Benchmarking enrichment analysis methods with the disease pathway network.

Enrichment analysis (EA) is a common approach to gain functional insights from genome-scale experiments. As a consequence, a large number of EA methods have been developed, yet it is unclear from previous studies which method is the best for a given dataset. The main issues with previous benchmarks include the complexity of correctly assigning true pathways to a test dataset, and lack of generality of the evaluation metrics, for which the rank of a single target pathway is commonly used. We here provide a generalized EA benchmark and apply it to the most widely used EA methods, representing all four categories of current approaches. The benchmark employs a new set of 82 curated gene expression datasets from DNA microarray and RNA-Seq experiments for 26 diseases, of which only 13 are cancers. In order to address the shortcomings of the single target pathway approach and to enhance the sensitivity evaluation, we present the Disease Pathway Network, in which related Kyoto Encyclopedia of Genes and Genomes pathways are linked. We introduce a novel approach to evaluate pathway EA by combining sensitivity and specificity to provide a balanced evaluation of EA methods. This approach identifies Network Enrichment Analysis methods as the overall top performers compared with overlap-based methods. By using randomized gene expression datasets, we explore the null hypothesis bias of each method, revealing that most of them produce skewed P-values.

Proteomic Profiling of Dilated Cardiomyopathy Plasma Samples ─ Searching for Biomarkers with Potential to Predict the Outcome of Therapy.

Determination of the prognosis and treatment outcomes of dilated cardiomyopathy is a serious problem due to the lack of valid specific protein markers. Using in-depth proteome discovery analysis, we compared 49 plasma samples from patients suffering from dilated cardiomyopathy with plasma samples from their healthy counterparts. In total, we identified 97 proteins exhibiting statistically significant dysregulation in diseased plasma samples. The functional enrichment analysis of differentially expressed proteins uncovered dysregulation in biological processes like inflammatory response, wound healing, complement cascade, blood coagulation, and lipid metabolism in dilated cardiomyopathy patients. The same proteome approach was employed in order to find protein markers whose expression differs between the patients well-responding to therapy and nonresponders. In this case, 45 plasma proteins revealed statistically significant different expression between these two groups. Of them, fructose-1,6-bisphosphate aldolase seems to be a promising biomarker candidate because it accumulates in plasma samples obtained from patients with insufficient treatment response and with worse or fatal outcome. Data are available via ProteomeXchange with the identifier PXD046288.

Integrated transcriptomics and histopathology approach identifies a subset of rejected donor livers with potential suitability for transplantation.

BACKGROUND: Liver transplantation is an effective treatment for liver failure. There is a large unmet demand, even as not all donated livers are transplanted. The clinical selection criteria for donor livers based on histopathological evaluation and liver function tests are variable. We integrated transcriptomics and histopathology to characterize donor liver biopsies obtained at the time of organ recovery. We performed RNA sequencing as well as manual and artificial intelligence-based histopathology (10 accepted and 21 rejected for transplantation). RESULTS: We identified two transcriptomically distinct rejected subsets (termed rejected-1 and rejected-2), where rejected-2 exhibited a near-complete transcriptomic overlap with the accepted livers, suggesting acceptability from a molecular standpoint. Liver metabolic functional genes were similarly upregulated, and extracellular matrix genes were similarly downregulated in the accepted and rejected-2 groups compared to rejected-1. The transcriptomic pattern of the rejected-2 subset was enriched for a gene expression signature of graft success post-transplantation. Serum AST, ALT, and total bilirubin levels showed similar overlapping patterns. Additional histopathological filtering identified cases with borderline scores and extensive molecular overlap with accepted donor livers. CONCLUSIONS: Our integrated approach identified a subset of rejected donor livers that are likely suitable for transplantation, demonstrating the potential to expand the pool of transplantable livers.

Integration analysis of miRNA-mRNA pairs between two contrasting genotypes reveals the molecular mechanism of jujube (Ziziphus jujuba Mill.) response to high-temperature stress.

