CHI Xiao-hua, JING Xu-chen, LIU Li-hong, YANG Bo, LU Xue-chun, TUO Shuai, TUO Chao-wei. Screening for human hematopoietic and immune-related genes regulated by amifostine and their bioinformatics predictingJ. ACADEMIC JOURNAL OF CHINESE PLA MEDICAL SCHOOL, 2011, 32(7): 752-754. DOI: CNKI:11-3275/R.20110127.0928.000
Citation: CHI Xiao-hua, JING Xu-chen, LIU Li-hong, YANG Bo, LU Xue-chun, TUO Shuai, TUO Chao-wei. Screening for human hematopoietic and immune-related genes regulated by amifostine and their bioinformatics predictingJ. ACADEMIC JOURNAL OF CHINESE PLA MEDICAL SCHOOL, 2011, 32(7): 752-754. DOI: CNKI:11-3275/R.20110127.0928.000

Screening for human hematopoietic and immune-related genes regulated by amifostine and their bioinformatics predicting

  • Objective To analyze the amifostine-regulated human hematopoietic and immune-related genes retrieved from open gene chip databases with bioinformatics methodMethods Differently expressed amifostine-regulated human hematopoietic and immune-related genes were retrieved from internet gene expression databases including GEO,SAGE,GeneCard,InterPro,ProtoNet,UniProt,and BLOCKS using amifostine as the key word and analyzed with bioinformatics method,and their functional clustering was analyzed according to the Database of Annotation,Visualization and Integrated Discovery(DAVID)Results Only 1 expressed gene was screened from the GEO database.The functional clustering analysis showed that a significant difference was found only in expression of 2.14% of the whole genome(460/192 000) at transcription level after the K562 cells were treated with amifostine.Of the 460 differential genes,139 were the known genes.Of the 139 known genes,17 including 15 up-regulated and 2 down-regulated genes were related with hematopoiesis and immune system and divided into 8 categories in the biological pathwayConclusion Full use of open human gene chip databases can rapidly,conveniently and economically analyze the characteristics of drug-regulated gene expression profiling,thus providing a guidance for predicting and verifying the pharmacological actions of new drugs.
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