Single-Cell Sequencing of Breast Tumors to Investigate Genome Evolution

描述(申请人提供)：肿瘤内基因组的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长期以来一直在乳腺癌的细胞学研究中被观察到，并随着对肿瘤基因组的下一代测序研究而变得更加明显，这些研究显示，等位基因频率的混合与肿瘤细胞的单个克隆亚群不一致。尽管临床医生和研究人员清楚地意识到肿瘤的异质性，但癌症的这一特征往往被忽视，因为它使肿瘤的诊断和治疗变得复杂，而且没有研究它的工具。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，该方法可以通过分析单个肿瘤细胞的基因组拷贝数来完全解决肿瘤的异质性。使用这项技术，我们将检验我们的中心假设，即肿瘤的进化可以从基因组的异质性中重建出来。假设突变的复杂性随着时间的推移而增加，我们可以比较单个细胞的拷贝数分布来推断进展的谱系。我们的理论基础是，尽管非整倍体在人类肿瘤中的报道由来已久，但对基因组如何在原发肿瘤生长过程中进化这些复杂的重排知之甚少。这项应用的目的是利用单细胞测序来描绘三阴性(ER-、PR-、Her2-)乳腺肿瘤的克隆性亚结构，并推断原发肿瘤生长不同阶段的基因组进化。在目标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，还是以间断的突发性进化发生的。在AIM2中，我们将确定侵袭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。在目标3中，我们将研究乳腺肿瘤间质，以了解非整倍体是如何从正常的二倍体基因组进化而来的。我们的单细胞测序方法是创新的，因为它可以解析复杂的细胞群体，而标准的批量基因组方法仅限于报告平均信号，无法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肿瘤生长过程中进化复杂的重排。我们的长期目标是使用单细胞测序方法来研究人类肿瘤中不同分子时钟的进化，包括拷贝数异常、结构变异、插入和点突变，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房组织上进行的。建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也将对癌症以外的人类疾病产生积极影响，包括神经疾病、免疫性疾病、胚胎缺陷和改善植入前遗传诊断。

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.