Differentially Expressed Genes Genes Research Articles

Construction of the Interaction Network of Hub Genes in the Progression of Barrett's Esophagus to Esophageal Adenocarcinoma.

Esophageal adenocarcinoma (EAC) is one of the histologic types of esophageal cancer with a poor prognosis. The majority of EAC originate from Barrett's esophagus (BE). There are few studies focusing on the dynamic progression of BE to EAC. R software was used to analyze differentially expressed genes (DEGs) based on RNA-seq data of 94 normal esophageal squamous epithelial (NE) tissues, 113 BE tissues and 147 EAC tissues. The overlapping genes of DEGs between BE and EAC were analyzed by Venn diagram tool. The hub genes were selected by Cytoscape software based on the protein-protein interaction network of the overlapping genes using STRING database. The functional analysis of hub genes was performed by R software and the protein expression was identified by immunohistochemistry. In the present study, we found a large degree of genetic similarity between BE and EAC, and further identified seven hub genes (including COL1A1, TGFBI, MMP1, COL4A1, NID2, MMP12, CXCL1) which were all progressively upregulated in the progression of NE-BE-EAC. We have preliminarily uncovered the probable molecular mechanisms of these hub genes in disease development and constructed the ceRNA regulatory network of hub genes. More importantly, we explored the possibility of hub genes as biomarkers in the disease progression of NE-BE-EAC. For example, TGFBI can be used as biomarkers to predict the prognosis of EAC patients. COL1A1, NID2 and COL4A1 can be used as biomarkers to predict the response to immune checkpoint blockade (ICB) therapy. We also constructed a disease progression risk model for NE-BE-EAC based on CXCL1, MMP1 and TGFBI. Finally, the results of drug sensitivity analysis based on hub genes showed that drugs such as PI3K inhibitor TGX221, bleomycin, PKC inhibitor Midostaurin, Bcr-Abl inhibitor Dasatinib, HSP90 inhibitor 17-AAG, and Docetaxel may be potential candidates to inhibit the progression of BE to EAC. This study is based on a large number of clinical samples with high credibility, which is useful for revealing the probable carcinogenic mechanism of BE to EAC and developing new clinical treatment strategies.

Comprehensive analysis of scRNA-Seq and bulk RNA-Seq reveals dynamic changes in the tumor immune microenvironment of bladder cancer and establishes a prognostic model

BackgroundThe prognostic management of bladder cancer (BLCA) remains a great challenge for clinicians. Recently, bulk RNA-seq sequencing data have been used as a prognostic marker for many cancers but do not accurately detect core cellular and molecular functions in tumor cells. In the current study, bulk RNA-seq and single-cell RNA sequencing (scRNA-seq) data were combined to construct a prognostic model of BLCA.MethodsBLCA scRNA-seq data were downloaded from Gene Expression Omnibus (GEO) database. Bulk RNA-seq data were obtained from the UCSC Xena. The R package "Seurat" was used for scRNA-seq data processing, and the uniform manifold approximation and projection (UMAP) were utilized for downscaling and cluster identification. The FindAllMarkers function was used to identify marker genes for each cluster. The limma package was used to obtain differentially expressed genes (DEGs) affecting overall survival (OS) in BLCA patients. Weighted gene correlation network analysis (WGCNA) was used to identify BLCA key modules. The intersection of marker genes of core cells and genes of BLCA key modules and DEGs was used to construct a prognostic model by univariate Cox and Least Absolute Shrinkage and Selection Operator (LASSO) analyses. Differences in clinicopathological characteristics, immune microenvironment, immune checkpoints, and chemotherapeutic drug sensitivity between the high and low-risk groups were also investigated.ResultsscRNA-seq data were analyzed to identify 19 cell subpopulations and 7 core cell types. The ssGSEA showed that all 7 core cell types were significantly downregulated in tumor samples of BLCA. We identified 474 marker genes from the scRNA-seq dataset, 1556 DEGs from the Bulk RNA-seq dataset, and 2334 genes associated with a key module identified by WGCNA. After performing intersection, univariate Cox, and LASSO analysis, we obtained a prognostic model based on the expression levels of 3 signature genes, namely MAP1B, PCOLCE2, and ELN. The feasibility of the model was validated by an internal training set and two external validation sets. Moreover, patients with high-risk scores are predisposed to experience poor OS, a larger prevalence of stage III-IV, a greater TMB, a higher infiltration of immune cells, and a lesser likelihood of responding favorably to immunotherapy.ConclusionBy integrating scRNA-seq and bulk RNA-seq data, we constructed a novel prognostic model to predict the survival of BLCA patients. The risk score is a promising independent prognostic factor that is closely correlated with the immune microenvironment and clinicopathological characteristics.

