Identification of key genes and pathways associated with dilated cardiomyopathy development by bioinformatics analysis / 西安交通大学学报(医学版)

【Objective】 To explore the potential biomarkers and related enrichment pathways of dilated cardiomyopathy （DCM） by bioinformatics methods. 【Methods】 The data sets related to DCM in GEO database were searched， and microarray data sets GSE42955 and GSE1869 of human cardiomyocytes were extracted. Then， the differentially expressed genes （DEGS） were analyzed using R language， and the protein-protein interaction network was analyzed to identify the core genes and core modules of differential expression. The gene ontology database （GO） enrichment and Kyoto Gene and Genome Encyclopedia （KEGG） pathway analyses were performed. The data sets related to DCM in ArrayExpress database were searched， and the human cardiomyocytes microarray data set E-TABM-480 was extracted to verify the expressions of core genes and modules. 【Results】 We identified 10 DEGS， namely， DZIP3， FBXO32， BTBD6， FBXL5， ASB8， COMMD1， LTN1， FBXO21， RCHY1 and ARIH2， and the core DEG was DZIP3. After GO and KEGG analyses， the GO and KEGG of the above DEGS were mainly related to the ubiquitin-proteasome system. 【Conclusion】 Bioinformatics analysis shows that the ubiquitin-proteasome system plays an important role in the pathogenesis of DCM， and the mechanism remains to be further studied.

Pathogenesis and therapeutic targets of inflammatory cardiomyopathy based on bioinformatics analysis / 西安交通大学学报(医学版)

【Objective】 To make bioinformatics analysis of inflammatory cardiomyopathy so as to screen out hub genes related to etiology and therapeutic targets. 【Methods】 Differential expression analysis of inflammatory cardiomyopathy gene chip data from Gene Expression Omnibus （GEO） Database was carried out via GEO2R tool. Protein-protein interaction（PPI）network and hub genes identification were realized by String database and CytoHubba. GO and KEGG enrichment analysis for functional annotation and pathway analysis of hub genes were conducted by R language. Web-based enrichment analysis platform Enrichr and Drug Signatures database were applied to screen out candidate drugs targeting hub genes for inflammatory cardiomyopathy. 【Results】 The 149 DEGs were statistically significant， among which 44 were upregulated and 105 were downregulated. To identify hub genes， PPI network consisting of 37 nodes and 116 edges was constructed， and 16 hub genes were NDUFB7， POLR2L， NDUFS7， UQCR11， NDUFA13， NDUFA2， PHPT1， NDUFB10， UBA52， ATP5D， NDUFA3， COX6B1， POLR2J， COX4I2， AURKAIP1 and MRPL41. Hub genes were enriched to 113 different GO terms， and the most significant terms were mitochondrial ATP synthesis coupled electron transport， respiratory electron transport chain， oxidative phosphorylation， respiratory chain， mitochondrial inner membrane， NADH dehydrogenase activity and oxidoreductase activity. DEGs were enriched to 13 different signal pathways， including oxidative phosphorylation， non-alcoholic fatty liver disease， diabetic cardiomyopathy， and cardiac muscle contraction. We screened out candidate drugs targeting hub genes， namely， metformin hydrochloride， clindamycin， and hydralazine. 【Conclusion】 Hub genes screened out by decoding the expression profiles are convolved in the etiology and mechanism of inflammatory cardiomyopathy， which might serve as latent therapeutic targets and benefit patients with inflammatory cardiomyopathy.

