Classification of Neuroblastic Tumors by Whole Transcriptome Profiling

Abstract

Although primary pediatric tumors are extremely rare, they remain the leading cause of non-accidental death in children. Peripheral neuroblastic tumors (pNTs) account for about 10% of pediatric malignancies. Their incidence is approximately ten cases per million children each year. They are highly heterogeneous and are classified based on morphological characteristics. Since 2018, the Princess Máxima Center routinely uses RNA-sequencing to detect fusion genes, one of the most common genomic alterations in pediatric cancers. Through our study we aim to refine tissue-based diagnosis as well as predict the outcome of pNT patients. We reviewed the morphology of frozen tumor tissue fragments from patients with neuroblastic tumors from which RNA was extracted. Based on this morphology review we created three groups: undifferentiated, differentiating and differentiated tumors and sought to determine whether there was a correlation between the morphology and the RNA-seq data of the samples. We then investigated the RNA-seq data of pNTs, neurofibromas and Schwannomas to observe the relation between the expression profile and the histology-based diagnosis. The expression profiles described a differentiation gradient, moving from benign differentiated tumors such as schwannomas and neurofibromas to malign undifferentiated tumors such as poorly differentiated neuroblastomas. Subsequently, we explored the expression level of MYCN throughout the pNT cohort and found a correlation between the MYCN expression level and the differentiation gradient. We then analyzed differentially expressed genes (DEGs) and enriched pathways in undifferentiated versus differentiated tumors and in MYCNA versus non-MYCNA-PDNBs. Overall, based on our cohort, we showed that pNTs, neurofibromas and Schwannomas cluster together by morphological diagnosis and follow a cellular differentiation gradient. Further, we showed that these gene sets are differentially expressed between undifferentiated and differentiated tumors as well as between MYCNA and non-MYCNA PDNBs. Combining our data with clinical follow-up data, may provide new avenues for prediction of prognosis and targeted treatment for patients with peripheral neuroblastic tumors.