Gene Enrichment Analysis Research Articles

Comprehensive pharmacological and experimental study of Ginsenoside Re as a potential therapeutic agent for non-alcoholic fatty liver disease

ObjectiveGinsenoside Re, a unique tetracyclic triterpenoid compound found in ginseng, has been suggested in previous reports to improve non-alcoholic fatty liver disease (NAFLD) by modulating lipid imbalance. This study aims to elucidate the potential mechanisms of Ginsenoside Re in treating NAFLD through a combination of bioinformatics analysis and biological experiments. MethodsNetwork pharmacology methods were employed to systematically depict the effective components and mechanisms of Ginsenoside Re in improving NAFLD. Molecular docking was utilized to evaluate the binding affinity of Ginsenoside Re with NAFLD-related targets and identify potential targets. NAFLD-related target genes were obtained from the GEO database for gene enrichment analysis, revealing signaling pathways, biological processes, and gene differential expression. Finally, animal experiments were conducted to verify the mechanism of action of Ginsenoside Re in NAFLD. ResultsNetwork pharmacology analysis revealed that Ginsenoside Re improves NAFLD by modulating targets such as AKT1 and TLR4, findings corroborated by molecular docking, GEO database analysis, and experimental validation. Further investigation found that Ginsenoside Re ameliorates lipid metabolism disorders and inflammatory responses induced by NAFLD by modulating the PI3K/AKT and TLR4/NF-κB signaling pathways. ConclusionOur study demonstrates the pharmacological effects of Ginsenoside Re in treating NAFLD, implicating multiple components, targets, and pathways. This provides a solid foundation for considering Ginsenoside Re as an alternative therapy for NAFLD, with promising clinical applications.

Unique Splicing of Lrp5 in the Brain: A New Player in Neurodevelopment and Brain Maturation.

Low-density lipoprotein receptor-related protein 5 (LRP5) is a constitutively expressed receptor with observed roles in bone homeostasis, retinal development, and cardiac metabolism. However, the function of LRP5 in the brain remains unexplored. This study investigates LRP5's role in the central nervous system by conducting an extensive analysis using RNA-seq tools and in silico assessments. Two protein-coding Lrp5 transcripts are expressed in mice: full-length Lrp5-201 and a truncated form encoded by Lrp5-202. Wt mice express Lrp5-201 in the liver and brain and do not express the truncated form. Lrp5-/- mice express Lrp5-202 in the liver and brain and do not express Lrp5-201 in the liver. Interestingly, Lrp5-/- mouse brains show full-length Lrp5-201 expression, suggesting that LRP5 has a role in preserving brain function during development. Functional gene enrichment analysis on RNA-seq unveils dysregulated expression of genes associated with neuronal differentiation and synapse formation in the brains of Lrp5-/- mice compared to Wt mice. Furthermore, Gene Set Enrichment Analysis highlights downregulated expression of genes involved in retinol and linoleic acid metabolism in Lrp5-/- mouse brains. Tissue-specific alternative splicing of Lrp5 in Lrp5-/- mice supports that the expression of LRP5 in the brain is needed for the correct synthesis of vitamins and fatty acids, and it is indispensable for correct brain development.

Identification and Characterization of the miRNA Transcriptome Controlling Green Pigmentation of Chicken Eggshells

Green eggs are mainly caused by inserting an avian endogenous retrovirus (EVA-HP) fragment into the SLCO1B3 gene. Although the genotypes for this insertion allele are consistent, eggshell color (ESC) may vary after a peak laying period; light-colored eggs are undesired by consumers and farmers and result in financial loss, so it is necessary to resolve this problem. miRNAs are small non-coding RNAs that exert essential functions in animal development and diseases. However, the regulatory miRNAs and detailed molecular mechanisms regulating eggshell greenness remain unclear. In the present study, we determined the genotype of green-eggshell hens through the detection of a homozygous allele insertion in the SLCO1B3 gene. The shell gland epithelium was obtained from green-eggshell hens that produced white and green shell eggs to perform transcriptome sequencing and investigate the important regulatory mechanisms that influence the ESC. Approximately 921 miRNAs were expressed in these two groups, which included 587 known miRNAs and 334 novel miRNAs, among which 44 were differentially expressed. There were 22 miRNAs that were significantly upregulated in the green and white groups, respectively, which targeted hundreds of genes, including KIT, HMOX2, and several solute carrier family genes. A Gene Ontology enrichment analysis of the target genes showed that the differentially expressed miRNA-targeted genes mainly belonged to the functional categories of homophilic cell adhesion, gland development, the Wnt signaling pathway, and epithelial tube morphogenesis. A KEGG enrichment analysis showed that the Hedgehog signaling pathway was significantly transformed in this study. The current study provides an overview of the miRNA expression profiles and the interaction between the miRNAs and their target genes. It provides valuable insights into the molecular mechanisms underlying green eggshell pigmentation, screening more effective hens to produce stable green eggs and obtaining higher economic benefits.

