Functional Enrichment Analysis Research Articles

The influence of knocking down the expression of low-density lipoprotein receptor associated proteins on the vascular abnormalities in hepatocellular carcinoma and its mechanisms

Objectives: To investigate the effect of the expression of low-density lipoprotein receptor associated protein (LDLR) on the vascular abnormalities in hepatocellular carcinoma (HCC) and its mechanisms. Methods: Based on the information of Oncomine Cancer GeneChip database, we analyzed the correlation between the expression level of LDLR and the expression level of carcinoembryonic antigen (CEA) and CD31 in hepatocellular carcinoma tissues. Lentiviral transfection of short hairpin RNA target genes was used to construct LDLR-knockdown MHCC-97H and HLE hepatocellular carcinoma cells. The differential genes and their expression level changes in LDLR-knockdown hepatocellular carcinoma cells were detected by transcriptome sequencing, real-time fluorescence quantitative polymerase chain reaction, and protein immunoblotting. The gene-related signaling pathways that involve LDLR were clarified by enrichment analysis. The effect of LDLR on CEA was assessed by the detection of CEA content in conditioned medium of hepatocellular carcinoma cells. Angiogenesis assay was used to detect the effect of LDLR on the angiogenic capacity of human umbilical vein endothelial cells, as well as the role of CEA in the regulation of angiogenesis by LDLR. Immunohistochemical staining was used to detect the expression levels of LDLR in 176 hepatocellular carcinoma tissues, and CEA and CD31 in 146 hepatocellular carcinoma tissues, and analyze the correlations between the expression levels of LDLR, CEA, and CD31 in the tissues, serum CEA, and alanine transaminase (ALT). Results: Oncomine database analysis showed that the expressions of LDLR and CEA in the tissues of hepatocellular carcinoma patients with portal vein metastasis were negatively correlated (r=-0.64, P=0.001), whereas the expressions of CEA and CD31 in these tissues were positively correlated ( r=0.46, P=0.010). The transcriptome sequencing results showed that there were a total of 1 032 differentially expressed genes in the LDLR-knockdown group and the control group of MHCC-97H cells, of which 517 genes were up-regulated and 515 genes were down-regulated. The transcript expression level of CEACAM5 was significantly up-regulated in the cells of the LDLR-knockdown group. The Gene Ontology (GO) function enrichment analysis showed that the differential genes were most obviously enriched in the angiogenesis function. The Kyoto Encyclopedia of Genes and Genomes (KEGG) signaling pathway enrichment analysis showed that the relevant pathways involved mainly included the cellular adhesion patch, the extracellular matrix receptor interactions, and the interactions with the extracellular matrix receptors. The CEA content in the conditioned medium of the LDLR-knockdown group was 43.75±8.43, which was higher than that of the control group (1.15±0.14, P＜0.001). The results of angiogenesis experiments showed that at 5 h, the number of main junctions, the number of main segments, and the total area of the lattice formed by HUVEC cells cultured with the conditioned medium of MHCC-97H cells in the LDLR-knockdown group were 295.3±26.4, 552.5±63.8, and 2 239 781.0±13 8211.9 square pixels, which were higher than those of the control group (113.3±23.5, 194.8±36.5, and 660 621.0±280 328.3 square pixels, respectively, all P＜0.01).The number of vascular major junctions, the number of major segments, and the total area of the lattice formed by HUVEC cells cultured in conditioned medium with HLE cells in the LDLR-knockdown group were 245.3±42.4, 257.5±20.4, and 2 535 754.5±249 094.2 square pixels, respectively, which were all higher than those of the control group (113.3±23.5, 114.3±12.2, and 1 565 456.5±219 259.7 square pixels, respectively, all P＜0.01). In the conditioned medium for the control group of MHCC-97H cells,the number of main junctions, the number of main segments, and the total area of the lattice formed by the addition of CEA to cultured HUVEC cells were 178.9±12.0, 286.9±12.3, and 1 966 990.0±126 249.5 spixels, which were higher than those in the control group (119.7±22.1, 202.7±33.7, and 1 421 191.0±189 837.8 square pixels, respectively). The expression of LDLR in hepatocellular carcinoma tissues was not correlated with the expression of CEA, but was negatively correlated with the expression of CD31 (r=-0.167, P=0.044), the level of serum CEA (r=-0.061, P=0.032), and the level of serum ALT(r=-0.147,P=0.05). The expression of CEA in hepatocellular carcinoma tissues was positively correlated with the expression of CD31 (r=0.192, P=0.020). The level of serum CEA was positively correlated with the level of serum ALT (r=0.164, P=0.029). Conclusion: Knocking down LDLR can promote vascular abnormalities in HCC by releasing CEA.

