Amino acid metabolism characteristics of Banxia Baizhu Tianma Decoction in realizing drug withdrawal based on transcriptomic analysis / 中国中药杂志

This study aimed to demonstrate the effect of Banxia Baizhu Tianma Decoction(BBTD) on realizing withdrawal of anti-epileptic drugs and explore the relationship between BBTD and the amino acid metabolism by transcriptomic analysis in the rat model of epilepsy induced by lithium chloride-pilocarpine. The rats with epilepsy were divided into a control group(Ctrl), an epilepsy group(Ep), a BBTD & antiepileptic drug integrative group(BADIG), and an antiepileptic drug withdrawal group(ADWG). The Ctrl and Ep were given ultrapure water by gavage for 12 weeks. The BADIG was given BBTD extract and carbamazepine solution by gavage for 12 weeks. The ADWG was given carbamazepine solution and BBTD extract by gavage for the former 6 weeks, and then only given BBTD extract for the latter 6 weeks. The therapeutic effect was evaluated by behavioral observation, electroencephalogram(EEG), and hippocampal neuronal morphological changes. High-throughput sequencing was used to obtain amino acid metabolism-related differen-tial genes in the hippocampus, and the mRNA expression in the hippocampus of each group was verified by real-time quantitative polymerase chain reaction(RT-qPCR). The hub genes were screened out through protein-protein interaction(PPI) network, and Gene Ontology(GO) functional enrichment analysis and Kyoto Encyclopedia of Genes and Genomes(KEGG) pathway enrichment analysis were performed. Two ceRNA networks, namely circRNA-miRNA-mRNA and lncRNA-miRNA-mRNA, were constructed for ADWG vs BADIG. The experimental results showed that compared with those in Ep, rats in ADWG were significantly improved in the behavioral observation, EEG, and hippocampal neuronal impairment. Thirty-four amino acid metabolism-related differential genes were obtained by transcriptomic analysis, and the sequencing results were confirmed by RT-qPCR. Eight hub genes were obtained through PPI network, involving several biological processes, molecular functions, and signal pathways related to amino acid metabolism. Finally, the circRNA-miRNA-mRNA ternary transcription network of 17 circRNA, 5 miRNA, and 2 mRNA, and a lncRNA-miRNA-mRNA ternary network of 10 lncRNA, 5 miRNA, and 2 mRNA were constructed in ADWG vs BADIG. In conclusion, BBTD can effectively achieve the withdrawal of antiepileptic drugs, which may be related to the transcriptomic regulation of amino acid metabolism.

Analysis of Significant Genes and Pathways in Esophageal Cancer Based on Gene Expression Omnibus Database / 中国医学科学杂志(英文版)

Objective To screen antigen targets for immunotherapy by analyzing over-expressed genes, and to identify significant pathways and molecular mechanisms in esophageal cancer by using bioinformatic methods such as enrichment analysis, protein-protein interaction (PPI) network, and survival analysis based on the Gene Expression Omnibus (GEO) database.Methods By screening with highly expressed genes, we mainly analyzed proteins MUC13 and EPCAM with transmembrane domain and antigen epitope from TMHMM and IEDB websites. Significant genes and pathways associated with the pathogenesis of esophageal cancer were identified using enrichment analysis, PPI network, and survival analysis. Several software and platforms including Prism 8, R language, Cytoscape, DAVID, STRING, and GEPIA platform were used in the search and/or figure creation.Results Genes MUC13 and EPCAM were over-expressed with several antigen epitopes in esophageal squamous cell carcinoma (ESCC) tissue. Enrichment analysis revealed that the process of keratinization was focused and a series of genes were related with the development of esophageal cancer. Four genes including ALDH3A1, C2, SLC6A1,and ZBTB7C were screened with significant P value of survival curve.Conclusions Genes MUC13 and EPCAM may be promising antigen targets or biomarkers for esophageal cancer. Keratinization may greatly impact the pathogenesis of esophageal cancer. Genes ALDH3A1, C2, SLC6A1,and ZBTB7C may play important roles in the development of esophageal cancer.

