Characterizing cytotoxic therapy induced shifts in the cost-to-benefit ratio of high ploidy

细胞毒疗法引起高倍性成本效益比变化的特征

基本信息

批准号：
10521654
负责人：
Noemi Andor
金额：
$ 52.01万
依托单位：
H. LEE MOFFITT CANCER CTR & RES INST
依托单位国家：
美国
项目类别：
财政年份：
2022
资助国家：
美国
起止时间：
2022-09-01 至 2027-08-31
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10521654
关键词：
Affect Apoptosis Brain Neoplasms Cancer cell line Cell Death Cell Energetics Cell Line Cell Proliferation Cells Chromosome Segregation Chromosomes Clinical Coin Computing Methodologies Cytotoxic Chemotherapy DNA DNA Damage DNA sequencing Data Diploidy Disease Dose Drug Monitoring Drug Targeting Environment Event Evolution Fluorescence Microscopy Gastric Tissue Generations Genetic Materials Genome Genomic Segment Genomics Glioblastoma Glucose Growth Haploidy Human Genome Project Image In Vitro Joints Knowledge Malignant - descriptor Malignant Neoplasms Malignant neoplasm of brain Masks Measures Medicine Microtubules Mitotic Modeling Outcome Oxygen Parents Patients Pharmaceutical Preparations Phase Phenotype Ploidies Population Population Heterogeneity Process Prognosis Research Resistance Resources Risk Role S phase Somatic Cell Spatial Distribution Stomach Stomach Neoplasms Testing Time Tissues Validation Vinblastine base brain tissue cancer cell cancer type chromosome missegregation cost expectation experimental study fitness gastric cancer cell imaging platform in silico in vivo inorganic phosphate malignant stomach neoplasm mathematical methods mathematical model migration neoplastic cell prevent programs replication stress response segregation single cell sequencing single-cell RNA sequencing transcriptome translational potential tumor tumor DNA tumor heterogeneity tumor metabolism

项目摘要

SUMMARY Traditional phase I dose-finding strategies monitor drug response only for two weeks, based on the assumption that it will suﬃce to observe how therapy aﬀects doubling time of a homogeneous population over 2-4 generations. But with the paradigm shift that most cancers are heterogeneous comes an urgent need to consider that therapy-induced shifts in population composition manifest over longer time frames. We previously coined the “tip-over hypothesis of DNA damage therapy sensitivity”, proposing that cytotoxic therapy is eﬀective if it pushes a cell’s somatic copy number alteration (SCNA) load above a tipping point. Variable proximity of co-existing tumor cells to this tipping point imply that dose-response relations need not be monotonic. Cytotoxic therapy can drive one cell into apoptosis, while skyrocketing another cell into malignant proliferation. As the developers of widely used computational and mathematical methods, with established research programs in tumor metabolism, and with a broad record of modeling dynamic processes and integrating various omics- and imaging platforms, our team brings complementary expertise to develop a personalized cytotoxic therapy strategy that confines therapy-induced selection of resistant clones. We will test the potential of tumor cell DNA content and dNTP substrate availability to predict a tumor’s vulnerability to increasing SCNA rate. Hereby, the aforementioned tipping point is accounted for not by elevated SCNA load alone, but by an inability of the tissue micro-environment (TME) to provide the necessary resources. Experiments are proposed in stomach and brain tumors—two cancer types whose TME can “aﬀord” vastly diﬀerent amounts of DNA. Our preliminary studies show that energetic costs of DNA content levels required for >75% SCNA load do not, in the absence of cytotoxic therapy, justify the masking benefits they bring. In particular, we showed that limiting dNTP concentrations amplify divergence in S-phase duration between high- and low-ploidy cells. Our hypothesis is that cytotoxic therapy causes a net-increase in fitness of tumors that exceed the SCNA tipping point. This hypothesis is founded on two unexpected recent findings: (i) integrated single-cell RNA- and DNA-sequencing analyses of stomach cancer cells suggests that the risk of cell death immediately after an SCNA event, rather than just SCNA rate, impacts clonal diversity. Aim 1 will integrate single cell sequencing with imaging and mathematical modeling of heterogeneous populations that evolve through chromosome missegregations, to examine observed SCNA landscapes and missegregation tolerances, and to predict effective cytotoxic therapy doses. (ii) Even minimal changes in DNA content among co-existing clones within the same Glioblastoma can result in significantly longer S-phases. Aim 2 will evaluate Oxygen, Phosphate and Glucose as rate-limiting substrates of dNTP synthesis of co-evolving subpopulations in stomach and brain tissue environments. This is the first study to investigate if and how clinical decisions can benefit from integrating a tumor environment’s energetic provision with the energetic demands of cancer cells’ genomic makeup.

概括传统的 I 期剂量探索策略基于以下假设，仅监测药物反应两周足以观察治疗如何影响超过 2-4 个同质群体的倍增时间但随着大多数癌症世代具有异质性的范式转变，迫切需要考虑我们之前提出的，治疗引起的人口构成变化会在更长的时间内显现出来。 “DNA损伤疗法敏感性的翻倒假说”，提出细胞毒疗法如果推动的话是有效的细胞的体细胞拷贝数改变（SCNA）负载高于共存的可变接近度。肿瘤细胞达到这个临界点意味着剂量反应关系不必是单调的。促使一个细胞凋亡，同时使另一个细胞急剧增殖。广泛使用的计算和数学方法，在肿瘤领域建立了研究项目新陈代谢，并在建模动态过程和整合各种组学和成像平台，我们的团队带来互补的专业知识来开发个性化的细胞毒性治疗策略我们将测试肿瘤细胞 DNA 含量和潜力。 dNTP 底物可用性可预测肿瘤对 SCNA 率增加的脆弱性。上述临界点不是仅由 SCNA 负载升高造成的，而是由组织的无力造成的微环境（TME）提供必要的资源，建议在胃和大脑中进行实验。肿瘤——我们的初步研究表明，这两种癌症类型的 TME 可以“提供”截然不同的 DNA 量。表明，在没有细胞毒性的情况下，> 75% SCNA 负载所需的 DNA 含量水平的能量消耗不会疗法，证明它们带来的掩蔽益处是合理的，特别是，我们证明了限制 dNTP 浓度。放大高倍性细胞和低倍性细胞之间 S 期持续时间的差异。我们的假设是细胞毒性。治疗导致肿瘤健康度的净增加超过 SCNA 临界点。基于最近两个意想不到的发现：（i）整合单细胞 RNA 和 DNA 测序分析胃癌细胞表明 SCNA 事件后细胞立即死亡的风险，而不仅仅是 SCNA 目标 1 将单细胞测序与成像和数学相结合。对通过染色体错误分离进化的异质种群进行建模，以检查观察到的 SCNA 景观和错误分离耐受性，并预测有效的细胞毒性治疗剂量 (ii) Even。同一胶质母细胞瘤内共存克隆之间 DNA 含量的微小变化可能会导致目标 2 将评估氧、磷酸盐和葡萄糖作为限速底物。胃和脑组织环境中共同进化亚群的 dNTP 合成这是第一项研究。研究临床决策是否以及如何受益于整合肿瘤环境的能量提供癌细胞基因组构成的能量需求。