Systematic investigation of Radix Salviae for treating diabetic peripheral neuropathy disease based on network Pharmacology

BACKGROUND Diabetic peripheral neuropathy (DPN) is a debilitating complication of diabetes mellitus with limited available treatment options. Radix Salviae , a traditional Chinese herb, has shown promise in treating DPN, but its therapeutic mech-anisms have not been systematically investigated. AIM Radix Salviae (Danshen in pinin), a traditional Chinese medicine (TCM), is widely used to treat DPN in China. However, the mechanism through which Radix Salviae treats DPN remains unclear. Therefore, we aimed to explore the mechanism of action of Radix Salviae against DPN using network pharmacology. METHODS The active ingredients and target genes of Radix Salviae were screened using the TCM pharmacology database and analysis platform. The genes associated with DPN were obtained from the Gene Cards and OMIM databases, a drug-com-position-target-disease network was constructed, and a protein–protein inter-action network was subsequently constructed to screen the main targets. Gene Ontology (GO) functional annotation and pathway enrichment analysis were performed via the Kyoto Encyclopedia of Genes and Genomes (KEGG) using Bioconductor. RESULTS A total of 56 effective components, 108 targets and 4581 DPN-related target genes of Radix Salviae were screened. Intervention with Radix Salviae for DPN mainly involved 81 target genes. The top 30 major targets were selected for enrichment analysis of GO and KEGG pathways. CONCLUSION These results suggested that Radix Salviae could treat DPN by regulating the AGE-RAGE signaling pathway and the PI3K-Akt signaling pathway. Therefore, Danshen may affect DPN by regulating inflammation and apoptosis.

Blood RNA-sequencing across the continuum of ANA-positive autoimmunity reveals insights into initiating immunopathology

ObjectiveMechanisms underpinning clinical evolution to systemic lupus erythematosus (SLE) from preceding antinuclear antibodies (ANA) positivity are poorly understood. This study aimed to understand blood immune cell transcriptional signatures associated with...

Global transcriptome profiles provide insights into muscle cell development and differentiation on microstructured marine biopolymer scaffolds for cultured meat production

Biomaterial scaffolds play a pivotal role in the advancement of cultured meat technology, facilitating essential processes like cell attachment, growth, specialization, and alignment. Currently, there exists limited knowledge concerning the creation of consumable scaffolds tailored for cultured meat applications. This investigation aimed to produce edible scaffolds featuring both smooth and patterned surfaces, utilizing biomaterials such as salmon gelatin, alginate, agarose and glycerol, pertinent to cultured meat and adhering to food safety protocols. The primary objective of this research was to uncover variations in transcriptomes profiles between flat and microstructured edible scaffolds fabricated from marine-derived biopolymers, leveraging high-throughput sequencing techniques. Expression analysis revealed noteworthy disparities in transcriptome profiles when comparing the flat and microstructured scaffold configurations against a control condition. Employing gene functional enrichment analysis for the microstructured versus flat scaffold conditions yielded substantial enrichment ratios, highlighting pertinent gene modules linked to the development of skeletal muscle. Notable functional aspects included filament sliding, muscle contraction, and the organization of sarcomeres. By shedding light on these intricate processes, this study offers insights into the fundamental mechanisms underpinning the generation of muscle-specific cultured meat.

Prognostic significance and immune landscape of a cell cycle progression-related risk model in bladder cancer

BackgroundA greater emphasis has been placed on the part of cell cycle progression (CCP) in cancer in recent years. Nevertheless, the precise connection between CCP-related genes and bladder cancer (BCa) has remained elusive. This study endeavors to establish and validate a reliable risk model incorporating CCP-related factors, aiming to predict both the prognosis and immune landscape of BCa.MethodsClinical information and RNA sequencing data were collected from the GEO and TCGA databases. Univariate and multivariate Cox regression analyses were conducted to construct a risk model associated with CCP. The performance of the model was assessed using ROC and Kaplan–Meier survival analyses. Functional enrichment analysis was employed to investigate potential cellular functions and signaling pathways. The immune landscape was characterized using CIBERSORT algorithms. Integration of the risk model with various clinical variables led to the development of a nomogram.ResultsTo build the risk model, three CCP-related genes (RAD54B, KPNA2, and TPM1) were carefully chosen. ROC and Kaplan–Meier survival analysis confirm that our model has good performance. About immunological infiltration, the high-risk group showed decreased levels of regulatory T cells and dendritic cells coupled with increased levels of activated CD4 + memory T cells, M2 macrophages, and neutrophils. Furthermore, the nomogram showed impressive predictive power for OS at 1, 3, and 5 years.ConclusionThis study provides new insights into the association between the CCP-related risk model and the prognosis of BCa, as well as its impact on the immune landscape.

Molecular characterization of positively selected genes contributing aquatic adaptation in marine mammals.

