Classification of small blue round cell tumors by integrating peptide and N-glycan mass imaging spectrometric profiles.

BACKGROUND: Small blue round cell tumor (SBRCT) is an umbrella term for several tumor types of completely different cellular origin and differentiation. Members of this tumor group share a common morphological phenotype, which is characterized by small round cells with high nuclear-cytoplasmic ratio. The diagnosis cannot be made based on histomorphology alone, instead requiring a range of immunohistochemical and molecular analyses. Accurate diagnosis is essential for the correct choice of treatment and proper prognostic assessment, but can be challenging on small pre-therapeutic biopsies. RESULTS: In this proof-of-concept study matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI) of peptides and N-glycans from a TMA (tissue microarray) of 26 SBRCT samples comprising Ewing sarcoma (n = 5), rhabdomyosarcoma (n = 5), neuroendocrine carcinoma (n = 5), acute lymphoblastic leukemia (n = 5), nephroblastoma (n = 3), and neuroblastoma (n = 3) was used to create classification algorithms to distinguish between the tumor types. We trained and tested four different classification algorithms (gradient boosting (GB), support vector machine (SVM), k-nearest neighbor (KNN), linear discriminant analysis (LDA)) on pixel-level achieving accuracy values between 76 % and 100 %. The integration of peptide and N-glycan mass spectrometry in one dataset led to a 4-5 % increase in accuracy compared to the results on the individual datasets. GB was the most robust classifier. Tentative identification of discriminatory tryptic peptide and N-glycan signatures revealed proteins involved in epigenetic regulation and organization of the cytoskeleton as well as fucosylated N-glycans. SIGNIFICANCE: Peptide and N-glycan MSI has huge potential and is a promising tool to discriminate different SBRCT entities. Combining mass spectrometry imaging data from peptides and N-glycans even enhanced classification performance. At the same time, the results underline the importance of an accurate spatial mapping to create such integrated data sets.      «

BACKGROUND: Small blue round cell tumor (SBRCT) is an umbrella term for several tumor types of completely different cellular origin and differentiation. Members of this tumor group share a common morphological phenotype, which is characterized by small round cells with high nuclear-cytoplasmic ratio. The diagnosis cannot be made based on histomorphology alone, instead requiring a range of immunohistochemical and molecular analyses. Accurate diagnosis is essential for the correct choice of treatm...     »