Modelling breast cancer heterogeneity: Effects of stromal compartments on sub-clonal decision-making

乳腺癌异质性建模：基质区室对亚克隆决策的影响

• 批准号: 2289045
• 金额: --
• 依托单位: Imperial College London
• 依托单位国家: 英国
• 项目类别: Studentship
• 财政年份: 2019
• 资助国家: 英国
• 起止时间: 2019 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=studentship-2289045
• 关键词: Modelling; breast; cancer; heterogeneity; Effects

Significant progress has been made in the diagnosis and treatment of breast cancer (BC); however, tumour heterogeneity remains a considerable challenge in the design of effective therapies. The coexistence of subpopulations of cancer cells within one tumour with different genetic and phenotypic characteristic leads to negative treatment impact, ultimate recurrence risk and poor patient survival. Despite this identified impact on treatment efficacy the subject of cancer heterogeneity is often neglected. To this date, the implementation of the heterogeneity aspect into cancer studies is very limited due to the lack of adequate models or longitudinal data. So far, this issue is either tackled by analysing Patient-Derived Xenografts (PDXs) in mouse models or through application of computational biology for the reconstruction of cancer evolution and its heterogeneity from multiregional biopsies. BC mortality essentially results from metastases to distant sites and secondary tumours, which cellular and genetic profiles differ from the original tumour bulk data. Unfortunately, detailed longitudinal assessments of metastases composition are currently not available. Nevertheless, lately, the understanding of the importance of heterogeneity within the same tumour or between patients is steadily growing and is recognised to be a major factor in future diagnosis and treatment. In our laboratory, we currently are developing a spatio-temporal resolving in vitro 3D model for heterogeneity that we apply to understand the onset and progression of BC better. We are specifically interested in understanding the hierarchy of known and putative BC drivers in a multiclonal competing environment. Therefore, we develop a multigene-multifluorophore construct that allows us to induce specific cancer signatures and to trace different lineages in real-time. Our current model investigates a panel of 25 genes in different multigene-combinations which can be found in most BC cases independent of their molecular subtype. This panel covers genetic signatures of about 86% of all BC cases according to the cBioPortal data bank. Nevertheless, due to the constructs unique bio brick building system, the panel can easily be extended or exchanged. Having developed a model for BC heterogeneity and tumour evolution this study focuses on the interaction of the heterogeneous tumour mass with the microenvironment and the contribution of stromal cells, specifically endothelial cells, fibroblasts and resident or requited macrophages on tumour development and progression.We hypothesis that different sub-clonal populations will have specific and distinct interactions with each other and with the microenvironment itself depending on its composition. Relating to heterogeneity in BC the aim is to study the interaction of a multiclonal tumour in absence and presence of tumour microenvironment in vitro combining the RAFT system with a multiscale 3D model or in vivo using intravital imaging in mice. Ultimately, the study will 1) reveal the hierarchy of BC drivers and its possible variation depending on microenvironmental components; 2) consult existing computational heterogeneity and tumour progression models and develop one that captures this complex crosstalk; 3) analyse in vivo sub-clonal interactions with each other and with the microenvironment and later on sub-clonal preference for a secondary niche. Taking together, the study will test the hypothesis that sub-clonal variation in cellular profiles and behaviour in a heterogeneous tumour will lead to different survival and progression programmes and that these advantages in tumour development will change with the composition of the surrounding microenvironment.

乳腺癌（BC）的诊断和治疗取得了重大进展；然而，肿瘤异质性仍然是设计有效疗法的一个巨大挑战。一种肿瘤内具有不同遗传和表型特征的癌细胞亚群的共存会导致治疗的负面影响、最终的复发风险和患者生存率低下。尽管已确定对治疗效果有影响，但癌症异质性这一主题常常被忽视。迄今为止，由于缺乏足够的模型或纵向数据，异质性方面在癌症研究中的实施非常有限。到目前为止，这个问题要么通过分析小鼠模型中的患者来源异种移植物（PDX），要么通过应用计算生物学从多区域活检重建癌症进化及其异质性来解决。 BC 死亡率主要是由远处转移和继发性肿瘤引起的，其细胞和遗传特征与原始肿瘤批量数据不同。不幸的是，目前尚无法对转移瘤成分进行详细的纵向评估。然而，最近，人们对同一肿瘤内或患者之间异质性重要性的认识正在稳步增长，并被认为是未来诊断和治疗的主要因素。在我们的实验室中，我们目前正在开发一种异质性时空解析体外 3D 模型，用于更好地了解 BC 的发病和进展。我们特别感兴趣的是了解多克隆竞争环境中已知和假定的 BC 驱动程序的层次结构。因此，我们开发了一种多基因多荧光团构建体，使我们能够诱导特定的癌症特征并实时追踪不同的谱系。我们当前的模型研究了不同多基因组合中的一组 25 个基因，这些基因可以在大多数 BC 病例中找到，与其分子亚型无关。根据 cBioPortal 数据库，该小组涵盖了约 86% BC 病例的基因特征。尽管如此，由于构建了独特的生物砖建筑系统，面板可以轻松扩展或更换。开发了BC异质性和肿瘤进化的模型后，本研究重点关注异质肿瘤块与微环境的相互作用以及基质细胞，特别是内皮细胞、成纤维细胞和常驻或必需的巨噬细胞对肿瘤发生和进展的贡献。我们假设不同的亚克隆群体彼此之间以及与微环境本身具有特定且不同的相互作用 取决于它的成分。与 BC 的异质性相关，目的是结合 RAFT 系统与多尺度 3D 模型，在体外研究多克隆肿瘤在肿瘤微环境不存在和存在的情况下的相互作用，或使用小鼠活体成像在体内研究多克隆肿瘤的相互作用。最终，该研究将 1) 揭示 BC 驱动因素的层次结构及其根据微环境成分可能发生的变化； 2）参考现有的计算异质性和肿瘤进展模型，并开发一个捕获这种复杂串扰的模型； 3) 分析体内亚克隆彼此之间以及与微环境的相互作用，以及随后分析亚克隆对次要生态位的偏好。综上所述，该研究将检验以下假设：异质肿瘤中细胞特征和行为的亚克隆变异将导致不同的生存和进展程序，并且肿瘤发展中的这些优势将随着周围微环境的组成而变化。