Marine mammals, which have evolved independently into three distinct lineages, share common physiological features that contribute to their adaptation to the marine environment. To identify positively selected genes (PSGs) for adaptation to the marine environment using available genomic data from three taxonomic orders: cetaceans, pinnipeds, and sirenians. Based on the genomes within each group of Artiodactyla, Carnivora and Afrotheria, we performed selection analysis using the branch-site model in CODEML. Based on the branch-site model, 460, 614, and 359 PSGs were predicted for the cetaceans, pinnipeds, and sirenians, respectively. Functional enrichment analysis indicated that genes associated with hemostasis were positively selected across all lineages of marine mammals. We observed positive selection signals for the hemostasis and coagulation-related genes plasminogen activator, urokinase (PLAU), multimerin 1 (MMRN1), gamma-glutamyl carboxylase (GGCX), and platelet endothelial aggregation receptor 1 (PEAR1). Additionally, we found out that the sodium voltage-gated channel alpha subunit 9 (SCN9A), serine/arginine repetitive matrix 4 (SRRM4), and Ki-ras-induced actin-interacting protein (KRAP) are under positive selection pressure and are associated with cognition, neurite outgrowth, and IP3-mediated Ca2 + release, respectively. This study will contribute to our understanding of the adaptive evolution of marine mammals by providing information on a group of candidate genes that are predicted to influence adaptation to aquatic environments, as well as their functional characteristics.

Identification of potential candidate genes for the Houyan trait in developing Wulong goose embryos by transcriptomic analysis

ABSTRACT 1. The Wulong goose is a Chinese breed and a source of high-quality meat and eggs. A characteristic of the Wulong goose is that a proportion of the birds do not have eyelids, known as the Huoyon trait. 2. Wulong geese exhibiting the Huoyan trait at embryonic stages of 9 days (E9), 12 days (E12) and 14 days (E14) were selected alongside those with normal eyelids for comprehensive transcriptome sequencing. Differentially expressed gene (DEG) and functional enrichment analyses were performed and finally, eight DEG were chosen to verify the accuracy of qPCR sequencing. 3. Overall, 466, 962 and 550 DEG were obtained from the three control groups, D9 vs. N9, D12 vs. N12 and D14 vs. N14, respectively, by differential analysis (p < 0.05). CDKN1C, CRH, CROCC and TYSND1 were significantly expressed in the three groups. Enrichment analysis revealed the enrichment of CROCC and TYSND1 in pathways of cell cycle process, endocytosis, microtubule-based process, microtubule organising centre organisation, protein processing and protein maturation. CDKN1C and CRH were enriched in the cell cycle and cAMP signalling pathway. 4. Some collagen family genes were detected among the DEGs, including COL3A1, COL4A5, COL4A2 and COL4A1. FREM1 and FREM2 genes were detected in both Huoyan and normal eyelids. There was a significant difference (p < 0.01) in FREM1 expression between ED9 and ED14 in female embryos, but this difference was not observed in male embryos.

Label free quantitative proteomic profiling of serum samples of intellectually disabled young patients revealed dysregulation of complement coagulation and cholesterol cascade systems.

Intellectual disability is a heterogeneous disorder, diagnosed using intelligence quotient (IQ) score criteria. Currently, no specific clinical test is available to diagnose the disease and its subgroups due to inadequate understanding of the pathophysiology. Therefore, current study was designed to explore the molecular mechanisms involved in disease perturbation, and to identify potential biomarkers for disease diagnosis and prognosis. A total of 250 participants were enrolled in this study, including 200 intellectually disabled (ID) subjects from the subgroups (mild, moderate, and severe) with age and gender matched healthy controls (n = 50). Initially, IQ testing score and biochemical profile of each subject was generated, followed by label-free quantitative proteomics of subgroups of IQ and healthy control group through nano-LC/MS- mass spectrometry. A total of 310 proteins were identified, among them198 proteins were common among all groups. Statistical analysis (ANOVA) of the subgroups of ID showed 142 differentially expressed proteins, in comparison to healthy control group. From these, 120 proteins were found to be common among all subgroups. The remaining 22 proteins were categorized as exclusive proteins found only in disease subgroups. Furthermore, the hierarchical cluster analysis (HCL) of common significant proteins was also performed, followed by PANTHER protein classification and GO functional enrichment analysis. Results provides that the datasets of differentially expressed proteins, belong to the categories of immune / defense proteins, transfer carrier proteins, apolipoproteins, complement proteins, protease inhibitors, hemoglobin proteins etc., they are known to involvein immune system, and complement and coagulation pathway cascade and cholesterol metabolism pathway. Exclusively expressed 22 proteins were found to be disease stage specific and strong PPI network specifically those that have significant role in platelets activation and degranulation, such as Filamin A (FLNA). Furthermore, to validate the mass spectrometric findings, four highly significant proteins (APOA4, SAP, FLNA, and SERPING) were quantified by ELISA in all the study subjects. AUROC analysis showed a significant association of APOA4 (0.830), FLNA (0.958), SAP (0.754) and SERPING (0.600) with the disease. Apolipoprotein A4 (APOA4) has a significant role in cholesterol transport, and in modulation of glucose and lipid metabolism in the CNS. Similarly, FLNA has a crucial role in the nervous system, especially in the functioning of synaptic network. Therefore, both APOA4, and FLNA proteins represent good potential for candidate biomarkers for the diagnosis and prognosis of the intellectual disability. Overall, serum proteome of ID patients provides valuable information of proteins/pathways that are altered during ID progression.