With global warming, high temperature (HT) has become one of the most common abiotic stresses resulting in significant crop yield losses, especially for jujube (Ziziphus jujuba Mill.), an important temperate economic crop cultivated worldwide. This study aims to explore the coping mechanism of jujube to HT stress at the transcriptional and post-transcriptional levels, including identifying differentially expressed miRNAs and mRNAs as well as elucidating the critical pathways involved. High-throughput sequencing analyses of miRNA and mRNA were performed on jujube leaves, which were collected from "Fucumi" (heat-tolerant) and "Junzao" (heat-sensitive) cultivars subjected to HT stress (42 °C) for 0, 1, 3, 5, and 7 days, respectively. The results showed that 45 known miRNAs, 482 novel miRNAs, and 13,884 differentially expressed mRNAs (DEMs) were identified. Among them, integrated analysis of miRNA target genes prediction and mRNA-seq obtained 1306 differentially expressed miRNAs-mRNAs pairs, including 484, 769, and 865 DEMIs-DEMs pairs discovered in "Fucuimi", "Junzao" and two genotypes comparative groups, respectively. Furthermore, functional enrichment analysis of 1306 DEMs revealed that plant-pathogen interaction, starch and sucrose metabolism, spliceosome, and plant hormone signal transduction were crucial pathways in jujube leaves response to HT stress. The constructed miRNA-mRNA network, composed of 20 DEMIs and 33 DEMs, displayed significant differently expressions between these two genotypes. This study further proved the regulatory role of miRNAs in the response to HT stress in plants and will provide a theoretical foundation for the innovation and cultivation of heat-tolerant varieties.

NUSAP1 promotes pancreatic ductal adenocarcinoma progression by drives the epithelial-mesenchymal transition and reduces AMPK phosphorylation.

BACKGROUND: Pancreatic ductal adenocarcinoma (PDAC) has a poor prognosis, and its molecular mechanisms are unclear. Nucleolar and spindle-associated protein 1 (NUSAP1), an indispensable mitotic regulator, has been reported to be involved in the development of several types of tumors. The biological function and molecular mechanism of NUSAP1 in PDAC remain controversial. This study explored the effects and mechanism of NUSAP1 in PDAC. METHODS: Differentially expressed genes (DEGs) were screened. A protein‒protein interaction (PPI) network was constructed to identify hub genes. Experimental studies and tissue microarray (TMA) analysis were performed to investigate the effects of NUSAP1 in PDAC and explore its mechanism. RESULTS: Network analysis revealed that NUSAP1 is an essential hub gene in the PDAC transcriptome. Genome heterogeneity analysis revealed that NUSAP1 is related to tumor mutation burden (TMB), loss of heterozygosity (LOH) and homologous recombination deficiency (HRD) in PDAC. NUSAP1 is correlated with the levels of infiltrating immune cells, such as B cells and CD8 T cells. High NUSAP1 expression was found in PDAC tissues and was associated with a poor patient prognosis. NUSAP1 promoted cancer cell proliferation, migration and invasion, drives the epithelial-mesenchymal transition and reduces AMPK phosphorylation. CONCLUSIONS: NUSAP1 is an essential hub gene that promotes PDAC progression and leads to a dismal prognosis by drives the epithelial-mesenchymal transition and reduces AMPK phosphorylation.

Cellular and transcriptomic response to pathogenic and non-pathogenic Vibrio parahaemolyticus strains causing acute hepatopancreatic necrosis disease (AHPND) in Litopenaeus vannamei.