Activation of non-classical Wnt signaling pathway effectively enhances HLA-A presentation in acute myeloid leukemia.

The escape from T cell-mediated immune surveillance is an important cause of death for patients with acute myeloid leukemia (AML). This study aims to identify clonal heterogeneity in leukemia progenitor cells and explore molecular or signaling pathways associated with AML immune escape. Single-cell RNA sequencing (scRNA-seq) was performed to identified AML-related cellular subsets, and intercellular communication was analyzed to investigate molecular mechanisms associated with AML immune escape. Bulk RNA sequencing (RNA-seq) was performed to screen differentially expressed genes (DEGs) related to hematopoietic stem cell progenitors (HSC-Prog) in AML, and critical ore signaling pathways and hub genes were found by Gene Set Enrichment Analysis (GSEA), Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis. The mRNA level of the hub gene was verified using quantitative real-time PCR (qRT-PCR) and the protein level of human leukocyte antigen A (HLA-A) using enzyme-linked immuno sorbent assay (ELISA). scRNA-seq analysis revealed a large heterogeneity of HSC-Prog across samples, and the intercellular communication analysis indicated a strong association between HSC-Prog and CD8+-T cells, and HSC-Prog also had an association with HLA-A. Transcriptome analysis identified 1748 DEGs, enrichment analysis results showed that non-classical wnt signaling pathway was associated with AML, and 4 pathway-related genes (RHOA, RYK, CSNK1D, NLK) were obtained. After qRT-PCR and ELISA validation, hub genes and HLA-A were found to be down-regulated in AML and up-regulated after activation of the non-classical Wnt signaling pathway. In this study, clonal heterogeneity of HSC-Prog cells in AML was identified, non-classical wnt signaling pathways associated with AML were identified, and it was verified that HLA-A could be upregulated by activation of non-classical wnt signaling, thereby increasing antigen presentation.

Discovering New QTNs and Candidate Genes Associated with Rice-Grain-Related Traits within a Collection of Northeast Core Set and Rice Landraces.

Grain-related traits are pivotal in rice cultivation, influencing yield and consumer preference. The complex inheritance of these traits, involving multiple alleles contributing to their expression, poses challenges in breeding. To address these challenges, a multi-locus genome-wide association study (ML-GWAS) utilizing 35,286 high-quality single-nucleotide polymorphisms (SNPs) was conducted. Our study utilized an association panel comprising 483 rice genotypes sourced from a northeast core set and a landraces set collected from various regions in India. Forty quantitative trait nucleotides (QTNs) were identified, associated with four grain-related traits: grain length (GL), grain width (GW), grain aroma (Aro), and length-width ratio (LWR). Notably, 16 QTNs were simultaneously identified using two ML-GWAS methods, distributed across multiple chromosomes. Nearly 258 genes were found near the 16 significant QTNs. Gene annotation study revealed that sixty of these genes exhibited elevated expression levels in specific tissues and were implicated in pathways influencing grain quality. Gene ontology (GO), trait ontology (TO), and enrichment analysis pinpointed 60 candidate genes (CGs) enriched in relevant GO terms. Among them, LOC_Os05g06470, LOC_Os06g06080, LOC_Os08g43470, and LOC_Os03g53110 were confirmed as key contributors to GL, GW, Aro, and LWR. Insights from QTNs and CGs illuminate rice trait regulation and genetic connections, offering potential targets for future studies.

Computational Drug Discovery in Diaphragm Dysfunction via Text Mining and Biomedical Database.