Analysis of differentially expressed genes in bacterial and fungal keratitis

Purpose: This study was aimed at identifying differentially expressed genes (DEGs) in bacterial and fungal keratitis. The candidate genes can be selected and quantified to distinguish between causative agents of infectious keratitis to improve therapeutic outcomes. Methods: The expression profile of bacterial or fungal infection, and normal corneal tissues were downloaded from the Gene Expression Omnibus. The limma package in R was used to screen DEGs in bacterial and fungal keratitis. The Co-Express tool was used to calculate correlation coefficients of co-expressed genes. The "Advanced network merge" function of Cytoscape tool was applied to obtain a fusional co-expression network based on bacterial and fungal keratitis DEGs. Finally, functional enrichment analysis by DAVID software and KEGG analysis by KOBAS of DEGs in fusion network were performed. Results: In total, 451 DEGs in bacterial keratitis and 353 DEGs in fungal keratitis were screened, among which 148 DEGs were found only in bacterial keratitis and 50 DEGs only in fungal keratitis. Besides, 117 co-expressed gene pairs were identified among bacterial keratitis DEGs and 87 pairs among fungal keratitis DEGs. In total, nine biological pathways and seven KEGG pathways were screened by analyzing DEGs in the fusional co-expression network. Conclusion: TLR4 is the representative DEG specific to bacterial keratitis, and SOD2 is the representative DEG specific to fungal keratitis, both of which are promising candidate genes to distinguish between bacterial and fungal keratitis.

Identification of PTPRR and JAG1 as key genes in castration-resistant prostate cancer by integrated bioinformatics methods / 浙江大学学报（英文版）（B辑：生物医学和生物技术）

To identify novel genes in castration-resistant prostate cancer (CRPC), we downloaded three microarray datasets containing CRPC and primary prostate cancer in Gene Expression Omnibus (GEO). R packages affy and limma were performed to identify differentially expressed genes (DEGs) between primary prostate cancer and CRPC. After that, we performed functional enrichment analysis including gene ontology (GO) and Kyoto encyclopedia of genes and genomes (KEGG) pathway. In addition, protein-protein interaction (PPI) analysis was used to search for hub genes. Finally, to validate the significance of these genes, we performed survival analysis. As a result, we identified 53 upregulated genes and 58 downregulated genes that changed in at least two datasets. Functional enrichment analysis showed significant changes in the positive regulation of osteoblast differentiation pathway and aldosterone-regulated sodium reabsorption pathway. PPI network identified hub genes like cortactin-binding protein 2 (CTTNBP2), Rho family guanosine triphosphatase (GTPase) 3 (RND3), protein tyrosine phosphatase receptor-type R (PTPRR), Jagged1 (JAG1), and lumican (LUM). Based on PPI network analysis and functional enrichment analysis, we identified two genes (PTPRR and JAG1) as key genes. Further survival analysis indicated a relationship between high expression of the two genes and poor prognosis of prostate cancer. In conclusion, PTPRR and JAG1 are key genes in the CRPC, which may serve as promising biomarkers of diagnosis and prognosis of CRPC.

Identification of PTPRR and JAG1 as key genes in castration-resistant prostate cancer by integrated bioinformatics methods / 浙江大学学报（英文版）（B辑：生物医学和生物技术）

To identify novel genes in castration-resistant prostate cancer (CRPC), we downloaded three microarray datasets containing CRPC and primary prostate cancer in Gene Expression Omnibus (GEO). R packages affy and limma were performed to identify differentially expressed genes (DEGs) between primary prostate cancer and CRPC. After that, we performed functional enrichment analysis including gene ontology (GO) and Kyoto encyclopedia of genes and genomes (KEGG) pathway. In addition, protein-protein interaction (PPI) analysis was used to search for hub genes. Finally, to validate the significance of these genes, we performed survival analysis. As a result, we identified 53 upregulated genes and 58 downregulated genes that changed in at least two datasets. Functional enrichment analysis showed significant changes in the positive regulation of osteoblast differentiation pathway and aldosterone-regulated sodium reabsorption pathway. PPI network identified hub genes like cortactin-binding protein 2 (CTTNBP2), Rho family guanosine triphosphatase (GTPase) 3 (RND3), protein tyrosine phosphatase receptor-type R (PTPRR), Jagged1 (JAG1), and lumican (LUM). Based on PPI network analysis and functional enrichment analysis, we identified two genes (PTPRR and JAG1) as key genes. Further survival analysis indicated a relationship between high expression of the two genes and poor prognosis of prostate cancer. In conclusion, PTPRR and JAG1 are key genes in the CRPC, which may serve as promising biomarkers of diagnosis and prognosis of CRPC.