NR1I2 as a core biological target in chronic venous ulcer tissues treated with ultrasound therapy.

Ultrasound therapy is a method of applying ultrasonic energy to the stimulation produced by human body to change the function and tissue state of the body in order to achieve the purpose of treating diseases. Chronic venous ulcer is a common chronic skin ulcer. GSE222503 for ultrasound therapy of chronic venous ulcers was downloaded from gene expression omnibus database, which were used to identify differentially expressed genes. Weighted gene co-expression network analysis, functional enrichment analysis, gene set enrichment analysis, immune infiltration analysis and construction and analysis of protein-protein interaction network were performed. Draw gene expression heatmaps. Comparative toxicogenomics database analysis was performed. Two hundred thirty-five differentially expressed genes were obtained. According to gene ontology analysis, in biological process analysis, they were mainly enriched in positive regulation of cellular biosynthetic process, reproductive cell development, vasculogenesis, vascular morphogenesis, and inflammatory response. In cellular component analysis, they were mainly enriched in leading edge of growing cell, extracellular matrix binding organelle, F-actin capping protein complex. In molecular function analysis, they were mainly concentrated in receptor ligand activity, cytokine receptor binding. In Kyoto encyclopedia of genes and genomes analysis, they were mainly enriched in cytokine-cytokine receptor interaction, PI3K-Akt signaling pathway, HIF-1 signaling pathway, heme biosynthesis. In weighted gene co-expression network analysis, the soft threshold power was set to 9. Thirty modules were generated. PF4, NR1I2, TTC16, H3C12, KLRB1, CYP21A2 identified by 4 algorithms (MCC, EPC, closeness, stress). Heatmap of core gene expression showed that H3C12, KLRB1, PF4, NR1I2 were all underexpressed in samples of ultrasound-treated chronic venous ulcers and overexpressed in samples of untreated chronic venous ulcers. Comparative toxicogenomics database analysis showed that H3C12, KLRB1, PF4, NR1I2 are associated with thrombophlebitis, phlebitis, vascular malformations, metabolic syndrome, ulcers, and inflammation. In samples of chronic venous ulcer tissue treated with ultrasound, NR1I2 shows low expression, while in samples of chronic venous ulcer tissue without ultrasound treatment, it shows high expression. This finding suggests a potential role of NR1I2 in the process of ultrasound therapy for chronic venous ulcers, which may be related to the therapeutic effect of ultrasound therapy on chronic venous ulcers.

Analysis and validation of biomarkers of immune cell-related genes in postmenopausal osteoporosis: An observational study.

Postmenopausal osteoporosis (PMOP) is a common metabolic inflammatory disease. In conditions of estrogen deficiency, chronic activation of the immune system leads to a hypo-inflammatory phenotype and alterations in its cytokine and immune cell profile, although immune cells play an important role in the pathology of osteoporosis, studies on this have been rare. Therefore, it is important to investigate the role of immune cell-related genes in PMOP. PMOP-related datasets were downloaded from the Gene Expression Omnibus database. Immune cells scores between high bone mineral density (BMD) and low BMD samples were assessed based on the single sample gene set enrichment analysis method. Subsequently, weighted gene co-expression network analysis was performed to identify modules highly associated with immune cells and obtain module genes. Differential analysis between high BMD and low BMD was also performed to obtain differentially expressed genes. Module genes are intersected with differentially expressed genes to obtain candidate genes, and functional enrichment analysis was performed. Machine learning methods were used to filter out the signature genes. The receiver operating characteristic (ROC) curves of the signature genes and the nomogram were plotted to determine whether the signature genes can be used as a molecular marker. Gene set enrichment analysis was also performed to explore the potential mechanism of the signature genes. Finally, RNA expression of signature genes was validated in blood samples from PMOP patients and normal control by real-time quantitative polymerase chain reaction. Our study of PMOP patients identified differences in immune cells (activated dendritic cell, CD56 bright natural killer cell, Central memory CD4 T cell, Effector memory CD4 T cell, Mast cell, Natural killer T cell, T follicular helper cell, Type 1 T-helper cell, and Type 17 T-helper cell) between high and low BMD patients. We obtained a total of 73 candidate genes based on modular genes and differential genes, and obtained 5 signature genes by least absolute shrinkage and selection operator and random forest model screening. ROC, principal component analysis, and t-distributed stochastic neighbor embedding down scaling analysis revealed that the 5 signature genes had good discriminatory ability between high and low BMD samples. A logistic regression model was constructed based on 5 signature genes, and both ROC and column line plots indicated that the model accuracy and applicability were good. Five signature genes were found to be associated with proteasome, mitochondria, and lysosome by gene set enrichment analysis. The real-time quantitative polymerase chain reaction results showed that the expression of the signature genes was significantly different between the 2 groups. HIST1H2AG, PYGM, NCKAP1, POMP, and LYPLA1 might play key roles in PMOP and be served as the biomarkers of PMOP.

