中国男科学杂志
中國男科學雜誌
중국남과학잡지
CHINESE JOURNAL OF ANDROLOGY
2013年
9期
11-16
,共6页
计算生物学%前列腺肿瘤%肿瘤转移%基因芯片
計算生物學%前列腺腫瘤%腫瘤轉移%基因芯片
계산생물학%전렬선종류%종류전이%기인심편
computational biology%prostatic neoplasms%neoplasm metastasis%gene chips
目的:从分子水平揭示前列腺癌骨转移的发病机制,为临床诊疗提供新思路。方法在公共基因芯片数据库(GEO)中下载前列腺癌骨转移的相关基因芯片数据,利用BRB-ArrayTools 软件、STRING、ToppGene、GOEAST、DAVID等生物信息学工具进行数据挖掘及生物信息学分析。结果 BRB分析筛选出501个前列腺癌骨转移差异基因,其中上调181个,下调320个。对其进行生物信息学分析发现SPP1、HBB、AR、MMP9、AZGP1、POSTN、FN1、VCAN等基因以及胶原蛋白及其生物合成、细胞黏附、小分子代谢过程、黏着斑、ECM受体相互作用、细胞周期、整合素信号通路等分子生物学过程及通路在前列腺癌骨转移的发生发展中可能起着重要作用。结论利用生物信息学的方法能有效分析基因芯片数据,并获取生物内在信息,为发现前列腺癌骨转移的早期诊断标志与治疗靶点提供新的思路。
目的:從分子水平揭示前列腺癌骨轉移的髮病機製,為臨床診療提供新思路。方法在公共基因芯片數據庫(GEO)中下載前列腺癌骨轉移的相關基因芯片數據,利用BRB-ArrayTools 軟件、STRING、ToppGene、GOEAST、DAVID等生物信息學工具進行數據挖掘及生物信息學分析。結果 BRB分析篩選齣501箇前列腺癌骨轉移差異基因,其中上調181箇,下調320箇。對其進行生物信息學分析髮現SPP1、HBB、AR、MMP9、AZGP1、POSTN、FN1、VCAN等基因以及膠原蛋白及其生物閤成、細胞黏附、小分子代謝過程、黏著斑、ECM受體相互作用、細胞週期、整閤素信號通路等分子生物學過程及通路在前列腺癌骨轉移的髮生髮展中可能起著重要作用。結論利用生物信息學的方法能有效分析基因芯片數據,併穫取生物內在信息,為髮現前列腺癌骨轉移的早期診斷標誌與治療靶點提供新的思路。
목적:종분자수평게시전렬선암골전이적발병궤제,위림상진료제공신사로。방법재공공기인심편수거고(GEO)중하재전렬선암골전이적상관기인심편수거,이용BRB-ArrayTools 연건、STRING、ToppGene、GOEAST、DAVID등생물신식학공구진행수거알굴급생물신식학분석。결과 BRB분석사선출501개전렬선암골전이차이기인,기중상조181개,하조320개。대기진행생물신식학분석발현SPP1、HBB、AR、MMP9、AZGP1、POSTN、FN1、VCAN등기인이급효원단백급기생물합성、세포점부、소분자대사과정、점착반、ECM수체상호작용、세포주기、정합소신호통로등분자생물학과정급통로재전렬선암골전이적발생발전중가능기착중요작용。결론이용생물신식학적방법능유효분석기인심편수거,병획취생물내재신식,위발현전렬선암골전이적조기진단표지여치료파점제공신적사로。
Objective To better understand the molecular pathogenesis of prostate cancer bone metastasis, and provide novel approaching for clinical diagnosis and treatment of this malignancy. Methods The data of whole genomic expression profiles on prostate cancer bone metastasis were obtained from GEO database.A set of bioinformatics tools, such as BRB-ArrayTools, STRING, ToppGene, GOEAST and DAVID softwares were used to accomplish the data-mining and bioinformatics analysis. Results BRB analysis results showed there were 501 differentially expressed genes related to prostate cancer bone metastasis, including 181 up-regulated and 320 down-regulated. Bioinformatic analysis results suggested that SPP1, HBB, AR, MMP9, AZGP1, POSTN, FN1 and VCAN played essential roles in such important biological processes as collagen biosynthetic,cell adhesion,Focal adhesion,Integrin signalling pathway and ECM-receptor interaction. Conclusion Bioinformatic analysis had a high efficiency in analyzing gene chip data and revealing internal biology information. It will offer a new view to find early biomarkers and treatment targets of prostate cancer bone metastasis.