Machine learning-based predictive models and drug prediction for schizophrenia in multiple programmed cell death patterns.

Schizophrenia (SC) is one of the most common mental illnesses. However, the underlying genes that cause it and its effective treatments are unknown. Programmed cell death (PCD) is associated with many immune diseases and plays an important role in schizophrenia, which may be a diagnostic indicator of the disease. Two groups as training and validation groups were chosen for schizophrenia datasets from the Gene Expression Omnibus Database (GEO). Furthermore, the PCD-related genes of the 12 patterns were extracted from databases such as KEGG. Limma analysis was performed for differentially expressed genes (DEG) identification and functional enrichment analysis. Machine learning was employed to identify minimum absolute contractions and select operator (LASSO) regression to determine candidate immune-related center genes, construct protein-protein interaction networks (PPI), establish artificial neural networks (ANN), and validate with consensus clustering (CC) analysis, then Receiver operating characteristic curve (ROC curve) was drawn for diagnosis of schizophrenia. Immune cell infiltration was developed to investigate immune cell dysregulation in schizophrenia, and finally, related drugs with candidate genes were collected via the Network analyst online platform. In schizophrenia, 263 genes were crossed between DEG and PCD-related genes, and machine learning was used to select 42 candidate genes. Ten genes with the most significant differences were selected to establish a diagnostic prediction model by differential expression profiling. It was validated using artificial neural networks (ANN) and consensus clustering (CC), while ROC curves were plotted to assess diagnostic value. According to the findings, the predictive model had a high diagnostic value. Immune infiltration analysis revealed significant differences in Cytotoxic and NK cells in schizophrenia patients. Six candidate gene-related drugs were collected from the Network analyst online platform. Our study systematically discovered 10 candidate hub genes (DPF2, ATG7, GSK3A, TFDP2, ACVR1, CX3CR1, AP4M1, DEPDC5, NR4A2, and IKBKB). A good diagnostic prediction model was obtained through comprehensive analysis in the training (AUC 0.91, CI 0.95-0.86) and validation group (AUC 0.94, CI 1.00-0.85). Furthermore, drugs that may be useful in the treatment of schizophrenia have been obtained (Valproic Acid, Epigallocatechin gallate).

Genome-wide DNA methylation and transcription analysis reveal the potential epigenetic mechanism of heat stress response in the sea cucumber Apostichopus japonicus

DNA methylation is an important epigenetic modification that regulates many biological processes. The sea cucumber Apostichopus japonicus often suffers from heat stress that affects its growth and leads to significant economic losses. In this study, the mRNA expression patterns and DNA methylation characteristics in the body wall of A. japonicus under heat stress were analyzed by whole-genome bisulfite sequencing (WGBS) and transcriptome sequencing (RNA-seq). We found that CpG was the main DNA methylation type, and heat stress caused a significant increase in the overall methylation level and methylation rate, especially in the intergenic region of the A. japonicus genome. In total, 1,409 differentially expressed genes (DEGs) and 17,927 differentially methylated genes (DMGs) were obtained by RNA-seq and WGBS, respectively. Association analysis between DNA methylation and transcription identified 569 negatively correlated genes in both DMGs and DEGs, which indicated that DNA methylation affects on transcriptional regulation in response to heat stress. These negatively correlated genes were significantly enriched in pathways related to energy metabolism and immunoregulation, such as the thyroid hormone signaling pathway, renin secretion, notch signaling pathway and microRNAs in cancer. In addition, potential key genes, including heat shock protein (hsp70), calcium-activated chloride channel regulator 1(clca1), and tenascin R (tnr), were obtained and their expression and methylation were preliminarily verified. The results provide a new perspective for epigenetic and transcriptomic studies of A. japonicus response to heat stress, and provide a reference for breeding sea cucumbers resistant to high temperatures.

Five-hub genes identify potential mechanisms for the progression of asthma to lung cancer.

Previous studies have shown that asthma is a risk factor for lung cancer, while the mechanisms involved remain unclear. We attempted to further explore the association between asthma and non-small cell lung cancer (NSCLC) via bioinformatics analysis. We obtained GSE143303 and GSE18842 from the GEO database. Lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC) groups were downloaded from the TCGA database. Based on the results of differentially expressed genes (DEGs) between asthma and NSCLC, we determined common DEGs by constructing a Venn diagram. Enrichment analysis was used to explore the common pathways of asthma and NSCLC. A protein-protein interaction (PPI) network was constructed to screen hub genes. KM survival analysis was performed to screen prognostic genes in the LUAD and LUSC groups. A Cox model was constructed based on hub genes and validated internally and externally. Tumor Immune Estimation Resource (TIMER) was used to evaluate the association of prognostic gene models with the tumor microenvironment (TME) and immune cell infiltration. Nomogram model was constructed by combining prognostic genes and clinical features. 114 common DEGs were obtained based on asthma and NSCLC data, and enrichment analysis showed that significant enrichment pathways mainly focused on inflammatory pathways. Screening of 5 hub genes as a key prognostic gene model for asthma progression to LUAD, and internal and external validation led to consistent conclusions. In addition, the risk score of the 5 hub genes could be used as a tool to assess the TME and immune cell infiltration. The nomogram model constructed by combining the 5 hub genes with clinical features was accurate for LUAD. Five-hub genes enrich our understanding of the potential mechanisms by which asthma contributes to the increased risk of lung cancer.

