Integrated bioinformatic analysis reveals YWHAB as a novel diagnostic biomarker for idiopathic pulmonary arterial hypertension

Idiopathic pulmonary arterial hypertension (IPAH) is a severe cardiovascular disease that is a serious threat to human life. However, the specific diagnostic biomarkers have not been fully clarified and candidate regulatory targets for IPAH have not been identified. The aim of this study was to explore the potential diagnostic biomarkers and possible regulatory targets of IPAH. We performed a weighted gene coexpression network analysis and calculated module-trait correlations based on a public microarray data set (GSE703) and six modules were found to be related to IPAH. Two modules which have the strongest correlation with IPAH were further analyzed and the top 10 hub genes in the two modules were identified. Furthermore, we validated the data by quantitative real-time polymerase chain reaction (qRT-PCR) in an independent sample set originated from our study center. Overall, the qRT-PCR results were consistent with most of the results of the microarray analysis. Intriguingly, the highest change was found for YWHAB, a gene encodes a protein belonging to the 14-3-3 family of proteins, members of which mediate signal transduction by binding to phosphoserine-containing proteins. Thus, YWHAB was subsequently selected for validation. In congruent with the gene expression analysis, plasma 14-3-3β concentrations were significantly increased in patients with IPAH compared with healthy controls, and 14-3-3β expression was also positively correlated with mean pulmonary artery pressure ( R ² = 0.8783; p < 0.001). Taken together, using weighted gene coexpression analysis, YWHAB was identified and validated in association with IPAH progression, which might serve as a biomarker and/or therapeutic target for IPAH.     

基于转录组的肝豆状核变性调控网络的构建和分析

本研究旨在利用生物信息学方法构建经铜诱导的ATP7B基因敲除HepG2细胞系的转录调控网络。探讨关键转录因子在肝豆状核变性发生、发展中的潜在作用机制。收集公共基因表达数据库(gene expression omnibus, GEO)中包含野生型、ATP7B基因敲除型、铜诱导的野生型和铜诱导的ATP7B基因敲除型HepG2细胞系数据。筛选由铜诱导产生的差异表达基因(differentially expressed genes,DEGs)后进行基因本体论(gene ontology,GO)、京都基因和基因组百科全书(Kyoto encyclopedia of genes and genomes, KEGG)富集分析。基于蛋白相互作用网络,识别疾病关键基因和功能模块,并对关键功能模块中的基因进行富集分析。最后,构建转录调控网络,筛选核心转录因子。共筛选出1 034个差异表达基因,其中上调525个,下调509个。上、下调关键功能模块分别包括了3785个和3931个基因。关键功能模块中的基因主要定位于细胞-基质连接、染色体、剪接复合体、核糖体等区域,共同参与了mRNA加工、组蛋白修饰、RNA剪切...     

CD14 Mediates Toll-like Receptor 4 (TLR4) Endocytosis and Spleen Tyrosine Kinase (Syk) and Interferon Regulatory Transcription Factor 3 (IRF3) Activation in Epithelial Cells and Impairs Neutrophil Infiltration and Pseudomonas aeruginosa Killing in Vivo

In the current study, we examined the role of CD14 in regulating LPS activation of corneal epithelial cells and Pseudomonas aeruginosa corneal infection. Our findings demonstrate that LPS induces Toll-like receptor 4 (TLR4) internalization in corneal epithelial cells and that blocking with anti-CD14 selectively inhibits TLR4 endocytosis, spleen tyrosine kinase (Syk) and IRF3 phosphorylation, and production of CCL5/RANTES and IFN-β, but not IL-8. Using a murine model of P. aeruginosa corneal infection, we show that although infected CD14^−/− corneas produce less CCL5, they exhibit significantly increased CXC chemokine production, neutrophil recruitment to the corneal stroma, and bacterial clearance than C57BL/6 mice. We conclude that CD14 has a critical role in mediating TLR4 signaling through IRF3 in resident corneal epithelial cells and macrophages and thereby modulates TLR4 cell surface activation of the MyD88/NF-κB/AP-1 pathway and production of CXC chemokines and neutrophil infiltration to infected tissues.     

