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疾病机制:前列腺癌微阵列基因表达研究中的生物标志物和分子靶点

Mechanisms of Disease: biomarkers and molecular targets from microarray gene expression studies in prostate cancer.

作者信息

Cooper Colin S, Campbell Colin, Jhavar Sameer

机构信息

Male Urological Cancer Research Centre, Institute of Cancer Research, Sutton, UK.

出版信息

Nat Clin Pract Urol. 2007 Dec;4(12):677-87. doi: 10.1038/ncpuro0946.

Abstract

Molecular biomarkers can serve as useful diagnostic markers, as prognostic markers for predicting clinical behavior, or as targets for new therapeutic strategies. Application of expression microarray technology, which allows the expression of all or most of the genes in the human genome to be analyzed simultaneously, has dramatically enhanced the discovery of prostate cancer biomarkers. The diagnostic markers identified include AMACR (alpha-methylacyl CoA racemase), a protein that has already been translated into clinical use as an aid in distinguishing prostate cancer from benign disease. Individual genes, such as the polycomb gene EZH2 whose expression indicates poor survival, have been identified. The power of microarray technology is that it has allowed the identification of gene signatures (each composed of multiple genes) that might provide improved prediction of clinical outcomes in human prostate cancer. The development of a new method for analyzing expression microarray data, called COPA, has led to the discovery of TMPRSS2-ERG gene fusion involvement in the development of prostate cancer, while expression analysis of castration-resistant prostate cancer has suggested the use of novel therapeutic approaches for advanced disease. Despite these successes, there are limitations in the application of microarray technology to prostate cancer; for example, unlike with other cancers, this approach has failed to provide a consistent unsupervised classification of the disease. Overcoming the reasons for these failures represents a major challenge for future research endeavors.

摘要

分子生物标志物可作为有用的诊断标志物、预测临床行为的预后标志物或新治疗策略的靶点。表达微阵列技术能够同时分析人类基因组中所有或大部分基因的表达情况,该技术的应用极大地促进了前列腺癌生物标志物的发现。已确定的诊断标志物包括AMACR(α-甲基酰基辅酶A消旋酶),这是一种已转化为临床应用的蛋白质,有助于区分前列腺癌与良性疾病。已鉴定出个别基因,如多梳基因EZH2,其表达表明预后不良。微阵列技术的优势在于,它能够识别可能改善人类前列腺癌临床结果预测的基因特征(每个特征由多个基因组成)。一种名为COPA的分析表达微阵列数据的新方法的开发,导致发现TMPRSS2-ERG基因融合与前列腺癌的发生有关,而对去势抵抗性前列腺癌的表达分析则提示了针对晚期疾病的新型治疗方法。尽管取得了这些成功,但微阵列技术在前列腺癌应用中仍存在局限性;例如,与其他癌症不同,这种方法未能对该疾病提供一致的无监督分类。克服这些失败的原因是未来研究工作面临的一项重大挑战。

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