Halogenated boroxine increases propensity to apoptosis in leukemia (UT-7) but not non-tumor cells invitro.

A hallmark of the development of solid and hematological malignancies is the dysregulation of apoptosis, which leads to an imbalance between cell proliferation, cell survival and death. Halogenated boroxine [K2 (B3 O3 F4 OH)] (HB) is a derivative of cyclic anhydride of boronic acid, with reproducible anti-tumor and anti-proliferative effects in different cell models. Notably, these changes are observed to be more profound in tumor cells than in normal cells. Here, we investigated the underlying mechanisms through an extensive evaluation of (a) deregulated target genes and (b) their interactions and links with main apoptotic pathway genes upon treatment with an optimized concentration of HB. To provide deeper insights into the mechanism of action of HB, we performed identification, visualization, and pathway association of differentially expressed genes (DEGs) involved in regulation of apoptosis among tumor and non-tumor cells upon HB treatment. We report that HB at a concentration of 0.2 mg·mL-1 drives tumor cells to apoptosis, whereas non-tumor cells are not affected. Comparison of DEG profiles, gene interactions and pathway associations suggests that the HB effect and tumor-'selectivity' can be explained by Bax/Bak-independent mitochondrial depolarization by ROS generation and TRAIL-like activation, followed by permanent inhibition of NFκB signaling pathway specifically in tumor cells.

Integrated Assessment of Macrophage Lipids Homeostasis Omics Data: Identification of Potential Genes and Pathways in Atherosclerosis

Atherosclerosis is a chronic inflammatory disease characterized by the formation of lipid-rich plaques within the arterial wall. Increasing evidences have shown that cellular senescence may contribute to the progression of atherosclerosis, but the mechanism remains unclear. Hence, the present study aimed to identify potential therapeutic biomarkers for atherosclerosis by analyzing the gene expression profiles of macrophages incubated with total lipoproteins. The microarray dataset no. GSE84791 obtained from Gene Expression Omnibus (GEO) database was used for this study. In the comparison of two groups: (i) THP-1 macrophage models incubated with non-LPL hydrolysed products and (ii) LPL hydrolysed products, a total of 283 differentially expressed genes (DEGs) were identified. The Gene Ontology (GO) analysis indicated that the upregulated DEGs gene set were mainly enriched in cellular response to inflammation, stress, substance uptake and intracellular transport. Besides, upregulated DEGs were significantly enriched in PPAR signalling pathway by the Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis. Notably, GO analysis revealed that the downregulated DEGs were mainly enriched in cellular proliferation, while the KEGG analysis showed that the gene set was significantly enriched in cell cycle process. The top 10 hub genes including KIF2C, NCAPG, BUB1, TOP2A, CENPF, TTK, CCNA2, PLK4, CDC6, and KIF11, was identified from the Protein-Protein Interaction (PPI) network, which constructed using STRING and further analysed using the Network Analyzer, MCODE and cytoHubba. The present study indicated that the downregulation of these genes which involved in the process of cell cycle may have an implication on atherosclerosis development.

Identification of hub genes and pathophysiological mechanism related to acute unilateral vestibulopathy by integrated bioinformatics analysis.

BackgroundAlthough many pathological mechanisms and etiological hypotheses of acute unilateral vestibulopathy (AUVP) have been reported, but the actual etiology remains to be elucidated.ObjectiveThis study was based on comprehensive bioinformatics to identify the critical genes of AUVP and explore its pathological mechanism.MethodsGene expression profiles of AUVP and normal samples were collected from GSE146230 datasets of the Gene Expression Omnibus (GEO) database. Weighted gene co-expression network analysis (WGCNA) was constructed, and the WGCNA R-package extracted significant modules. The limma R-package was applied to identify differentially expressed genes (DEGs). The common genes of practical modules and DEGs were screened for GO and KEGG pathways analysis. The protein–protein interaction (PPI) layout and hub genes validation was created by Cytoscape software using the link from the STRING database. The functions of hub genes were predicted through the CTD (comparative genetics database).ResultsA total of 332 common genes were screened from practical modules and DEGs. Functional enrichment analysis revealed that these genes were predominantly associated with inflammation and infection. After construction of PPI, expressions of hub genes, and drawing ROC curves, LILRB2, FPR1, AQP9, and LILRA1 are highly expressed in AUVP (p < 0.05) and have a certain diagnostic efficacy for AUVP (AUC > 0.7), so they were selected as hub genes. The functions of hub genes suggested that the occurrence of AUVP may be related to inflammation, necrosis, hepatomegaly, and other conditions in CTD.ConclusionLILRB2, FPR1, AQP9, and LILRA1 may play essential roles in developing AUVP, providing new ideas for diagnosing and treating AUVP.