The diaphragm, which is crucial for ventilation, is the primary muscle responsible for inspiration. Patients with severe burns who experience diaphragmatic dysfunction have an increased risk of mortality. Unfortunately, there are currently no effective medications available to prevent or treat this condition. The objective of our study is to utilize bioinformatics to identify potential genes and drugs associated with diaphragmatic dysfunction. In this study, text-mining techniques were utilized to identify genes associated with diaphragmatic dysfunction and recovery. Common genes were then analyzed using GO and KEGG pathway analysis, as well as protein-protein interaction network analysis. The obtained hub genes were processed using Cytoscape software, and their expression levels in diaphragmatic dysfunction were validated using quantitative real-time polymerase chain reaction (qRT-PCR) in severe burn rats. Genes that were confirmed were then examined in drug-gene interaction databases to identify potential drugs associated with these genes. Our analysis revealed 96 genes that were common to both the "diaphragm dysfunction" and "functional recovery" text mining concepts. Gene enrichment analysis identified 19 genes representing 10 pathways. qRT-PCR showed a significant increase in expression levels of 13 genes, including CCL2, CCL3, CD4, EGF, HGF, IFNG, IGF1, IL17A, IL6, LEP, PTGS2, TGFB1, and TNF, in samples with diaphragmatic dysfunction. Additionally, we found that a total of 56 drugs targeted 5 potential genes. These findings provide new insights into the development of more effective drugs for treating diaphragmatic dysfunction and also present substantial opportunities for researching new target pharmacology and promoting drugs in the pharmaceutical industry.

Copy number variations affecting growth curve parameters in a crossbred chicken population

Copy number variations (CNVs) are key structural variations in the genome and may contribute to phenotypic differences. In this study, we used a F2 chicken population created from reciprocal crossing between fast-growing Arian broiler line and Urmia native chickens. The chickens were genotyped by 60 K SNP BeadChip, and PennCNV algorithm was used to detect genome-wide CNVs. The growth curve parameters of W0, k, L, Wf, Wi, ti and average GR were used as phenotypic data. The association between CNV and growth curve parameters was carried out using the CNVRanger R/Bioconductor package. Five CNV regions (CNVRs) were chosen for the validation experiment using qPCR. Gene enrichment analysis was done using WebGestalt. The STRING database was used to search for significant pathways. The results identified 966 CNVs and 600 CNVRs including 468 gains, 67 losses, and 65 both events on autosomal chromosomes. Validation of the CNVRs obtained from the qPCR assay were 79 % consistent with the prediction by PennCNV. A total of 43 significant CNVs were obtained for the seven growth curve parameters. The 416 genes annotated for significant CNVs. Six genes out of 416 genes were most related to growth curve parameters. These genes were LCP2, Dock2, CD80, CYFIP1, NIPA1 and NIPA2. Some of these genes in their biological process were associated with the growth, reproduction and development of cells or organs that ultimately lead to the growth of the body. The results of the study could pave the way for better understanding the molecular process of CNVs and growth curve parameters in birds.

Role of SYT11 in human pan-cancer using comprehensive approaches

BackgroundSynaptotagmin 11 (SYT11) plays a pivotal role in neuronal vesicular trafficking and exocytosis. However, no independent prognostic studies have focused on various cancers. In this study, we aimed to summarize the clinical significance and molecular landscape of SYT11 in various tumor types.MethodsUsing several available public databases, we investigated abnormal SYT11 expression in different tumor types and its potential clinical association with prognosis, methylation profiling, immune infiltration, gene enrichment analysis, and protein–protein interaction analysis, and identified common pathways.ResultsTCGA and Genotype-Tissue Expression (GTEx) showed that SYT11 was widely expressed across tumor and corresponding normal tissues. Survival analysis showed that SYT11 expression correlated with the prognosis of seven cancer types. Additionally, SYT11 mRNA expression was not affected by promoter methylation, but regulated by certain miRNAs and associated with cancer patient prognosis. In vitro experiments further verified a negative correlation between the expression of SYT11 and miR-19a-3p in human colorectal, lung, and renal cancer cell lines. Moreover, aberrant SYT11 expression was significantly associated with immune infiltration. Pathway enrichment analysis revealed that the biological and molecular processes of SYT11 were related to clathrin-mediated endocytosis, Rho GTPase signaling, and cell motility-related functions.ConclusionsOur results provide a clear understanding of the role of SYT11 in various cancer types and suggest that SYT11 may be of prognostic and clinical significance.

