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

项目摘要/摘要 这份有指导意义的职业发展奖提案将有助于我的职业目标成为一名 独立翻译研究人员利用实验基因组学和生物信息学的进展来开发 改善难以治愈的癌症儿童的精准医学治疗。在为期5年的培训期间 我计划获得计算生物学方面的关键技能，并继续进行转录方面的额外教学培训 调节、死亡途径、单细胞分析和早期临床试验设计。建议进行的研究及 培训将在陈启宗博士和Sarah Tasian博士的共同指导下完成，两人都是国际上的 在系统和单细胞生物学以及转化性白血病方面拥有互补专业知识的公认领导者 分别进行了研究。我的多学科咨询委员会由世界知名的科学家组成，他们 有丰富的指导经验和不同的专业知识，包括志当博士，南希·斯派克博士，约翰·马里斯博士， 还有杨晓路。该科学提案旨在阐明与激酶协同作用的关键依赖关系。 费城类染色体(Ph-like)急性淋巴细胞白血病(ALL)的致癌基因途径成瘾 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% 而且与极高的复发率和非常差的总体存活率有关。我们在临床前观察到 与所有使用JAK抑制剂Ruxolitinib治疗的PH模型一样，Ruxolitinib的疗效不完全，也导致 全球基因表达发生变化。因此，有效针对关键治疗方法的联合治疗方法 逃生机制是必要的。此外，Ph中的单细胞变异性可能会驱动靶向 治疗耐药性尚不清楚。我推测Ruxolitinib治疗JAK/STAT通路改变了类Ph 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(可能是通过 C-myc)，导致细胞周期停滞和凋亡启动，服从于共靶向。我在目标1中建议建立 白血病患者体内对激酶抑制的反应和识别转录调控网络的变化 在慢性Ruxolitinib治疗期间，随后进行功能验证。这是一种不偏不倚的做法。 以识别未知的致癌依赖关系。在目标2中，我将使用单细胞技术来检测基因 和非遗传亚种群在靶向药物扰动期间随时间的变化，然后表征和 目标为耐药细胞状态。这些研究将为开发合理的分子组合奠定基础。 有针对性的治疗，以提高类Ph ALL患者的治愈率。总而言之，我将受益于 我的导师和咨询委员会卓越的跨学科专业知识和业绩记录，以及 CHOP和宾夕法尼亚大学拥有丰富的智力环境和科学资源，这为我们提供了理想的环境 为最终的临床翻译进行尖端的组学分析。这些研究和培训 这些努力将帮助我实现自己的最终目标，即将大数据转化为与临床相关的治疗方法，用于治疗患有 癌症。

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.