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

Abstract

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 (IMS) analysis on formalin-fixed, paraffin embedded tissue samples (FFPE) 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 five peptides that were differentially expressed in the two groups. From these data, 29 out of 30 SN and 26 out 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 IMS analysis can reliably differentiate SN from SMM in FFPE tissue based on proteomic differences.

Diabetic nephropathy induces alterations in the glomerular and tubule lipid profiles

“…Interestingly, unlike in all other mammals, ganglioside technology enables molecular profi ling of specifi c areas of the tissues while preserving tissue morphology. This technology has been instrumental in understanding molecular changes on the border between normal and cancer tissues ( 42 ), classifying tumor types ( 28,43 ), determining tissue drug distributions ( 44,45 ), and identifying candidate markers of disease ( 20,46 ). As demonstrated in this study, it is now possible to analyze the molecular composition and molecular modifi cations in distinct renal tissue regions, and even within smaller structures such as glomeruli and tubules.…”

Drug compound characterization by mass spectrometry imaging in cancer tissue

“…MALDI-MSI studies on the clinical status and as risk assessments with respect to disease developments, e.g., cancer states of tumor genesis (Fehniger et al 2011), and drug responders, as well as long-term survival (Marko-Varga et al 2012;Sugihara et al 2014). In addition to our own melanoma studies, studies undertaken by Caprioli et al, was first to present MALDI-MSI data where they used metastatic tumors, identifying calcyclin (Hardesty and Caprioli 2008;Lazova et al 2012).…”

Literature Update on Melanocytic Nevi and Pigmented Lesions in the Pediatric Population

“…Al Dhaybi and colleagues proposed the expression of p16 as a potential marker of childhood nodular Spitzoid malignant melanomas, which may aid in distinguishing this subtype from Spitz nevi [55]. Other recent diagnostic approaches include imaging mass spectrometry, which was able to classify Spitz nevi correctly with 97 % sensitivity and 90 % specificity based on proteomic differences [56]. In a small pilot study, hyperspectral data also was utilized to create an index at a molecular pigmentary level to diagnose melanoma, with a sensitivity of 90 % and specificity of 84 % [57].…”