Elucidating Critical Dependencies Underlying Therapeutic Evasion in Philadelphia Chromosome-like Acute Lymphoblastic Leukemia

PROJECT SUMMARY/ABSTRACT This mentored career development award proposal will facilitate my career goal to become an independent translational researcher using advances in experimental genomics and bioinformatics to develop improved precision medicine therapies for children with difficult-to-cure cancers. During the 5-year training period

I plan to acquire critical skills in computational biology and pursue additional didactic training in transcriptional regulation, death pathways, single cell analyses, and early-phase clinical trial design. The proposed studies and training will be completed under the co-mentorship of Dr. Kai Tan and Dr. Sarah Tasian, both internationally

recognized leaders with complementary expertise in systems and single cell biology and in translational leukemia research, respectively. My multi-disciplinary Advisory Committee is composed of world-renowned scientists who have extensive mentoring experience and diverse expertise, including Drs. Chi Dang, Nancy Speck, John Maris,

and Xiaolu Yang. The scientific proposal is aimed at elucidating critical dependencies that synergize with kinase pathway oncogene addiction in Philadelphia chromosome-like (Ph-like) acute lymphoblastic leukemia (ALL), a kinase-driven leukemia with dismal outcomes. Ph-like ALL comprises 15-40% of childhood and adult ALL cases

and is associated with extremely high relapse rates and very poor overall survival. We observed in preclinical Ph-like ALL models that treatment with the JAK inhibitor ruxolitinib has incomplete efficacy and also resulted in global gene expression changes. Thus, combination therapy approaches that effectively target key therapeutic

escape mechanisms are needed. Additionally, single-cell variability in Ph-like ALL that may drive targeted therapy resistance is unknown. I hypothesize that ruxolitinib treatment in JAK/STAT pathway-altered Ph-like ALL cells leads to rewiring of the gene regulatory network at transcriptional and epigenetic levels (likely mediated by

c-MYC), resulting in cell cycle arrest and apoptotic priming amenable to co-targeting. I propose in Aim 1 to model patient leukemia reponse to kinase inhibition in vivo and to identify transcriptional regulatory network changes during chronic ruxolitinib treatment with subsequent functional validation. This represents an unbiased approach

to identifying unknown oncogenic dependencies. In Aim 2, I will use single-cell techniques to examine genetic and non-genetic sub-populational changes during targeted drug perturbation over time, then to characterize and target resistant cell states. These studies will form the basis for developing rational combinations of molecularly

targeted therapies to improve cure rates for patients with Ph-like ALL. In summary, I will benefit from the exceptional interdisciplinary expertise and track-record of my mentors and Advisory Committee, as well as the rich intellectual environment and scientific resources available at CHOP and Penn, which provide an ideal setting

in which to conduct cutting-edge omics analyses for eventual clinical translation. These research and training

efforts will help me realize my ultimate goal to translate “big data” into clinically relevant cures for children with cancer.