A human neural crest model reveals the developmental impact of neuroblastoma-associated chromosomal aberrations [Parse scRNA-seq]
Early childhood tumours arise from transformed embryonic cells, which often carry large copy number alterations (CNA). However, it remains unclear how CNAs contribute to embryonic tumourigenesis due to a lack of suitable models. Here we employ female human embryonic stem cell (hESC) differentiation and single-cell transcriptome and epigenome analysis to assess the effects of chromosome 17q/1q gains, which are prevalent in the embryonal tumour neuroblastoma (NB). We show that CNAs impair the specification of trunk neural crest (NC) cells and their sympathoadrenal derivatives, the putative cells-of-origin of NB. This effect is exacerbated upon overexpression of MYCN, whose amplification co-occurs with CNAs in NB. Moreover, CNAs potentiate the pro-tumourigenic effects of MYCN and mutant NC cells resemble NB cells in tumours. These changes correlate with a stepwise aberration of developmental transcription factor networks. Together, our results sketch a mechanistic framework for the CNA-driven initiation of embryonal tumours. Overall design: 1 multiplexed scRNA-seq dataset comprising 96 samples from hESCs differentiation toward trunk neural crest and sympathoadrenal derivatives at 9 key stages (day 0, 3, 6, 9, 10, 12, 14, 19, 28) and in different experimental conditions (H7 hESCs: wild-type, 17q gain, 17q+1q gain, all with/without MYCN overexpression; H9 hESCs: WT, 17q+1q, 17q+1q+MYCN overexpression); most sample groups are represented by 2 replicates (independent differentiation experiments with the same cell lines). Single-cell libraries were prepared using split-pool barcoding by Parse Bioscience (WT Mega kit). Please note that all samples were pooled in this scRNA-seq reaction using split Parse Biosciences pool combinatorial barcoding The data stem from a combinatorial indexing scRNA-seq experiment (Parse Bio), which means that all files contain reads from many single cells and all samples mixed up into one. Demultiplexing of both samples and cells is done in one step by Parse's pipeline as described in the sample data processing field.