Tissue microarrays (TMAs) for high-throughput molecular pathology research
Tissue microarrays (TMAs) for high-throughput molecular pathology research
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DOI：
10.1002/ijc.1385
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发表时间：
2001-10-01
影响因子：
6.4
通讯作者：
Sauter, G
中科院分区：
文献类型：
--
作者：
Nocito, A;Kononen, J;Sauter, G
越来越多的基因被怀疑在癌症生物学中发挥作用。为了评估新发现的潜在癌症基因的临床意义，通常需要检查大量具有良好特征的原发肿瘤。使用传统的分子病理学方法，这是一项耗时的努力，迅速耗尽宝贵的组织资源。为了实现高通量的组织分析，我们开发了一种“组织芯片”方法(Kononen等人，NA.地中海医院。1998年；4：844-7)。使用这种组织微阵列(TMA)技术，来自多达1000种不同肿瘤的样本被排列在一个接收者石蜡块中，其中的切片可用于所有类型的原位分析。然后，来自TMA块的切片可以用于在DNA、RNA或蛋白质水平上同时分析多达1000种不同的肿瘤。TMA允许在几个毛刺内对数千个肿瘤进行高通量分子分析。目前所有可用的数据都表明，微小排列的组织标本具有很高的供体组织代表性。有多种不同类型的TMA可用于癌症研究，包括多肿瘤阵列(包含不同的肿瘤类型)、肿瘤进展阵列(不同阶段的肿瘤)和预后阵列(具有临床终点的肿瘤)。多种不同的TMA的组合允许对感兴趣的生物标记物进行非常快速但全面的表征。我们预计，TMA的使用将极大地加速基础研究成果向临床应用的转变。(C)2001年Wiley-Liss，Inc.
A rapidly increasing number of genes are being suspected to play a role in cancer biology. To evaluate the clinical significance of newly detected potential cancer genes, it is usually required to examine a high number of well-characterized primary tumors. Using traditional methods of molecular pathology, this is a time consuming endeavor rapidly exhausting precious tissue resources. To allow for a high throughput tissue analysis we have developed a "tissue chip" approach (Kononen et al., Nat. Med. 1998;4:844-7). Using this tissue microarray (TMA) technology, samples from up to 1,000 different tumors are arrayed in one recipient paraffin block, sections of which can be used for all kind of in situ analyses. Sections from TMA blocks can then be utilized for the simultaneous analysis of up to 1,000 different tumors on the DNA, RNA or protein level. TMAs allow a high through-put molecular analysis of thousands of tumors within a few burs. All currently available data have suggested that minute arrayed tissue specimens are highly representative of their donor tissues. There are multiple different types of TMAs that can be utilized in cancer research including multi tumor arrays (containing different tumor types), tumor progression arrays (tumors of different stages) and prognostic arrays (tumors with clinical endpoints). The combination of multiple different TMAs allows a very quick but comprehensive characterization of biomarkers of interest. We anticipate that the use of TMAs will greatly accelerate the transition of basic research findings to clinical applications. (C) 2001 Wiley-Liss, Inc.