Construction of endogenous RNA regulatory network for colorectal cancer based on bioinformatics / 中南大学学报(医学版)

OBJECTIVES@#The high morbidity and mortality of colorectal cancer (CRC) have posed great threats to human health. Circular RNA (circRNA) and microRNA (miRNA), acting as competing endogenous RNAs (ceRNAs), have been found to play vital roles in carcinogenesis. This paper aims to construct a circRNA/miRNA/mRNA regulatory network so as to explore the molecular mechanism of CRC.@*METHODS@#The sequencing data of circRNA from CRC were obtained from Gene Expression Omnibus (GEO). The differential circRNA was screened and its structure was identified by Cancer-specific CircRNA Database (CSCD); the sequencing data of miRNA and messenger RNA (mRNAs) were downloaded from The Cancer Genome Atlas (TCGA) database and the differentially expressed genes were screened; the corresponding miRNA of differential circRNAs were predicted by CircInteractome database; DIANA, Miranda, PicTar, and TargetScan databases were used to predict the target genes of different miRNAs; the target genes from Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) were enriched by R language; String database combined with Cytoscape 3.7.2 software was used to construct protein-protein interaction (PPI) network and hub genes were screened; the expressions of mRNAs in the Top10 hub genes were verified in CRC. The network diagrams of circRNAs/miRNAs/mRNAs and circRNAs/miRNAs/Top10 hub mRNAs were constructed by Cytoscape3.7.2. Real-time PCR was used to examine the expression levels of hsa_circRNA_0065173, hsa-mir-450b, hsa-mir-582, adenylate cyclase 5 (ADCY5), muscarinic acetylcholine receptor M2 (CHRM2), cannabinoid receptor 1 (CNR1), and lysophosphatidic acid receptor 1 (LPAR1) in the CRC tissues and the adjacent normal tissues.@*RESULTS@#A total of 14 differential circRNAs were identified, and 8 were found in CSCD; 34 miRNAs targeted by circRNAs were obtained. The PPI network was constructed, and the Top10 hub genes were identified, which were CHRM2, melanin concentrating hormone receptor 2 (MCHR2), G-protein gamma 3 subunit (GNG3), neuropeptide Y receptor Y1 (NPY1R), CNR1, LPAR1, ADCY5, adenylate cyclase 2 (ADCY2), gamma 7 (GNG7) and chemokine 12 (CXCL12), respectively. The expressions of Top 10 hub genes were also verified, and the results showed that the Top 10 hub genes were down-regulated in CRC; the constructed network diagram showed that hsa_circRNA_0065173 may regulate ADCY5, CHRM2, and Hsa-mir-450b by modulating hsa-mir-450b and hsa-mir-582. CNR1 and LPAR1 genes might serve as potentially relevant targets for the treatment of CRC. Real-time PCR results showed that the expression levels of hsa_circRNA_0065173, ADCY5, CHRM2, CNR1 and LPAR1 in the CRC tissues were significantly reduced compared with the adjacent normal tissues (all P<0.05); the expression levels of hsa-mir-450b and hsa-miR-582 were significantly increased (both P<0.05).@*CONCLUSIONS@#In this study, a potential circRNAs/miRNAs/mRNAs network is successfully constructed, which provides a new insight for CRC development mechanism through ceRNA mediated by circRNAs.

Research advances on the role of competing endogenous RNAs in wound healing / 中华烧伤杂志

Wound healing, as one of the important public health issues, has been a worldwide problem. Due to the unique biological wound environment, wound healing is a very complex process with current treatments requiring long cycles, being poorly effective, and bringing high economic burden to patients. An increasing number of studies have shown that non-coding RNAs (ncRNAs) play important roles in wound healing process. The competing endogenous RNAs (ceRNAs) hypothesis in recent years is a new proposal on the inter-regulation of RNAs, which suggests a "mode of communication" between different RNAs. ceRNA regulatory network (ceRNET) combines the functions of protein-coding mRNA with ncRNA (e.g., microRNA, long non-coding RNA, pseudogenes, and circular RNA). Recent studies have shown that ceRNAs play important roles in wound healing, which may provide new effective therapeutic targets for wound healing. This paper starting with ceRNET systematically reviewed the research progress on the effects of various ceRNAs in wound healing and the future research challenges, with the aim to deeply explore the molecular mechanisms and clinical significance of ceRNAs in the process of wound healing.