Bioinformatics analysis and functional prediction of potential lung cancer associated genes in female non-smokers / 中国肿瘤生物治疗杂志

@#[Abstract] Objective: To explore the pathogenosis and prognostic markers for non-smoking female lung cancer patients with bioinfor‐ matics analysis and functional prediction of potential lung cancer associated genes in female non-smokers. Methods: Data for nonsmoking female patients with lung cancer were downloaded from the Gene Expression Omnibus (GEO) database and the differentially expressed genes (DEGs) were identified using GEO2R. DAVID online data base was used to perform gene ontology (GO) and Kyoto encyclopedia of genes and genomes (KEGG), and STRING online software was used to perform protein-protein interaction (PPI) analysis; then the plug-in (M-CODE) was used to screen the key DEGs; finally, GEPIA and Kaplan-Meier plotter were used to perform function prediction and prognosis analysis of key DEGs. Results: A total of 160 DEGs were screened, including 54 up-regulated and 106 down-regulated genes; GO enrichment analysis showed that these DEGs were mainly related to neovascularization, single cell adhesion, positive regulation of GTPase activity and signal transduction (all P<0.05). KEGG pathway analysis revealed that DEGs were mainly involved in cell adhesion molecules (CAMs), leukocyte transendothelial migration, tight junction and endocytosis (all P<0.05); PPI network analysis revealed 8 key DEGs, including TIE1, PECAM1, CLDN5, VEGFD, ICAM2, ESAM, EMCN and ROBO4. Conclusion: TIE1, CLDN5, ICAM2, ESAM, VEGFD and ROBO4 may be the research targets of the pathogenesis of non-smoking female lung cancer patients. PECAM1 and EMCN may be the new bio-markers to predict the progression and prognosis of nonsmoking female lung cancer patients.

Analysis of differentially expressed genes and signaling pathways in colorectal cancer with liver metastasis / 中国肿瘤生物治疗杂志

@#[Abstract] Objective: To explore the key genes and molecular mechanisms of liver metastasis in colorectal cancer (CRC), and to provide potential targets and biomarkers for the treatment of CRC with liver metastasis. Methods: Based on the bioinformatics method, the gene data sets of CRC liver metastasis were downloaded from the GEO database to screen the differentially expressed genes (DEGs); the GO and KEGG enrichment analyses of DEGs were performed by using DAVID online tool, and the protein-protein interaction (PPI) network was constructed to screen out the key genes, and subsequently the prognosis was analyzed. Results: A total of 321 DEGs were selected from 183 CRC specimens and 39 liver metastasis specimens, including 153 up-regulated genes and 168 downregulated genes. The results of enrichment analysis of GO and KEGG showed that the functions of DEGs were mainly related to protein activation cascade, inflammatory response, extracellular matrix, platelet degranulation, complement and coagulation cascade reaction etc. 8 key CRC genes (ALB, APOB, FGA, F2, APOA1, SERPINC1, FGG and AHSG) were screened by PPI network. Survival analysis showed that patients with high expressions of SERPINC1 and FGG had poor prognosis(all P<0.05). Conclusion: The biological functions and signaling pathways of DEGs are related to the occurrence and development of liver metastasis. The 8 key genes may be the potential therapeutic targets of CRC liver metastasis, and SERPINC1 and FGG may be new prognostic markers.

Characterization of the transcriptional profiles in common buckwheat (Fagopyrum esculentum) under PEG-mediated drought stress

BACKGROUND: Common buckwheat (Fagopyrum esculentum) is an important staple food crop in southwest China, where drought stress is one of the largest limiting factors that lead to decreased crop production. To reveal the molecular mechanism of common buckwheat in response to drought stress, we performed a comprehensive transcriptomics study to evaluate gene expression profiles of common buckwheat during PEG-mediated drought treatment. RESULTS: In total, 45 million clean reads were assembled into 53,404 unigenes with an average length of 749 bp and N50 length of 1296 bp. A total of 1329 differentially expressed genes (DEGs) were identified by comparing wellwatered and drought-treated plants, out of which 666 were upregulated and 663 were downregulated. Furthermore, we defined the functional characteristics of DEGs using GO and KEGG classifications. GO enrichment analysis showed that the DEGs were significantly overrepresented in four categories, namely, "oxidoreductase activity," "oxidation­reduction process," "xyloglucan:xyloglucosyl transferase activity," and "apoplast." Using KEGG pathway analysis, a large number of annotated genes were overrepresented in terms such as "plant hormone signal transduction," "phenylpropanoid biosynthesis," "photosynthesis," and "carbon metabolism." Conclusions: These results can be further exploited to investigate the molecular mechanism of common buckwheat in response to drought treatment and could supply with valuable molecular sources for abiotic-tolerant elite breeding programs in the future.