Identification of key genes as potential diagnostic biomarkers in sepsis by bioinformatics analysis.

Sepsis, an infection-triggered inflammatory syndrome, poses a global clinical challenge with limited therapeutic options. Our study is designed to identify potential diagnostic biomarkers of sepsis onset in critically ill patients by bioinformatics analysis. Gene expression profiles of GSE28750 and GSE74224 were obtained from the Gene Expression Omnibus (GEO) database. These datasets were merged, normalized and de-batched. Weighted gene co-expression network analysis (WGCNA) was performed and the gene modules most associated with sepsis were identified as key modules. Functional enrichment analysis of the key module genes was then conducted. Moreover, differentially expressed gene (DEG) analysis was conducted by the "limma" R package. Protein-protein interaction (PPI) network was created using STRING and Cytoscape, and PPI hub genes were identified with the cytoHubba plugin. The PPI hub genes overlapping with the genes in key modules of WGCNA were determined to be the sepsis-related key genes. Subsequently, the key overlapping genes were validated in an external independent dataset and sepsis patients recruited in our hospital. In addition, CIBERSORT analysis evaluated immune cell infiltration and its correlation with key genes. By WGCNA, the greenyellow module showed the highest positive correlation with sepsis (0.7, p=2e-19). 293 DEGs were identified in the merged datasets. The PPI network was created, and the CytoHubba was used to calculate the top 20 genes based on four algorithms (Degree, EPC, MCC, and MNC). Ultimately, LTF, LCN2, ELANE, MPO and CEACAM8 were identified as key overlapping genes as they appeared in the PPI hub genes and the key module genes of WGCNA. These sepsis-related key genes were validated in an independent external dataset (GSE131761) and sepsis patients recruited in our hospital. Additionally, the immune infiltration profiles differed significantly between sepsis and non-sepsis critical illness groups. Correlations between immune cells and these five key genes were assessed, revealing that plasma cells, macrophages M0, monocytes, T cells regulatory, eosinophils and NK cells resting were simultaneously and significantly associated with more than two key genes. This study suggests a critical role of LTF, LCN2, ELANE, MPO and CEACAM8 in sepsis and may provide potential diagnostic biomarkers and therapeutic targets for the treatment of sepsis.

Precision Drug Repurposing: A Deep Learning Toolkit for Identifying 34 Hyperpigmentation-Associated Genes and Optimizing Treatment Selection.

Hyperpigmentation is a skin disorder characterized by a localized darkening of the skin due to increased melanin production. When patients fail first line topical treatments, secondary treatments such as chemical peels and lasers are offered. However, these interventions are not devoid of risks and are associated with postinflammatory hyperpigmentation. In the quest for novel therapeutic potentials, this study aims to investigate computational methods in the identification of new targeted therapies in the treatment of hyperpigmentation. We used a comprehensive approach, which integrated text mining, interpreting gene lists through enrichment analysis and integration of diverse biological information (GeneCodis), protein-protein association networks and functional enrichment analyses (STRING), and plug-in network centrality parameters (Cytoscape) to pinpoint genes closely associated with hyperpigmentation. Subsequently, analysis of drug-gene interactions to identify potential drugs (Cortellis) was utilized to select drugs targeting these identified genes. Lastly, we used Deep Learning Based Drug Repurposing Toolkit (DeepPurpose) to conduct drug-target interaction predictions to ultimately identify candidate drugs with the most promising binding affinities. Thirty-four hyperpigmentation-related genes were identified by text mining. Eight key genes were highlighted by utilizing GeneCodis, STRING, Cytoscape, gene enrichment, and protein-protein interaction analysis. Thirty-five drugs targeting hyperpigmentation-associated genes were identified by Cortellis, and 29 drugs, including 16 M2PK1 inhibitors, 11 KRAS inhibitors, and 2 BRAF inhibitors were recommended by DeepPurpose. The study highlights the promise of advanced computational methodology for identifying potential treatments for hyperpigmentation.

