pan-Immune Dysfunction Genes (PIDG), a conservative PIAM-derivated GEP indicating the dysfunction of immune cell cooperation, which was associated with upregulation of metastatic programs (extracellular matrix receptor interaction, TGF-ß signaling, epithelial-mesenchymal transition and calcium signaling) but downregulation of proliferative signalings (MYC targets, E2F targets, mTORC1 signaling, and DNA replication and repair). Moreover, we developed 'GSClassifier', an ensemble toolkit based on top scoring pairs and extreme gradient boosting, for population-based modeling and personalized identification of GEP subtypes. With PIAM and PIDG, we developed four Pan-immune Activation and Dysfunction (PAD) subtypes and a GSClassifier model 'PAD for individual' with high accuracy in predicting response to pembrolizumab (anti-PD-1) in advance GC (AUC = 0.833). Intriguingly, PAD-II (PIAMhighPIDGlow) displayed the highest objective response rate (60.0%) compared with other subtypes (PAD-I, PIAMhighPIDGhigh, 0%; PAD-III, PIAMlowPIDGhigh, 0%; PAD-IV, PIAMlowPIDGlow, 17.6%; P = 0.003), which was further validated in the metastatic urothelial cancer cohort treated with atezolizumab (anti-PD-L1) (P = 0.018). In all, we provided 'GSClassifier' as a refined computational framework for GEP-based stratification and PAD subtypes as a promising strategy for exploring ICI responders in GC. Metastatic pathways could be potential targets for GC patients with high immune infiltration but resistance to ICI therapy.

In silico prediction of polyketide biosynthetic gene clusters in the genomes of Hypericum-borne endophytic fungi.

BACKGROUND: The search for new bioactive natural compounds with anticancer activity is still of great importance. Even though their potential for diagnostics and treatment of cancer has already been proved, the availability is still limited. Hypericin, a naphthodianthrone isolated essentially from plant source Hypericum perforatum L. along with other related anthraquinones and bisanthraquinones belongs to this group of compounds. Although it has been proven that hypericin is synthesized by the polyketide pathway in plants, none of the candidate genes coding for key enzymes has been experimentally validated yet. Despite the rare occurrence of anthraquinones in plants, their presence in microorganisms, including endophytic fungi, is quite common. Unlike plants, several biosynthetic genes grouped into clusters (BGCs) in fungal endophytes have already been characterized. RESULTS: The aim of this work was to predict, identify and characterize the anthraquinone BGCs in de novo assembled and functionally annotated genomes of selected endophytic fungal isolates (Fusarium oxysporum, Plectosphaerella cucumerina, Scedosporium apiospermum, Diaporthe eres, Canariomyces subthermophilus) obtained from different tissues of Hypericum spp. The number of predicted type I polyketide synthase (PKS) BGCs in the studied genomes varied. The non-reducing type I PKS lacking thioesterase domain and adjacent discrete gene encoding protein with product release function were identified only in the genomes of C. subthermophilus and D. eres. A candidate bisanthraquinone BGC was predicted in C. subthermophilus genome and comprised genes coding the enzymes that catalyze formation of the basic anthraquinone skeleton (PKS, metallo-beta-lactamase, decarboxylase, anthrone oxygenase), putative dimerization enzyme (cytochrome P450 monooxygenase), other tailoring enzymes (oxidoreductase, dehydrogenase/reductase), and non-catalytic proteins (fungal transcription factor, transporter protein). CONCLUSIONS: The results provide an insight into genetic background of anthraquinone biosynthesis in Hypericum-borne endophytes. The predicted bisanthraquinone gene cluster represents a basis for functional validation of the candidate biosynthetic genes in a simple eukaryotic system as a prospective biotechnological alternative for production of hypericin and related bioactive anthraquinones.

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.

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.

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.

Identification of differentially expressed ER stress-related genes and their association with pulmonary arterial hypertension.

BACKGROUND: Pulmonary arterial hypertension (PAH) is a complex and progressive illness that has a multifaceted origin, significant fatality rates, and profound effects on health. The pathogenesis of PAH is poorly defined due to the insufficient understanding of the combined impact of endoplasmic reticulum (ER) stress and immune infiltration, both of which play vital roles in PAH development. This study aims to identify potential ER stress-related biomarkers in PAH and investigate their involvement in immune infiltration. METHODS: The GEO database was used to download gene expression profiles. Genes associated with ER stress were obtained from the MSigDB database. Weighted gene co-expression network analysis (WGCNA), GO, KEGG, and protein-protein interaction (PPI) were utilized to conduct screening of hub genes and explore potential molecular mechanisms. Furthermore, the investigation also delved into the presence of immune cells in PAH tissues and the correlation between hub genes and the immune system. Finally, we validated the diagnostic value and expression levels of the hub genes in PAH using subject-workup characterization curves and real-time quantitative PCR. RESULTS: In the PAH and control groups, a total of 31 genes related to ER stress were found to be differentially expressed. The enrichment analysis revealed that these genes were primarily enriched in reacting to stress in the endoplasmic reticulum, dealing with unfolded proteins, transporting proteins, and processing proteins within the endoplasmic reticulum. EIF2S1, NPLOC4, SEC61B, SYVN1, and DERL1 were identified as the top 5 hub genes in the PPI network. Immune infiltration analysis revealed that these hub genes were closely related to immune cells. The receiver operating characteristic (ROC) curves revealed that the hub genes exhibited excellent diagnostic efficacy for PAH. The levels of SEC61B, NPLOC4, and EIF2S1 expression were in agreement with the findings of bioinformatics analysis in the PAH group. CONCLUSIONS: Potential biomarkers that could be utilized are SEC61B, NPLOC4, and EIF2S1, as identified in this study. The infiltration of immune cells was crucial to the development and advancement of PAH. This study provided new potential therapeutic targets for PAH.

