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通过非侵入性成像解码肝癌中的全局基因表达程序

Decoding global gene expression programs in liver cancer by noninvasive imaging.

作者信息

Segal Eran, Sirlin Claude B, Ooi Clara, Adler Adam S, Gollub Jeremy, Chen Xin, Chan Bryan K, Matcuk George R, Barry Christopher T, Chang Howard Y, Kuo Michael D

机构信息

Dept. of Computer Science and Applied Mathematics, Weizmann Institute of Science, Rehovot 76100, Israel.

出版信息

Nat Biotechnol. 2007 Jun;25(6):675-80. doi: 10.1038/nbt1306. Epub 2007 May 21.

Abstract

Paralleling the diversity of genetic and protein activities, pathologic human tissues also exhibit diverse radiographic features. Here we show that dynamic imaging traits in non-invasive computed tomography (CT) systematically correlate with the global gene expression programs of primary human liver cancer. Combinations of twenty-eight imaging traits can reconstruct 78% of the global gene expression profiles, revealing cell proliferation, liver synthetic function, and patient prognosis. Thus, genomic activity of human liver cancers can be decoded by noninvasive imaging, thereby enabling noninvasive, serial and frequent molecular profiling for personalized medicine.

摘要

与基因和蛋白质活性的多样性相平行,病理性人体组织也呈现出多样的放射学特征。我们在此表明,无创计算机断层扫描(CT)中的动态成像特征与原发性人类肝癌的整体基因表达程序系统相关。28种成像特征的组合能够重建78%的整体基因表达谱,揭示细胞增殖、肝脏合成功能及患者预后。因此,人类肝癌的基因组活性可通过无创成像进行解码,从而实现用于个性化医疗的无创、系列及频繁分子分析。

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