Bioinformatics screening and analysis of key differentially expressed genes characteristics in nonalcoholic fatty liver disease / 中华肝脏病杂志

Objective: To screen and analyze the key differentially expressed genes characteristics in nonalcoholic fatty liver disease (NAFLD) with bioinformatics method. Methods: NAFLD-related expression matrix GSE89632 was downloaded from the GEO database. Limma package was used to screen differentially expressed genes (DEGs) in healthy, steatosis (SS), and nonalcoholic steatohepatitis (NASH) samples. WGCNA was used to analyze the output gene module. The intersection of module genes and differential genes was used to determine the differential genes characteristic, and then GO function and KEGG signaling pathway enrichment analysis were performed. The protein-protein interaction network (PPI) was constructed using the online website STRING and Cytoscape software, and the key (Hub) genes were screened. Finally, R software was used to analyze the receiver operating characteristic curve (ROC) of the Hub gene. Results: 92 differentially expressed genes characteristic were obtained through screening, which were mainly enriched in inflammatory response-related functions of "lipopolysaccharide response and molecular response of bacterial origin", as well as cancer signaling pathways of "proteoglycan in cancer" and "T-cell leukemia virus infection-related". 10 hub genes (FOS, CXCL8, SERPINE1, CYR61, THBS1, FOSL1, CCL2, MYC, SOCS3 and ATF3) had good diagnostic value. Conclusion: The differentially expressed hub genes among the 10 NAFLD disease-related characteristics obtained with bioinformatics analysis may become a diagnostic and prognostic marker and potential therapeutic target for NAFLD. However, further basic and clinical studies are needed to validate.

Screening Biomarkers of Sudden Coronary Death Based on mRNA Expression Profile of Rat Myocardial Tissues / 法医学杂志

OBJECTIVES@#To explore the differential expression of messenger RNA (mRNA) in myocardial tissues of rats with sudden coronary death (SCD), and to provide ideas for the forensic identification of SCD.@*METHODS@#The rat SCD model was established, and the transcriptome sequencing was performed by next-generation sequencing technology. Differentially expressed genes (DEGs) in myocardial tissues of SCD rats were screened by using the R package limma. A protein-protein interaction (PPI) network was constructed by using the STRING database and Cytoscape 3.8.2 on DEG, and hub genes were screened based on cytoHubba plug-in. Finally, the R package clusterProfiler was used to analyze the biological function and signal pathway enrichment of the selected DEG.@*RESULTS@#A total of 177 DEGs were associated with SCD and were mainly involved in the renin-angiotensin system and PI3K-Akt signaling pathway. The genes including angiotensinogen (AGT), complement component 4a (C4a), Fos proto-oncogene (FOS) and others played key roles in the development of SCD.@*CONCLUSIONS@#Genes such as AGT, C4a, FOS and other genes are expected to be potential biomarkers for forensic identification of SCD. The study based on mRNA expression profile can provide a reference for forensic identification of SCD.

Quantifying the state of cell differentiation based on the gene networks entropy / 生物工程学报

Studies of cellular dynamic processes have shown that cells undergo state changes during dynamic processes, controlled mainly by the expression of genes within the cell. With the development of high-throughput sequencing technologies, the availability of large amounts of gene expression data enables the acquisition of true gene expression information of cells at the single-cell level. However, most existing research methods require the use of information beyond gene expression, thus introducing additional complexity and uncertainty. In addition, the prevalence of dropout events hampers the study of cellular dynamics. To this end, we propose an approach named gene interaction network entropy (GINE) to quantify the state of cell differentiation as a means of studying cellular dynamics. Specifically, by constructing a cell-specific network based on the association between genes through the stability of the network, and defining the GINE, the unstable gene expression data is converted into a relatively stable GINE. This method has no additional complexity or uncertainty, and at the same time circumvents the effects of dropout events to a certain extent, allowing for a more reliable characterization of biological processes such as cell fate. This method was applied to study two single-cell RNA-seq datasets, head and neck squamous cell carcinoma and chronic myeloid leukaemia. The GINE method not only effectively distinguishes malignant cells from benign cells and differentiates between different periods of differentiation, but also effectively reflects the disease efficacy process, demonstrating the potential of using GINE to study cellular dynamics. The method aims to explore the dynamic information at the level of single cell disorganization and thus to study the dynamics of biological system processes. The results of this study may provide scientific recommendations for research on cell differentiation, tracking cancer development, and the process of disease response to drugs.

