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首页> 外文期刊>American Journal of Dermatopathology >Imaging mass spectrometry - A new and promising method to differentiate Spitz nevi from Spitzoid malignant melanomas
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Imaging mass spectrometry - A new and promising method to differentiate Spitz nevi from Spitzoid malignant melanomas

机译:成像质谱-一种将Spitz痣与Spitzoid恶性黑色素瘤区分开的新方法

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Background: Differentiating Spitz nevus (SN) from Spitzoid malignant melanoma (SMM) is one the most difficult problems in dermatopathology. Specific Aim: To identify differences on proteomic level between SN and SMM. Methods: We performed Imaging Mass Spectrometry analysis on formalin-fixed, paraffin-embedded tissue samples to identify differences on proteomic level between SN and SMM. The diagnosis of SN and SMM was based on histopathologic criteria, clinical features, and follow-up data, which confirmed that none of the lesions diagnosed as SN recurred or metastasized. The melanocytic component (tumor) and tumor microenvironment (dermis) from 114 cases of SN and SMM from the Yale Spitzoid Neoplasm Repository were analyzed. After obtaining mass spectra from each sample, classification models were built using a training set of biopsies from 26 SN and 25 SMM separately for tumor and for dermis. The classification algorithms developed on the training data set were validated on another set of 30 samples from SN and 33 from SMM. Results: We found proteomic differences between the melanocytic components of SN and SMM and identified 5 peptides that were differentially expressed in the 2 groups. From these data, 29 of 30 SN and 26 of 29 SMM were recognized correctly based on tumor analysis in the validation set. This method correctly classified SN with 97% sensitivity and 90% specificity in the validation cohort. Conclusions: Imaging Mass Spectrometry analysis can reliably differentiate SN from SMM in formalin-fixed, paraffin-embedded tissue based on proteomic differences.
机译:背景:将斯皮兹痣(SN)与斯皮兹德恶性黑色素瘤(SMM)区分开来是皮肤病理学中最困难的问题之一。具体目标:识别SN和SMM之间在蛋白质组学水平上的差异。方法:我们对福尔马林固定,石蜡包埋的组织样品进行了成像质谱分析,以识别SN和SMM之间的蛋白质组水平差异。 SN和SMM的诊断基于组织病理学标准,临床特征和随访数据,这证实没有诊断为SN的病变会复发或转移。分析了来自Yale Spitzoid肿瘤库中114例SN和SMM患者的黑素细胞成分(肿瘤)和肿瘤微环境(真皮)。从每个样品获得质谱后,分别使用来自26个SN和25个SMM的活检样本的训练集建立分类模型,以用于肿瘤和真皮。在训练数据集上开发的分类算法已在另一套来自SN的30个样本和来自SMM的33个样本中得到验证。结果:我们发现SN和SMM的黑素细胞成分之间存在蛋白质组学差异,并鉴定了5种在2组中差异表达的肽。从这些数据中,基于验证集中的肿瘤分析,可以正确识别30 SN中的29个和29 SMM中的26个。该方法在验证队列中以97%的敏感性和90%的特异性正确分类了SN。结论:基于蛋白质组学差异,成像质谱分析可以可靠地将福尔马林固定,石蜡包埋的组织中的SN与SMM区分。

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