Differentially Expressed Cellular Gene Profiles between Healthy HIV-infected Koreans and AIDS Patients

BACKGROUND: The global effect of HIV infection on the host cell gene expression profiles in healthy HIV-infected patients, as long-term non-progressors, remains largely unknown. To identify the cellular genes related with HIV infection and delayed disease progression in vivo, the host gene expression profiles between healthy HIV-infected Koreans and AIDS patients were investigated. METHODS:Differential expression gene analysis was performed via oligonucleotide microarray with using Magic-oligo 10K chip. Ten HIV-uninfected persons and 10 HIV-infected patients (healthy HIV-infected patients vs. AIDS patients. respectively) were studied. RESULTS: Only 10.8% (1,097 genes) of the total genes, that is, 331 up-regulated genes and 766 down- regulated genes were differentially expressed with more than a two-fold change in the HIV-infected persons as compared to those of the HIV-uninfected persons. Especially, 97 genes (8.8%) among 1,097 genes were commonly up- or down-regulated in both the healthy HIV-infected patients and the AIDS patients. 187 genes were differently expressed on the gene expression analysis between the healthy HIV-infected patients and the AIDS patients. Twenty-eight genes out of them showed very significant differences with a P value <0.01. Especially, tripartite motif (TRIM) 14 protein and interferon gamma receptor 2 were dramatically up-regulated in healthy HIV-infected patients, while death-associated protein, DNA directed RNA polymerase II polypeptide A and STAT were over-expressed in AIDS patients. CONCLUSION: Although this microarray study has some limitations, the above results will be helpful for performing more detailed, future functional studies on the differentially expressed genes related to HIV infection and delayed disease progression in vivo.

Difference of Gene Expression in Venous Malformation

PURPOSE: Venous malformation(VM) which often causes pain and discomfort is the most common type of vascular malformations. Although it is presented with disfigured appearance and associated soft tissue or skeletal hypertrophy, the molecular bases of VMs are poorly understood. Differentially expressed genes(DEGs) of VMs were investigated to illuminate the molecular mechanism of the disease entity. METHODS: Gene expressions of VM patients' subcutaneous tissue were studied in comparison with normal persons' by GeneFishing(TM) technique using the annealing control primers (ACPs) to identify DEGs. Candidate genes were sequenced and screened by basic local alignment search tool (BLAST) afterwards. RESULTS: Among seventy DEGs identified, forty DEGs which had shown significantly different expression pattern were sequenced. Twenty eight out of 40 were up- regulated while 12 were down-regulated. BLAST searches revealed that 37 were known genes and 3 were unknown genes. Many genes were involved in the differentiation and remodeling of smooth muscle cells, opposed to the previous hypothesis that a lot of angiogenetic genes would be involved. Furthermore, several transcription factors and related genes, as well as cell signaling and metabolism regulators, were up regulated. CONCLUSION: It suggests that analysis of DEGs in VMs provide basic knowledge about its pathophysiology. and new therapeutic approaches.

Idenfitied Differentially Expressed Genes in Keratoconus

PURPOSE: To evaluate the pathogenesis of keratoconus through differentially expressed genes in human keratocyte of keratoconus. METHODS: Total RNAs extracted from primary cultured keratocytes in normal cornea and keratoconus were used for the synthesis of cDNA. Differentially expressed genes were screened by ACP-based PCR method using GeneFishingTM DEG kits. The differentially expressed bands were sequenced and analyzed, and identified genes were further evaluated by RT-PCR. RESULTS: Over-expressions of BMP4 and CFL1 and under-expression of CFL1, GRCC10, and TIMP3 were verified, and comfirmed by RT-PCR. All confirmed genes were concerned with cytoskeleton, wound healing, and apoptosis. CONCLUSIONS: The identified differentially expressed genes seem to be important role in the mechanism of keratoconus, and apoptosis as well as cytoskeleton and wound healing may be attributed to the underlying stromal keratocyte.