Joint differentiation-state plasticity and genetic diversity modeling to predict response and improve efficacy of drug combination therapy

项目总结 每个肿瘤都面临一组共同的障碍，这些障碍来自于肿瘤的内在动力学、微环境信号 和治疗性干预。肿瘤发生的“规范”观点是每一种肿瘤 通过组合各种战术来克服这些障碍，走出了一条独特的道路。一些早期的 癌症治疗的突破直接源于将这些途径粗略地划分为不同的 基于“基因组标志”的亚型，如慢性粒细胞白血病的bcr-abl融合。然而， 在急性髓系白血病(AML)中，大多数患者缺乏可操作的突变，近一半的AML 核型正常的患者。对于某些AML驱动程序突变，分子靶向药物具有 显示出初步的临床前景，但没有长期耐受性；耐药性仍然是靶向的关键挑战 疗法，促使转向组合策略。肿瘤内的异质性和可塑性以及 肿瘤微环境在形成对治疗的反应和发展中起着基础性作用 抵抗。最近的发现表明，靶向药物在不同的时间对AML细胞有不同的疗效 不同阶段的髓系分化导致不同的耐药机制。这一观察打开了 通过将靶向药物与细胞表型相匹配来提高临床实用性的潜力。一种特殊的，但在临床上 这一观察的重要案例是靶向bcl2抑制剂ventoclax和MEK的不同疗效 急性髓系白血病细胞髓系分化不同阶段的抑制物。在我们对BEAT AML的初步分析中 队列，我们观察到这种表型与bcl2下游转录影响之间的一致性。 和MCL1蛋白，提示与先前描述的万乃馨抗性机制有关的分子链接。 我们假设，分化态的可塑性是短期抵抗广泛的 靶向化合物的范围。细胞分化-状态可塑性联合作用的机制理解 通过基因组驱动的细胞过程可以改善患者对治疗的分层并提出更多建议 量身定制的组合疗法。为此，我将使用匹配的多组体的最大集合数据集 来自BEAT AML的原发白血病样本的组合概况、药物筛选和临床信息 奈特癌症研究所的项目。我的目标是对大量基因组进行系统分析， 功能体外分析(药物和CRISPR)，结合单细胞转录，体外细胞TOF和 AML原发样本的单细胞药物反应数据，以了解肿瘤异质性和 药物反应的可塑性以前所未有的细节。预期结果是：1)患者病情改善 通过准确地将治疗与个别患者匹配而取得的结果和2)新的提名 减轻基于可塑性的耐药性的方法。

PROJECT SUMMARY Each tumor faces a common set of obstacles arising from tumor-intrinsic dynamics, microenvironment signals and therapeutic interventions. The “canonical” view of tumorigenesis is a landscape within which each tumor navigates a unique path by combining various tactics to overcome these obstacles. A number of the early breakthroughs in cancer treatment directly resulted from coarse demarcations of these paths into distinct subtypes based on “genomic landmarks” such as the BCR-ABL fusion in chronic myeloid leukemia. However, in acute myeloid leukemia (AML), the majority of patients lack actionable mutations and nearly half of AML patients present with normal karyotype. For certain AML driver mutations, molecularly targeted drugs have shown initial clinical promise but not long-term durability; resistance remains a key challenge for targeted therapies, prompting a shift to combination strategies. Intratumor heterogeneity and plasticity as well as the tumor microenvironment play a fundamental role in shaping response to therapy and development of resistance. Recent findings indicate that targeted agents have different efficacies on AML cells at distinct stages of myeloid differentiation and lead to different resistance mechanisms. This observation opens the potential to improve clinical utility by matching targeted drugs to cell phenotypes. A specific, yet clinically important case of this observation is the different efficacies of targeted BCL2 inhibitor venetoclax and MEK inhibitors in AML cells at distinct stages of myeloid differentiation. In our preliminary analysis of the Beat AML cohort, we observe a concordance between this phenotype and the downstream transcriptional impact of BCL2 and MCL1 proteins suggesting a molecular link to a previously described venetoclax resistance mechanism. We hypothesize that differentiation-state plasticity is a general modulator of short-term resistance to a wide range of targeted compounds. A mechanistic understanding of cell differentiation-state plasticity in conjunction with genome-driven cellular processes can improve stratification of patients to therapies and suggest more tailored combinatorial treatments. To that end, I will use the largest assembled dataset of matched multi-omic assembled profiles, drug screens, and clinical information for primary leukemia samples from the Beat AML project at the Knight Cancer Institute. My objective is to perform systematic analysis of bulk genomic, functional ex-vivo assays (drug and CRISPR), conjointly with single-cell transcriptomic, ex-vivo CyTOF and single-cell drug response data in AML primary samples to understand the effects of tumor heterogeneity and plasticity on drug response at an unprecedented detail. The anticipated outcomes are 1) improved patient outcomes achieved by accurately matching therapies to individual patients and 2) nomination of new approaches to mitigate plasticity-based drug resistance.