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Mass spectrometry imaging in the diagnosis of difficult atypical spitzoid neoplasms
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Cancer Science & Therapy

ISSN: 1948-5956

Open Access

Mass spectrometry imaging in the diagnosis of difficult atypical spitzoid neoplasms


Global Summit on Melanoma & Carcinoma

July 14-15, 2016 Brisbane, Australia

Rossitza Lazova

Yale University School of Medicine, USA

Scientific Tracks Abstracts: J Cancer Sci Ther

Abstract :

Background: In a previous study using Mass Spectrometry Imaging (MSI), we discovered differences on a protein level between Spitz nevi and Spitzoid malignant melanomas. Objective: The objective is to investigate whether MSI can help in the differentiation between benign melanocytic nevi (BMN) and conventional malignant melanomas (MM). Methods: Archival formalin-fixed, paraffin embedded tissue samples from 51 BMN and 54 primary cutaneous MM were analyzed by MSI to identify proteomic differences. After obtaining mass spectra from each sample in the teaching set comprising 25 nevi and 25 melanomas, statistical correlation models were generated using a genetic algorithm. A combination of peaks that separates best between benign nevi and malignant melanomas was established. A diagnosis of either nevus or melanoma was rendered on a separate validation set of 26 nevi and 29 melanomas based on the proteomic signature, which diagnosis was then correlated with the histopathologic diagnosis and clinical behavior. Results: MSI classified 28/29 cases of MM and 22/26 BMN correctly. The sensitivity for recognizing melanomas was 97% and specificity was 85%. Conclusions: MSI can differentiate between BMN and MM based on proteomic differences. MSI is an objective and reliable method that may be helpful in difficult cases, in which rendering a firm diagnosis of either benign nevus or malignant melanoma may be very difficult. The identification of protein expression profiles, which discriminate between BMN and MM, may lead to the discovery of clinically useful protein biomarkers and translate into tumor biomarkers that can be incorporated into standard diagnostic and treatment strategies.

Biography :

Email: rossitza.lazova@yale.edu

Google Scholar citation report
Citations: 3968

Cancer Science & Therapy received 3968 citations as per Google Scholar report

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