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

基本信息

批准号：
10550185
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
项目类别：
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/10550185
关键词：
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 division Cells Cessation of life Cicatrix DNA Data Development Diagnosis Disease Disease Outcome Disease Progression Dissociation Engineering Erythrocytes Event Gene Expression Genealogy Genetic Transcription 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 Testing Therapeutic Studies Time Tissues Trees United States cancer cell cancer stem cell disease phenotype genome sequencing hematopoietic stem cell expansion individual patient mouse model overpopulation patient subsets programs stem cells targeted treatment technology platform therapeutic evaluation tool transcriptome transcriptomics treatment strategy tumor progression whole genome

项目摘要

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.

项目概要有趣的是，在某些癌症中，相同的突变会导致不同的疾病表型显着不同。一个例子是一种称为骨髓增生性肿瘤 (MPN) 的血癌，其中有一个单一的癌症。 JAK2 基因中的核苷酸变化可能导致红细胞数量增加、不同患者的血小板数量或骨髓组织的疤痕程度不同，疾病的结果也不同。一些患者数十年没有表现出任何症状，而另一些患者则迅速发展为急性症状。白血病的基因型和表型之间的脱节可能是由于造血系统的特性造成的。首先发生突变的干细胞 (HSC) 并非所有 HSC 都是相同的，有些可能会优先发生突变。此外，还产生某些类型的血细胞，随后导致突变干细胞群体的扩张。不同患者的细胞可能不同，因此，要了解疾病表现的异质性，我们想知道每位患者的癌症突变首次发生在何时、在哪个细胞中，是如何发生的？突变的HSCs数量扩大了，癌细胞的分化轨迹达到了何种程度与健康细胞不同，我们提出了一个全面的研究计划来制造这些细胞。对个别 MPN 患者进行测量以了解癌细胞和癌细胞之间的差异。对于每位患者的健康细胞，我们将单独分析癌症中每个细胞的批量测量平均值。细胞和健康细胞，并模糊了分化轨迹上的不同细胞状态。开发了一个技术平台，可以同时读出完整的转录组和癌症突变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。每个患者体内癌症干细胞的扩增历史，我们将重建其谱系树通过对单个 HSC 的整个基因组中的体细胞突变进行测序来检测 HSC 发生的体细胞突变。随机地在每次细胞分裂中传递给细胞的后代。至关重要的是，我们还将追踪。通过识别独特标记的体细胞突变，确定每个 HSC 后代的分化轨迹综合起来，这些测量将提供最多的单细胞转录组数据。单细胞分辨率下 MPN 的详细分子图像以及最全面的分子历史最后，为了识别和测试 MPN 的潜在疗法，我们将设计。动物模型，从而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，其中单个细胞在自己的 DNA 中记录其谱系历史通过使用 Cas9 在合成靶阵列中诱导可遗传突变，并使用该阵列进行转录和读出我们的提案将回答有关 MPN 的一些最突出和基本的问题。最终，我们的测量应该揭示针对患者的针对性治疗。优先消灭癌症干细胞或阻碍其分化。