IRF1 as a potential biomarker in Mycobacterium tuberculosis infection

Pulmonary tuberculosis (PTB) is a major global public health problem. The purpose of this study was to find biomarkers that can be used to diagnose tuberculosis. We used four NCBI GEO data sets to conduct analysis. Among the four data sets, GSE139825 is lung tissue microarray, and GSE83456 , GSE19491 and GSE50834 are blood microarray. The differential genes of GSE139825 and GSE83456 were 68 and 226, and intersection genes were 11. Gene ontology (GO) analyses of 11 intersection genes revealed that the changes were mostly enriched in regulation of leucocyte cell-cell adhesion and regulation of T-cell activation. Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis of DEGs revealed that the host response in TB strongly involves cytokine-cytokine receptor interactions and folate biosynthesis. In order to further narrow the range of biomarkers, we used protein-protein interaction to establish a hub gene network of two data sets and a network of 11 candidate genes. Eventually, IRF1 was selected as a biomarker. As validation, IRF1 levels were shown to be up-regulated in patients with TB relative to healthy controls in data sets GSE19491 and GSE50834 . Additionally, IRF1 levels were measured in the new patient samples using ELISA. IRF1 was seen to be significantly up-regulated in patients with TB compared with healthy controls with an AUC of 0.801. These results collectively indicate that IRF1 could serve as a new biomarker for the diagnosis of pulmonary tuberculosis.     

紫外辐照恢复早期耐辐射奇球菌的转录组学分析（英文）

目的 耐辐射奇球菌是一种对紫外线、电离、干燥和化学试剂具有较强抗性的极端微生物。然而，该菌在紫外辐照后恢复早期的分子响应还不完全清楚。本文的目的是揭示耐辐射奇球菌在这一阶段的转录组响应。方法 本研究采用RNA-seq技术，测定了正常和紫外辐照培养条件下耐辐射奇球菌的转录组。为确定关键的差异表达基因及其调控关系，进行了功能富集分析。选取部分关键差异表达基因，进行实时定量PCR实验验证。利用以往研究中的转录组数据，寻找紫外辐照、电离辐射和干燥胁迫条件下公共的差异表达基因。构建了蛋白质-蛋白质相互作用网络；对蛋白质互作网络中的枢纽基因和主要模块进行了鉴定；对这些枢纽基因和模块进行了功能富集分析。结果 紫外辐照后的恢复早期，上调基因数量是下调基因数量的2倍以上，且多数与应激反应和DNA修复有关。恢复早期的修复途径主要有单链退火（SSA）途径（涉及基因：ddr A-D）、非同源端连接（NHEJ）途径（涉及基因：lig B、ppr A）和核苷酸切除修复（NER）途径（涉及基因：uvr A-C），前两种途径为同源重组（HR）做准备，而NER途径去除紫外线照射带来的嘧啶二聚体。通过比较紫外辐照、电离辐...     

Identification of differentially expressed genes and biological characteristics of colorectal cancer by integrated bioinformatics analysis

Colorectal cancer (CRC) ranks as one of the most common malignant tumors worldwide. Its mortality rate has remained high in recent years. Therefore, the aim of this study was to identify significant differentially expressed genes (DEGs) involved in its pathogenesis, which may be used as novel biomarkers or potential therapeutic targets for CRC. The gene expression profiles of GSE21510, GSE32323, GSE89076, and GSE113513 were downloaded from the Gene Expression Omnibus (GEO) database. After screening DEGs in each GEO data set, we further used the robust rank aggregation method to identify 494 significant DEGs including 212 upregulated and 282 downregulated genes. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed by DAVID and the KOBAS online database, respectively. These DEGs were shown to be significantly enriched in different cancer-related functions and pathways. Then, the STRING database was used to construct the protein–protein interaction network. The module analysis was performed by the MCODE plug-in of Cytoscape based on the whole network. We finally filtered out seven hub genes by the cytoHubba plug-in, including PPBP, CCL28, CXCL12, INSL5, CXCL3, CXCL10, and CXCL11. The expression validation and survival analysis of these hub genes were analyzed based on The Cancer Genome Atlas database. In conclusion, the robust DEGs associated with the carcinogenesis of CRC were screened through the GEO database, and integrated bioinformatics analysis was conducted. Our study provides reliable molecular biomarkers for screening and diagnosis, prognosis as well as novel therapeutic targets for CRC.     