Characterization of chromatin accessibility in psoriasis / 医学前沿

The pathological hallmarks of psoriasis involve alterations in T cell genes associated with transcriptional levels, which are determined by chromatin accessibility. However, to what extent these alterations in T cell transcriptional levels recapitulate the epigenetic features of psoriasis remains unknown. Here, we systematically profiled chromatin accessibility on Th1, Th2, Th1-17, Th17, and Treg cells and found that chromatin remodeling contributes significantly to the pathogenesis of the disease. The chromatin remodeling tendency of different subtypes of Th cells were relatively consistent. Next, we profiled chromatin accessibility and transcriptional dynamics on memory Th/Treg cells. In the memory Th cells, 803 increased and 545 decreased chromatin-accessible regions were identified. In the memory Treg cells, 713 increased and 1206 decreased chromatin-accessible regions were identified. A total of 54 and 53 genes were differentially expressed in the peaks associated with the memory Th and Treg cells. FOSL1, SPI1, ATF3, NFKB1, RUNX, ETV4, ERG, FLI1, and ETC1 were identified as regulators in the development of psoriasis. The transcriptional regulatory network showed that NFKB1 and RELA were highly connected and central to the network. NFKB1 regulated the genes of CCL3, CXCL2, and IL1RN. Our results provided candidate transcription factors and a foundational framework of the regulomes of the disease.

Therapeutic cell engineering: designing programmable synthetic genetic circuits in mammalian cells

Cell therapy approaches that employ engineered mammalian cells for on-demand production of therapeutic agents in the patient's body are moving beyond proof-of-concept in translational medicine. The therapeutic cells can be customized to sense user-defined signals, process them, and respond in a programmable and predictable way. In this paper, we introduce the available tools and strategies employed to design therapeutic cells. Then, various approaches to control cell behaviors, including open-loop and closed-loop systems, are discussed. We also highlight therapeutic applications of engineered cells for early diagnosis and treatment of various diseases in the clinic and in experimental disease models. Finally, we consider emerging technologies such as digital devices and their potential for incorporation into future cell-based therapies.

Identification of onco-miRNAs in hepatocellular carcinoma and analysis of their regulatory network / 南方医科大学学报

OBJECTIVE@#To construct the regulatory network of survival-related onco-miRNAs and their target genes in hepatocellular carcinoma (HCC) and verify the interactions between the key miRNAs and their targets.@*METHODS@#We screened survival-related miRNAs in HCC in OncomiR and Oncolnc databases, predicted their target genes using miRNet, and conducted survival and expression analysis using GEPIA2 and Ualcan, respectively. The miRNA-target gene co-expression analysis was performed and the miRNA-target network was constructed. Enrichment analysis was performed in Enrichr and protein-protein interaction analysis in STRING database. We tested the effects of transfection with the mimic or inhibitor of hsa-miR-1226-3p or hsa-miR-221-5p on proliferation of HepG2 cells using CCK8 assay and examined the changes in the expressions of the target genes using RT-qPCR. The effect of transfection with hsa-miR-221-5p mimic or inhibitor on protein expressions of the target genes was examined using Western blotting in. A dual luciferase reporter assay was used to test the interaction between hsa-miR-221-5p and its potential target gene GCDH. We further examined the effect of transfection with hsa-miR-221-5p mimic and pEGFP N1-GCDH, alone or in combination, on proliferation, migration and invasion of HepG2 cells.@*RESULTS@#We identified 223 survival-related miRNAs in HCC from OncomiR and 146 miRNAs from Oncolnc with an intersection of 131 miRNAs, and 48 miRNAs were identified as onco-miRNAs in HCC after survival and expression analysis. Twenty-seven eligible target genes were identified after miRNA-mRNA co-expression analysis. The constructed miRNA-target gene network consisted of 25 miRNAs and 27 target genes. The most enriched term was fatty acid metabolism for the target genes. In HepG2 cells, transfection with the mimic or inhibitor of hsa-miR-1226-3p or hsa-miR-221-5p caused significant changes of the mRNA and protein levels of their respective target genes (P < 0.05). The results of dual luciferase reporter assay confirmed the targeting relationship between hsa-miR-221-5p and GCDH gene (P < 0.05). Transfection with hsa-miR-221-5p mimic significantly suppressed the proliferation, migration and invasion of HepG2 cells, but this effect was obviously relieved by co-transformation with pEGFP N1-GCDH (P < 0.05).@*CONCLUSION@#Fatty acid metabolism might be one of the most crucial pathways that mediate the effect of the oncomiRNAs in HCC, and the hsa-miR-221-5p/GCDH axis is an important molecular mechanism for HCC progression.