Exploration and validation of the hub genes involved in hypoxia-induced endothelial-mesenchymal transition of systemic sclerosis.

During the development of systemic sclerosis (SSc), endothelial-mesenchymal transition (EndoMT) has been shown to be one of the mechanisms leading to pulmonary fibrosis. However, the correlation between hypoxia and EndoMT was mostly unknown. R software was used to analyse differentially expressed genes (DEGs) in vascular endothelial cells under hypoxic conditions, and fibroblasts derived from SSc-related pulmonary fibrotic tissues, respectively. Using a web-based online Venn diagram tool, we analysed overlapping genes of DEGs between endothelial cells and fibroblasts. Finally, the protein-protein interaction network of EndoMT hub genes were constructed using the STRING database. The hub genes were knockdown by transfection of siRNAs in the hypoxia model of HULEC-5a cells constructed by liquid paraffin closure and then used to detect the effect on EndoMT-related biomarkers by western blot. In this study, we found that INHBA, DUSP1, NOX4, PLOD2, BHLHE40 were upregulated in SSc fibroblasts and hypoxic-treated endothelial cells, while VCAM1, RND3, CCL2, and TXNIP were downregulated. In the hypoxia model of HULEC-5a cells, the expression of these 9 hub genes was confirmed by western blot. In addition, through Spearman's correlation analysis and Western blot, we confirmed that these hub genes were closely related to the EndoMT-related markers. The mechanisms of these hypoxia-induced EndoMT hub genes may be related to TGF-β, Notch, Wnt, NF-κ B, TNF and mTOR signalling pathways. Our study provides new insights into the occurrence and development of SSc-related pulmonary fibrosis resulting from hypoxia-induced EndoMT.

Comparative analysis of Neptunea cumingii growth, related digestive and immune enzyme indicators, and liver transcriptome under different feeding conditions

Neptunea cumingii is a carnivorous snail with a very high market value, but it cannot be cultivated on a large scale at present due to the lack of an appropriate artificial feed. In this study, we fed N. cumingii four kinds of diets (Cristaria plicata meat, Chlamys farreri mantle, Mytilus edulis meat, and artificial feed) for 90 days and then measured growth indexes and digestive and immune enzyme indexes. We also subjected liver samples to transcriptome sequencing to detect significant differences among the four groups at the transcriptome level. The survival rate of N. cumingii fed with each type of feed was &amp;gt; 90%. The weight, shell length, shell height, and weight gain of the N. cumingii in the C. plicata meat group were significantly higher than those of the other treatment groups, while the values in the artificial feed group were significantly lower than those of the other treatment groups. The superoxide dismutase, catalase, amylase, protease, and lipase activities were higher in the stomach, intestine, and liver of snails in the C. plicata meat feeding group than in those of the other treatment groups, and they were significantly higher than those of the artificial feed group (p &amp;lt; 0.05); the opposite was true for malondialdehyde content. A total of 3407 differentially expressed genes (DEGs) were found in the M. edulis meat group vs. C. plicata meat group comparison. A total of 3422 DEGs genes were identified in the artificial feed group vs. C. plicata meat group comparison. A total of 3,929 DEGs were found in the C. plicata meat group vs. C. farreri mantle group comparison. Through Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis, we found the DEGs in the liver of N. cumingii fed with the different diets were mainly enriched in the energy metabolism, growth, and immunity pathways. Our results indicated that among the four diets tested, C. plicata meat had the best effect on N. cumingii, and they provided an important reference for identification of suitable diets for the development of N. cumingii artificial breeding.

Combined transcriptomic and metabolomic analysis reveals a role for adenosine triphosphate-binding cassette transporters and cell wall remodeling in response to salt stress in strawberry.