The shrimp industry has historically been affected by viral and bacterial diseases. One of the most recent emerging diseases is Acute Hepatopancreatic Necrosis Disease (AHPND), which causes severe mortality. Despite its significance to sanitation and economics, little is known about the molecular response of shrimp to this disease. Here, we present the cellular and transcriptomic responses of Litopenaeus vannamei exposed to two Vibrio parahaemolyticus strains for 98 h, wherein one is non-pathogenic (VpN) and the other causes AHPND (VpP). Exposure to the VpN strain resulted in minor alterations in hepatopancreas morphology, including reductions in the size of R and B cells and detachments of small epithelial cells from 72 h onwards. On the other hand, exposure to the VpP strain is characterized by acute detachment of epithelial cells from the hepatopancreatic tubules and infiltration of hemocytes in the inter-tubular spaces. At the end of exposure, RNA-Seq analysis revealed functional enrichment in biological processes, such as the toll3 receptor signaling pathway, apoptotic processes, and production of molecular mediators involved in the inflammatory response of shrimp exposed to VpN treatment. The biological processes identified in the VpP treatment include superoxide anion metabolism, innate immune response, antimicrobial humoral response, and toll3 receptor signaling pathway. Furthermore, KEGG enrichment analysis revealed metabolic pathways associated with survival, cell adhesion, and reactive oxygen species, among others, for shrimp exposed to VpP. Our study proves the differential immune responses to two strains of V. parahaemolyticus, one pathogenic and the other nonpathogenic, enlarges our knowledge on the evolution of AHPND in L. vannamei, and uncovers unique perspectives on establishing genomic resources that may function as a groundwork for detecting probable molecular markers linked to the immune system in shrimp.

TES and SLC40A1 as Potential Biomarkers for Predicting Survival in T-Cell Acute Lymphoblastic Leukemia.

INTRODUCTION: Identifying patients with high-risk T-cell acute lymphoblastic leukemia (T-ALL) is crucial for personalized therapy; however, the lack of robust biomarkers hinders prognosis assessment. To address this issue, our study aimed to screen and validate genes whose expression may serve as predictive indicators of outcomes in T-ALL patients while also investigating the underlying molecular mechanisms. METHODS: Differentially expressed genes (DEGs) between T-ALL patients and healthy controls were identified by integrating data from three independent public datasets. Functional annotation of these DEGs and protein-protein interactions were also conducted. Further, we enrolled a prospective cohort of T-ALL patients (n = 20) at our center, conducting RNA-seq analysis on their bone marrow samples. Survival-based univariate Cox analysis was employed to identify gene expressions related to survival, and an intersection algorithm was sequentially applied. Furthermore, we validated the identified genes using cases from the Therapeutically Applicable Research to Generate Effective Treatments database, plotting Kaplan-Meier curves for secondary validation. RESULTS: Through the integration of survival-related genes with DEGs identified in T-ALL, our analysis revealed six T-ALL-specific genes, the expression levels of which were linked to prognostic value. Notably, the independent prognostic value of SLC40A1 and TES expression levels was confirmed in both an external cohort and a prospective cohort at our center. CONCLUSION: In summary, our preliminary study indicates that the expression levels of TES and SLC40A1 genes show promise as potential indicators for predicting survival outcomes in T-ALL patients.

Effect of Calebin-A on Critical Genes Related to NAFLD: A Protein-Protein Interaction Network and Molecular Docking Study.

Background: Calebin-A is a minor phytoconstituent of turmeric known for its activity against inflammation, oxidative stress, cancerous, and metabolic disorders like Non-alcoholic fatty liver disease(NAFLD). Based on bioinformatic tools. Subsequently, the details of the interaction of critical proteins with Calebin-A were investigated using the molecular docking technique. Methods: We first probed the intersection of genes/ proteins between NAFLD and Calebin-A through online databases. Besides, we performed an enrichment analysis using the ClueGO plugin to investigate signaling pathways and gene ontology. Next, we evaluate the possible interaction of Calebin-A with significant hub proteins involved in NAFLD through a molecular docking study. Results: We identified 87 intersection genes Calebin-A targets associated with NAFLD. PPI network analysis introduced 10 hub genes (TP53, TNF, STAT3, HSP90AA1, PTGS2, HDAC6, ABCB1, CCT2, NR1I2, and GUSB). In KEGG enrichment, most were associated with Sphingolipid, vascular endothelial growth factor A (VEGFA), C-type lectin receptor, and mitogen-activated protein kinase (MAPK) signaling pathways. The biological processes described in 87 intersection genes are mostly concerned with regulating the apoptotic process, cytokine production, and intracellular signal transduction. Molecular docking results also directed that Calebin-A had a high affinity to bind hub proteins linked to NAFLD. Conclusion: Here, we showed that Calebin-A, through its effect on several critical genes/ proteins and pathways, might repress the progression of NAFLD.