Plasma-derived exosomal miRNA profiles associated with type 1 diabetes.

AIMS: Recently, exosomal miRNAs have been shown to play important roles in multiple diseases, including type 1 diabetes (T1D). To assess the biomarker potential of exosomal miRNAs for T1D, we measured the expression profiles of plasma-derived exosomal miRNAs in T1D and explored their potential functions by bioinformatic analysis. MATERIALS AND METHODS: In the discovery phase, exosome samples were isolated from plasma by size exclusion chromatography from 10 T1D patients and 10 sex- (p = 0.36), age- (p = 0.97), and body mass index-matched (p = 0.47) healthy control subjects. Exosomal miRNA expression profiles were measured using the Illumina NovaSeq 6000 platform. With verification by quantitative real-time PCR (qRT-PCR), we used multiple bioinformatics approaches to explore the potential biological functions of the identified differentially expressed miRNAs. The diagnostic signature of exosomal miRNAs was evaluated by least absolute shrinkage and selection operator (LASSO) regression and evaluated based on the area under the receiver operating characteristic curve (AUC). RESULTS: In total, 43 differentially expressed miRNAs, among which 34 were upregulated and 9 were downregulated, were identified in T1D. After correcting for multiple testing using false discovery rate, 11 identified exosomal miRNAs still showed statistical significance. Among the 5 selected miRNAs, 3 miRNAs (miR-103a-3p, miR-144-5p and miR-454-3p) were successfully validated by qRT-PCR. The biological analysis-enriched terms included protein autophosphorylation and the Hedgehog signalling pathway. The highest AUC of exosomal miRNA was 0.889 under the LASSO model. The expression levels of 5 selected exosomal miRNAs were correlated with multiple clinical characteristics such as fasting C-peptide and postprandial C-peptide. CONCLUSIONS: Our results indicated that plasma-derived exosomal miRNAs could serve as promising diagnostic biomarkers of T1D.

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.

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.

Comprehensive analysis of the prognostic value of glutathione S-transferases Mu family members in breast cancer.

Breast cancer (BC) remains a significant public health concern globally, with a high number of reported cases and a substantial number of deaths every year. Accumulating reactive oxygen species (ROS) and oxidative stress are related to BC and the Glutathione S-transferases Mu (GSTM) family is one of the most important enzymatic detoxifiers associated with many cancers. In this study, UALCAN, Kaplan-Meier plotter, bc-GenExMiner, cBioPortal, STRING, Enrichr, and TIMER databases were employed to carry out a comprehensive bioinformatic analysis and provide new insight into the prognostic value of GSTMs in BC. GSTM2-5 genes in mRNA and protein levels were found to be expressed at lower levels in breast tumors compared to normal tissues, and reduction in mRNA levels is linked to shorter overall survival (OS) and relapse-free survival (RFS). The lower mRNA levels of GSTMs were strongly associated with the worse Scarff-Bloom-Richardson (SBR) grades (p < 0.0001). The mRNA levels of all five GSTMs were substantially higher in estrogen receptor (ER)-positive and progesterone receptor (PR)-positive compared to ER-negative and PR-negative BC patients. As well, when nodal status was compared, GSTM1, GSTM3, and GSTM5 were significantly higher in nodal-positive BC patients (p < .01). Furthermore, GSTM4 had the most gene alteration (4%) among other family members, and GSTM5 showed the strongest correlation with CD4+ T cells (Cor= .234, p = 2.22e-13). In conclusion, our results suggest that GSTM family members may be helpful as biomarkers for prognosis and as therapeutic targets in BC.

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.

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 the GSE143303 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.

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.

Transcriptional differences between vesicular hand eczema and atopic dermatitis.

