Abstract

Simple SummaryThe childhood tumor, neuroblastoma, has a broad clinical presentation. Risk assessment at diagnosis is particularly difficult in molecularly heterogeneous high-risk cases. Here we investigate the potential of imaging mass spectrometry to directly detect intratumor heterogeneity on the protein level in tissue sections. We show that this approach can produce discriminatory peptide signatures separating high- from low- and intermediate-risk tumors, identify 8 proteins aassociated with these signatures and validate two marker proteins using tissue immunostaining that have promise for further basic and translational research in neuroblastoma. We provide proof-of-concept that mass spectrometry-based technology could assist early risk assessment in neuroblastoma and provide insights into peptide signature-based detection of intratumor heterogeneity.Risk classification plays a crucial role in clinical management and therapy decisions in children with neuroblastoma. Risk assessment is currently based on patient criteria and molecular factors in single tumor biopsies at diagnosis. Growing evidence of extensive neuroblastoma intratumor heterogeneity drives the need for novel diagnostics to assess molecular profiles more comprehensively in spatial resolution to better predict risk for tumor progression and therapy resistance. We present a pilot study investigating the feasibility and potential of matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI) to identify spatial peptide heterogeneity in neuroblastoma tissues of divergent current risk classification: high versus low/intermediate risk. Univariate (receiver operating characteristic analysis) and multivariate (segmentation, principal component analysis) statistical strategies identified spatially discriminative risk-associated MALDI-based peptide signatures. The AHNAK nucleoprotein and collapsin response mediator protein 1 (CRMP1) were identified as proteins associated with these peptide signatures, and their differential expression in the neuroblastomas of divergent risk was immunohistochemically validated. This proof-of-concept study demonstrates that MALDI-MSI combined with univariate and multivariate analysis strategies can identify spatially discriminative risk-associated peptide signatures in neuroblastoma tissues. These results suggest a promising new analytical strategy improving risk classification and providing new biological insights into neuroblastoma intratumor heterogeneity.

Highlights

  • Neuroblastoma is a pediatric cancer arising in approximately 1 of 100,000 children under 15 years of age in Germany [1]

  • We evaluated the technical feasibility of MALDI-MSI to identify potential discriminative protein features of more aggressive neuroblastomas from formalin-fixed, paraffin-embedded (FFPE) tissue sections

  • Unsupervised segmentation analysis of m/z values from these areas produced three segment clusters with different peptide signatures in high-risk tumors, but only a single segment cluster in neuroblastomas were classified as lower risk (Figure 1)

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Summary

Introduction

Neuroblastoma is a pediatric cancer arising in approximately 1 of 100,000 children under 15 years of age in Germany [1]. It is the most common malignant solid tumor diagnosed in infants with a median age at diagnosis of 17 months [2]. Neuroblastoma treatment recommendations range from mere observation or surgical resection alone to very aggressive therapy protocols including high-dose chemotherapy, irradiation and immunotherapy [5].To address the issue of appropriate therapy intensity, a common international staging and risk classification system (INSS/INRG) has been developed [6,7]. Neuroblastoma samples from patients with low and intermediate risk (INSS/INRG) were grouped together for this retrospective study and high-risk patients were defined as in Table 1 (Stage 4 > 18 months plus all MYCN-amplified cases)

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