Genome-wide DNA methylation and transcriptomic analysis of liver tissues subjected to early ischemia/reperfusion injury upon human liver transplantation.

INTRODUCTION AND OBJECTIVES: Epigenetic changes represent a mechanism connecting external stresses with long-term modifications of gene expression programs. In solid organ transplantation, ischemia-reperfusion injury (IRI) appears to induce epigenomic changes in the graft, although the currently available data are extremely limited. The present study aimed to characterize variations in DNA methylation and their effects on the transcriptome in liver transplantation from brain-dead donors. PATIENTS AND METHODS: 12 liver grafts were evaluated through serial biopsies at different timings in the procurement-transplantation process: T0 (warm procurement, in donor), T1 (bench surgery), and T2 (after reperfusion, in recipient). DNA methylation (DNAm) and transcriptome profiles of biopsies were analyzed using microarrays and RNAseq. RESULTS: Significant variations in DNAm were identified, particularly between T2 and T0. Functional enrichment of the best 1000 ranked differentially methylated promoters demonstrated that 387 hypermethylated and 613 hypomethylated promoters were involved in spliceosomal assembly and response to biotic stimuli, and inflammatory immune responses, respectively. At the transcriptome level, T2 vs. T0 showed an upregulation of 337 and downregulation of 61 genes, collectively involved in TNF-α, NFKB, and interleukin signaling. Cell enrichment analysis individuates macrophages, monocytes, and neutrophils as the most significant tissue-cell type in the response. CONCLUSIONS: In the process of liver graft procurement-transplantation, IRI induces significant epigenetic changes that primarily act on the signaling pathways of inflammatory responses dependent on TNF-α, NFKB, and interleukins. Our DNAm datasets are the early IRI methylome literature and will serve as a launch point for studying the impact of epigenetic modification in IRI.

Comparative pangenomic analysis of predominant human vaginal lactobacilli strains towards population-specific adaptation: understanding the role in sustaining a balanced and healthy vaginal microenvironment.

The vaginal microenvironment of healthy women has a predominance of Lactobacillus crispatus, L. iners, L. gasseri, and L. jensenii. The genomic repertoire of the strains of each of the species associated with the key attributes thereby regulating a healthy vaginal environment needs a substantial understanding.We studied all available human strains of the four lactobacilli across different countries, isolated from vaginal and urinal sources through phylogenetic and pangenomic approaches. The findings showed that L. iners has the highest retention of core genes, and L. crispatus has more gene gain in the evolutionary stratum. Interestingly, L. gasseri and L. jensenii demonstrated major population-specific gene-cluster gain/loss associated with bacteriocin synthesis, iron chelating, adherence, zinc and ATP binding proteins, and hydrolase activity. Gene ontology enrichment analysis revealed that L. crispatus strains showed greater enrichment of functions related to plasma membrane integrity, biosurfactant, hydrogen peroxide synthesis, and iron sequestration as an ancestral derived core function, while bacteriocin and organic acid biosynthesis are strain-specific accessory enriched functions. L. jensenii showed greater enrichment of functions related to adherence, aggregation, and exopolysaccharide synthesis. Notably, the key functionalities are heterogeneously enriched in some specific strains of L. iners and L. gasseri.This study shed light on the genomic features and their variability that provides advantageous attributes to predominant vaginal Lactobacillus species maintaining vaginal homeostasis. These findings evoke the need to consider region-specific candidate strains of Lactobacillus to formulate prophylactic measures against vaginal dysbiosis for women's health.

