Kasper Karlsson

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.

Cancer cells are all different, and this heterogeneity is an important reason why cancer is difficult to treat. In order for a patient to be cured, it is necessary that all different tumor populations are reached with the treatment. However, this fundamental aspect of tumor biology is rarely taken into account when developing new therapies, as it is difficult to model tumor heterogeneity. We have developed methods to label the DNA of cancer cells with a barcode, which allows us to follow how thousands of individual tumor clones respond to different drugs and can identify surviving cell populations. Neuroblastoma is the most common solid childhood tumor outside the brain, and the 5-year survival rate for high-risk neuroblastoma is approximately 50%. In this project, we will first identify drugs that are effective against neuroblastoma via drug screening against neuroblastoma organoids, and then use DNA barcode technology to investigate which of these drugs specifically target the cells that survive current chemotherapy treatment for neuroblastoma. The most promising candidates for combination therapy will then be verified both in neuroblastoma organoids and in xenograft experiments. Our goal is to identify and verify drugs that complement current neuroblastoma therapy in such a way that it specifically targets those tumor clones that survive current treatment. We also envision that our studies will exemplify for the broader cancer research community how cell barcoding can be used to identify effective combination therapies based on principles of tumor heterogeneity and identification of low cross-resistance with current treatment, which would increase the likelihood of a cure, not just a life-prolonging one , cancer treatment.