Precision strategies to eradicate metastatic cells in neuroblastoma

Tumors are heterogeneous in nature due to genetic instability and ongoing selection.

Tumor recurrency often depends on outgrowth of rare, therapy resistant subclones and commonly used strategies to evaluate efficient drug combinations, including finding synergistic interactions, are optimized on enhancing cell killing in short-term drug response experiments, which makes them poorly suited to identify and address rare cell resistance.

We propose to use precision lethality, and other precision strategies like radiopharmaceutical therapy, to overcome clonal heterogeneity in pediatric neuroblastoma.

In precision lethality cell barcoding is used to tag thousands of distinct tumor subclones, which make it possible to quantify subclone frequency, to identify sub-populations that enrich under specific drugs, and to systematically search for other drugs that target those sub-populations.

Here we extend the precision lethality concept to include single cell transcription measurements and apply this to develop deep learning models of drug response and to combine drugs for efficient differentiation of neuroblastoma cells.

Building on previous proof-of-concept studies, this multi-disciplinary research proposal comprehensively assesses clonal heterogeneity to find drugs that supplement standard of care therapy, by targeting rare, treatment resistant cells, and thereby increase the chance of survival for children with high-risk neuroblastoma.