首页> 外文期刊>Romanian Journal of Morphology and Embryology >Identifying molecular features for prostate cancer with Gleason 7 based on microarray gene expression profiles
【24h】

Identifying molecular features for prostate cancer with Gleason 7 based on microarray gene expression profiles

机译:基于微阵列基因表达谱用Gleason 7鉴定前列腺癌的分子特征

获取原文
       

摘要

Prostate cancer represents the first leading cause of cancer among western male population, with different clinical behavior ranging from indolent to metastatic disease. Although many molecules and deregulated pathways are known, the molecular mechanisms involved in the development of prostate cancer are not fully understood. The aim of this study was to explore the molecular variation underlying the prostate cancer, based on microarray analysis and bioinformatics approaches. Normal and prostate cancer tissues were collected by macrodissection from prostatectomy pieces. All prostate cancer specimens used in our study were Gleason score 7. Gene expression microarray (Agilent Technologies) was used for Whole Human Genome evaluation. The bioinformatics and functional analysis were based on Limma and Ingenuity software. The microarray analysis identified 1119 differentially expressed genes between prostate cancer and normal prostate, which were up- or down-regulated at least 2-fold. P-values were adjusted for multiple testing using Benjamini-Hochberg method with a false discovery rate of 0.01. These genes were analyzed with Ingenuity Pathway Analysis software and were established 23 genetic networks. Our microarray results provide new information regarding the molecular networks in prostate cancer stratified as Gleason 7. These data highlighted gene expression profiles for better understanding of prostate cancer progression.
机译:前列腺癌是西方男性人群中癌症的首位主要诱因,其临床行为范围从惰性到转移性疾病不等。尽管已知许多分子和失控的途径,但尚未完全了解前列腺癌发展中涉及的分子机制。这项研究的目的是基于微阵列分析和生物信息学方法,探索前列腺癌的分子变异。通过宏观解剖从前列腺切除术片收集正常和前列腺癌组织。本研究中使用的所有前列腺癌标本均为Gleason评分7。基因表达微阵列(安捷伦科技公司)用于全人类基因组评估。生物信息学和功能分析均基于Limma和Ingenuity软件。微阵列分析鉴定了在前列腺癌和正常前列腺之间的1119个差异表达的基因,其被上调或下调了至少2倍。使用Benjamini-Hochberg方法调整P值进行多次测试,错误发现率为0.01。使用Ingenuity Pathway Analysis软件分析了这些基因,并建立了23个遗传网络。我们的微阵列结果提供了有关分层为Gleason 7的前列腺癌分子网络的新信息。这些数据突出显示了基因表达谱,以更好地了解前列腺癌的进展。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号