M133S mutation possibly involve in the ER stress and mitophagy pathway in maintenance hemodialysis patients with occult hepatitis B infection

Occult hepatitis B virus infection (OBI) is characterized by the presence of HBV DNA in the absence of detectable HBsAg. OBI is an important risk factor for cirrhosis and hepatocellular carcinoma, but its pathogenesis has not been fully elucidated. Mutations in the HBV preS/S genes can lead to impaired secretion of either HBsAg or S-protein resulting in the accumulation of defective viruses or S protein in cells. In our previous work, the M133S mutation was present in the HBV S gene of maintenance hemodialysis (MHD) patients with OBI. In this study, we investigated the potential role of amino acid substitutions in S proteins in S protein production and secretion through the construction of mutant S gene plasmids, structural prediction, transcriptome sequencing analysis, and in vitro functional studies. Protein structure prediction showed that the S protein M133S mutant exhibited hydrophilic modifications, with greater aggregation and accumulation of the entire structure within the membrane phospholipid bilayer. Differential gene enrichment analysis of transcriptome sequencing data showed that differentially expressed genes were mainly concentrated in protein processing in the endoplasmic reticulum (ER). The expression of heat shock family proteins and ER chaperone molecules was significantly increased in the wild-type and mutant groups, whereas the expression of mitochondria-associated proteins was decreased. Immunofluorescence staining and protein blotting showed that the endoplasmic reticulum-associated protein PDI, the autophagy marker LC3, and the lysosome-associated protein LAMP2 co-localized with the S proteins in the wild-type and mutant strains, and their expression was increased. The mitochondria-associated TOMM20 protein was also co-expressed with the S protein, but expression was significantly reduced in the mutant. The M133S mutation in the S gene is expressed as a defective and misfolded protein that accumulates in the endoplasmic reticulum causing secretion-impaired endoplasmic reticulum stress, which in turn triggers mitochondrial autophagy and recruits lysosomes to fuse with the autophagosome, leading to mitochondrial clearance. This study preliminarily demonstrated that the mutation of M133S in the S gene can cause OBI and is associated with disease progression, providing a theoretical basis for the diagnosis and treatment of OBI.

A Copernican revolution of multigenic analysis: A retrospective study on clinical exome sequencing in unclear genetic disorders

Despite the inevitable shift in medical practice towards a deeper understanding of disease etiology and progression through multigenic analysis, the profound historical impact of Mendelian diseases cannot be overlooked. These diseases, such as cystic fibrosis and thalassemia, are characterized by a single variant in a single gene leading to clinical conditions, and have significantly shaped our medical knowledge and treatments. In this respect, the monogenic approach inevitably results in the underutilization of Next-Generation Sequencing (NGS) data.Herein, a retrospective study was performed to assess the diagnostic value of the clinical exome in 32 probands with specific phenotypic characteristics (patients with autoinflammation and immunological dysregulation, N = 20; patients diagnosed with Hemolytic uremic syndrome N = 9; and patients with Waldenström macroglobulinemia, N = 3). A gene enrichment analysis was performed using the *. VCF file generated by SOPHiA-DDM-v4. This analysis selected a subset of genes containing pathogenic or likely pathogenic variants with autosomal dominant (AD) inheritance. In addition, all variants of uncertain significance (VUS) were included, filtered by AD inheritance mode, the presence of compound heterozygotes, and a minor allele frequency (MAF) cutoff of 0.05 %.The aim of the pipeline described here is based on a perspective shift that focuses on analyzing patients’ gene assets, offering new light on the complex interplay between genetics and disease presentation. Integrating this approach into clinical practices could significantly enhance the management of patients with rare genetic disorders.

In silico identification of differentially expressed microRNAs in thyroid cancer

BackgroundAbnormal expression of microRNAs is one of the crucial features contributing to the thyroid cancer (TC) progression. However, a comprehensive identification of the dysregulated microRNA profile and the associated molecular pathways that underlie the TC pathogenesis has not been completely provided. In the current study, bioinformatic analysis tools and microarray datasets were used to evaluate the biological roles of differentially expressed microRNAs and their targets in TC. MethodsGEO2R was used to identify differentially expressed microRNAs in TC samples. The mRNA targets of these microRNAs were predicted using different databases. DAVID and Reactome databases were used to perform gene ontology and pathway enrichment analyses of target genes. Then, the protein-protein interaction networks were constructed among them through the STRING database. MCODE was applied to screen hub genes. The prognostic values of hub genes were examined in TCGA THCA dataset using GEPIA2 platform. The relationship between hub genes and the ERBB2 protein was revealed using GeneMANIA. ResultsWe found a significant decrease in five microRNAs and a significant increase in five others in TC samples. Target genes of upregulated and downregulated microRNAs in TC were associated with ERBB2 signaling and ion exchanger pathways, respectively. CUX2 and DCUN1D4, the targets of upregulated microRNAs, were downregulated, whereas AP1S1, the target of downregulated microRNAs, were overexpressed in TCGA THCA samples. EZR and CUL5 were mediators for the interaction of ERBB2 with CUX2 or DCUN1D4, respectively. ConclusionWe suggest that CUX2/DCUN1D4 and AP1S1 may act as tumor suppressor and oncogene in TC onset and progression, respectively.

