Mathematical model of phenotypic plasticity predicts interconversion is a drug target for neuroblastoma.

Abstract

Neuroblastoma is a paediatric cancer arising from the sympathetic nervous system as neural crest cells, made up of noradrenergic (NOR/ADRN/N), mesenchymal like (MES/S), and intermediate (I-type/I) cell types. These cells can interconvert between types, contributing to treatment resistance and relapse. We developed a mathematical model to investigate how interconversion patterns affect the efficacy of phenotype-specific inhibitors. We used three ordinary differential equations to describe the dynamics of the three populations, including logistic growth, interconversion, and drug-induced death. Of the 64 possible interconversion patterns, five reduced the target population: two for N cells and three for S cells. N targeting patterns were more effective with higher interconversion rates, while mesenchymal targeting patterns were more effective with lower interconversion rates. Stability analysis revealed that natural tumour growth was always unstable, but during treatment, N-suppressing patterns combined with an S inhibitor gave the most consistently stable origin. Testing multi-stage and cyclic treatment schedules revealed that N-suppressing patterns with an S inhibitor, followed by an S-suppressing pattern with an N inhibitor, achieved more reliable remission. Three of the five patterns of interest correspond to reported biological plausibility, and known compounds exist to induce most of the required transitions, supporting the clinical relevance of these strategies for improving neuroblastoma treatment outcomes.