Differential Lipid Profiles of Normal Human Brain Matter and Gliomas by Positive and Negative Mode Desorption Electrospray Ionization - Mass Spectrometry Imaging.
Differential Lipid Profiles of Normal Human Brain Matter and Gliomas by Positive and Negative Mode Desorption Electrospray Ionization - Mass Spectrometry Imaging.
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DOI：
10.1371/journal.pone.0163180
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发表时间：
2016
期刊：
影响因子：
3.7
通讯作者：
Cooks RG
中科院分区：
文献类型：
--
作者：
Jarmusch AK;Alfaro CM;Pirro V;Hattab EM;Cohen-Gadol AA;Cooks RG
采用解吸电喷雾电离-质谱仪(DEI-MS)对39例受试者脑组织切片进行正负电离顺序分析。由于一些磷脂在正离子模式下优先电离，而另一些磷脂在负离子模式下优先电离，因此获得这两种MS极性可以更完整地分析人脑肿瘤脂质体。结合主成分分析和线性判别分析，利用正负离子模式Desi-MS脂谱，区分正常脑实质和胶质瘤的灰质和白质。阳性模式的主成分-线性判别分析能够区分灰质、白质和胶质瘤，其平均敏感性和特异性分别为93.2%和96.6%，而阴性模式的平均敏感性和特异性分别为94.1%和97.4%。阳性和阴性模式的血脂谱提供了互补的信息。通过数据融合对阳性和阴性模式组合的血脂谱进行主成分-线性判别分析，得出阳性和阴性模式单独使用时的平均敏感度(94.7%)和特异度(97.6%)大致相同。然而，它们相辅相成，当联合使用时，提高了所有类别(灰质、白质和胶质瘤)的敏感性和特异性超过90%。使用融合数据的进一步主成分分析导致将胶质瘤细分为分别与灰质和白质相关的两组，这种分离在单独的正模式和负模式数据的主成分分析得分曲线图中不明显。讨论了肿瘤细胞百分比和脂质分布的相互关系，以及如何使用这种测量方法来测量手术切缘的残留肿瘤。
Desorption electrospray ionization—mass spectrometry (DESI-MS) imaging was used to analyze unmodified human brain tissue sections from 39 subjects sequentially in the positive and negative ionization modes. Acquisition of both MS polarities allowed more complete analysis of the human brain tumor lipidome as some phospholipids ionize preferentially in the positive and others in the negative ion mode. Normal brain parenchyma, comprised of grey matter and white matter, was differentiated from glioma using positive and negative ion mode DESI-MS lipid profiles with the aid of principal component analysis along with linear discriminant analysis. Principal component–linear discriminant analyses of the positive mode lipid profiles was able to distinguish grey matter, white matter, and glioma with an average sensitivity of 93.2% and specificity of 96.6%, while the negative mode lipid profiles had an average sensitivity of 94.1% and specificity of 97.4%. The positive and negative mode lipid profiles provided complementary information. Principal component–linear discriminant analysis of the combined positive and negative mode lipid profiles, via data fusion, resulted in approximately the same average sensitivity (94.7%) and specificity (97.6%) of the positive and negative modes when used individually. However, they complemented each other by improving the sensitivity and specificity of all classes (grey matter, white matter, and glioma) beyond 90% when used in combination. Further principal component analysis using the fused data resulted in the subgrouping of glioma into two groups associated with grey and white matter, respectively, a separation not apparent in the principal component analysis scores plots of the separate positive and negative mode data. The interrelationship of tumor cell percentage and the lipid profiles is discussed, and how such a measure could be used to measure residual tumor at surgical margins.
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影响因子：
9.3
作者：
Ifa DR;Eberlin LS
通讯作者：
Eberlin LS
DOI：
10.1073/pnas.1408129111
发表时间：
2014-10-21
影响因子：
11.1
作者：
Calligaris, David;Caragacianu, Diana;Agar, Nathalie Y. R.
通讯作者：
Agar, Nathalie Y. R.
影响因子：
4.3
作者：
Dill, Allison L.;Eberlin, Livia S.;Cooks, R. Graham
通讯作者：
Cooks, R. Graham
影响因子：
12.7
作者：
Claes A;Idema AJ;Wesseling P
通讯作者：
Wesseling P
影响因子：
3.2
作者：
Eberlin, Livia S.;Ferreira, Christina R.;Dill, Allison L.;Ifa, Demian R.;Cheng, Liang;Cooks, R. Graham
通讯作者：
Cooks, R. Graham