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

项目总结/摘要 这个指导性的职业发展奖励计划将促进我的职业目标，成为一个 利用实验基因组学和生物信息学的进展， 为患有难以治愈的癌症的儿童提供更精确的药物治疗。在5年的培训期间， 我计划获得计算生物学的关键技能，并在转录方面进行额外的教学培训。 调控、死亡途径、单细胞分析和早期临床试验设计。拟议的研究和 培训将在谭凯博士和萨拉·塔西安博士的共同指导下完成，这两名博士都是国际性的 在系统和单细胞生物学以及转化性白血病领域具有互补专业知识的公认领导者 研究，分别。我的跨学科咨询委员会由世界知名的科学家组成， 拥有丰富的指导经验和多样化的专业知识，包括Chi Dang博士，Nancy Speck，John Maris， 还有杨小璐。这项科学提案旨在阐明与激酶协同作用的关键依赖性 费城染色体样（Ph样）急性淋巴细胞白血病（ALL）中的通路癌基因成瘾， 激酶驱动的白血病，结果令人沮丧。Ph样ALL占儿童和成人ALL病例的15-40% 并且与极高的复发率和非常差的总体存活率相关。我们在临床前观察到， 用JAK抑制剂ruxolitinib治疗的Ph样ALL模型具有不完全的功效，并且还导致 全球基因表达变化。因此，有效靶向关键治疗药物的联合治疗方法是可行的。 需要有逃生机制。此外，Ph样ALL中的单细胞变异性可能导致靶向 治疗抗性未知。我假设鲁索利替尼治疗JAK/STAT通路改变的Ph样ALL 细胞导致基因调控网络在转录和表观遗传水平上的重新布线（可能由 c-MYC），导致细胞周期停滞和适于共靶向的凋亡引发。我在目标1中提出， 白血病患者体内对激酶抑制的反应，并确定转录调控网络的变化 在长期鲁索利替尼治疗期间，随后进行功能验证。这是一种不带偏见的做法 来识别未知的致癌依赖性。在目标2中，我将使用单细胞技术来检查遗传 和非遗传亚群在靶向药物扰动期间随时间的变化，然后表征和 靶向抗性细胞状态。这些研究将为开发合理的分子组合奠定基础。 靶向治疗，以提高Ph样ALL患者的治愈率。总之，我将受益于 卓越的跨学科专业知识和我的导师和咨询委员会的跟踪记录，以及 CHOP和Penn拥有丰富的知识环境和科学资源，为您提供理想的环境 在那里进行尖端的组学分析，最终用于临床转化。这些研究和训练 这些努力将帮助我实现我的最终目标，将“大数据”转化为临床相关的治疗方法， 癌

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.