Multiple statistical analysis techniques corroborate intratumor heterogeneity in imaging mass spectrometry datasets of myxofibrosarcoma.
Multiple statistical analysis techniques corroborate intratumor heterogeneity in imaging mass spectrometry datasets of myxofibrosarcoma.
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DOI：
10.1371/journal.pone.0024913
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发表时间：
2011
期刊：
影响因子：
3.7
通讯作者：
McDonnell LA
中科院分区：
文献类型：
--
作者：
Jones EA;van Remoortere A;van Zeijl RJ;Hogendoorn PC;Bovée JV;Deelder AM;McDonnell LA
MALDI质谱法可以直接从组织中生成包含数百种生物分子离子的图谱。空间相关分析，MALDI成像MS，可以同时揭示这些生物分子离子在临床组织样品中的变化。使用统计数据分析工具来识别包含相关质谱谱的区域被称为基于成像MS的分子组织学，因为其能够仅基于成像MS数据来注释组织。一些报告表明，成像MS为基础的分子组织学可能能够补充建立的组织学和组织化学技术，通过区分病理重叠/相同的形态和揭示生物分子肿瘤内的异质性。识别具有相关质谱谱的成像MS数据集区域的数据分析管道可以导致开发用于改进诊断（区分不同组织学组内的亚组）和注释肿瘤的空间化学组成的新方法。在这里，它表明，突出显示的区域内的成像MS数据集的质谱配置文件被发现是相关的五个独立的多变量方法提供了一个一贯准确的总结的空间化学异质性。通过使用多个多变量方法提供的确证，有效地应用于自动化程序中，提供了确定的区域确实具有不同的质谱特征的保证，这是其作为补充组织学工具发展的关键要求。当同时应用于成像MS数据集从多个患者样本的中级粘液纤维肉瘤，一种异质性软组织肉瘤，结节与质谱谱发现是不同的五种不同的多变量方法检测到形态相同的区域内的所有患者组织样本。为了帮助进一步开发基于成像MS的分子组织学作为补充组织学工具，包括一致性分析的Matlab代码、说明和简化的数据集作为支持信息。
MALDI mass spectrometry can generate profiles that contain hundreds of biomolecular ions directly from tissue. Spatially-correlated analysis, MALDI imaging MS, can simultaneously reveal how each of these biomolecular ions varies in clinical tissue samples. The use of statistical data analysis tools to identify regions containing correlated mass spectrometry profiles is referred to as imaging MS-based molecular histology because of its ability to annotate tissues solely on the basis of the imaging MS data. Several reports have indicated that imaging MS-based molecular histology may be able to complement established histological and histochemical techniques by distinguishing between pathologies with overlapping/identical morphologies and revealing biomolecular intratumor heterogeneity. A data analysis pipeline that identifies regions of imaging MS datasets with correlated mass spectrometry profiles could lead to the development of novel methods for improved diagnosis (differentiating subgroups within distinct histological groups) and annotating the spatio-chemical makeup of tumors. Here it is demonstrated that highlighting the regions within imaging MS datasets whose mass spectrometry profiles were found to be correlated by five independent multivariate methods provides a consistently accurate summary of the spatio-chemical heterogeneity. The corroboration provided by using multiple multivariate methods, efficiently applied in an automated routine, provides assurance that the identified regions are indeed characterized by distinct mass spectrometry profiles, a crucial requirement for its development as a complementary histological tool. When simultaneously applied to imaging MS datasets from multiple patient samples of intermediate-grade myxofibrosarcoma, a heterogeneous soft tissue sarcoma, nodules with mass spectrometry profiles found to be distinct by five different multivariate methods were detected within morphologically identical regions of all patient tissue samples. To aid the further development of imaging MS based molecular histology as a complementary histological tool the Matlab code of the agreement analysis, instructions and a reduced dataset are included as supporting information.
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