Wu Zhiyang, Hundsdoerfer Patrick, Schulte Johannes H, Astrahantseff Kathy, Boral Senguel, Schmelz Karin, Eggert Angelika, Klein Oliver
BIH Center for Regenerative Therapies BCRT, Charité-Universitätsmedizin Berlin, 13353 Berlin, Germany.
Department of Pediatric Oncology, Helios Klinikum Berlin-Buch, 13125 Berlin, Germany.
Cancers (Basel). 2021 Jun 25;13(13):3184. doi: 10.3390/cancers13133184.
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.
风险分类在神经母细胞瘤患儿的临床管理和治疗决策中起着至关重要的作用。目前,风险评估基于诊断时单次肿瘤活检的患者标准和分子因素。越来越多的证据表明神经母细胞瘤存在广泛的肿瘤内异质性,这促使人们需要新的诊断方法,以便在空间分辨率上更全面地评估分子谱,从而更好地预测肿瘤进展和治疗耐药的风险。我们开展了一项初步研究,调查基质辅助激光解吸/电离质谱成像(MALDI-MSI)在不同当前风险分类(高风险与低/中风险)的神经母细胞瘤组织中识别空间肽异质性的可行性和潜力。单变量(受试者操作特征分析)和多变量(分割、主成分分析)统计策略确定了基于MALDI的具有空间判别力的风险相关肽特征。AHNAK核蛋白和塌陷反应介导蛋白1(CRMP1)被确定为与这些肽特征相关的蛋白质,并且它们在不同风险的神经母细胞瘤中的差异表达通过免疫组织化学得到了验证。这项概念验证研究表明,MALDI-MSI结合单变量和多变量分析策略能够在神经母细胞瘤组织中识别具有空间判别力的风险相关肽特征。这些结果提示了一种有前景的新分析策略,可改善风险分类并为神经母细胞瘤肿瘤内异质性提供新的生物学见解。