Revealing the heterogeneity in neuroblastoma cells via nanopillar-guided subnuclear deformation

Neuroblastoma is a hard-to-treat childhood cancer that is well known for the heterogeneity of its clinical phenotypes. Although the risk levels of neuroblastoma have been defined from a complex matrix of clinical and tumor biological factors to guide treatment, the accuracy in predicting cancer relapse and related fatality is still poor in many cases, where heterogeneity with subpopulations in highly malignant or drug-resistant tumors is believed to be underestimated by the current analysis methods. Therefore, new technologies to probe neuroblastoma heterogeneity are needed for the improvement of risk stratification. In this study, we introduce the nanopillar-guided subnuclear morphology as an effective indicator for heterogeneity evaluation among individual neuroblastoma cells. Nuclear polymorphisms, especially the generation of subnuclear irregularities, are well-known markers of high cancer metastasis risk and poor prognosis. By quantitatively evaluating the orientation of nanopillar-guided nuclear envelope features in neuroblastoma cells, we identified two subpopulations with differential motilities and EMT marker levels. Moreover, with endogenous expression, cells with high levels of the nuclear structure protein lamin A exhibit anisotropic deformation on nanopillars and migrate faster than low-lamin A cells, indicating a greater potential for metastasis. Overexpression of lamin A, however, reduces both the coherency and migration speed, suggesting that subpopulations with similar lamin A levels may have different metastatic potentials. We further verified that nanopillar-generated nuclear deformation patterns can quantitatively reveal individual cells' responses to anti-cancer drug treatment. Overall, we envision that the nanopillar-based assessment of subnuclear irregularities brings new additions to our toolkits for both precise risk stratification in neuroblastoma and the evaluation of related anti-cancer therapeutics.

Automated summary

Neuroblastoma is a highly heterogeneous childhood cancer, and accurate risk stratification is crucial for treatment planning. A new nanopillar-guided subnuclear morphology evaluation method identifies subpopulations with differential motilities, linking nuclear irregularities to cancer metastasis risk and prognosis. This method also reveals individual cell responses to anti-cancer drug treatments, enhancing our understanding of neuroblastoma heterogeneity and potential therapeutic strategies.