Modeling cell differentiation in neuroblastoma: insights into development, malignancy, and treatment relapse

TL;DR

This paper introduces a new mathematical model of cell differentiation in neuroblastoma, revealing how developmental dynamics influence tumor heterogeneity, malignancy, and relapse risk, based on Bayesian inference of clinical data.

Contribution

A novel phenotypically structured model of sympathoadrenal development that links differentiation dynamics to neuroblastoma heterogeneity and relapse risk.

Findings

Model accurately explains cell heterogeneity in neuroblastoma.

Altered differentiation dynamics relate to malignancy and tumor growth.

Developmental robustness reduces malignancy accumulation.

Abstract

Neuroblastoma is a paediatric extracranial solid cancer that arises from the developing sympathetic nervous system and is characterised by an abnormal distribution of cell types in tumours compared to healthy infant tissues. In this paper, we propose a new mathematical model of cell differentiation during sympathoadrenal development. By performing Bayesian inference of the model parameters using clinical data from patient samples, we show that the model successfully accounts for the observed differences in cell type heterogeneity among healthy adrenal tissues and four common types of neuroblastomas. Using a phenotypically structured model, we show that alterations in healthy differentiation dynamics are related to cell malignancy, and tumour volume growth. We use this model to analyse the evolution of malignant traits in a tumour. Our findings suggest that normal development dynamics make the embryonic sympathetic nervous system more robust to perturbations and accumulation of malignancies, and that the diversity of differentiation dynamics found in the neuroblastoma subtypes lead to unique risk profiles for neuroblastoma relapse after treatment.