Choline metabolism reprogramming mediates an immunosuppressive microenvironment in non-small cell lung cancer (NSCLC) by promoting tumor-associated macrophage functional polarization and endothelial cell proliferation

IntroductionLung cancer is a prevalent malignancy globally, and immunotherapy has revolutionized its treatment. However, resistance to immunotherapy remains a challenge. Abnormal cholinesterase (ChE) activity and choline metabolism are associated with tumor oncogenesis, progression, and poor prognosis in multiple cancers. Yet, the precise mechanism underlying the relationship between ChE, choline metabolism and tumor immune microenvironment in lung cancer, and the response and resistance of immunotherapy still unclear.MethodsFirstly, 277 advanced non-small cell lung cancer (NSCLC) patients receiving first-line immunotherapy in Sun Yat-sen University Cancer Center were enrolled in the study. Pretreatment and the alteration of ChE after 2 courses of immunotherapy and survival outcomes were collected. Kaplan–Meier survival and cox regression analysis were performed, and nomogram was conducted to identify the prognostic and predicted values. Secondly, choline metabolism-related genes were screened using Cox regression, and a prognostic model was constructed. Functional enrichment analysis and immune microenvironment analysis were also conducted. Lastly, to gain further insights into potential mechanisms, single-cell analysis was performed.ResultsFirstly, baseline high level ChE and the elevation of ChE after immunotherapy were significantly associated with better survival outcomes for advanced NSCLC. Constructed nomogram based on the significant variables from the multivariate Cox analysis performed well in discrimination and calibration. Secondly, 4 choline metabolism-related genes (MTHFD1, PDGFB, PIK3R3, CHKB) were screened and developed a risk signature that was found to be related to a poorer prognosis. Further analysis revealed that the choline metabolism-related genes signature was associated with immunosuppressive tumor microenvironment, immune escape and metabolic reprogramming. scRNA-seq showed that MTHFD1 was specifically distributed in tumor-associated macrophages (TAMs), mediating the differentiation and immunosuppressive functions of macrophages, which may potentially impact endothelial cell proliferation and tumor angiogenesis.ConclusionOur study highlights the discovery of ChE as a prognostic marker in advanced NSCLC, suggesting its potential for identifying patients who may benefit from immunotherapy. Additionally, we developed a prognostic signature based on choline metabolism-related genes, revealing the correlation with the immunosuppressive microenvironment and uncovering the role of MTHFD1 in macrophage differentiation and endothelial cell proliferation, providing insights into the intricate workings of choline metabolism in NSCLC pathogenesis.

Analysis and Validation of the Network Pharmacology of the Mechanism of Glycyrrhetinic Acid for the Treatment of High-Altitude Pulmonary Hypertension

Glycyrrhetinic acid (GA) is a pentacyclic triterpene component in Glycyrrhize glabra L, it has demonstrated an inhibitive effect on high-altitude pulmonary hypertension (HAPH), but the molecular action is still not known. We aimed to explore the mechanism of GA for the treatment of HAPH based on network pharmacology and molecular docking method. Cell experiment validation was also conducted. The targets for GA were screened using the Swiss Target Prediction and Batman databases. The HAPH-related targets were obtained using the GeneCards and OMIM databases. The common targets for diseases and drugs were obtained using a Venn diagram. The core targets were screened using the String database. Then, a component-target-disease diagram and protein–protein interaction (PPI) network mutual assistance diagram were developed using Cytoscape3.9.1 software. GO functional and KEGG pathway enrichment analyses were conducted using the Metascape database. Finally, molecular docking of the target and its corresponding active components were performed using Autodock software. A total of 68 common targets for glycyrrhetinic acid high-altitude pulmonary hypertension were screened out. The core targets include PTGS1, MMP1, SERPINA6, and nitric oxide synthase (NOS2), involving PPAR signal pathway, human cytomegalovirus infection, IL-17 signal pathway, proteoglycans in cancer, and other pathways. The molecular docking affinity was −8.4 kcal·mol−1 in average, indicating that GA has a good binding stability with key target proteins. In the PDGF-BB-induced PASMC proliferation model, PASMC proliferation and the p-p38, p38, p-ERK1/2, and ERK1/2 protein expression were inhibited. The pharmacological mechanism of GA for the treatment of HAPH was characterized by multi-target and multi pathway. GA may serve as a promising therapeutic candidate for HAPH but still needs further in vivo/in vitro experiment.