BACKGROUND: Transcriptome analyses of vesicular hand eczema (VHE) indicated a large overlap with atopic dermatitis (AD). However, differentially expressed genes (DEGs) that differentiate VHE from AD are unknown. OBJECTIVE: To identify distinctive transcriptional features of VHE in comparison to AD. METHODS: We re-analysed RNA sequencing data of 10 lesional palmar VHE epidermal biopsies and performed DEG analyses. We adjusted the obtained DEG results of 57 lesional whole AD skin biopsies of the upper extremities or trunk to our criteria. Up- and down-regulated DEGs in both skin diseases, VHE-only, AD-only, and opposite regulated DEGs were identified. Enrichment analyses and Chi-squared tests were conducted to test for differences in gene set enrichment between both skin diseases. RESULTS: Comparing 3028 DEGs in VHE (1645 up; 1383 down) with 5391 DEGs in AD (3842 up; 1549 down), revealed 1516 shared DEGs (1179 up; 337 down) and 1512 DEGs unique to VHE (466 up, 1046 down). Interferon signalling and necroptosis were significantly more prominent in VHE compared to AD. Downregulated genes identified only in VHE (like DNASE1L2, KRT2, KRT9 and KRT25) indicate an aberrant epidermal differentiation. CONCLUSION: Our study indicates a common pathophysiology between VHE and AD, but also reveals transcriptional differences between VHE and AD.

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.

Exploring Ribosomal Genes as Potential Biomarkers of the Immune Microenvironment in Respiratory Syncytial Virus Infection.

Respiratory syncytial virus (RSV) is the most common pathogen causing acute lower respiratory tract infection in infants and children. Due to limited knowledge of the pathological and molecular mechanisms of immunodeficiency underlying RSV disease, there is currently a lack of an approved and effective RSV vaccine to combat RSV infections. This study aimed to identify genes associated with immune dysfunction using bioinformatics methods to gain insights into the role of dysregulated immune genes in RSV disease progression, and to predict potential therapeutic drugs by targeting dysregulated immune-related genes. 423 immune-related differential genes (DEIRGs) were filtered from the blood samples of 87 healthy individuals and 170 RSV patients. According to CIBERSORT analysis, the blood of RSV patients showed increased infiltration of various immune cells. Subsequently, ten immune-related hub genes were screened via Protein-Protein Interaction Networks. Six signature immune-related genes (RPS2, RPS5, RPS13, RPS14, RPS18, and RPS4X) as candidate characteristic genes for the diagnostic model were identified by Lasso regression. The AUC value of the ROC curve of the six signature genes was 0.884. This result, intriguingly, suggested that all six immune-related genes with a good internal validation effect were ribosome family genes. Finally, through molecular docking analyses targeting these differential immune genes, ADO and fluperlapine were found to have high stable binding to major proteins of important immune-related genes in nine drug-protein interactions. Overall, the present study screened immune-related genes that are dysregulated in the development of RSV disease to investigate the pathogenesis of RSV infection from the standpoint of immune disorders. Unexpectedly, bioinformatics analysis revealed that ribosome family genes may be involved in the immune dysregulation of RSV disease, and these genes as targets formed the basis for potential drug modification candidates in RSV disease.

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.

Identification of Genes Crucial for Biological Processes in Breast Cancer Liver Metastasis Relapse.

Breast cancer, when advancing to a metastatic stage, involves the liver, impacting over 50% of cases and significantly diminishing survival rates. Presently, a lack of tailored therapeutic protocols for breast cancer liver metastasis (BCLM) underscores the need for a deeper understanding of molecular patterns governing this complication. Therefore, by analyzing differentially expressed genes (DEGs) between primary breast tumors and BCLM lesions, we aimed to shed light on the diversities of this process. This research investigated breast cancer liver metastasis relapse by employing a comprehensive approach that integrated data filtering, gene ontology and KEGG pathway analysis, overall survival analysis, identification of the alteration in the DEGs, visualization of the protein-protein interaction network, Signor 2.0, identification of positively correlated genes, immune cell infiltration analysis, genetic alternation analysis, copy number variant analysis, gene-to-mRNA interaction, transcription factor analysis, molecular docking, and identification of potential treatment targets. This study's integrative approach unveiled metabolic reprogramming, suggesting altered PCK1 and LPL expression as key in breast cancer metastasis recurrence.

Investigation on the Potential Functions of ZmEPF/EPFL Family Members in Response to Abiotic Stress in Maize.

Maize is an important crop used for food, feed, and fuel. Abiotic stress is an important factor affecting maize yield. The EPF/EPFL gene family encodes class-specific secretory proteins that play an important role in the response to abiotic stress in plants. In order to explore and utilize the EPF/EPFL family in maize, the family members were systematically identified, and their chromosomal localization, physicochemical properties, cis-acting element prediction in promoters, phylogenetic tree construction, and expression pattern analysis were carried out using bioinformatics techniques. A total of 18 ZmEPF/EPFL proteins were identified in maize, which are mostly alkaline and a small portion acidic. Subcellular localization results showed that ZmEPF6, ZmEPF12, and ZmEPFL2 are localized in the nucleus and cytoplasm. Analysis of cis-acting elements revealed that members of the ZmEPF/EPFL family contain regulatory elements such as light response, anoxic, low temperature, and hormone response regulatory elements. RT-qPCR results showed that these family members are indeed responding to cold stress and hormone treatments. These results of this study provide a theoretical basis for improving the abiotic stress resistance of maize in future research.