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前列腺癌的分子图谱分析

Molecular profiling of prostate cancer.

作者信息

Huppi Konrad, Chandramouli G V R

机构信息

Cancer Prevention Studies Branch, National Cancer Institute/National Institutes of Health, 6116 Executive Blvd., Suite 705, Rockville, MD 20852, USA.

出版信息

Curr Urol Rep. 2004 Feb;5(1):45-51. doi: 10.1007/s11934-004-0011-0.

Abstract

The ability to distinguish between aggressive and nonaggressive tumors has not changed despite vast improvements in the detection of prostate cancer (PCA). To improve predictive accuracy, additional PCA-specific biomarkers must be identified and it is the emerging microarray technology and gene expression profiling that appear to be capable of achieving this goal. Through comparisons of a number of published microarray studies of PCA, several potential biomarkers appear on the horizon, including the serine protease Hepsin, a-methylacyl CoA racemase, and the human homologue of the Drosophila protein Enhancer of Zeste. Although these markers will move toward validation by eventual protein expression studies, another aspect of microarray expression, global signature expression patterns through multidimensional scaling, appears to be promising in distinguishing between aggressive and nonaggressive forms of PCA or in distinguishing PCA from benign prostatic hyperplasia or normal prostate tissue.

摘要

尽管前列腺癌(PCA)检测有了巨大进步,但区分侵袭性和非侵袭性肿瘤的能力并未改变。为提高预测准确性,必须识别出更多PCA特异性生物标志物,而新兴的微阵列技术和基因表达谱分析似乎有能力实现这一目标。通过比较多项已发表的PCA微阵列研究,一些潜在的生物标志物崭露头角,包括丝氨酸蛋白酶Hepsin、α-甲基酰基辅酶A消旋酶以及果蝇蛋白Zeste增强子的人类同源物。尽管这些标志物最终将通过蛋白质表达研究进行验证,但微阵列表达的另一个方面,即通过多维标度分析的全局特征表达模式,在区分侵袭性和非侵袭性PCA形式或区分PCA与良性前列腺增生或正常前列腺组织方面似乎很有前景。

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