NET-Related Gene as Potential Diagnostic Biomarkers for Diabetic Tubulointerstitial Injury

Background: Tubulointerstitial injury plays a pivotal role in the progression of diabetic kidney disease (DKD), yet the link between neutrophil extracellular traps (NETs) and diabetic tubulointerstitial injury is still unclear.Methods: We analyzed microarray data (GSE30122) from the Gene Expression Omnibus (GEO) database to identify differentially expressed genes (DEGs) associated with DKD’s tubulointerstitial injury. Functional and pathway enrichment analyses were conducted to elucidate the involved biological processes (BP) and pathways. Weighted gene coexpression network analysis (WGCNA) identified modules associated with DKD. LASSO regression and random forest selected NET-related characteristic genes (NRGs) related to DKD tubulointerstitial injury.Results: Eight hundred ninety-eight DEGs were identified from the GSE30122 dataset. A significant module associated with diabetic tubulointerstitial injury overlapped with 15 NRGs. The hub genes, CASP1 and LYZ, were identified as potential biomarkers. Functional enrichment linked these genes with immune cell trafficking, metabolic alterations, and inflammatory responses. NRGs negatively correlated with glomerular filtration rate (GFR) in the Neph v5 database. Immunohistochemistry (IHC) validated increased NRGs in DKD tubulointerstitial injury.Conclusion: Our findings suggest that the CASP1 and LYZ genes may serve as potential diagnostic biomarkers for diabetic tubulointerstitial injury. Furthermore, NRGs involved in diabetic tubulointerstitial injury could emerge as prospective targets for the diagnosis and treatment of DKD.

Elevated mRNA level indicates FSIP1 promotes EMT and gastric cancer progression by regulating fibroblasts in tumor microenvironment.

Fiber sheath interaction protein 1 (FSIP1) plays a crucial role in cancer development and occurrence, but its influence on gastric cancer is still unclear. In this study, differential mRNA analysis was performed by TCGA database for the Limma analysis algorithm, and the gene ontology, the Kyoto Encyclopedia of Genes and Genomes, and the gene set enrichment analysis (GSEA) were used for bioinformatics functional enrichment analysis. A gastric cancer cell model with FSIP1 mRNA knockdown was constructed by RNA interference. Cell counting kit-8 and transwell migration/invasion assay were performed to verify the cell function, and western blotting was employed to confirm the expression of target genes. The GSEA analysis revealed that FSIP1 was associated with epithelial-mesenchymal transition (EMT). The high expression group also had a significant positive correlation with the markers of fibroblast in tumor microenvironment (TME). Western blotting showed that FSIP1 was generally upregulated in gastric cancer cell lines. FSIP1 mRNA knockdown cell lines inhibited gastric cells proliferation, migration, and metastasis in vitro, and the protein levels of EMT-related markers N-cadherin and vimentin were reduced. Our work proved that FSIP1 promoted EMT by regulating fibroblasts in the TME, thereby promoting the carcinogenic activity of cancer cells in proliferation, invasion, and migration. FSIP1 may take a role of the occurrence and could be a potential therapeutic target and offer a new insight into the underlying mechanism of gastric cancer.

Identification of Molecular Subtypes Associated with PCD in Esophageal Squamous Cell Carcinoma and Analysis of Immune Microenvironment.

Esophageal squamous cell carcinoma (ESCC) is a highly fatal malignancy with increasing incidence, and programmed cell death (PCD) plays an important role in homeostasis. This study aimed to explore the ESCC of heterogeneity based on the PCD signatures for the diagnosis and treatment of patients. The clinical information and RNA-seq data of patients with ESCC and the PCD-related genes set were used to identify PCD signatures.The "limma" package was used to identify the differentially expressed genes (DEGs). "Clusterprofiler" package was used for function enrichment analysis, and the "ConsensusClusterPlus" package was performed for consensus clustering. Finally, the "GSVA" package and the Cibersort algorithm were used for the immune infiltration analysis. We performed differential expression analysis between ESCC and normal samples and identified 1659 DEGs, of which 124 DEGs were PCD genes. Then, the patients were divided into cluster1 and cluster2 based on the expression of 124 PCD genes. There was a significant difference in immune infiltration between the two clusters. The patients in cluster 1 had a higher immune score and more CD56dim natural killer cells, monocytes, activated CD4 T cells, eosinophil, and activated B cells infiltration, while cluster2 had a higher stromal score, more immune regulation, and immune checkpoint genes expression. We identified two clusters based on PCD gene expression and characterized their tumor microenvironment and immune checkpoint difference. Our findings may provide some new insight into the treatment of ESCC.

