Multicenter Study Using Desorption-Electrospray-Ionization-Mass-Spectrometry Imaging for Breast-Cancer Diagnosis.
Multicenter Study Using Desorption-Electrospray-Ionization-Mass-Spectrometry Imaging for Breast-Cancer Diagnosis.
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DOI：
10.1021/acs.analchem.8b01961
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发表时间：
2018-10-02
影响因子：
7.4
通讯作者：
Eberlin LS
中科院分区：
文献类型：
--
作者：
Porcari AM;Zhang J;Garza KY;Rodrigues-Peres RM;Lin JQ;Young JH;Tibshirani R;Nagi C;Paiva GR;Carter SA;Sarian LO;Eberlin MN;Eberlin LS
乳腺癌的组织学和分子亚型需要不同的治疗方法。浸润性导管癌（IDC）根据雌激素受体（ER）、孕酮受体（PR）和HER 2状态以及其他标志物进行亚型分型。解吸-电喷雾电离-质谱成像（ESI-MSI）是一种环境电离MS技术，以前曾用于诊断IDC。为了研究环境电离MS在不同患者人群和实验室间使用中用于IDC诊断和亚型分型的稳健性，我们报告了一项多中心研究，使用DESI-MSI分析了来自美国和巴西独立分析的103名患者的样本。IDC和正常乳腺组织的脂质谱在不同患者种族之间是一致的，并且与样本采集的国家无关。在两个实验室中使用的类似实验参数在质荷比（m/z）高于700时产生一致的质谱数据，其中观察到复合脂质。使用在美国获得的数据建立的统计分类器对癌症诊断的灵敏度为97.6%，特异性为96.7%，准确性为97.6%。实验室内验证集（99.2%的准确度），最显着的是，在巴西独立获得的实验室间验证集（95.3%的准确度），观察到相当的性能。为ER和PR状态以及它们的组合激素受体（HR）状态建立的单独分类模型提供了预测准确性（>89.0%），尽管HER 2状态的分类准确性较低。总而言之，我们的多中心研究表明，乳腺癌MSI是一个强大的和可重复的技术，用于快速乳腺癌组织诊断，因此是临床使用的价值。
The histological and molecular subtypes of breast cancer demand distinct therapeutic approaches. Invasive ductal carcinoma (IDC) is subtyped according to estrogen-receptor (ER), progesterone-receptor (PR), and HER2 status, among other markers. Desorption-electrospray-ionization-mass-spectrometry imaging (DESI-MSI) is an ambient-ionization MS technique that has been previously used to diagnose IDC. Aiming to investigate the robustness of ambient-ionization MS for IDC diagnosis and subtyping over diverse patient populations and interlaboratory use, we report a multicenter study using DESI-MSI to analyze samples from 103 patients independently analyzed in the United States and Brazil. The lipid profiles of IDC and normal breast tissues were consistent across different patient races and were unrelated to country of sample collection. Similar experimental parameters used in both laboratories yielded consistent mass-spectral data in mass-to-charge ratios (m/z) above 700, where complex lipids are observed. Statistical classifiers built using data acquired in the United States yielded 97.6% sensitivity, 96.7% specificity, and 97.6% accuracy for cancer diagnosis. Equivalent performance was observed for the intralaboratory validation set (99.2% accuracy) and, most remarkably, for the interlaboratory validation set independently acquired in Brazil (95.3% accuracy). Separate classification models built for ER and PR statuses as well as the status of their combined hormone receptor (HR) provided predictive accuracies (>89.0%), although low classification accuracies were achieved for HER2 status. Altogether, our multicenter study demonstrates that DESI-MSI is a robust and reproducible technology for rapid breast-cancer-tissue diagnosis and therefore is of value for clinical use.
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影响因子：
9.3
作者：
Ifa DR;Eberlin LS
通讯作者：
Eberlin LS
DOI：
10.1016/j.bbalip.2013.03.011
发表时间：
2013-10
期刊：
Biochimica et biophysica acta
影响因子：
--
作者：
Baumann J;Sevinsky C;Conklin DS
通讯作者：
Conklin DS
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：
Baenke F;Peck B;Miess H;Schulze A
通讯作者：
Schulze A
影响因子：
4.3
作者：
Dill, Allison L.;Eberlin, Livia S.;Cooks, R. Graham
通讯作者：
Cooks, R. Graham