Identification of blood-derived candidate gene markers and a new 7-gene diagnostic model for multiple sclerosis

BACKGROUND: Multiple sclerosis (MS) is a central nervous system disease with a high disability rate. Modern molecular biology techniques have identified a number of key genes and diagnostic markers to MS, but the etiology and pathogenesis of MS remain unknown. RESULTS: In this study, the integration of three peripheral blood mononuclear cell (PBMC) microarray datasets and one peripheral blood T cells microarray dataset allowed comprehensive network and pathway analyses of the biological functions of MS-related genes. Differential expression analysis identified 78 significantly aberrantly expressed genes in MS, and further functional enrichment analysis showed that these genes were associated with innate immune response-activating signal transduction (p = 0.0017), neutrophil mediated immunity (p = 0.002), positive regulation of innate immune response (p = 0.004), IL-17 signaling pathway (p < 0.035) and other immune-related signaling pathways. In addition, a network of MS-specific protein-protein interactions (PPI) was constructed based on differential genes. Subsequent analysis of network topology properties identified the up-regulated CXCR4, ITGAM, ACTB, RHOA, RPS27A, UBA52, and RPL8 genes as the hub genes of the network, and they were also potential biomarkers of MS through Rap1 signaling pathway or leukocyte transendothelial migration. RT-qPCR results demonstrated that CXCR4 was obviously up-regulated, while ACTB, RHOA, and ITGAM were down-regulated in MS patient PBMC in comparison with normal samples. Finally, support vector machine was employed to establish a diagnostic model of MS with a high prediction performance in internal and external datasets (mean AUC = 0.97) and in different chip platform datasets (AUC = (0.93). CONCLUSION: This study provides new understanding for the etiology/pathogenesis of MS, facilitating an early identification and prediction of MS.

Differential mRNA expression in C57BL/6 mice with bleomycin-induced pulmonary fibrosis and its association with LncRNA co-expression network / 南方医科大学学报

OBJECTIVE@#To study the changes in mRNA and long non-coding RNA (lncRNA) expression profiles in a mouse model of bleomycin-induced lung fibrosis and identify lung fibrosis-related mRNA for coding-noncoding coexpression (CNC) bioinformatics analysis of the differential lncRNAs.@*METHODS@#Lung fibrosis was induced by intratracheal injection of bleomycin in 10 C57BL/6 mice and another 10 mice with intratracheal injection of saline served as the control group. Lung tissues were harvested from the mice at 14 days after the injections and lung fibrosis was assessed using Masson and HE staining. LncRNA chip technology was used to screen the differentially expressed mRNAs and lncRNAs in mice with lung fibrosis, and GO and KEGG pathway analyses of the differential mRNAs were performed using NCBI database and UCSC database to identify possible fibrosis-related mRNAs, which were validated by qRT-PCR to construct a coding and non-coding co- expression network with the differential lncRNAs.@*RESULTS@#Compared with the control mice, the mice with intratracheal injection of bleomycin showed obvious lung fibrosis. The results of gene chip analysis showed that 127 mRNAs were upregulated and 184 mRNAs were down-regulated in the model group as compared with the control group. GO and pathway analysis suggested that the differentially expressed genes participated mainly in immune response, cell differentiation, and cytoskeletons; the involved signal pathways were associated mainly with cytokine and cytokine receptor interaction and chemokine signal transduction. Bioinformatics analysis identified a significant coexpression network between the fibrosisrelated mRNA and the differentially expressed lncRNA.@*CONCLUSIONS@#In mice with lung fibrosis, the differential expressions of fibrosis-related mRNAs in the lung tissues are closely correlated with the co- expressions of a large number of differential lncRNAs, which points to a new direction for investigation of the pathogenesis of pulmonary fibrosis.

