Single-Cell Sequencing of Breast Tumors to Investigate Genome Evolution

描述（申请人提供）：肿瘤内的基因组异质性是困扰乳腺癌临床诊断和基础研究的主要因素之一。癌症的这一显著特征早已在乳腺癌的细胞学研究中被观察到，并且随着肿瘤基因组的下一代测序研究变得越来越清楚，这些研究表明，等位基因频率的混合与肿瘤细胞的单克隆亚群不一致。尽管临床医生和研究人员清楚地意识到肿瘤的异质性，但这一癌症的标志往往被忽视，因为它使肿瘤的诊断和治疗复杂化，而且因为没有工具来研究它。在这项资助中，我们建议开发和应用一种创新的单细胞测序方法，通过分析单个肿瘤细胞的基因组拷贝数来完全解决肿瘤异质性。利用这项技术，我们将检验我们的中心假设，即肿瘤进化可以从基因组异质性中重建。假设突变复杂性随着时间的推移而增加，我们可以比较单细胞的拷贝数概况来推断进展的谱系。我们的基本原理是，虽然非整倍体在人类肿瘤中早就有报道，但对于原发性肿瘤生长过程中基因组如何进化这些复杂的重排知之甚少。本应用程序的目的是使用单细胞测序来描绘三阴性（ER-, PR-, Her2-）乳腺肿瘤的克隆亚结构，并推断原发肿瘤生长不同阶段的基因组进化。在目的1中，我们将研究晚期乳腺肿瘤的拷贝数进化，以确定重排是逐渐发生的还是在进化的间歇爆发中发生的。在目的2中，我们将确定浸润性亚群是直接来自早期乳腺癌的原位亚群，还是它们是独立进化的细胞亚群。在目的3中，我们将研究乳腺肿瘤基质，以了解非整倍体如何从正常的二倍体基因组进化而来。我们的单细胞测序方法是创新的，因为它可以解决复杂的细胞群体，而标准的批量基因组方法仅限于报告平均信号，不能检测罕见的肿瘤克隆。这项研究意义重大，因为实现这些目标将提高我们对人类乳腺癌克隆多样性的基本理解，以及非整倍体基因组如何在原发性肿瘤生长过程中进化出复杂的重排。我们的长期目标是利用单细胞测序方法研究人类肿瘤中不同分子钟的进化，包括拷贝数畸变、结构变异、索引和点突变，以了解肿瘤是如何进化的。我们的发现与人类癌症直接相关，因为我们所有的实验都是在人类乳腺组织上进行的。拟议的研究目标与美国国立卫生研究院降低乳腺癌死亡率的使命直接一致。开发这些强大的单细胞测序工具还将对癌症以外的人类疾病产生积极影响，包括神经系统疾病、免疫疾病、胚胎缺陷和改善植入前遗传学诊断。

DESCRIPTION (provided by applicant): One of the major factors confounding both the clinical diagnosis and basic research of breast cancer is the genomic heterogeneity within tumors. This salient feature of cancer has long been observed in cytological studies of breast cancer and is becoming ever-more clear with next-generation sequencing studies of tumor genomes, which show mixtures of allele frequencies that are inconsistent with single clonal subpopulations of tumor cells. Although clinicians and researchers are starkly aware of tumor heterogeneity, this hallmark of cancer is often ignored because it complicates both the diagnosis and treatment of tumors, and because tools do not exist to study it. In this grant we propose to develop and apply an innovative single-cell sequencing method that can fully resolve tumor heterogeneity by profiling genomic copy number in individual tumor cells. Using this technology we will test our central hypothesis that tumor evolution can be reconstructed from genomic heterogeneity. Assuming that mutational complexity increases with time, we can compare copy number profiles of single cells to infer lineages of progression. Our rationale is that while aneuploidy has long been reported in human tumors, very little is known about how genomes evolve these complex rearrangements during primary tumor growth. The objective of this application is to use single cell-sequencing to delineate the clonal substructure of triple-negative (ER-, PR-, Her2-) breast tumors and infer genomic evolution at different stages of primary tumor growth. In aim 1 we will investigate copy number evolution in advanced breast tumors to determine if rearrangements occur gradually or in punctuated bursts of evolution. In aim2 we will determine if invasive subpopulations emerge directly from in situ subpopulations in early stage breast cancers, or alternatively if they are independently evolving subpopulations of cells. In aim3 we will study breast tumor stroma to understand how aneuploidy evolves from normal diploid genomes. Our single- cell sequencing approach is innovative because it can resolve complex populations of cells, while standard bulk genomic methods are limited to reporting an average signal and cannot detect rare tumor clones. This research is significant because achieving these aims will improve our fundamental understanding of clonal diversity in human breast cancer and how aneuploid genomes evolve complex rearrangements during primary tumor growth. Our long-term goal is to use single-cell sequencing methods to study the evolution of different molecular clocks in human tumors, including copy number aberrations, structural variation, indels and point mutations to understand how tumors evolve. Our findings are directly relevant to human cancer, because we conduct all of our experiments on human breast tissues. The proposed research aims are directly aligned with the mission of NIH to reduce mortality in breast cancer. Developing these powerful single-cell sequencing tools will also have a positive impact on human diseases beyond cancer, including neurological disorders, immunological diseases, embryonic defects and improving preimplantation genetic diagnosis.