Frequency and consequences of chromosome missegregation in breast cancer

乳腺癌染色体错误分离的频率和后果

• 批准号: 10362558
• 负责人: Andrew Lynch
• 金额: $ 3.38万
• 依托单位: UNIVERSITY OF WISCONSIN-MADISON
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-03-01 至 2023-02-28
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10362558
• 关键词: Abnormal Cell; Acute; Address; Aneuploidy; Biological; Biological Assay; Breast Cancer Patient; Breast Cancer cell line; Cancer Biology; Cell Death; Cell Line; Cell division; Cell model; Cell physiology; Cells; Cellular biology; Chemicals; Chromosomal Instability; Chromosomal Rearrangement; Chromosome Segregation; Chromosomes; Clinical; Communication; Communities; Complex; Computer Models; Core Biopsy; Cytogenetics; DNA sequencing; Data; Evolution; Frequencies; Gene Expression Profile; Generations; Genetic Models; Genetic Transcription; Genomics; Goals; Harvest; Heterogeneity; Human; Incidence; Institution; Karyotype; Karyotype determination procedure; Knowledge; Malignant Neoplasms; Mammalian Cell; Mammary Neoplasms; Measures; Methods; Microscopic; Modeling; Mutation; Organoids; Outcome; Paclitaxel; Patients; Pattern; Positioning Attribute; Process; Prognostic Marker; Recording of previous events; Research; Research Personnel; Research Project Summaries; Resolution; Role; Solid Neoplasm; Tetracyclines; Time; Tissues; Training; Transcription Alteration; Transcription Process; Work; Yeasts; analytical method; biological adaptation to stress; breast cancer progression; cancer genomics; cancer therapy; career; chemotherapy; chromosome loss; chromosome missegregation; clinically significant; computer framework; design; experience; genome sequencing; improved; innovation; insight; malignant breast neoplasm; member; multidisciplinary; multimodality; patient prognosis; patient response; pressure; programs; response; single cell sequencing; skills; taxane; transcriptome sequencing; transcriptomics; tumor; tumor heterogeneity

PROJECT SUMMARY Research. Chromosomal instability (CIN) – observed as the first cancer hallmark over 100 years ago – is characterized by the persistent loss and gain of whole chromosomes through abnormal cell division. This process results in aneuploidy, the state of having an incorrect number of chromosomes, which is present in over 70% of solid tumors, some of which display recurring patterns of aneuploidy. Persistent ‘missegregation’ of chromosomes is associated with worse patient prognosis and advanced clinical features. This is attributed to the increased adaptability of a tumor having increased genomic diversity via a broad landscape of different aneuploid clones. At higher rates of missegregation it appears to cause cell death and tumor inhibition. The occurrence of CIN is also theorized to sensitize tumors to CIN-inducing chemotherapies like taxanes. Despite CIN’s long history, its clinical use as a prognostic marker and biomarker for taxane efficacy is inaccessible as current methods of quantifying rates of chromosome missegregation are either infeasible in tissue, insufficiently informative and/or labor intensive. A critical goal for this proposal to combine stochastic computational modeling of cell division with single cell sequencing of tumors in order to allow for the quantification of intratumoral rates of chromosome missegregation. Additionally, cellular processes after chromosome missegregation that underlie karyotypic selection have not been explored. We hypothesize that post- missegregation transcriptional processes either preclude or permit the propagation of clones with specific aneuploid chromosome combinations. We will stochastically generate many combinations of chromosome copy number alterations in transformed and non-transformed cell lines and analyze the acute transcriptional alterations and clonal composition at single cell resolution. Overall, the long-term goal for this proposal is to resolve the complex relationship between chromosome missegregation and breast cancer progression with respect to its incidence in human breast tumors and downstream transcriptional consequences that underlie tumor evolution. This work is innovative in its approach and will significantly improve our understanding of tumor evolution and how to evaluate CIN in patients. Training. Through completion of the proposed research, I will develop my skills in the design and implementation of high impact and rigorous scientific studies. Through coursework and interactions with lab members and collaborators, I will develop multi-disciplinary expertise in cell biological and genomics/transcriptomics experimental and analytical methods. I will hone professional skills in scientific communication, public engagement, and networking through the many opportunities afforded to me to interact with and present my research to collaborators, field-experts, legislators, and community members. The unique, multi-disciplinary training proposed here will position me well for a career as an independent investigator in the field of cancer genomics at an academic or federal research institution.

项目摘要 研究。染色体不稳定性（CIN） - 100年前被视为第一个癌症标志 - 是 以异常细胞分裂的持续损失和整个染色体的增益为特征。这个过程 导致非整倍性，其染色体数量不正确，该状态存在于70％以上 实体瘤，其中一些显示了非整倍性的经常性模式。持续的“错误分析” 染色体与患者预后和晚期临床特征有关。这归因于 通过不同非整倍体的广阔景观增加了基因组多样性增加的肿瘤的适应性 克隆。在较高的错误分析率下，它似乎会导致细胞死亡和肿瘤抑制作用。出现 CIN还被认为是将肿瘤感知到诸如紫杉烷等化学疗法的肿瘤。尽管Cin很长 历史，其作为预后标志物的临床用途和紫杉烷效率的生物标志物是无法访问的 量化染色体错误分析速率的方法在组织中是不可行的，不足 信息丰富和/或劳动密集型。该提案结合随机计算的关键目标 用肿瘤的单细胞测序对细胞分裂进行建模，以便允许数量 染色体错误分析的肿瘤内率。另外，染色体后的细胞过程 尚未探索核型选择基础的错误分析。我们假设这是 错误陈述转录过程要么排除或允许克隆传播 特定的非整倍体染色体组合。我们将随机生成许多组合 转化和未转化的细胞系中的染色体拷贝数变化，并分析急性 单细胞分辨率下的转录改变和克隆组成。总体而言，这是长期目标 提案是解决染色体错误分析与乳腺癌之间的复杂关系 在人类乳腺肿瘤和下游转录的发生率方面的进展 肿瘤进化的后果。这项工作的方法是创新的，将大大 提高我们对肿瘤进化的理解以及如何评估患者的CIN。 训练。通过完成拟议的研究，我将在设计和实施方面发展自己的技能 高影响力和严格的科学研究。通过课程和与实验室成员的互动以及 合作者，我将在细胞生物学和基因组学/转录组学方面发展多学科专业知识 实验和分析方法。我将在科学沟通，公众方面获得专业技能 参与度，并通过许多机会与我互动并介绍我 对合作者，现场专家，立法者和社区成员的研究。独特的多学科 在这里提出的培训将使我在职业生涯中成为一个独立研究者的职业 学术或联邦研究机构的癌症基因组学。