RESUMEN
Microarray data of astrocytes extracted from the optic nerves of donors with and without glaucoma were analyzed to screen for differentially expressed genes (DEGs). Functional exploration with bioinformatic tools was then used to understand the roles of the identified DEGs in glaucoma. Microarray data were downloaded from the Gene Expression Omnibus (GEO) database, which contains 13 astrocyte samples, 6 from healthy subjects and 7 from patients suffering from glaucoma. Data were pre-processed, and DEGs were screened out using R software packages. Interactions between DEGs were identified, and networks were built using Search Tool for the Retrieval of Interacting Genes/Proteins (STRING). GENECODIS was utilized for the functional analysis of the DEGs, and GOTM was used for module division, for which functional annotation was conducted with the Database for Annotation, Visualization, and Integrated Discovery (DAVID). A total of 371 DEGs were identified between glaucoma-associated samples and normal samples. Three modules included in the PPID database were generated with 11, 12, and 2 significant functional annotations, including immune system processes, inflammatory responses, and synaptic vesicle endocytosis, respectively. We found that the most significantly enriched functions for each module were associated with immune function. Several genes that play interesting roles in the development of glaucoma are described; these genes may be potential biomarkers for glaucoma diagnosis or treatment.
Asunto(s)
Perfilación de la Expresión Génica , Regulación de la Expresión Génica , Glaucoma/genética , Análisis de Secuencia por Matrices de Oligonucleótidos , Redes Reguladoras de Genes , HumanosRESUMEN
The aim of this study was to identify differentially expressed genes (DEGs) in renal medullary hypertension and reveal their pathogenic mechanisms. We downloaded the gene expression profile of GSE28360 from the Gene Expression Omnibus database. The profile included 14 samples (5 normal and 9 hypertension). The DEGs in normal and disease samples were distinguished with a false-discovery rate threshold of <0.05 and a fold-change value of >2 or <-2. We put the selected genes into the online program String 8.3 to obtain the protein-protein interaction network and selected the hub proteins. These hub proteins were then placed in the PANTHER database to determine hub protein-related pathways and explain their functions. Finally, we cleared up the single-nucleotide polymorphisms (SNPs) of the hub genes via combing with the National Center for Biotechnology SNP database. A total of 13 genes were identified as DEGs between normal and disease samples. Five selected hub proteins, B-cell translocation gene 2 (BTG2), FBJ murine osteosarcoma viral oncogene homolog (FOS), nuclear receptor subfamily 4, group A, member 1 (NR4A1), NR4A member 2 (NR4A2), and NR4A member 3 (NR4A3), were mainly related to angiogenesis and B-cell activation. After SNP analysis, 103, 103, 595, 150, and 493 SNPs were found to correspond to BTG2, FOS, NR4A1, NR4A2, and NR4A3, respectively. Our results suggest that pathways of angiogenesis and B-cell activation may involve in the progression of renal medulla hypertension.
Asunto(s)
Linfocitos B/citología , Hipertensión Renal/genética , Activación de Linfocitos , Inductores de la Angiogénesis/metabolismo , Presión Sanguínea/genética , Proteínas de Unión al ADN/genética , Proteínas de Unión al ADN/metabolismo , Humanos , Proteínas Inmediatas-Precoces/genética , Proteínas Inmediatas-Precoces/metabolismo , Análisis por Micromatrices , Miembro 1 del Grupo A de la Subfamilia 4 de Receptores Nucleares/genética , Miembro 1 del Grupo A de la Subfamilia 4 de Receptores Nucleares/metabolismo , Miembro 2 del Grupo A de la Subfamilia 4 de Receptores Nucleares/genética , Miembro 2 del Grupo A de la Subfamilia 4 de Receptores Nucleares/metabolismo , Polimorfismo de Nucleótido Simple , Proteínas Proto-Oncogénicas c-fos/genética , Proteínas Proto-Oncogénicas c-fos/metabolismo , Receptores de Esteroides/genética , Receptores de Esteroides/metabolismo , Receptores de Hormona Tiroidea/genética , Receptores de Hormona Tiroidea/metabolismo , Transcriptoma , Proteínas Supresoras de Tumor/genética , Proteínas Supresoras de Tumor/metabolismoRESUMEN
Bladder cancer is a highly heterogeneous neoplasm. We examined the gene expression profile in 3 bladder cancer stages (Ta, T1, T2) using expression microarray analysis of 40 bladder tumors. Differentially expressed genes were found by the t-test, with <0.005 as the significance threshold. KEGG pathway-enrichment analysis was used to study the signaling pathways of the genes. We found 36 genes that could be used as molecular markers for predicting the transition from Ta-T1 to T1-T2. Among these, 11 overlapped between Ta-T1 and T1-T2 stages. Six genes were down-regulated at the Ta-T1 stage, but were up-regulated at the T1-T2 stage (ANXA5, ATP6V1B2, CTGF, GEM, IL13RA1, and LCP1); 5 genes were up-regulated at the Ta-T1 stage, but down-regulated at the T1-T2 stage (ACPP, GNL1, RIPK1, RAPGEF3, and ZER1). Another 25 genes changed relative expression levels at the T1-T2 stage. These genes (including COL1A1, COL1A2, FN1, ITGA5, LGALS1, SPP1, VIM, POSTN, and COL18A1) may be involved in bladder cancer progression by affecting extracellular matrix-receptor interaction and focal adhesion. The cytokine-cytokine receptor interaction, neuroactive ligand-receptor interaction, and calcium-signaling pathway were associated with bladder cancer progression at both the Ta-T1 and T1-T2 stages.