Identification of key genes and pathways of thyroid cancer by integrated bioinformatics analysis

Thyroid cancer is a common endocrine malignancy with a rapidly increasing incidence worldwide. Although its mortality is steady or declining because of earlier diagnoses, its survival rate varies because of different tumour types. Thus, the aim of this study was to identify key biomarkers and novel therapeutic targets in thyroid cancer. The expression profiles of GSE3467, GSE5364, GSE29265 and GSE53157 were downloaded from the Gene Expression Omnibus database, which included a total of 97 thyroid cancer and 48 normal samples. After screening significant differentially expressed genes (DEGs) in each data set, we used the robust rank aggregation method to identify 358 robust DEGs, including 135 upregulated and 224 downregulated genes, in four datasets. Gene Ontology and Kyoto Encyclopaedia of Genes and Genomes pathway enrichment analyses of DEGs were performed by DAVID and the KOBAS online database, respectively. The results showed that these DEGs were significantly enriched in various cancer-related functions and pathways. Then, the STRING database was used to construct the protein–protein interaction network, and modules analysis was performed. Finally, we filtered out five hub genes, including LPAR5, NMU, FN1, NPY1R, and CXCL12, from the whole network. Expression validation and survival analysis of these hub genes based on the The Cancer Genome Atlas database suggested the robustness of the above results. In conclusion, these results provided novel and reliable biomarkers for thyroid cancer, which will be useful for further clinical applications in thyroid cancer diagnosis, prognosis and targeted therapy.     

Identification of potentially critical genes in the development of heart failure after ST-segment elevation myocardial infarction (STEMI)

Heart failure (HF) remains a common complication after acute ST-segment elevation myocardial infarction (STEMI). Here, we aim to identify critical genes related to the developed HF in patients with STEMI using bioinformatics analysis. The microarray data of GSE59867, including peripheral blood samples from nine patients with post-infarct HF and eight patients without post-infarct HF, were downloaded from the Gene Expression Omnibus database. Differentially expressed genes (DEGs) between HF and non-HF groups were screened by LIMMA package. Functional enrichment analyses of DEGs were conducted, followed by construction of a protein-protein interaction (PPI) network. The dynamic messenger RNA (mRNA) level of the hub genes during the follow-up was analyzed to further elucidate their role in HF development. A total of 58 upregulated and 75 downregulated DEGs were screen out. They were mainly enriched in biological processes about inflammatory response, extracellular matrix organization, response to cAMP, immune response, and positive regulation of cytosolic calcium ion concentration. Pathway analysis revealed that the DEGs were also involved in hematopoietic cell lineage, pathways in cancer, and extracellular matrix-receptor interaction. In the PPI network consisting of 58 nodes and 72 interactions, CXCL8 (degree = 15), THBS1 (degree = 8), FOS (degree = 7), and ITGA2B (degree = 6) were identified as the hub genes. In the comparison of patients with and without post-infarct HF, the mRNA level of these hub genes were all higher within 30 days but reached similar at 6 months after STEMI. In conclusion, CXCL8, THBS1, FOS, and ITGA2B may play important roles in the development of HF after acute STEMI.     

应用GSEA和WGCNA方法分析细菌性败血症宿主关键差异基因及意义

【目的】采用生物信息学方法分析公共数据库来源的细菌性败血症患者全血转录组学表达谱,探讨细菌败血症相关的宿主关键差异基因及意义。【方法】基于GEO数据库中GSE80496和GSE72829全血转录组基因数据集,采用GEO2R、基因集富集分析(GSEA)联用加权基因共表达网络分析(WGCNA)筛选细菌性败血症患者相比健康人群显著改变的差异基因,通过R软件对交集基因进行GO功能分析和KEGG富集分析。同时,通过String 11.0和Cytoscape分析枢纽基因,验证枢纽基因在数据集GSE72809(Health组52例,Definedsepsis组52例)全血标本中的表达情况,并探讨婴儿性别、月(胎)龄、出生体重、是否接触抗生素等因素与靶基因表达谱间的关系。【结果】分析GSE80496和GSE72829数据集分别筛选得到932个基因和319个基因,联合WGCNA枢纽模块交集得到与细菌性败血症发病相关的10个枢纽基因(MMP9、ITGAM、CSTD、GAPDH、PGLYRP1、FOLR3、OSCAR、TLR5、IL1RN和TIMP1);GSEA分析获得关键通路(氨基酸糖类-核糖代谢、PPAR信号通路、聚糖生物合成通路、自噬调控通路、补体、凝血因子级联反应、尼古丁和烟酰胺代谢、不饱和脂肪酸生物合成和阿尔兹海默症通路)及生物学过程(类固醇激素分泌、腺苷酸环化酶的激活、细胞外基质降解和金属离子运输)。【结论】本项研究通过GEO2R、GSEA联用WGCNA分析,筛选出与细菌性败血症发病相关的2个枢纽模块、10个枢纽基因以及一些关键信号通路和生物学过程,可为后续深入研究细菌性败血症致病机制奠定理论依据。     

