Epithelial ovarian carcinoma diagnosis by desorption electrospray ionization mass spectrometry imaging.
Epithelial ovarian carcinoma diagnosis by desorption electrospray ionization mass spectrometry imaging.
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DOI：
10.1038/srep39219
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发表时间：
2016-12-15
影响因子：
4.6
通讯作者：
Takats Z
中科院分区：
文献类型：
--
作者：
Dória ML;McKenzie JS;Mroz A;Phelps DL;Speller A;Rosini F;Strittmatter N;Golf O;Veselkov K;Brown R;Ghaem-Maghami S;Takats Z
卵巢癌在欧洲妇女中非常普遍，是妇科癌症死亡的主要原因。目前肿瘤严重程度的组织病理学诊断是基于例如免疫组织化学染色的解释。解吸电喷雾质谱成像（ESIMS-MSI）生成组织的空间分辨代谢谱，并支持肿瘤生物学的客观调查。在这项研究中，不同的卵巢组织类型进行了分析，通过微卫星不稳定性和共同注册与其相应的苏木精和伊红（H&E）染色的图像。质谱数据揭示了组织类型依赖性脂质谱，其在本研究中使用的n = 110份样本（n = 107例患者）中一致。使用多变量统计方法对样品进行分类并鉴定区分组织类型的分子特征。比较了三组主要样本（上皮性卵巢癌、交界性卵巢肿瘤、正常卵巢间质）以及癌组织类型（浆液性、类浆液性、透明细胞）。所有分析的分类率均>84%，确定了组间统计学差异的变量，并确定了puerythema。在各种脂质类型中观察到的变化有助于提供肿瘤生物化学方面的背景。未发现的样本的分类证明了MSP-MSI对卵巢样本的分类能力，并克服了经典组织病理学中现有的局限性。
Ovarian cancer is highly prevalent among European women, and is the leading cause of gynaecological cancer death. Current histopathological diagnoses of tumour severity are based on interpretation of, for example, immunohistochemical staining. Desorption electrospray mass spectrometry imaging (DESI-MSI) generates spatially resolved metabolic profiles of tissues and supports an objective investigation of tumour biology. In this study, various ovarian tissue types were analysed by DESI-MSI and co-registered with their corresponding haematoxylin and eosin (H&E) stained images. The mass spectral data reveal tissue type-dependent lipid profiles which are consistent across the n = 110 samples (n = 107 patients) used in this study. Multivariate statistical methods were used to classify samples and identify molecular features discriminating between tissue types. Three main groups of samples (epithelial ovarian carcinoma, borderline ovarian tumours, normal ovarian stroma) were compared as were the carcinoma histotypes (serous, endometrioid, clear cell). Classification rates >84% were achieved for all analyses, and variables differing statistically between groups were determined and putatively identified. The changes noted in various lipid types help to provide a context in terms of tumour biochemistry. The classification of unseen samples demonstrates the capability of DESI-MSI to characterise ovarian samples and to overcome existing limitations in classical histopathology.
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DOI：
10.1038/nrc2644
发表时间：
2009-06
期刊：
Nature reviews. Cancer
影响因子：
--
作者：
通讯作者：
--
影响因子：
9.3
作者：
Ifa DR;Eberlin LS
通讯作者：
Eberlin LS
DOI：
10.1097/pas.0b013e3181cf3d79
发表时间：
2010-03
期刊：
The American journal of surgical pathology
影响因子：
--
作者：
Kurman RJ;Shih IeM
通讯作者：
Shih IeM
影响因子：
56.9
作者：
Fang, YM;Vilella-Bach, M;Chen, J
通讯作者：
Chen, J
影响因子：
7.4
作者：
Eberlin, Livia S.;Dill, Allison L.;Costa, Anthony B.;Ifa, Demian R.;Cheng, Liang;Masterson, Timothy;Koch, Michael;Ratliff, Timothy L.;Cooks, R. Graham
通讯作者：
Cooks, R. Graham