Early transcriptional similarities between two distinct neural lineages during ascidian embryogenesis

In chordates, the central nervous system arises from precursors that have distinct developmental and transcriptional trajectories. Anterior nervous systems are ontogenically associated with ectodermal lineages while posterior nervous systems are associated with mesoderm. Taking advantage of the well-documented cell lineage of ascidian embryos, we asked to what extent the transcriptional states of the different neural lineages become similar during the course of progressive lineage restriction. We performed single-cell RNA sequencing (scRNA-seq) analyses on hand-dissected neural precursor cells of the two distinct lineages, together with those of their sister cell lineages, with a high temporal resolution covering five successive cell cycles from the 16-cell to neural plate stages. A transcription factor binding site enrichment analysis of neural specific genes at the neural plate stage revealed limited evidence for shared transcriptional control between the two neural lineages, consistent with their different ontogenies. Nevertheless, PCA analysis and hierarchical clustering showed that, by neural plate stages, the two neural lineages cluster together. Consistent with this, we identified a set of genes enriched in both neural lineages at the neural plate stage, including miR-124, Celf3.a, Zic.r-b, and Ets1/2. Altogether, the current study has revealed genome-wide transcriptional dynamics of neural progenitor cells of two distinct developmental origins. Our scRNA-seq dataset is unique and provides a valuable resource for future analyses, enabling a precise temporal resolution of cell types not previously described from dissociated embryos.

Capturing the antimicrobial profile of Paeonia officinalis, Jasminum officinale and Rosa damascene against methicillin resistant Staphylococcus aureus with metabolomics analysis and network pharmacology

In the current study, we evaluated the in vitro antibacterial efficacy of the roots’ extracts of Jasminum officinale, Rosa damascene and Paeonia officinalis against MRSA (methicillin-resistant Staphylococcus aureus) by well diffusion technique. The root extract of P. officinalis exerted a potent anti-MRSA with MIC 0.4673 µg/ml, while both J. officinale and R. damascene exhibited very weak activity. Therefore, chemical profiling of the crude extract P. officinalis roots assisted by LC-HR-ESI-MS was performed and led to the dereplication of twenty metabolites of different classes, in which terpenes are the most abundant compounds. On a molecular level, network pharmacology was used to determine the targets of active metabolites to bacterial infections, particularly MRSA. Online databases PubChem, UniProt, STRING, and Swiss Target Prediction were used. In addition to using CYTOSCAPE software to display and analyze the findings, ShinyGO and FunRich tools were used to identify the gene enrichment analysis to the set of recognized genes. The results detected the identified metabolites were annotated by 254 targets. ALB, ACHE, TYMS, PRKCD, PLG, MMP9, MMP2, ERN1, EDNRA, BRD4 were found to be associated with MRSA infection. The top KEGG pathway was the vascular smooth muscle contraction pathway according to enrichment FDR. The present study suggested a possible implication of P. officinalis roots as a potent candidate having a powerful antibacterial activity against MRSA.

Assessment of long-term stored specimens in the Siriraj Hospital colorectal cancer biobank for RNA sequencing and profiling