Discovery of core gene families associated with liver metastasis in colorectal cancer and regulatory roles in tumor cell immune infiltration

In this study, we aimed to uncover genes that drive the pathogenesis of liver metastasis in colorectal cancer (CRC), and identify effective genes that could serve as potential therapeutic targets for treating with colorectal liver metastasis patients based on two GEO datasets. Several bioinformatics approaches were implemented. First, differential expression analysis screened out key differentially expressed genes (DEGs) across the two GEO datasets. Based on gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses, we identified the enrichment functions and pathways of the DEGs that were associated with liver metastasis in CRC. Second, immune infiltration analysis identified key immune signature gene sets associated with CRC liver metastasis, among which two key immune gene families (CD and CCL) identified as key DEGs were filtered by protein-protein interaction (PPI) network. Some of the members in these gene families were associated with disease free survival (DFS) or overall survival (OS) in two subtypes of CRC, namely COAD and READ. Finally, functional enrichment analysis of the two gene families and their neighboring genes revealed that they were closely associated with cytokine, leukocyte proliferation and chemotaxis. These results are valuable in comprehending the pathogenesis of liver metastasis in CRC, and are of seminal importance in understanding the role of immune tumor infiltration in CRC. Our study also identified potentially effective therapeutic targets for liver metastasis in CRC including CCL20, CCL24 and CD70.     

Downregulation of AC061961.2, LING01-AS1, and RP11–13E1.5 is associated with dilated cardiomyopathy progression

This study aimed to explore long noncoding RNAs (lncRNAs) implicated in dilated cardiomyopathy (DCM). Ten samples of failing hearts collected from the left ventricles of patients with DCM undergoing heart transplants, and ten control samples obtained from normal heart donors were included in this study. After sequencing, differentially expressed genes (DEGs) and lncRNAs between DCM and controls were screened, followed with functional enrichment analysis and weighted gene coexpression network analysis (WGCNA). Five key lncNRAs were validated through real-time polymerase chain reaction (PCR). Total 1,398 DEGs were identified, including 267 lncRNAs. WGCNA identified seven modules that were significantly correlated with DCM. The top 50 genes in the three modules (black, dark-green, and green–yellow) were significantly correlated with DCM disease state. Four core enrichment lncRNAs, such as AC061961.2, LING01-AS1, and RP11–557H15.4, in the green–yellow module were associated with neurotransmitter secretion. Five core enrichment lncRNAs, such as KB-1299A7.2 and RP11–13E1.5, in the black module were associated with the functions of blood circulation and heart contraction. AC061961.2, LING01-AS1, and RP11–13E1.5 were confirmed to be downregulated in DCM tissues by real-time PCR. The current study suggests that downregulation of AC061961.2, LING01-AS1, and RP11–13E1.5 may be associated with DCM progression, which may serve as key diagnostic biomarkers and therapeutic targets for DCM.     

Identification of EPHX2 and RMI2 as two novel key genes in cervical squamous cell carcinoma by an integrated bioinformatic analysis

Cervical cancer is the fourth most common malignancy in women worldwide and cervical squamous cell carcinoma (CESC) is the most common histological type of cervical cancer. The dysregulation of genes plays a significant role in cancer. In the present study, we screened out differentially expressed genes (DEGs) of CESC in the GSE63514 data set from the Gene Expression Omnibus database. An integrated bioinformatics analysis was used to select hub genes, as well as to investigate their related prognostic signature, functional annotation, methylation mechanism, and candidate molecular drugs. As a result, a total of 1907 DEGs were identified (944 were upregulated and 963 were downregulated). In the protein–protein interaction network, three hub modules and 30 hub genes were identified. And two hub modules and 116 hub genes were screened out from four CESC-related modules by the weighted gene coexpression network analysis. The gene ontology term enrichment analysis and Kyoto encyclopedia of genes and genomes pathway analysis were performed to better understand functions and pathways. Genes with a significant prognostic value were found by prognostic signature analysis. And there were five genes (EPHX2, CHAF1B, KIAA1524, CDC45, and RMI2) identified as significant CESC-associated genes after expression validation and survival analysis. Among them, EPHX2 and RMI2 were noted as two novel key genes for the CESC-associated methylation and expression. In addition, four candidate small molecule drugs for CESC (camptothecin, resveratrol, vorinostat, and trichostatin A) were defined. Further studies are required to explore these significant CESC-associated genes for their potentiality in diagnosis, prognosis, and targeted therapy.     