Strawberry (Fragaria × ananassa Duch) are sensitive to salt stress, and breeding salt-tolerant strawberry cultivars is the primary method to develop resistance to increased soil salinization. However, the underlying molecular mechanisms mediating the response of strawberry to salinity stress remain largely unknown. This study evaluated the salinity tolerance of 24 strawberry varieties, and transcriptomic and metabolomic analysis were performed of ‘Sweet Charlie’ (salt-tolerant) and ‘Benihoppe’ (salt-sensitive) to explore salt tolerance mechanisms in strawberry. Compared with the control, we identified 3412 differentially expressed genes (DEGs) and 209 differentially accumulated metabolites (DAMs) in ‘Benihoppe,’ and 5102 DEGs and 230 DAMs in ‘Sweet Charlie.’ DEGs Gene Ontology (GO) enrichment analyses indicated that the DEGs in ‘Benihoppe’ were enriched for ion homeostasis related terms, while in ‘Sweet Charlie,’ terms related to cell wall remodeling were over-represented. DEGs related to ion homeostasis and cell wall remodeling exhibited differential expression patterns in ‘Benihoppe’ and ‘Sweet Charlie.’ In ‘Benihoppe,’ 21 ion homeostasis-related DEGs and 32 cell wall remodeling-related DEGs were upregulated, while 23 ion homeostasis-related DEGs and 138 cell wall remodeling-related DEGs were downregulated. In ‘Sweet Charlie,’ 72 ion homeostasis-related DEGs and 275 cell wall remodeling-related DEGs were upregulated, while 11 ion homeostasis-related DEGs and 20 cell wall remodeling-related DEGs were downregulated. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses showed only four KEGG enriched pathways were shared between ‘Benihoppe’ and ‘Sweet Charlie,’ including flavonoid biosynthesis, phenylalanine metabolism, phenylpropanoid biosynthesis and ubiquinone, and other terpenoid-quinone biosynthesis. Integrating the results of transcriptomic and metabolomics analyses showed that adenosine triphosphate-binding cassette (ABC) transporters and flavonoid pathway genes might play important roles in the salt stress response in strawberry, and DAMs and DEGs related to ABC transporter and flavonoid pathways were differentially expressed or accumulated. The results of this study reveal that cell wall remodeling and ABC transporters contribute to the response to salt stress in strawberry, and that related genes showed differential expression patterns in varieties with different salt tolerances. These findings provide new insights into the underlying molecular mechanism of strawberry response to salt stress and suggest potential targets for the breeding of salt-tolerant strawberry varieties.

EGR2 is a hub-gene in myocardial infarction and aggravates inflammation and apoptosis in hypoxia-induced cardiomyocytes

BackgroundMyocardial infarction (MI) is characterized by coronary artery occlusion, ischemia and hypoxia of myocardial cells, leading to irreversible myocardial damage. Therefore, it is urgent to explore the potential mechanism of myocardial injury during the MI process to develop effective therapies for myocardial cell rescue.MethodsWe downloaded the GSE71906 dataset from GEO DataSets, and the R software was used to identify the differentially expressed genes (DEGs) in mouse heart tissues of MI and sham controls. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment were performed to understand the significantly activated signaling pathways in MI. Protein–protein interaction (PPI) network was constructed to highlight the hub genes in DEGs. The Western Blot, qRT-PCR and TUNEL staining were used to explore the function of hub gene in hypoxia-induced cardiomyocytes in vitro.ResultsA total of 235 DEGs were identified in GSE71906 dataset. Functional enrichment analysis revealed that the upregulated genes were primarily associated with the inflammatory response and apoptosis. 20 hub genes were identified in PPI network, and the early growth response 2 (EGR2) was highlighted. In vitro. We confirmed the EGR2 was upregulated induced by hypoxia and revealed the upregulated EGR2 aggravates pro-inflammation and pro-apoptotic genes expression. In addition, EGR2 knockout mitigates hypoxia-induced inflammation and apoptosis in cardiomyocytes.ConclusionThe present study identified the EGR2 was a hub gene in myocardial damage during MI process, the excessive EGR2 aggravates hypoxia-induced myocardial damage by accelerating inflammation and apoptosis in vitro. Therefore, targeting EGR2 offers a potential pharmacological strategy for myocardial cell rescue in MI.

Transcriptome Evidence Reveals Mitochondrial Unfolded Protein Response Participate in SH-SY5Y Cells Exposed to Manganese.