Changes in gene expression of adipose tissue CD14 / 中南大学学报(医学版)

OBJECTIVES@#To study the gene expression of adipose tissue CD14@*METHODS@#The data of GSE54350 were obtained from the public database of gene expression profiling. The data were pre-processed by Network Analyst, String 11.0, Cytoscape 3.7.1, and other analytical software. The differentially expressed genes were analyzed by gene ontology biological function and kyoto encycopedia of genes and genomes (KEGG) signaling pathway to establish differential gene protein interaction network, transcription factor-gene regulatory network, microRNA-gene regulatory network, environmental factors-gene regulatory network, and other interaction systems.@*RESULTS@#The gene expression pattern of CD14@*CONCLUSIONS@#The gene expression of adipose tissue CD14

Liver Tissue-specific Genes IGFALS,CYP3A4,SLC22A1 and CYP2E1 May be Associated with Poor Prognosis of Liver Cancer / 中国医学科学院学报

Objective To explore the function and mechanism of related genes in the occurrence and development of liver cancer, and the possibility of key genes as potential biomarkers and prognostic indicators for the treatment of liver cancer.Methods We selected 4 datasets(GSE57957, GSE121248, GSE36376 and GSE14520)from the GEO database.With

Met-Controlled Allosteric Module of Neural Generation as A New Therapeutic Target in Rodent Brain Ischemia / 中国结合医学杂志

OBJECTIVE@#To investigate a Met-controlled allosteric module (AM) of neural generation as a potential therapeutic target for brain ischemia.@*METHODS@#We selected Markov clustering algorithm (MCL) to mine functional modules in the related target networks. According to the topological similarity, one functional module was predicted in the modules of baicalin (BA), jasminoidin (JA), cholic acid (CA), compared with I/R model modules. This functional module included three genes: Inppl1, Met and Dapk3 (IMD). By gene ontology enrichment analysis, biological process related to this functional module was obtained. This functional module participated in generation of neurons. Western blotting was applied to present the compound-dependent regulation of IMD. Co-immunoprecipitation was used to reveal the relationship among the three members. We used IF to determine the number of newborn neurons between compound treatment group and ischemia/reperfusion group. The expressions of vascular endothelial growth factor (VEGF) and matrix metalloproteinase 9 (MMP-9) were supposed to show the changing circumstances for neural generation under cerebral ischemia.@*RESULTS@#Significant reduction in infarction volume and pathological changes were shown in the compound treatment groups compared with the I/R model group (P<0.05). Three nodes in one novel module of IMD were found to exert diverse compound-dependent ischemic-specific excitatory regulatory activities. An anti-ischemic excitatory allosteric module (AM@*CONCLUSIONS@#AM

Integration-based co-expression network analysis to investigate tumor-associated modules across three cancer types / 生物工程学报