Demystifying the impact of prenatal tobacco exposure on the placental immune microenvironment: Avoiding the tragedy of mending the fold after death

Prenatal tobacco exposure (PTE) correlates significantly with a surge in adverse pregnancy outcomes, yet its pathological mechanisms remain partially unexplored. This study aims to meticulously examine the repercussions of PTE on placental immune landscapes, employing a coordinated research methodology encompassing bioinformatics, machine learning and animal studies. Concurrently, it aims to screen biomarkers and potential compounds that could sensitively indicate and mitigate placental immune disorders. In the course of this research, two gene expression omnibus (GEO) microarrays, namely GSE27272 and GSE7434, were included. Gene set enrichment analysis (GSEA) and immune enrichment investigations on differentially expressed genes (DEGs) indicated that PTE might perturb numerous innate or adaptive immune-related biological processes. A cohort of 52 immune-associated DEGs was acquired by cross-referencing the DEGs with gene sets derived from the ImmPort database. A protein–protein interaction (PPI) network was subsequently established, from which 10 hub genes were extracted using the maximal clique centrality (MCC) algorithm (JUN, NPY, SST, FLT4, FGF13, HBEGF, NR0B2, AREG, NR1I2, SEMA5B). Moreover, we substantiated the elevated affinity of tobacco reproductive toxicants, specifically nicotine and nitrosamine, with hub genes through molecular docking (JUN, FGF13 and NR1I2). This suggested that these genes could potentially serve as crucial loci for tobacco's influence on the placental immune microenvironment. To further elucidate the immune microenvironment landscape, consistent clustering analysis was conducted, yielding three subtypes, where the abundance of follicular helper T cells (p < 0.05) in subtype A, M2 macrophages (p < 0.01), neutrophils (p < 0.05) in subtype B and CD8+ T cells (p < 0.05), resting NK cells (p < 0.05), M2 macrophages (p < 0.05) in subtype C were significantly different from the control group. Additionally, three pivotal modules, designated as red, blue and green, were identified, each bearing a close association with differentially infiltrated immunocytes, as discerned by the weighted gene co-expression network analysis (WGCNA). Functional enrichment analysis was subsequently conducted on these modules. To further probe into the mechanisms by which immune-associated DEGs are implicated in intercellular communication, 20 genes serving as ligands or receptors and connected to differentially infiltrating immunocytes were isolated. Employing a variety of machine learning techniques, including one-way logistic regression, LASSO regression, random forest and artificial neural networks, we screened 11 signature genes from the intersection of immune-associated DEGs and secretory protein-encoding genes derived from the Human Protein Atlas. Notably, CCL18 and IFNA4 emerged as prospective peripheral blood markers capable of identifying PTE-induced immune disorders. These markers demonstrated impressive predictive power, as indicated by the area under the curve (AUC) of 0.713 (0.548–0.857) and 0.780 (0.618–0.914), respectively. Furthermore, we predicted 34 potential compounds, including cyclosporine, oestrogen and so on, which may engage with hub genes and attenuate immune disorders instigated by PTE. The diagnostic performance of these biomarkers, alongside the interventional effect of cyclosporine, was further corroborated in animal studies via ELISA, Western blot and immunofluorescence assays. In summary, this study identifies a disturbance in the placental immune landscape, a secondary effect of PTE, which may underlie multiple pregnancy complications. Importantly, our research contributes to the noninvasive and timely detection of PTE-induced placental immune disorders, while also offering innovative therapeutic strategies for their treatment.     