Overexposure to manganese (Mn) can lead to neurodegenerative damage, resulting in manganism with similar syndromes to Parkinson's disease (PD). However, little is known about changes in transcriptomics induced by the toxicological level of Mn. In this study, we conducted RNA-seq to explore the candidate genes and signaling pathways included by Mn in human SH-SY5Y neuroblastoma cells. The differentially expressed genes (DEGs) between the Mn-treated group and the control group were screened, and weighted gene co-expression network analysis (WGCNA) was employed to identify hub genes. Then, pathway enrichment analyses for those candidate genes were performed in Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG). We further validated the concentration- and time-response effects of Mn exposure (0-500 μM, 3-12 h) on mitochondrial unfolded protein response (UPRMT) by real-time quantitative reverse transcription PCR (qRT-PCR). The results showed 179 up-regulated differentially expressed genes (DEGs) and 681 down-regulated DEGs after Mn exposure. Based on the intersection of DEGs genes and hub genes, 73 DEGs were related to neurotoxicity. The comprehensive pathway analysis showed Mn had widespread effects on the mitogen-activated protein kinase (MAPK) signaling pathway, unfolded protein response, longevity regulating pathway, inflammatory bowel disease, and mitophagy signaling pathway. After Mn exposure, the expressions of activating transcription factor 3 (ATF3) and C-C motif chemokine ligand 2 (CCL2) increased, while the expressions of C/EBP homologous protein (CHOP), caseinolytic protease P (CLPP), and Lon protease 1 (LONP1) decreased in a concentration- and time-dependent manner. Overall, our study suggests that UPRMT is a new sight in understanding the mechanism of Mn-induced neurotoxicity.

Identification of Hub Genes and Therapeutic Agents for IgA Nephropathy Through Bioinformatics Analysis and Experimental Validation.

BackgroundIgA nephropathy (IgAN) is the most common primary glomerular disease and the leading cause of the end-stage renal disease in the world. The pathogenesis of IgAN has not been well elucidated, and yet treatment is limited. High-throughput microarray has been applied for elucidating molecular biomarkers and potential mechanisms involved in IgAN. This study aimed to identify the potential key genes and therapeutics associated with IgAN using integrative bioinformatics and transcriptome-based computational drug repurposing approach.MethodsThree datasets of mRNA expression profile were obtained from the gene expression omnibus database and differentially expressed genes (DEGs) between IgAN glomeruli and normal tissue were identified by integrated analysis. Gene ontology and pathway enrichment analyses of the DEGs were performed by R software, and protein-protein interaction networks were constructed using the STRING online search tool. External dataset and immunohistochemical assessment of kidney biopsy specimens were used for hub gene validation. Potential compounds for IgAN therapy were obtained by Connectivity Map (CMap) analysis and preliminarily verified in vitro. Stimulated human mesangial cells were collected for cell proliferation and cell cycle analysis using cell counting kit 8 and flow cytometry, respectively.Results134 DEGs genes were differentially expressed across kidney transcriptomic data from IgAN patients and healthy living donors. Enrichment analysis showed that the glomerular compartments underwent a wide range of interesting pathological changes during kidney injury, focused on anion transmembrane transporter activity and protein digestion and absorption mostly. Hub genes (ITGB2, FCER1G, CSF1R) were identified and verified to be significantly upregulated in IgAN patients, and associated with severity of renal lesions. Computational drug repurposing with the CMap identified tetrandrine as a candidate treatment to reverse IgAN hub gene expression. Tetrandrine administration significantly reversed mesangial cell proliferation and cell cycle transition.ConclusionThe identification of DEGs and related therapeutic strategies of IgAN through this integrated bioinformatics analysis provides a valuable resource of therapeutic targets and agents of IgAN. Especially, our findings suggest that tetrandrine might be beneficial for IgAN, which deserves future research.

Indigenous Microorganisms Offset Arbuscular Mycorrhizal Fungi-Induced Plant Growth and Nutrient Acquisition Through Negatively Modulating the Genes of Phosphorus Transport and Nitrogen Assimilation.

Arbuscular mycorrhizal (AM) fungi that promote plant growth and nutrient acquisition are essential for nutrient-deficient karst areas, while they inevitably regulate host plants jointly with indigenous microorganisms in natural soil. However, how indigenous microorganisms regulate AM-induced benefits on plant growth and nutrient acquisition remains unclear. In this study, the Bidens tripartita as the common plant species in the karst region was cultivated into three soil substrates treated by AM fungi inoculation (AMF), AM fungi inoculation combining with indigenous microorganisms (AMI), and the control without AM fungi and indigenous microorganisms (CK). The plant biomass and concentration of nitrogen (N) and phosphorus (P) were measured, and the transcriptomic analysis was carried out using root tissues. The results showed that AM fungi significantly enhanced the plant biomass, N, and P accumulation with the reduction of plants’ N/P ratio; however, the indigenous microorganisms offset the AM-induced benefits in biomass and N and P acquisition. In addition, there are 819 genes in differentially expressed genes (DEGs) of AMF vs. AMI ∩ AMF vs. CK, meaning that AM fungi induced these genes that were simultaneously regulated by indigenous microorganisms. Furthermore, the enrichment analysis suggested that these genes were significantly associated with the metabolic processes of organophosphate, P, sulfur, N, and arginine biosynthesis. Notably, 34 and 17 genes of DEGs were related to P and N metabolism, respectively. Moreover, the indigenous microorganisms significantly downregulated these DEGs, especially those encoding the PHO1 P transporters and the glnA, glutamate dehydrogenase 2 (GDH2), and urease as key enzymes in N assimilation; however, the indigenous microorganisms significantly upregulated genes encoding PHO84 inducing cellular response to phosphate (Pi) starvation. These regulations indicated that indigenous microorganisms restrained the N and P metabolism induced by AM fungi. In conclusion, we suggested that indigenous microorganisms offset nutrient benefits of AM fungi for host plants through regulating these genes related to P transport and N assimilation.