Ovarian Cancer Risk Variants Are Enriched in Histotype-Specific Enhancers and Disrupt Transcription Factor Binding Sites.

Quantifying the functional effects of complex disease risk variants can provide insights into mechanisms underlying disease biology. Genome-wide association studies have identified 39 regions associated with risk of epithelial ovarian cancer (EOC). The vast majority of these variants lie in the non-coding genome, where they likely function through interaction with gene regulatory elements. In this study we first estimated the heritability explained by known common low penetrance risk alleles for EOC. The narrow sense heritability (hg2) of EOC overall and high-grade serous ovarian cancer (HGSOCs) were estimated to be 5%-6%. Partitioned SNP heritability across broad functional categories indicated a significant contribution of regulatory elements to EOC heritability. We collated epigenomic profiling data for 77 cell and tissue types from Roadmap Epigenomics and ENCODE, and from H3K27Ac ChIP-seq data generated in 26 ovarian cancer and precursor-related cell and tissue types. We identified significant enrichment of risk single-nucleotide polymorphisms (SNPs) in active regulatory elements marked by H3K27Ac in HGSOCs. To further investigate how risk SNPs in active regulatory elements influence predisposition to ovarian cancer, we used motifbreakR to predict the disruption of transcription factor binding sites. We identified 469 candidate causal risk variants in H3K27Ac peaks that are predicted to significantly break transcription factor (TF) motifs. The most frequently broken motif was REST (p value = 0.0028), which has been reported as both a tumor suppressor and an oncogene. Overall, these systematic functional annotations with epigenomic data improve interpretation of EOC risk variants and shed light on likely cells of origin.

Identification of module genes and functional pathway analysis in septic shock subtypes by integrated bioinformatics analysis.

BACKGROUND: The present study aimed to identify the module genes and key gene functions and biological pathways of septic shock (SS) through integrated bioinformatics analysis. METHODS: In the study, we performed batch correction and principal component analysis on 282 SS samples and 79 normal control samples in three datasets, GSE26440, GSE95233 and GSE57065, to obtain a combined corrected gene expression matrix containing 21,654 transcripts. Patients with SS were then divided into three molecular subtypes according to sample subtyping analysis. RESULTS: By analyzing the demographic characteristics of the different subtypes, we found no statistically significant differences in gender ratio and age composition among the three groups. Then, three subtypes of differentially expressed genes (DEGs) and specific upregulated DEGs (SDEGs) were identified by differential gene expression analysis. We found 7361 DEGs in the type I group, 5594 DEGs in the type II group, and 7159 DEGs in the type III group. There were 1698 SDEGs in the type I group, 2443 in the type II group, and 1831 in the type III group. In addition, we analyzed the correlation between the expression data of 5972 SDEGs in the three subtypes and the gender and age of 227 patients, constructed a weighted gene co-expression network, and identified 11 gene modules, among which the module with the highest correlation with gender ratio was MEgrey. The modules with the highest correlation with age composition were MEgrey60 and MElightyellow. Then, by analyzing the differences in module genes among different subgroups of SS, we obtained the differential expression of 11 module genes in four groups: type I, type II, type III and the control group. Finally, we analyzed the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment of all module DEGs, and the GO function and KEGG pathway enrichment of different module genes were different. CONCLUSIONS: Our findings aim to identify the specific genes and intrinsic molecular functional pathways of SS subtypes, as well as further explore the genetic and molecular pathophysiological mechanisms of SS.

Bioinformatics and system biology approaches to identify the diseasome and comorbidities complexities of SARS-CoV-2 infection with the digestive tract disorders.