Identifying potential biomarkers in hepatitis B virus infection and its response to the antiviral therapy by integrated bioinformatic analysis

The antiviral treatment efficacy varies among chronic hepatitis B (CHB) patients and the underlying mechanism is unclear. An integrated bioinformatics analysis was performed to investigate the host factors that affect the therapeutic responsiveness in CHB patients. Four GEO data sets (GSE54747, GSE27555, GSE66698 and GSE66699) were downloaded from the Gene Expression Omnibus (GEO) database and analysed to identify differentially expressed genes(DEGs). Enrichment analyses of the DEGs were conducted using the DAVID database. Immune cell infiltration characteristics were analysed by CIBERSORT. Upstream miRNAs and lncRNAs of hub DEGs were identified by miRWalk 3.0 and miRNet in combination with the MNDR platform. As a result, seventy-seven overlapping DEGs and 15 hub genes were identified including CCL5, CXCL9, MYH2, CXCR4, CD74, CCL4, HLA-DRB1, ACTA1, CD69, CXCL10, HLA-DRB5, HLA-DQB1, CXCL13, STAT1 and CKM. The enrichment analyses revealed that the DEGs were mainly enriched in immune response and chemokine signalling pathways. Investigation of immune cell infiltration in liver samples suggested significantly different infiltration between responders and non-responders, mainly characterized by higher proportions of CD8+ T cells and activated NK cells in non-responders. The prediction of upstream miRNAs and lncRNAs led to the identification of a potential mRNA-miRNA-lncRNA regulatory network composed of 2 lncRNAs (H19 and GAS5) and 5 miRNAs (hsa-mir-106b-5p, hsa-mir-17-5p, hsa-mir-20a-5p, hsa-mir-6720-5p and hsa-mir-93-5p) targeting CCL5 mRNA. In conclusion, our study suggested that host genetic factors could affect therapeutic responsiveness in CHB patients. The antiviral process might be associated with the chemokine-mediated immune response and immune cell infiltration in the liver microenvironment.     

Cotton (Gossypium hirsutum) 14‐3‐3 proteins participate in regulation of fibre initiation and elongation by modulating brassinosteroid signalling

Cotton (Gossypium hirsutum) fibre is an important natural raw material for textile industry in the world. Understanding the molecular mechanism of fibre development is important for the development of future cotton varieties with superior fibre quality. In this study, overexpression of Gh14‐3‐3L in cotton promoted fibre elongation, leading to an increase in mature fibre length. In contrast, suppression of expression of Gh14‐3‐3L, Gh14‐3‐3e and Gh14‐3‐3h in cotton slowed down fibre initiation and elongation. As a result, the mature fibres of the Gh14‐3‐3 RNAi transgenic plants were significantly shorter than those of wild type. This ‘short fibre’ phenotype of the 14‐3‐3 RNAi cotton could be partially rescued by application of 2,4‐epibrassinolide (BL). Expression levels of the BR‐related and fibre‐related genes were altered in the Gh14‐3‐3 transgenic fibres. Furthermore, we identified Gh14‐3‐3 interacting proteins (including GhBZR1) in cotton. Site mutation assay revealed that Ser163 in GhBZR1 and Lys51/56/53 in Gh14‐3‐3L/e/h were required for Gh14‐3‐3‐GhBZR1 interaction. Nuclear localization of GhBZR1 protein was induced by BR, and phosphorylation of GhBZR1 by GhBIN2 kinase was helpful for its binding to Gh14‐3‐3 proteins. Additionally, 14‐3‐3‐regulated GhBZR1 protein may directly bind to GhXTH1 and GhEXP promoters to regulate gene expression for responding rapid fibre elongation. These results suggested that Gh14‐3‐3 proteins may be involved in regulating fibre initiation and elongation through their interacting with GhBZR1 to modulate BR signalling. Thus, our study provides the candidate intrinsic genes for improving fibre yield and quality by genetic manipulation.     

Interaction network analysis revealed biomarkers in myocardial infarction

Myocardial infarction (MI) is a serious heart disease. The cardiac cells of patients with MI will die due to lack of blood for a long time. In this study, we aimed to find new targets for MI diagnosis and therapy. We downloaded GSE22229 including 12 blood samples from healthy persons and GSE29111 from Gene Expression Omnibus including 36 blood samples from MI patients. Then we identified differentially expressed genes (DEGs) in patients with MI compared to normal controls with p value < 0.05 and |logFC| > 1. Furthermore, interaction network and sub-network of these of these DEGs were constructed by NetBox. Linker genes were screened in the Global Network database. The degree of linker genes were calculated by igraph package in R language. Gene ontology and kyoto encyclopedia of genes and genomes pathway analysis were performed for DEGs and network modules. A total of 246 DEGs were identified in MI, which were enriched in the immune response. In the interaction network, LCK, CD247, CD3D, FYN, HLA-DRA, IL2, CD8A CD3E, CD4, CD3G had high degree, among which CD3E, CD4, CD3G were DEGs while others were linker genes screened from Global Network database. Genes in the sub-network were also enriched in the immune response pathway. The genes with high degree may be biomarkers for MI diagnosis and therapy.     