Ferroptosis-related local immune cytolytic activity in tumor microenvironment of basal cell and squamous cell carcinoma.

Background: Ferroptosis, a recently discovered form of cell death, whose role in basal cell carcinoma (BCC) and squamous cell carcinoma (SCC) has not been well disclosed. To improve our understanding of the differences in tumor progression and therapeutic effects between BCC and SCC, and to find potential therapeutic targets, this study systematically analyzed ferroptosis-related genes (FRGs) and their associated local immune cytolytic activity (LICA) and tumor microenvironment (TME) metabolic function differences.Methods: Two bulk RNA-seq datasets, GSE7553 and GSE125285, from the Gene Expression Omnibus database were compared within and between groups to screen for common differentially expressed genes (DEGs) for enrichment analysis. The currently recognized FRGs in DEGs gene set were selected as the targets to analyze their correlation and difference in LICA and TME metabolic functions. And validated using immune cell populations from another single-cell RNA-seq (scRNA-seq) dataset (GSE123813) to accurately understand the difference in LICA. All of the gene sets for functional enrichment analysis comes from published results and MSigDB database.Results: Ten FRGs were used to further analyze the differences in LICA and TME metabolic functions between BCC and SCC. In the SCC samples, LICA (e.g. Treg, CCR, Cytolytic activity, etc.) and TME metabolic functions (e.g. lipid and energy, etc.) were significantly related to ferroptosis genes (e.g. SLC1A5, CD44, NQO1, HMOX1 and STEAP3), and the ferroptosis potential index were also significantly higher than that in the BCC samples. Finally, based on these ten FRGs and related enrichment results, we postulated a model of NQO1 homeostasis regulated by FRGs during induction of ferroptosis in SCC.Conclusions: The results showed that three FRGs, SLC1A5, CD44 and NQO1, have significant potential in targeted therapies for SCC chemotherapy resistance. And two FRGs, STEAP3 and HMOX1, formed a synergistic effect on the occurrence of ferroptosis in tumor cells. Our findings can be used as the main research materials for metastasis and chemotherapy resistance in SCC patients.

Screening of Potential Key Biomarkers for Ewing Sarcoma: Evidence from Gene Array Analysis.

BackgroundEwing’s sarcoma (ES) is a common bone cancer in children and adolescents. There are ethnic differences in the incidence and treatment effects. People have made great efforts to clarify the cause; however, the molecular mechanism of ES is still poorly understood.MethodsWe download the microarray datasets GSE68776, GSE45544 and GSE17674 from the Gene Expression Omnibus (GEO) database. The differentially expressed genes (DEGs) of the three datasets were screened and enrichment analysis was performed. STRING and Cytoscape were used to carry out module analysis, building a protein–protein interaction (PPI) network. Finally, a series of analyses such as survival analysis and immune infiltration analysis were performed on the selected genes.ResultsA total of 629 differentially expressed genes were screened, including 206 up-regulated genes and 423 down-regulated genes. The pathways and rich-functions of DEGs include protein activation cascade, carbohydrate binding, cell-cell adhesion junctions, mitotic cell cycle, p53 pathway, and cancer pathways. Then, a total of 10 hub genes were screened out. Biological process analysis showed that these genes were mainly enriched in mitotic nuclear division, protein kinase activity, cell division, cell cycle, and protein phosphorylation.ConclusionSurvival analysis and multiple gene comparison analysis showed that CDCA8, MAD2L1 and FANCI may be involved in the occurrence and prognosis of ES. The purpose of our study is to clarify the DEG and key genes, which will help us know more about the molecular mechanisms of ES, provide potential pathway or targets for the diagnosis and treatment.

