Core Unit Chip Application, Institut für Humangenetik, University Hospital Jena, Jena, Germany.
J Histochem Cytochem. 2010 Oct;58(10):929-37. doi: 10.1369/jhc.2010.956656. Epub 2010 Jul 19.
Carcinoma tissue consists of not only tumor cells but also fibroblasts, endothelial cells or vascular structures, and inflammatory cells forming the supportive tumor stroma. Therefore, the spatial distribution of proteins that promote growth and proliferation in these complex functional units is of high interest. Matrix-assisted laser desorption/ionization imaging mass spectrometry is a newly developed technique that generates spatially resolved profiles of protein signals directly from thin tissue sections. Surface-enhanced laser desorption/ionization mass spectrometry (MS)combined with tissue microdissection allows analysis of defined parts of the tissue with a higher sensitivity and a broader mass range. Nevertheless, both MS-based techniques have a limited spatial resolution. IHC is a technique that allows a resolution down to the subcellular level. However, the detection and measurement of a specific protein expression level is possible only by semiquantitative methods. Moreover, prior knowledge about the identity of the proteins of interest is necessary. In this study, we combined all three techniques to gain highest spatial resolution, sensitivity, and quantitative information. We used frozen tissue from head and neck tumors and chose two exemplary proteins (HNP1-3 and S100A8) to highlight the advantages and disadvantages of each technique. It could be shown that the combination of these three techniques results in congruent but also synergetic data.
癌组织不仅包含肿瘤细胞,还包含成纤维细胞、内皮细胞或脉管结构以及炎性细胞,这些细胞共同构成了支持肿瘤生长的基质。因此,这些复杂的功能单元中促进生长和增殖的蛋白质的空间分布情况具有重要的研究意义。基质辅助激光解吸/电离成像质谱分析是一种新兴技术,可直接从组织薄片中获取蛋白质信号的空间分辨率图谱。表面增强激光解吸/电离质谱(MS)与组织微切割相结合,可以对组织的特定区域进行分析,其具有更高的灵敏度和更宽的质量范围。然而,这两种基于 MS 的技术的空间分辨率均有限。免疫组织化学(IHC)是一种可以达到亚细胞分辨率的技术。但是,只能通过半定量方法来检测和测量特定蛋白质的表达水平。此外,还需要预先了解感兴趣的蛋白质的身份。在这项研究中,我们结合了这三种技术,以获得最高的空间分辨率、灵敏度和定量信息。我们使用来自头颈部肿瘤的冷冻组织,并选择了两种典型的蛋白质(HNP1-3 和 S100A8)来突出每种技术的优缺点。结果表明,这三种技术的结合可以产生一致且协同的数据。