Tumor-associated macrophage-derived chemokine CCL5 facilitates the progression and immunosuppressive tumor microenvironment of clear cell renal cell carcinoma

Background: Tumor-associated macrophages (TAMs) dominate the malignancy of cancers by perturbing the tumor microenvironment (TME). However, the clinical implications of heterogeneous subpopulations of TAMs in clear cell renal cell carcinoma (ccRCC) remain to be elucidated.Methods: We comprehensively evaluated the prognostic implications, biological behaviors, and immunogenomics features of the C-C Motif Chemokine Ligand 5 (CCL5) expression and CCL5⁺ TME in vitro and in 932 real-world ccRCC patients from testing and public validation cohorts. Flow cytometry was used to examine the functional patterns of CCL5⁺ TAMs with TME cell-infiltrating characterizations.Results: Our results identified distinct prognostic clusters with gradual changes in clinicopathological indicators based on CCL5 expression. Knockdown of CCL5 significantly restrained cell viability, migration capabilities of ccRCC cells, and the inhibits the proliferation and chemotaxis of THP1-derived TAMs. Mechanically, down-regulation of CCL5 arrested epithelial-mesenchymal transition by modulating the PI3K/AKT pathway in ccRCC cells. In ccRCC samples with CCL5 upregulation, the proportion of CCL5⁺ TAMs and PD-L1⁺ CD68⁺ TAMs were prominently increased, showing a typical suppressive tumor immune microenvironment (TIME). Besides, intra-tumoral CCL5⁺ TAMs showed distinct pro-tumorigenic TME features characterized by exhausted CD8⁺ T cells and increased expression of immune checkpoints. Furthermore, elevated CCL5⁺ TAMs infiltration was prominently associated with a dismal prognosis for patients with ccRCC.Conclusion: In conclusion, this study first revealed the predictive value of the chemokine CCL5 on the progression and TME of ccRCC. The intra-tumoral CCL5⁺ TAMs could be applied to comprehensively evaluate the prognostic patterns as well as unique TME characteristics among individuals, allowing for the identification of immunophenotypes and promotion of treatment efficiency for ccRCC.     

Analysis of the potential pathways and target genes in spinal cord injury using bioinformatics methods

Spinal cord injury (SCI) remains to be the most devastating type of trauma for patients because of long lasting disability and limited response to the acute drug administration and efforts at rehabilitation. With the purpose to identify potential targets for SCI treatment and to gain more insights into the mechanisms of SCI, the microarray data of GSE2270, including 119 raphe magnus (RM) samples and 125 sensorimotor cortex (SMTC) samples, was downloaded from the Gene Expression Omnibus database. Differentially expressed genes (DEGs) were screened in RM group and SMTC group compared with their corresponding controls, respectively. A protein–protein interaction (PPI) network was constructed based on the common DEGs identified in both RM group and SMTC group. Gene ontology (GO) and pathway enrichment analyses of the overlapping DEGs were performed. Furthermore, the common DEGs enriched in each pathway were analyzed to identify significant regulatory elements. Totally, 173 overlapping DEGs (130 up-regulated and 43 down-regulated) were identified in both RM and SMTC samples. These overlapping DEGs were enriched in different GO terms. Pathway enrichment analysis revealed that DEGs were mainly related to inflammation and immunity. CD68 molecule (CD68) was a hub protein in the PPI network. Moreover, the regulatory network showed that ras-related C3 botulinum toxin substrate 2 (RAC2), CD44 molecule (CD44), and actin related protein 2/3 complex (ARPC1B) were hub genes. RAC2, CD44, and ARPC1B may be significantly involved in the pathogenesis of SCI by participating significant pathways such as extracellular matrix-receptor signaling pathway and Toll-like receptor signaling pathway.