Single-Cell RNA Sequencing Maps Neuroblastoma Intratumoral Heterogeneity

Neuroblastoma is the most common solid tumor found outside of the brain in children, yet why some children respond well to treatment while others do not has remained poorly understood. St. Jude Children's Research Hospital scientists and their collaborators built one of the most comprehensive datasets of neuroblastoma cells to date, using it to define the tumor's cell types and identify a gene signature marking a malignant cell population tied to poor prognosis.

The team also created patient-derived models that capture this population, which older laboratory cell lines had missed. The findings, published today in Cancer Cell, give researchers a new framework and a set of tools to study high-risk neuroblastoma.

Neuroblastoma cells are divided into two cell states: adrenergic cells (which are associated with low-risk disease) and mesenchymal cells (which are associated with high-risk disease, treatment resistance and poor outcomes). However, directly identifying cancer-related mesenchymal cells in patient tumors has been challenging because the body also contains healthy mesenchymal cells, which can be mistaken for their malignant counterparts, complicating efforts to study them.

To find a better way to identify these treatment-resistant cancer cells, the researchers looked at 54 tumors from 50 patients. The scientists constructed one of the most comprehensive dataset of neuroblastoma cells to date, incorporating multiple cutting-edge technologies, including single-cell RNA sequencing and spatial omics.

By leveraging patient-derived xenografts, which are patient tumor cells grown within mice, the team isolated a clear gene expression profile connected to malignant mesenchymal cells. The healthy mesenchymal cells from the patient tumor do not grow in xenografts. The xenografted tumor cells, which were generated as part of the St. Jude Childhood Solid Tumor Network (CSTN), were crucial in proving that these cells not only exist, but in defining their molecular and cellular features.

With this new gene expression signature for mesenchymal cells in neuroblastoma, we can dig into why outcomes are so varied between different children with this cancer."

Michael Dyer, PhD, Study Co-Corresponding Author and Chair, Department of Developmental Neurobiology, St. Jude Children's Research Hospital

To verify that this newfound signature was more effective than previous methods at identifying cancer-related mesenchymal cells in patient tumors, the researchers tested it using an independent database of patient tumor RNA sequencing data. The new signal improved predictions for outcomes significantly, while a pre-existing signature from decades-old cell lines did not.

Validating a New Gene Expression Signature in Neuroblastoma

To assess the signature, the researchers created organoids (three-dimensional growths of cancer cells formed in the lab) and cell lines, in addition to their xenografts. The scientists used multiple approaches across these systems, including spatial transcriptomics, spatial proteomics, electron microscopy and chromatin profiling.

The gene expression signature differentiated between the two neuroblastoma cell types in all cases. The scientists also found the two cell types had distinct cellular shapes, internal spatial organization and behaviors.

"I'm just endlessly fascinated by the signature itself, because regardless of the test, it's been very robust," said first author Anand Patel, MD, PhD, St. Jude Department of Oncology. "These markers are going to be powerful tools to understand neuroblastoma better."

With the marker identified and validated, the group created additional invitro models and new cell lines from xenografts derived from patient samples that had varying proportions of mesenchymal to adrenergic cells. Those models are available upon request through the CSTN, giving researchers a resource that could reinvigorate investigations into high-risk disease. Those tools may help scientists better understand tumor cell states, identify vulnerabilities and evaluate potential treatment strategies.

"Our new models are a launching point for neuroblastoma research," said co-corresponding author Elizabeth Stewart, MD, St. Jude Department of Oncology. "Using this dataset as our foundation, the field is poised to explore the biology of this pediatric cancer more deeply, and ultimately, move us toward improving our patients' outcomes."