Abstract Objectives Biobanks play an important role in advancing cancer research, yet concerns persist regarding the molecular integrity of long-term stored samples. This study assessed fresh frozen (FF) tissues and formalin-fixed paraffin-embedded (FFPE) tissues from the Siriraj Hospital colorectal cancer (CRC) biobank collected during two distinct periods (2011–2012 and 2020–2021). Methods In 2022, FF and FFPE primary cancer tissues from 75 CRC patients were evaluated. RNA sequencing (RNA-Seq) analyzed comprehensive gene expression profiles in FF tissues preserved at −80 °C, while nCounter profiling elucidated cancer-specific RNA transcripts in FFPE tissues stored at ambient temperature. Comparative analyses were conducted between specimens from 2011 to 2012 and 2020–2021. Results The FF tissues stored for approximately 10.5 years were well-suited for RNA-Seq compared to the intact tissues preserved for 1.5 years. Despite consistencies in RNA quantity, RNA integrity, amount of sequencing reads, and CRC gene signature, gene enrichment analysis revealed the decreased ribosome biogenesis, spliceosome and antifolate resistance pathways in the 2011–2012 group. Moreover, the FFPE tissues also showed no alteration in RNA quantity between the two periods, and the nCounter profiling demonstrated comparable CRC-specific gene counts in spite of the significant reduction of raw counts in the 2011–2012 group. Conclusions We report that FF tissues from CRC patients, stored for 10 years, are viable for whole transcriptome RNA-Seq, despite altered pathways such as ribosome biogenesis, spliceosome, and antifolate resistance. Moreover, 10-year-stored FFPE CRC tissues remain suitable for specific RNA profiling using the nCounter pan-cancer panel, despite a significant reduction in raw counts. These findings underscore the enduring contribution of biobanks to molecular research, highlighting their value a decade post-collection.

Targeting dendritic cell activation: the therapeutic impact of paeoniflorin in cortosteroid-dependent dermatitis management.

This study investigates the mechanism through which paeoniflorin inhibits TSLP expression to regulate dendritic cell activation in corticosteroid-dependent dermatitis treatment. Utilizing databases like TCMSP, we identified paeoniflorin's components, targets, and constructed networks. Molecular docking and gene enrichment analysis helped pinpoint key targets and pathways affected by paeoniflorin. In vitro and in vivo models were used to study CD80, CD86, cytokines, T-cell activation, skin lesions, histopathological changes, TSLP, CD80, and CD86 expression. Our study revealed paeoniflorin's active constituent targeting IL-6 in corticosteroid-dependent dermatitis. In vitro experiments demonstrated reduced TSLP expression, CD80, CD86, and cytokine secretion post-paeoniflorin treatment. In vivo, paeoniflorin significantly decreased skin lesion severity, cytokine levels, TSLP, CD80, and CD86 expression. The study highlights paeoniflorin's efficacy in inhibiting TSLP expression and suppressing dendritic cell activation in corticosteroid-dependent dermatitis, suggesting its potential as a therapeutic intervention. Additionally, it offers insights into the complex molecular mechanisms underlying paeoniflorin's anti-inflammatory properties in treating corticosteroid-dependent dermatitis.

The diagnostic value of inflammation-related genes in bronchopulmonary dysplasia

This study aims to explore the diagnostic value of inflammation-related genes in peripheral blood mononuclear cells in bronchopulmonary dysplasia (BPD). By using bioinformatics analysis, three datasets including GSE32472, GSE125873, and GSE220135, which contain whole-genome expression profile data of 251 neonates, were included. The GSE32472 dataset was used as a training dataset to detect differentially expressed genes between non-BPD and BPD neonates in peripheral blood mononuclear cells. The gene enrichment analysis (GSEA) was used to detect the pathway enrichment of up-regulated genes in BPD newborns. The main regulatory factors analysis (MRA) algorithm was used to filter the main regulatory genes in the inflammation-related pathway (GO:0006954). After obtaining the main regulatory genes, the expression of the main regulatory genes in the GSE32472, GSE125873, and GSE220135 datasets was detected. Through the logistic regression model, risk scoring was conducted for neonates, and the risk scores of non-BPD and BPD neonates were compared. Lastly, the classification performance of the model was evaluated using the area under the curve (AUC). The results showed that compared with non-BPD neonates, there were 486 up-regulated genes and 433 down-regulated genes in the peripheral blood mononuclear cells of BPD neonates. The inflammation-related pathway was highly enriched in the up-regulated genes. Ultimately, phospholipase C beta 1 (PLCB1), nidogen 1 (NID1), serum response factor binding protein 1 (SRFBP1), centrosomal protein 72 (CEP72), excision repair cross complementation group 6 like (ERCC6L), and peptidylprolyl isomerase like 1 (PPIL1) were identified as the main regulatory genes. The prediction model's calculation formula for risk score was PLCB1×0.26+NID1×0.97+SRFBP1×1.58+CEP72×(-0.36)+ERCC6L×2.14+PPIL1×0.67. The AUCs in the GSE32472 test dataset, GSE125873 dataset, and GSE220135 dataset were 0.88, 0.86, and 0.89, respectively. This prediction model could distinguish between non-BPD and BPD neonates. In conclusion, the prediction model based on inflammation-related pathway genes has a certain diagnostic value for BPD.