Identification of a Tumor Cell Associated Type I IFN Resistance Gene Expression Signature of Human Melanoma, the Components of Which Have a Predictive Potential for Immunotherapy

We developed a human melanoma model using the HT168-M1 cell line to induce IFN-α2 resistance in vitro (HT168-M1res), which was proven to be maintained in vivo in SCID mice. Comparing the mRNA profile of in vitro cultured HT168-M1res cells to its sensitive counterpart, we found 79 differentially expressed genes (DEGs). We found that only a 13-gene core of the DEGs was stable in vitro and only a 4-gene core was stable in vivo. Using an in silico cohort of IFN-treated melanoma tissues, we validated a differentially expressed 9-gene core of the DEGs. Furthermore, using an in silico cohort of immune checkpoint inhibitor (ICI)-treated melanoma tissues, we tested the predictive power of the DEGs for the response rate. Analysis of the top four upregulated and top four downregulated genes of the DEGs identified WFDC1, EFNA3, DDX10, and PTBP1 as predictive genes, and analysis of the “stable” genes of DEGs for predictive potential of ICI response revealed another 13 genes, out of which CDCA4, SOX4, DEK, and HSPA1B were identified as IFN-regulated genes. Interestingly, the IFN treatment associated genes and the ICI-therapy predictive genes overlapped by three genes: WFDC1, BCAN, and MT2A, suggesting a connection between the two biological processes.

Investigation of genes and pathways involved in breast cancer subtypes through gene expression meta-analysis

BackgroundMolecular-based studies have revealed heterogeneity in Breast cancer BC while also improving classification and treatment. However, efforts are underway to distinguish between distinct subtypes of breast cancer. In this study, the results of several microarray studies were combined to identify genes and pathways specific to each BC subtype. MethodsMeta-analysis of multiple gene expression profile datasets was screened to find differentially expressed genes (DEGs) across subtypes of BC and normal breast tissue samples. Protein-protein interaction network and gene set enrichment analysis were used to identify critical genes and pathways associated with BC subtypes. The differentially expressed genes from meta-analysis was validated using an independent comprehensive breast cancer RNA-sequencing dataset obtained from the Cancer Genome Atlas (TCGA). ResultsWe identified 110 DEGs (13 DEGs in all and 97 DEGs in each subtype) across subtypes of BC. All subtypes had a small set of shared DEGs enriched in the Chemokine receptor bind chemokine pathway. Luminal A specific were enriched in the translational elongation process in mitochondria, and the enhanced process in luminal B subtypes was interferon-alpha/beta signaling. Cell cycle and mitotic DEGs were enriched in the basal-like group. All subtype-specific DEG genes (100%) were successfully validated for Luminal A, Luminal B, ERBB2, and Normal-like. However, the validation percentage for Basal-like group was 77.8%. ConclusionIntegrating researches such as a meta-analysis of gene expression might be more effective in uncovering subtype-specific DEGs and pathways than a single-study analysis. It would be more beneficial to increase the number of studies that use matched BC subtypes along with GEO profiling approaches to reach a better result regarding DEGs and reduce probable biases. However, achieving 77.8% overlap in basal-specific genes and complete concordance in specific genes related to other subtypes can implicate the strength of our analysis for discovering the subtype-specific genes.

Identification and Validation of Hub Genes in Acute Pancreatitis and Hypertriglyceridemia.

BackgroundThe pathogenesis of acute pancreatitis (AP) and the relationship between acute pancreatitis and hypertriglyceridemia are complex and not fully understood. The purpose of this study was to identify the hub genes along with common differentially expressed genes (DEGs) between acute pancreatitis and hypertriglyceridemia.MethodsWe downloaded three gene expression profiles of AP and one gene expression profile of hypertriglyceridemia from the Gene Expression Omnibus (GEO) database and filtered the DEGs based on the above four datasets. Next, we identified the hub genes by performing the Gene Ontology (GO) term analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis, and protein–protein interaction (PPI) construction. We also constructed the miRNA-hub gene network and established mouse models with hypertriglyceridemia and AP using a high-fat diet and injection of caerulein (CAE), respectively. Finally, the immunohistochemical analysis was used to verify the differential expressions of hub genes in AP, hypertriglyceridemia, and normal pancreatic tissue.ResultsA total of 105 DEGs associated with AP and 149 DEGs associated with hypertriglyceridemia were identified. Additionally, we identified six hub genes of AP, all of which were closely related to the cytoskeleton while two DEGs genes were common in both AP and hypertriglyceridemia. We also verified their expression in mouse models. Finally, a network of miRNA-mRNA was also constructed, and the top seven interactive miRNAs (hsa-mir-1–3p, hsa-mir-5195–3p, hsa-mir-145–5p, hsa-let-7b-5p, hsa-mir-10b-5p, hsa-mir-206, and hsa-mir-613) targeting the most hub genes were identified.ConclusionOverall, we identified six hub genes associated with AP and two common DEGs associated with AP and hypertriglyceridemia along with seven miRNAs that may regulate AP. This study could provide new ideas for further elucidation of the pathogenesis of hypertriglyceridemia-induced acute pancreatitis in the future.