Coronavirus Disease 2019 (COVID-19), although most commonly demonstrates respiratory symptoms, but there is a growing set of evidence reporting its correlation with the digestive tract and faeces. Interestingly, recent studies have shown the association of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) infection with gastrointestinal symptoms in infected patients but any sign of respiratory issues. Moreover, some studies have also shown that the presence of live SARS-CoV-2 virus in the faeces of patients with COVID-19. Therefore, the pathophysiology of digestive symptoms associated with COVID-19 has raised a critical need for comprehensive investigative efforts. To address this issue we have developed a bioinformatics pipeline involving a system biological framework to identify the effects of SARS-CoV-2 messenger RNA expression on deciphering its association with digestive symptoms in COVID-19 positive patients. Using two RNA-seq datasets derived from COVID-19 positive patients with celiac (CEL), Crohn's (CRO) and ulcerative colitis (ULC) as digestive disorders, we have found a significant overlap between the sets of differentially expressed genes from SARS-CoV-2 exposed tissue and digestive tract disordered tissues, reporting 7, 22 and 13 such overlapping genes, respectively. Moreover, gene set enrichment analysis, comprehensive analyses of protein-protein interaction network, gene regulatory network, protein-chemical agent interaction network revealed some critical association between SARS-CoV-2 infection and the presence of digestive disorders. The infectome, diseasome and comorbidity analyses also discover the influences of the identified signature genes in other risk factors of SARS-CoV-2 infection to human health. We hope the findings from this pathogenetic analysis may reveal important insights in deciphering the complex interplay between COVID-19 and digestive disorders and underpins its significance in therapeutic development strategy to combat against COVID-19 pandemic.

IFN-beta and EIF2AK2 are potential biomarkers for interstitial lung disease in anti-MDA5 positive dermatomyositis.

OBJECTIVE: DM with positive anti-melanoma differentiation-related gene 5 (MDA5) antibody is an autoimmune disease with multiple complications. Interstitial lung diseases (ILDs) are significantly associated with DM and are particularly related to MDA5+ DM. This article aims to explore potential molecular mechanisms and develop new diagnostic biomarkers for MDA5+ DM-ILD. METHODS: The series matrix files of DM and non-specific interstitial pneumonia (NSIP) were downloaded from the Gene Expression Omnibus (GEO) database to identify the differentially expressed genes (DEGs). Gene set enrichment analysis (GSEA) was used to screen the common enriched pathways related to DM and NSIP. Next, the co-expressed differential expressed genes (co-DEGs) between MDA5+, MDA5- and NSIP groups were identified by Venn plots, and then selected for different enrichment analyses and protein-protein interaction (PPI) network construction. The mRNA expression levels of IFN-beta and EIF2AK2 were measured by RT-qPCR. The protein expression levels of IFN-beta were measured by ELISA. RESULTS: Using GSEA, the enriched pathway 'herpes simplex virus 1 infection' was both up-regulated in DM and NSIP. Enrichment analysis in MDA5+ DM, MDA5- DM and NSIP reported that the IFN-beta signalling pathway was an important influencing factor in the MDA5+ DM-ILD. We also identified that eukaryotic translation initiation factor 2 alpha kinase 2 (EIF2AK2) was an important gene signature in the MDA5+ DM-ILD by PPI analysis. The expression levels of IFN-beta and EIF2AK2 were significantly increased in MDA5+ DM-ILD patients. CONCLUSIONS: IFN-beta and EIF2AK2 contributed to the pathogenesis of MDA5+ DM-ILD, which could be used as potential therapeutic targets.

Systems biology approach to understand the interplay between Bacillus anthracis and human host genes that leads to CVDs.

Humans infected with invasive Bacillus anthracis (B. anthracis) have a very poor prognosis and are at high risk for developing cardiovascular diseases (CVDs) and shock. Several bacterial elements probably have significant pathogenic roles in this pathogenic process of anthrax. In our current work, we have analysed the molecular level interactions between B. anthracis and human genes to understand the interplay during anthrax that leads to the CVDs. Our results have shown dense interactions between the functional partners in both host and the B. anthracis Gene interaction network (GIN). The functional enrichment analysis indicated that the clusters in the host GIN had genes related to hypoxia and autophagy in response to the lethal toxin; and genes related to adherens junction and actin cytoskeleton in response to edema toxin play a significant role in multiple stages of the disease. The B. anthracis genes BA_0530, guaA, polA, rpoB, ribD, secDF, metS, dinG and human genes ACTB, EGFR, EP300, CTNNB1, ESR1 have shown more than 50 direct interactions with the functional partners and hence they can be considered as hub genes in the network and they are observed to have important roles in CVDs. The outcome of our study will help to understand the molecular pathogenesis of CVDs in anthrax. The hub genes reported in the study can be considered potential drug targets and they can be exploited for new drug discovery.

