An HR-MAS MR metabolomics study on breast tissues obtained with core needle biopsy.
An HR-MAS MR metabolomics study on breast tissues obtained with core needle biopsy.
复制标题
DOI：
10.1371/journal.pone.0025563
复制
发表时间：
2011
期刊：
影响因子：
3.7
通讯作者：
Moon WK
中科院分区：
文献类型：
--
作者：
Li M;Song Y;Cho N;Chang JM;Koo HR;Yi A;Kim H;Park S;Moon WK
许多研究致力于开发新的乳腺癌诊断方法，包括那些涉及高分辨率魔角旋转(HR-MAS)磁共振(MR)光谱技术的方法。以前的HR-MAS MR结果都是从术后标本中获得的，这限制了它们的直接临床适用性。在本研究中，我们对经皮芯针活检获得的31例乳腺组织(13例癌组织和18例非癌组织)进行了HR-MAS磁共振波谱研究。结果表明，利用磁共振波谱的正交投影-潜在结构判别分析(OPLS-DA)模型可以很好地区分癌和非癌样本。随后的盲法试验显示，在预测癌症状态方面，灵敏度为69%，特异度为94%。光谱分析显示，在癌细胞中，含有牛磺酸和胆碱的化合物含量升高。此外，我们的方法还可以预测癌症患者的孕激素受体状态。核心针活检获得的完整乳腺组织的HR-MAS MR代谢组学可能有可能被用作对目前乳腺癌诊断和预后措施的补充。
Much research has been devoted to the development of new breast cancer diagnostic measures, including those involving high-resolution magic angle spinning (HR-MAS) magnetic resonance (MR) spectroscopic techniques. Previous HR-MAS MR results have been obtained from post-surgery samples, which limits their direct clinical applicability. In the present study, we performed HR-MAS MR spectroscopic studies on 31 breast tissue samples (13 cancer and 18 non-cancer) obtained by percutaneous core needle biopsy. We showed that cancer and non-cancer samples can be discriminated very well with Orthogonal Projections to Latent Structure-Discriminant Analysis (OPLS-DA) multivariate model on the MR spectra. A subsequent blind test showed 69% sensitivity and 94% specificity in the prediction of the cancer status. A spectral analysis showed that in cancer cells, taurine- and choline-containing compounds are elevated. Our approach, additionally, could predict the progesterone receptor statuses of the cancer patients. HR-MAS MR metabolomics on intact breast tissues obtained by core needle biopsy may have a potential to be used as a complement to the current diagnostic and prognostic measures for breast cancers.
登录
查看更多内容
影响因子：
4.4
作者：
Holmes, E.;Cloarec, O.;Nicholson, J. K.
通讯作者：
Nicholson, J. K.
影响因子：
2.9
作者：
NEGENDANK, W
通讯作者：
NEGENDANK, W
影响因子：
2.4
作者：
Bylesjo, Max;Rantalainen, Mattias;Trygg, Johan
通讯作者：
Trygg, Johan
影响因子：
4.4
作者：
Chan, Eric Chun Yong;Koh, Poh Koon;Keun, Hector C.
通讯作者：
Keun, Hector C.
DOI：
10.1073/pnas.0904489106
发表时间：
2009-08-25
影响因子：
11.1
作者：
Clayton, T. Andrew;Baker, David;Nicholson, Jeremy K.
通讯作者：
Nicholson, Jeremy K.