Causal relationship between inflammatory proteins and glioblastoma: a two-sample bi‑directional mendelian randomization study

Background: Observational studies have indicated a potential correlation between glioblastoma and circulating inflammatory proteins. Further investigation is required to establish a causal relationship between these two factors.Methods: We performed a Mendelian randomization (MR) analysis using genome-wide association study (GWAS) summary of 91 circulating inflammation-related proteins (N = 14,824) to assess their causal impact on glioblastoma. The GWAS summary data for glioblastoma included 243 cases and 287,137 controls. The inverse variance weighted (IVW) method was used as the primary analytical method to assess causality. Four additional MR methods [simple mode, MR-Egger, weighted median, and weighted mode] were used to supplement the IVW results. Furthermore, several sensitivity analyses were performed to assess heterogeneity, horizontal pleiotropy, and stability. Reverse MR analysis was also performed. glioblastoma transcriptomic data from The Cancer Genome Atlas (TCGA) were analyzed to validate the findings obtained through MR, while pathway and functional enrichment analyses were conducted to predict the potential underlying mechanisms.Results: Our findings from employing the inverse variance weighted method in our forward MR analysis provide robust evidence supporting a potential association between glioblastoma and elevated levels of Cystatin D, as well as decreased levels of fibroblast growth factor 21 (FGF21) in the circulation. Moreover, our reverse MR analysis revealed that glioblastoma may contribute to increased concentrations of C-X-C motif chemokine 9 (CXCL9) and Interleukin-33 (IL-33) in the bloodstream. Transcriptomic analysis showed that FGF21 expression was inversely associated with the risk of developing glioblastoma, whereas an increased risk was linked to elevated levels of CXCL9 and IL-33. Pathway and functional enrichment analyses suggested that Cystatin D might exert its effects on glioblastoma through intracellular protein transport, whereas FGF21 might affect glioblastoma via glucose response mechanisms.Conclusion: These results indicate that FGF21 is a significant factor in glioblastoma susceptibility. Glioblastoma also affects the expression of inflammatory proteins such as C-X-C motif chemokine 9 and Interleukin-33, providing new insights into the mechanisms of glioblastoma genesis and clinical research.

Establishment and Validation of Lactate Metabolism-Related Genes as a Prognostic Model for Gastric Cancer.

Gastric Cancer (GC) has become one of the most important causes of cancer-related deaths worldwide due to its intractability. Studying the mechanisms of gastric carcinogenesis, recurrence, and metastasis, and searching for new therapeutic targets have become the main directions of today's gastric cancer research. Lactate is considered a metabolic by-product of tumor aerobic glycolysis, which can regulate tumor development through various mechanisms, including cell cycle regulation, immunosuppression, and energy metabolism. However, the effects of genes related to lactate metabolism on the prognosis and tumor microenvironmental characteristics of GC patients are unknown. <P> </P> Method: In this study, we have collected gene expression data of gastric cancer from The Cancer Genome Atlas (TCGA) and identified differentially expressed genes in gastric cancer using the "Limma" software package. <P> </P> Result: 76 differentially expressed lactate metabolism-related genes were screened, and then the Least Absolute Shrinkage and Selection Operator (LASSO) and Cox regression analysis were employed that identified 8 genes, constructed Lactate Metabolism-related gene signals (LMRs), and verified the reliability of the prognostic risk mapping by using TCGA training set and TCGA internal test set. Finally, the functional enrichment analysis was employed to identify the molecular mechanism. <P> </P> Conclusion: Eight lactate metabolism-related genes were constructed into a new predictive signal that better predicted the overall survival of gastric cancer patients and can guide clinical decisions for more precise and personalized treatment.

DNA-Binding Proteins and Passenger Proteins in Plasma DNA–Protein Complexes: Imprint of Parental Cells or Key Mediators of Carcinogenesis Processes?