Gene network interaction analysis to elucidate the antimicrobial resistance mechanisms in the Clostridiumdifficile.

Antimicrobial resistance has caused chaos worldwide due to the depiction of multidrug-resistant (MDR) infective microorganisms. A thorough examination of antimicrobial resistance (AMR) genes and associated resistant mechanisms is vital to solving this problem. Clostridium difficile (C. difficile) is an opportunistic nosocomial bacterial strain that has acquired exogenous AMR genes that confer resistance to antimicrobials such as erythromycin, azithromycin, clarithromycin, rifampicin, moxifloxacin, fluoroquinolones, vancomycin, and others. A network of interactions, including 20 AMR genes, was created and analyzed. In functional enrichment analysis, Cellular components (CC), Molecular Functions (MF), and Biological Processes (BP) were discovered to have substantial involvement. Mutations in the rpl genes, which encode ribosomal proteins, confer resistance in Gram-positive bacteria. Full erythromycin and azithromycin cross-resistance can be conferred if more than one of the abovementioned genes is present. In the enriched BP, rps genes related to transcriptional regulation and biosynthesis were found. The genes belong to the rpoB gene family, which has previously been related to rifampicin resistance. The genes rpoB, gyrA, gyrB, rpoS, rpl genes, rps genes, and Van genes are thought to be the hub genes implicated in resistance in C. difficile. As a result, new medications could be developed using these genes. Overall, our observations provide a thorough understanding of C. difficile AMR mechanisms.

LCK, FOXC1 and hsa-miR-146a-5p as potential immune effector molecules associated with rheumatoid arthritis.

Rheumatoid arthritis (RA) is a type of systemic immune disease characterized by chronic inflammatory disease of the joints. However, the aetiology and underlying molecular events of RA are unclear. Here, we applied bioinformatics analysis to identify potential immune effector molecules involved in RA. The three microarray datasets were downloaded from the Gene Expression Omnibus (GEO) database. We used the R software screen 115 overlapping differentially expressed genes (DEGs). Subsequently, we constructed a protein-protein interaction (PPI) network encoded by these DEGs and identified 10 genes closely associated with RA - LCK, GZMA, GZMB, CD2, LAG3, IL-15, TNFRSF4, CD247, CCR5 and CCR7. Furthermore, in the miRNA-hub gene networks, we screened out hsa-miR-146a-5p, which is the miRNA controlling the largest number of hub genes. Finally, we found some transcription factors that closely interact with hub genes, such as FOXC1, GATA2, YY1, RUNX2, SREBF1, CEBPB and NFIC. This study successfully predicted that LCK, FOXC1 and hsa-miR-146a-5p can be used as potential immune effector molecules of RA. Our study may have potential implications for future prediction of disease progression in patients with symptomatic RA, and has important significance for the pathogenesis and targeted therapy of RA.

Uncovering potential diagnostic biomarkers of acute myocardial infarction based on machine learning and analyzing its relationship with immune cells.

