Tracing the lineage histories and differentiation trajectories of individual cancer cells in myeloproliferative neoplasms

追踪骨髓增生性肿瘤中单个癌细胞的谱系历史和分化轨迹

• 批准号: 10327270
• 负责人: Sahand Hormoz
• 金额: $ 44.25万
• 依托单位: DANA-FARBER CANCER INST
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-01-15 至 2026-01-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10327270
• 关键词: Acute; Acute leukemia; Allogeneic Bone Marrow Transplantation; Animal Model; Atlases; Blood; Blood Cells; Bone Marrow; Bone marrow biopsy; CRISPR/Cas technology; Cell Communication; Cell Death; Cell Differentiation process; Cell division; Cells; Cessation of life; Cicatrix; DNA; Data; Development; Diagnosis; Disease; Disease Outcome; Disease Progression; Engineering; Erythrocytes; Event; Gene Expression; Genealogy; Genome; Genotype; Growth; Hematologic Neoplasms; Hematopoietic; Hematopoietic Neoplasms; Hematopoietic stem cells; Heritability; Heterogeneity; Human; In Situ; In Vitro; Individual; JAK2 gene; Malignant Neoplasms; Measurement; Measures; Microscopy; Molecular; Mothers; Mus; Mutate; Mutation; Myeloproliferative disease; Nature; Nucleotides; Patients; Pattern; Persons; Phenotype; Platelet Count measurement; Point Mutation; Population; Procedures; Process; Proliferating; Recording of previous events; Research; Resolution; Role; Series; Somatic Mutation; Symptoms; Technology; Testing; Therapeutic Studies; Time; Tissues; Trees; United States; cancer cell; cancer stem cell; disease phenotype; genome sequencing; individual patient; mouse model; patient population; patient subsets; progenitor; programs; stem cells; targeted treatment; therapeutic evaluation; time use; tool; transcriptome; transcriptomics; treatment strategy; tumor progression; whole genome

Project Summary In some cancers, intriguingly, the same mutation results in drastically different disease phenotypes in different patients. An example is a type of blood cancer, known as myeloproliferative neoplasm (MPN), where a single nucleotide change in the JAK2 gene, may result in either an increase in the number of red blood cells, an increase in the number of platelets, or scarring of bone marrow tissue, in different patients. The disease outcome is just as unpredictable. Some patients show no symptoms for decades whereas others rapidly progress to acute leukemias. This disconnect between genotype and phenotype may be due to the identity of the hematopoietic stem cell (HSC) in which the mutation first occurs. Not all HSCs are equivalent and some may preferentially give rise to certain types of blood cells. Additionally, the subsequent expansion of the population of mutated stem cells may be different in different patients. Therefore, to understand the heterogeneity in disease presentation, we would like to know when and in which cell the cancer mutation first occurred in each patient, how the population of mutated HSCs expanded, and to what extent the differentiation trajectory of the cancer cells deviates from that of the healthy cells. Here, we propose a comprehensive research program to make these measurements in individual MPN patients. To understand the difference between the cancer cells and the healthy cells in each patient, we will profile each cell individually. Bulk measurements average over the cancer cells and healthy cells, and obscure different cell states along the differentiation trajectory. We have recently developed a technology platform to simultaneously read out the full transcriptome and the cancer mutation in single cells. We will apply this platform to cells obtained from bone marrow biopsies of MPN patients. To obtain the history of the expansion of the cancer stem cells in each patient, we will reconstruct the lineage tree of the HSCs by sequencing the somatic mutations in the whole genomes of individual HSCs. Somatic mutations occur randomly at each cell division and are passed on to a cell’s descendants. Critically, we will also trace the differentiation trajectories of the progenies of each HSC by identifying the somatic mutations that uniquely mark each HSC in our single-cell transcriptomic data. Taken together, these measurements will provide the most detailed molecular picture of MPN at a single-cell resolution and the most comprehensive molecular history of cancer progression in individual patients. Finally, to identify and test potential therapies for MPN, we will engineer animal models whereby lineage histories of individual cells can be obtained without whole genome sequencing. We will engineer a mouse model of MPN in which individual cells record their lineage histories in their own DNA by using Cas9 to induce heritable mutations in synthetic target arrays that are transcribed and read out using sequencing. Our proposal will answer some of the most outstanding and fundamental questions about MPNs and blood development. Ultimately, our measurements should reveal patient-specific targeted therapies that preferentially eradicate the cancer stem cells or hinder their differentiation.

项目摘要 有趣的是，在某些癌症中，相同的突变在不同的癌症中导致截然不同的疾病表型。 患者一个例子是一种类型的血癌，称为骨髓增生性肿瘤（MPN），其中单一的骨髓增生性肿瘤（MPN）， JAK2基因中的核苷酸变化，可能导致红细胞数量增加， 血小板的数量，或者骨髓组织的疤痕，在不同的病人身上。疾病的结果只是 不可预测一些患者几十年没有症状，而另一些患者则迅速进展为急性 白血病基因型和表型之间的这种脱节可能是由于造血干细胞的同一性。 干细胞（HSC），其中突变首先发生。不是所有的HSC都是等价的，有些可能优先给予 生成特定类型的血细胞此外，随后的突变干细胞群体的扩大 细胞在不同的患者中可能不同。因此，为了了解疾病表现的异质性， 我们想知道癌症突变在每个患者中何时以及在哪个细胞中首次发生， 突变的HSC群体扩增，以及癌细胞的分化轨迹在多大程度上 与健康细胞不同。在这里，我们提出了一个全面的研究计划，使这些 在个别MPN患者中进行测量。为了了解癌细胞和癌细胞之间的区别， 每个病人体内的健康细胞，我们将单独分析每个细胞。癌症的整体测量平均值 细胞和健康细胞，并使沿着分化轨迹的不同细胞状态模糊。我们最近 开发了一个技术平台，可以同时读出完整转录组和癌症突变 单细胞我们将把这个平台应用于从MPN患者的骨髓活检中获得的细胞。获得 在每个患者中癌症干细胞扩增的历史，我们将重建肿瘤干细胞的谱系树。 通过对单个HSC的全基因组中的体细胞突变进行测序来鉴定HSC。发生体细胞突变 在每次细胞分裂时随机产生，并传递给细胞的后代。关键的是，我们还将追踪 通过鉴定独特标记HSC的体细胞突变， 我们的单细胞转录组数据中的每个HSC。综合起来，这些测量将提供最 MPN在单细胞分辨率下的详细分子图像和MPN最全面的分子历史 个别患者的癌症进展。最后，为了确定和测试MPN的潜在疗法，我们将设计 动物模型，无需全基因组测序即可获得单个细胞的谱系历史。 我们将设计一个MPN小鼠模型，其中单个细胞将其谱系历史记录在自己的DNA中 通过使用Cas9诱导合成靶阵列中的可遗传突变，所述合成靶阵列使用 测序我们的建议将回答一些关于MPN的最突出和最基本的问题 血液发育。最终，我们的测量应该揭示患者特异性靶向治疗， 优先根除癌症干细胞或阻碍其分化。