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基于微阵列基因表达谱鉴定 Gleason 评分为 7 的前列腺癌的分子特征。

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

作者信息

Bălăcescu Loredana, Bălăcescu O, Crişan N, Fetica B, Petruţ B, Bungărdean Cătălina, Rus Meda, Tudoran Oana, Meurice G, Irimie Al, Dragoş N, Berindan-Neagoe Ioana

机构信息

Department of Functional Genomics and Experimental Pathology, "Prof. dr. Ion Chiricuta" Cancer Institute, Cluj-Napoca, Romania.

出版信息

Rom J Morphol Embryol. 2011;52(4):1195-202.

Abstract

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.

摘要

前列腺癌是西方男性人群中首要的癌症病因,其临床行为各异,从惰性疾病到转移性疾病都有。尽管已知许多分子和失调的信号通路,但前列腺癌发生发展所涉及的分子机制尚未完全明确。本研究旨在基于微阵列分析和生物信息学方法,探索前列腺癌潜在的分子变异情况。通过宏观解剖从前列腺切除组织块中收集正常和前列腺癌组织。我们研究中使用的所有前列腺癌标本的 Gleason 评分为 7 分。采用基因表达微阵列(安捷伦科技公司)进行全人类基因组评估。生物信息学和功能分析基于 Limma 和 Ingenuity 软件。微阵列分析确定了前列腺癌与正常前列腺之间 1119 个差异表达基因,这些基因上调或下调至少 2 倍。使用 Benjamini-Hochberg 方法对多重检验的 P 值进行调整,错误发现率为 0.01。运用 Ingenuity 通路分析软件对这些基因进行分析,并建立了 23 个遗传网络。我们的微阵列结果为 Gleason 评分为 7 的前列腺癌分子网络提供了新信息。这些数据突出了基因表达谱,有助于更好地理解前列腺癌进展。

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