Imaging Mass Spectrometry-A New and Promising Method to Differentiate Spitz Nevi From Spitzoid Malignant Melanomas

被引:77
|
作者
Lazova, Rossitza [1 ,2 ]
Seeley, Erin H. [3 ]
Keenan, Megan [2 ,4 ]
Gueorguieva, Ralitza [2 ,4 ]
Caprioli, Richard M. [3 ]
机构
[1] Yale Univ, Sch Med, Dept Dermatol, New Haven, CT 06520 USA
[2] Yale Canc Ctr, New Haven, CT 06520 USA
[3] Vanderbilt Univ, Mass Spectrometry Res Ctr, Nashville, TN USA
[4] Yale Univ, Sch Med, Yale Sch Publ Hlth, New Haven, CT 06520 USA
基金
美国国家卫生研究院;
关键词
Spitz nevus; Spitzoid melanoma; imaging mass spectrometry; atypical Spitzoid neoplasm; malignant melanoma; MALDI; matrix-assisted laser desorption ionization; proteomics; DIAGNOSIS; TUMORS; DISCORDANCE; THROUGHPUT; MUTATIONS; HISTOLOGY; SUBTYPE; CELLS; HRAS;
D O I
10.1097/DAD.0b013e31823df1e2
中图分类号
R75 [皮肤病学与性病学];
学科分类号
100206 ;
摘要
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.
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页码:82 / 90
页数:9
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