Knowledge of the composition of proteins that interact with plasma DNA will provide a better understanding of the homeostasis of circulating nucleic acids and the various modes of interaction with target cells, which may be useful in the development of gene targeted therapy approaches. The goal of the present study is to shed light on the composition and architecture of histone-containing nucleoprotein complexes (NPCs) from the blood plasma of healthy females (HFs) and breast cancer patients (BCPs) and to explore the relationship of proteins with crucial steps of tumor progression: epithelial–mesenchymal transition (EMT), cell proliferation, invasion, cell migration, stimulation of angiogenesis, and immune response. MALDI-TOF mass spectrometric analysis of NPCs isolated from blood samples using affine chromatography was performed. Bioinformatics analysis showed that the shares of DNA-binding proteins in the compositions of NPCs in normal and cancer patients are comparable and amount to 40% and 33%, respectively; in total, we identified 38 types of DNA-binding motifs. Functional enrichment analysis using FunRich 3.13 showed that, in BCP blood, the share of DNA-binding proteins involved in nucleic acid metabolism increased, while the proportion of proteins involved in intercellular communication and signal transduction decreased. The representation of NPC passenger proteins in breast cancer also changes: the proportion of proteins involved in transport increases and the share of proteins involved in energy biological pathways decreases. Moreover, in the HF blood, proteins involved in the processes of apoptosis were more represented in the composition of NPCs and in the BCP blood—in the processes of active secretion. For the first time, bioinformatics approaches were used to visualize the architecture of circulating NPCs in the blood and to show that breast cancer has an increased representation of passenger proteins involved in EMT, cell proliferation, invasion, cell migration, and immune response. Using breast cancer protein data from the Human Protein Atlas (HPA) and DEPC, we found that 86% of NPC proteins in the blood of BCPs were not previously annotated in these databases. The obtained data may indirectly indicate directed protein sorting in NPCs, which, along with extracellular vesicles, can not only be diagnostically significant molecules for liquid biopsy, but can also carry out the directed transfer of genetic material from donor cells to recipient cells.

A cuproptosis-based prognostic model for predicting survival in low-grade glioma.

It is unknown what variables contribute to the formation and multiplication of low-grade gliomas (LGG). An emerging process of cell death is called cuproptosis. Our research aims to increase therapeutic options and gain a better understanding of the role that cuproptosis-related genes play in the physical characteristics of low-grade gliomas. The TCGA database was utilized to find cuproptosis genes that may be used to develop LGG risk model. Cox analysis in three different formats: univariate, multivariate, and LASSO. The gene signature's independent predictive ability was assessed using ROC curves and Cox regression analysis based on overall survival. Use of CGGA data and nomogram model for external validation Immunohistochemistry, gene mutation, and functional enrichment analysis are also employed to clarify risk models' involvement. Next, we analyzed changes in the immunological microenvironment in the risk model and forecasted possible chemotherapeutic drugs to target each group. Finally, we validated the protein expression levels of cuproptosis-related genes using LGG and adjacent normal tissues in a small self-case-control study. This study developed a glioma predictive model based on five cuproptosis-associated genes. Compared to the high-risk group, the low-risk group's OS was significantly longer. The ROC curves showed high genetic signature performance in both groups. The signature-based categorisation was also linked to clinical characteristics and molecular subgroups. The prognosis of individuals with grade 2 or 3 glioma is also influenced by our risk model. Immunological testing revealed that the high-risk group had more immune cells and immunological function. The risk model also predicted immunotherapy and chemotherapy medication results. Also, this study confirmed that the expression of cuproptosis-related genes by Western blot. We developed a prediction model for LGG patients using genes associated with cuproptosis. With acceptable prediction performance, this risk model may effectively stratify the prognosis of glioma patients.

Bioinformatics Analysis of Hub Genes in Craniofacial Microsomia Combined With Congenital Heart Disease

Objective: The primary objective of this study was to investigate potential mechanisms and explore hub genes of craniofacial microsomia (CFM) patients associated with congenital heart defects (CHD). Methods: Initially, the authors acquired target gene data related to CFM and congenital cardiac anomalies. Subsequently, the authors established a protein-protein interaction (PPI) network. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses and molecular complex detection were conducted using Metascape. Finally, the authors hub genes were screened by the cytoHubba plugin. Results: A total of 43 CFM genes and 120 optimal CHD candidate genes were selected. The PPI networks for pathogenic genes contained 163 nodes and 1179 edges. Functional enrichment analysis largely focused on tissue formation and development. Five modules were identified from the PPI network, and 7 hub genes were screened out. The genes most relevant to CFM associated with congenital cardiac anomalies pathogenesis included fibroblast growth factor 3, GATA binding protein 3, nuclear factor of activated T cells 1, histone cell cycle regulator, EPAS1, mitogen-activated protein kinase 1, and CRK like proto-oncogene, adaptor protein. Conclusions: This study identified some significant hub genes, pathways, and modules of CFM associated with CHD by bioinformatics analyses. Our findings indicate that gene subfamilies fibroblast growth factor 3, GATA binding protein 3, nuclear factor of activated T cells 1, histone cell cycle regulator, EPAS1, mitogen-activated protein kinase 1, and CRK like proto-oncogene, adaptor protein may have had significant involvement in both CFM and CHD.