Joint effects of CD8A and ICOS in Long QT Syndrome (LQTS) and Beckwith-Wiedemann Syndrome (BWS)

BackgroundLong QT Syndrome (LQTS) and Beckwith-Wiedemann Syndrome (BWS) are complex disorders with unclear origins, underscoring the need for in-depth molecular investigations into their mechanisms. The main aim of this study is to identify the shared key genes between LQTS and BWS, shedding light on potential common molecular pathways underlying these syndromes.MethodsThe LQTS and BWS datasets are available for download from the GEO database. Differential expression genes (DEGs) were identified. Weighted gene co-expression network analysis (WGCNA) was used to detect significant modules and central genes. Gene enrichment analysis was performed. CIBERSORT was used for immune cell infiltration analysis. The predictive protein interaction (PPI) network of core genes was constructed using STRING, and miRNAs regulating central genes were screened using TargetScan.ResultsFive hundred DEGs associated with Long QT Syndrome and Beckwith-Wiedemann Syndrome were identified. GSEA analysis revealed enrichment in pathways such as T cell receptor signaling, MAPK signaling, and adrenergic signaling in cardiac myocytes. Immune cell infiltration indicated higher levels of memory B cells and naive CD4 T cells. Four core genes (CD8A, ICOS, CTLA4, LCK) were identified, with CD8A and ICOS showing low expression in the syndromes and high expression in normal samples, suggesting potential inverse regulatory roles.ConclusionThe expression of CD8A and ICOS is low in long QT syndrome and Beckwith-Wiedemann syndrome, indicating their potential as key genes in the pathogenesis of these syndromes. The identification of shared key genes between LQTS and BWS provides insights into common molecular mechanisms underlying these disorders, potentially facilitating the development of targeted therapeutic strategies.

FTY720 ameliorates experimental MPO-ANCA-associated vasculitis by regulating fatty acid oxidation via the neutrophil PPARα-CPT1a pathway.

Increasing studies demonstrated the importance of C5a and anti-neutrophil cytoplasmic antibody (ANCA)-induced neutrophil activation in the pathogenesis of ANCA-associated vasculitis (AAV). Sphingosine-1-phosphate (S1P) acts as a downstream effector molecule of C5a and enhances neutrophil activation induced by C5a and ANCA. The current study investigated the role of a S1P receptor modulator, FTY720, in experimental autoimmune vasculitis (EAV) and explored the immunometabolism-related mechanisms of FTY720 in modulating ANCA-induced neutrophil activation. The effects of FTY720 in EAV were evaluated by quantifying haematuria, proteinuria, crescent formation, tubulointerstitial injury and pulmonary haemorrhage. RNA sequencing of renal cortex and gene enrichment analysis were performed. The proteins of key identified pathways were analysed in neutrophils isolated from peripheral blood of patients with active AAV and normal controls. We assessed the effects of FTY720 on ANCA-induced neutrophil respiratory burst and neutrophil extracellular traps formation (NETosis). FTY720 treatment significantly attenuated renal injury and pulmonary haemorrhage in EAV. RNA sequencing analyses of renal cortex demonstrated enhanced fatty acid oxidation (FAO) and peroxisome proliferator-activated receptor (PPAR) signalling in FTY720-treated rats. Compared with normal controls, patients with active AAV showed decreased FAO in neutrophils. FTY720-treated differentiated HL-60 cells showed increased expression of carnitine palmitoyltransferase 1a (CPT1a) and PPARα. Blocking or knockdown of CPT1a or PPARα in isolated human neutrophils and HL-60 cells reversed the inhibitory effects of FTY720 on ANCA-induced neutrophil respiratory burst and NETosis. FTY720 attenuated renal injury in EAV through upregulating FAO via the PPARα-CPT1a pathway in neutrophils, offering potential immunometabolic targets in AAV treatment.