Single-Cell Methods for Analysis of Clonal Heterogeneity and Evolution in Cancer

用于分析癌症克隆异质性和进化的单细胞方法

基本信息

批准号：
8655834
负责人：
Jerald Patrick Radich
金额：
$ 57.38万
依托单位：
FRED HUTCHINSON CANCER RESEARCH CENTER
依托单位国家：
美国
项目类别：
财政年份：
2013
资助国家：
美国
起止时间：
2013-05-01 至 2018-04-30
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/8655834
关键词：
Abnormal Cell Acute Myelocytic Leukemia Address Age Basic Science Biological Biological Assay Blood Cancer Biology Cell Differentiation process Cell Proliferation Cell physiology Cells Chronic Myeloid Leukemia Clinical Clinical Research Clonal Evolution Clonality Clone Cells Complex Computer Analysis Data Development Diagnosis Diagnostic Discipline Disease Disease remission Dysmyelopoietic Syndromes Dysplasia ERBB2 gene Event Evolution Gene Expression Genetic Genetic Marker Expression Genetic Markers Hematopoietic Hematopoietic System Hematopoietic stem cells Heterogeneity Imatinib Individual Malignant - descriptor Malignant Neoplasms Measures Methods Microfluidics Minority Modeling Molecular Molecular Biology Monitor Myeloproliferative disease Neoplasms Normal Cell Normal tissue morphology Patients Pattern Phenotype RNA Splicing Refractory Relapse Resistance Risk Roche brand of trastuzumab Role Sampling Staging Stem cells Stratification Structure Sum Techniques Therapeutic Tretinoin Tumor Tissue Validation Variant Work bcr-abl Fusion Proteins cancer cell cancer initiation cancer therapy cancer type chemotherapeutic agent chemotherapy computer framework computerized tools cost cost effective design leukemia malignant breast neoplasm neoplastic normal aging novel public health relevance response single cell analysis stem therapy resistant tool tumor tumorigenesis

项目摘要

DESCRIPTION (provided by applicant): Biological differences between healthy and disease states are the sum of contributions between physiologically normal and abnormal cells. Recent data suggests that intra-tumor cellular differences may be key to understanding the varied responses to therapy between patients. A major limitation in our ability to effectively treat cance is the innate variability of the response to therapy between patients, i.e., predicting those who will relapse/be refractory and those who will achieve remission for a given therapy. The development of robust and rapid assays of intercellular heterogeneity is thus essential for our understanding of both normal and abnormal biology and how cancer phenotypes develop and evolve during therapy. In this proposal we will refine robust methods to assay and quantify cellular heterogeneity using the model of the hematopoietic system. We will compare the heterogeneity in normal stem and progenitor cells to that seen in acute myeloid leukemia (AML), a leukemia that derives from normal hematopoietic stem cells and in myelodysplastic syndrome (MDS), a myeloid malignancy that can progress to AML. To do so, we will 1) Develop robust single-cell assays and analysis methods. We will expand our current single cell molecular biology methods to accurately measure and quantify heterogeneity in genetics and gene expression of single cells. Statistical, and technological validation of these assays will be performed alongside development of computational tools to handle and compare single-cell genetic data. 2) Measure clonal variation in normal and malignant hematopoietic cells. We will assess cell-to-cell heterogeneity in normal and malignant hematopoietic stem and progenitor cells to tease apart what combinations of alterations represent neoplastic "hits" and what are neutral changes. By comparing the patterns of heterogeneity seen in MDS to that in AML will allow us to identify features common in myeloid malignancies, and those that are disease-specific and those related to relapse after therapy. 3) Design high-throughput microfluidic methods to capture and interrogate single cells. Current macroscale methods for single-cell analysis are by definition limited by scale, and thus cost and sample handling challenges, whereas these bottlenecks can be remedied via microscale methods. We will design and implement a microfluidic platform that will capture single cells, and efficiently quantify genetic markers and expression levels, making further single cell of analyses on additional AML and MDS clinical samples realistic, rapid and cost-effective. The implications of current therapeutic strategies for cancer treatment with respect to clonal evolution are substantial and broadly applicable to many cancer types. Understanding the clonal structure within a tumor and its change with chemotherapy would allow us to 1) develop diagnostics to quickly quantify clones at diagnosis and during therapy and 2) apply adaptive therapies responsive to clonal evolution. The development of the molecular tools required is a crucial first step to understanding the role of clonal evolution in cancer.

描述（由申请人提供）：健康和疾病状态之间的生物学差异是生理上正常和异常细胞之间的贡献之和。最近的数据表明，肿瘤内细胞差异可能是了解患者对治疗的各种反应的关键。我们有效治疗CANCE的能力的一个主要局限性是患者对治疗反应的先天变异性，即预测那些将复发/难治性的人和那些将为给定治疗而缓解的人。因此，鲁棒和快速测定的细胞间异质性的发展对于我们对正常和异常生物学的理解以及癌症表型在治疗过程中的发展和演变至关重要。在此提案中，我们将使用造血系统模型来完善强大的方法来测定和量化细胞异质性。我们将比较正常茎和祖细胞中的异质性与急性髓样白血病（AML）中的异质性，这是一种从正常造血干细胞和脊髓增生性综合征（MDS）的白血病，一种可能发展为AML的髓样恶性肿瘤。为此，我们将1）开发强大的单细胞测定和分析方法。我们将扩展当前的单细胞分子生物学方法，以准确测量和量化单细胞的遗传学和基因表达中的异质性。这些测定法的统计和技术验证将与开发计算工具一起处理和比较单细胞遗传数据。 2）测量正常和恶性造血细胞的克隆变异。我们将评估正常和恶性造血茎和祖细胞中细胞对细胞异质性，以分开改变的变化组合代表肿瘤的“命中”，哪些是中性变化。通过比较MD中看到的异质性模式与AML中的异质性模式将使我们能够识别髓样恶性肿瘤中常见的特征，以及疾病特异性的特征，以及与治疗后复发有关的特征。 3）设计高通量微流体方法来捕获和询问单细胞。当前用于单细胞分析的宏观方法在定义上受到规模限制，因此成本和样本处理挑战，而这些瓶颈可以通过微观方法来补救。我们将设计和实施一个微流体平台，该平台将捕获单个细胞，并有效地量化遗传标记和表达水平，从而在其他AML和MDS临床样本上进一步进行分析的单个单元，真实，快速且具有成本效益。当前的治疗策略在克隆进化方面对癌症治疗的影响是很大的，并且广泛适用于许多癌症类型。了解肿瘤内的克隆结构及其对化学疗法的变化将使我们到1）开发诊断，以在诊断和治疗期间快速量化克隆，以及2）应用对克隆进化有效的自适应疗法。所需分子工具的发展是了解克隆进化在癌症中的作用的关键第一步。