In case/control gene expression data, differential expression (DE) represents changes in gene expression levels across various biological conditions, whereas differential co-expression (DC) represents an alteration of correlation coefficients between gene pairs. Both DC and DE genes have been studied extensively in human diseases. However, effective approaches for integrating DC-DE analyses are lacking. Here, we report a novel analytical framework named DC&DEmodule for integrating DC and DE analyses and combining information from multiple case/control expression datasets to identify disease-related gene co-expression modules. This includes activated modules (gaining co-expression and up-regulated in disease) and dysfunctional modules (losing co-expression and down-regulated in disease). By applying this framework to microarray data associated with liver, gastric and colon cancer, we identified two, five and two activated modules and five, five and one dysfunctional module(s), respectively. Compared with the other methods, pathway enrichment analysis demonstrated the superior sensitivity of our method in detecting both known cancer-related pathways and those not previously reported. Moreover, we identified 17, 69, and 11 module hub genes that were activated in three cancers, which included 53 known and three novel cancer prognostic markers. Random forest classifiers trained by the hub genes showed an average of 93% accuracy in differentiating tumor and adjacent normal samples in the TCGA and GEO database. Comparison of the three cancers provided new insights into common and tissue-specific cancer mechanisms. A series of evaluations demonstrated the framework is capable of integrating the rapidly accumulated expression data and facilitating the discovery of dysregulated processes.

Identification of potential molecular mechanisms and small molecule drugs in myocardial ischemia/reperfusion injury

Myocardial ischemia/reperfusion (MI/R) injury is a complex phenomenon that causes severe damage to the myocardium. However, the potential molecular mechanisms of MI/R injury have not been fully clarified. We identified potential molecular mechanisms and therapeutic targets in MI/R injury through analysis of Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) were found between MI/R injury and normal samples, and overlapping DEGs were found between GSE61592 and GSE67308. Gene Ontology (GO) and pathway analysis were performed for overlapping DEGs by Database for Annotation, Visualization and Integration Discovery (DAVID). Then, a network of protein-protein interaction (PPI) was constructed through the Search Tool for the Retrieval of Interacting Genes (STRING) database. Potential microRNAs (miRNAs) and therapeutic small molecules were screened out using microRNA.org database and the Comparative Toxicogenomics database (CTD), respectively. Finally, we identified 21 overlapping DEGs related to MI/R injury. These DEGs were significantly enriched in IL-17 signaling pathway, cytosolic DNA-sensing pathway, chemokine signaling, and cytokine-cytokine receptor interaction pathway. According to the degree in the PPI network, CCL2, LCN2, HP, CCL7, HMOX1, CCL4, and S100A8 were found to be hub genes. Furthermore, we identified potential miRNAs (miR-24-3p, miR-26b-5p, miR-2861, miR-217, miR-4251, and miR-124-3p) and therapeutic small molecules like ozone, troglitazone, rosiglitazone, and n-3 polyunsaturated fatty acids for MI/R injury. These results identified hub genes and potential small molecule drugs, which could contribute to the understanding of molecular mechanisms and treatment for MI/R injury.

Identification of Molecular Signatures in Mild Intrinsic Atopic Dermatitis by Bioinformatics Analysis

BACKGROUND: Atopic dermatitis (AD) is recognized as a common inflammatory skin disease and frequently occurred in Asian and Black individuals.OBJECTIVE: Since the limitation of dataset associated with human severe AD, this study aimed to screen potential novel biomarkers involved in mild AD.METHODS: Expression profile data (GSE75890) were obtained from the database of Gene Expression Omnibus. Using limma package, the differentially expressed genes (DEGs) between samples from AD and healthy control were selected. Furthermore, function analysis was conducted. Meanwhile, the protein-protein interaction (PPI) network and transcription factor (TF)-miRNA-target regulatory network were constructed. And quantitative real-time polymerase chain reaction (qRT-PCR) was used to validate the expressions patterns of key genes.RESULTS: In total, 285 DEGs including 214 upregulated and 71 downregulated genes were identified between samples from two groups. The upregulated DEGs were mainly involved in nine pathways, such as hematopoietic cell lineage, pertussis, p53 signaling pathway, staphylococcus aureus infection, and cell cycle, while tight junction was the only pathway enriched by the downregulated DEGs. Cyclin B (CCNB)1, CCNB2, cyclin A (CCNA)2, C-X-C motif chemokine ligand (CXCL)10, and CXCL9 were key nodes in PPI network. The TF-miRNA-target gene regulatory network focused on miRNAs such as miR-106b, miR-106a, and miR-17, TFs such as nuclear factor kappa B subunit 1, RELA proto-oncogene, Sp1 transcription factor, and genes such as matrix metallopeptidase 9, peroxisome proliferator activated receptor gamma , and serpin family E member 1. Moreover, the upregulation of these genes, including CCNB1, CCNB2, CCNA2, CXCL10, and CXCL9 were confirmed by qRT-PCR.CONCLUSION: CCNB1, CCNB2, CCNA2, and CXCL9 might be novel markers of mild AD. miR-106b and miR-17 may involve in regulation of immune response in AD patients.