BACKGROUND: Acute myocardial infarction (AMI) is a common cardiovascular disease. This study aimed to mine biomarkers associated with AMI to aid in clinical diagnosis and management. METHODS: All mRNA and miRNA data were downloaded from public database. Differentially expressed mRNAs (DEmRNAs) and differentially expressed miRNAs (DEmiRNAs) were identified using the metaMA and limma packages, respectively. Functional analysis of the DEmRNAs was performed. In order to explore the relationship between miRNA and mRNA, we construct miRNA-mRNA negative regulatory network. Potential biomarkers were identified based on machine learning. Subsequently, ROC and immune correlation analysis were performed on the identified key DEmRNA biomarkers. RESULTS: According to the false discovery rate < 0.05, 92 DEmRNAs and 272 DEmiRNAs were identified. GSEA analysis found that kegg_peroxisome was up-regulated in AMI and kegg_steroid_hormone_biosynthesis was down-regulated in AMI compared to normal controls. 5 key DEmRNA biomarkers were identified based on machine learning, and classification diagnostic models were constructed. The random forests (RF) model has the highest accuracy. This indicates that RF model has high diagnostic value and may contribute to the early diagnosis of AMI. ROC analysis found that the area under curve of 5 key DEmRNA biomarkers were all greater than 0.7. Pearson correlation analysis showed that 5 key DEmRNA biomarkers were correlated with most of the differential infiltrating immune cells. CONCLUSION: The identification of new molecular biomarkers provides potential research directions for exploring the molecular mechanism of AMI. Furthermore, it is important to explore new diagnostic genetic biomarkers for the diagnosis and treatment of AMI.

Transcriptome analysis reveals molecular pathways in the iron-overloaded Tibetan population.

Iron overload can lead to chronic complications, serious organ dysfunction or death in the body. Under hypoxic conditions, the body needs more iron to produce red blood cells to adapt to the hypoxic environment. The prevalence of iron overload in the Tibetan population is higher than that in the Han population. To explore the molecular mechanism of iron-overload in the Tibetan population, this study investigated the transcriptome of the Tibetan iron overload population to obtain differentially expressed genes (DEGs) between the iron-overloaded population and the normal iron population. Functional enrichment analysis identified key related pathways, gene modules and coexpression networks under iron-overload conditions, and the 4 genes screened out have the potential to become target genes for studying the development of iron overload. A total of 28 pathways were screened to be closely related to the occurrence and development of iron overload, showing that iron overload is extremely related to erythrocyte homeostasis, cell cycle, oxidative phosphorylation, immunity, and transcriptional repression.

Identification of critical prognosis signature associated with lymph node metastasis of stomach adenocarcinomas.

Lymph node metastasis (LNM) is an important factor affecting the prognosis of patients with gastric adenocarcinoma (STAD), which is the most common malignancy of the human digestive system. Current detection techniques have limited sensitivity and specificity, and there is a lack of effective biomarkers to screen for LNM. Therefore, it is critical to screen for biomarkers that predict LNM in STAD. Gene expression differential analysis (false discovery rate < 0.05, |log2Fold change| ≥1.5) was performed on 102 LNM samples, 224 non-LNM samples, and 29 normal gastric tissue samples from The Cancer Genome Atlas (TCGA) STAD dataset, and 269 LNM-specific genes (DEGs) were obtained. Enrichment analysis showed that LNM-specific genes functioned mainly in cytokine-cytokine receptor interactions, calcium signaling, and other pathways. Ten DEGs significantly associated with overall survival in STAD patients were screened by multivariate Cox regression, and an LNM-based 10-mRNA prognostic signature was established (Logrank P < 0.0001). This 10-mRNA signature was well predicted in both the TCGA training set and the Gene Expression Omnibus validation dataset (GSE84437) and was associated with survival in patients with LNM or advanced-stage STAD. Using Kaplan-Meier survival, receiver operating characteristic curve, C-index analysis, and decision curve analysis, the 10-mRNA signature was found to be a more effective predictor of prognosis in STAD patients than the other two reported models (P < 0.0005). Protein-protein interaction network and gene set enrichment analysis of the 10-mRNA signature revealed that the signature may affect the expression of multiple biological pathways and related genes. Finally, the expression levels of prognostic genes in STAD tissues and cell lines were verified using qRT-PCR, Western blot, and the Human Protein Atlas database. Taken together, the prognostic signature constructed in this study may become an indicator for clinical prognostic assessment of LNM-STAD and provide a new strategy for future targeted therapy.