Integración de la Bioinformática en la caracterización Clínica y Genómica de Retinitis Pigmentosa, Síndrome de Noonan y Síndrome de Retraso Mental Martin-Probs, en un mismo individuo. Reporte de un Caso / Integration of Bioinformatics in the Clinical and Genomic Characterization of Retinitis Pigmentosa, Noonan Syndrome and Martin-Probs Mental Retardation Syndrome, in the Same Individual. Case report

Introducción: El avance en las técnicas bioinformáticas ha permitido realizar acercamientos y mejoras en los diagnósticos clínicos, correlacionando genotipo ­ fenotipo y permitiendo el acercamiento a una terapia personalizada. Objetivo: Realizar mediante técnicas bioinformáticas, la caracterización molecular y de expresión génica de una paciente con manifestaciones clínicas (dismorfias, retraso en el desarrollo) de una enfermedad compleja (poligénica). Materiales y métodos: Se realizó la secuenciación de exoma completo a partir de una muestra de sangre periférica. Se analizaron los datos obtenidos mediante análisis in-sílico, utilizando programas como SIFT, Mutation Tester, UMD y Provean, para determinar la significancia clínica de variantes encontradas; además se usó programa GeneMania para determinar las interacciones génicas. Resultados:Se encontraron 3 variantes en los genes SEMA4A, PTPN11 y RAB40A, asociados a Retinitis pigmentosa 35, Síndrome de Noonan y Sindrome de retraso mental Martin-Probs, respectivamente; encontrando según los softwares predictores, en el primer caso un significado clínico aparentemente benigno, y en los dos últimos genes un significado clínico patogénico. El análisis de redes génicas reveló alteraciones en funciones biológicas como la señalización mediada por fosfatidilinositol, respuesta al factor del crecimiento fibroblástico, vía de señalización de neutrofina y la morfogénesis de vasos sanguíneo que permitieron explicar gran parte de la sintomatología observada. Conclusión: El análisis personalizado de las patologías complejas mediante el uso de la clínica, herramientas genómicas y bioinformaticas han permitido un avance significativo en las técnicas para el procesamiento y análisis de datos, beneficiando los estudios científicos que permiten el acercamiento a un correcto diagnóstico y adecuada consejería genética.

Introduction: Advances in bioinformatics techniques have allowed approaches and improvements in clinical diagnoses, correlating genotype - phenotype and allowing the approach to personalized therapy. Objective: In order to perform the molecular characterization and gene expression in a patient with complex clinical manifestations through bioinformatics techniques, complete exome sequencing was performed by a peripheral blood sample to a woman with facial dysmorphisms and developmental disorders. Material and methods: We analyzed the data obtained by in-silico analysis, using programs such as SIFT, Mutation Tester, UMD and Provean, to determine the clinical significance of the found variants and GeneMania program was used to determine gene interactions. Results: 3 variants were found in the genes SEMA4A, PTPN11 and RAB40A, associated with Retinitis pigmentosa 35, Noonan Syndrome and Mental Retardation Syndrome Martin-Probs, respectively; according to the predictive softwares, in the first case an apparently benign clinical meaning, and in the last two genes a clinical pathogenic meaning. The analysis of gene networks revealed alterations in biological functions such as signaling mediated by phosphatidylinositol, response to the fibroblastic growth factor, neutrophin signaling pathway and blood vessel morphogenesis that allowed us to explain a large part of the observed symptomatology. Conclusion: The personalized analysis of complex pathologies through the use of clinical, genomic and bioinformatic tools has allowed a significant advance in techniques for processing and analyzing data, benefiting scientific studies that allow the approach to a correct diagnosis and adequate genetic counseling.