Project 1:Evolutionary dynamics and drivers of breast cancer metastasis and relapse

摘要/项目摘要 虽然早期乳腺癌(BC)的预后已显著改善，但20%-30%的患者在 并最终死于疾病。到目前为止，BC复发的空间和时间模式 一直很难预测。此外，转移潜能何时以及如何确定在很大程度上是个未知数。 未知。为了解决这些问题，我们开发了空间计算和数学模型 肿瘤进展，以推断转移播种的“时间”。这些技术在配对小学中的应用 有匹配转移的乳腺癌，为早期转移种子提供了定量证据，通常为2- 4年后可检测到原发病变(NAT Gen 2020)，与实验和临床数据一致 这表明BC细胞可以早期传播并持续存在。 同时，我们定义了11个综合集群(IC)的复发率和复发率 对2,000例早期BCS进行分析，并进行长期随访(METABRIC队列：自然2019年；2012年)。这些 包括两个具有不同复发轨迹三重阴性BC亚群和四个ER+/HER2-IC(1、2、6和 9)确诊后长达20年的高复发风险。总体而言，这些高风险 亚组占所有ER+/HER2-肿瘤的26%，大多数BC复发。复制的模式 这些高危IC中的数量扩增(CNA)和过度表达与HER2+BC的回声相同 藏有可下药的克隆基因组驱动因素。这一突破性的发现导致了生物标记物驱动的临床 对早期高危BC患者进行新靶向治疗的试验评估。然而，最终的驱动因素和 这些亚组的进展机制尚未确定。此外，局部组织是如何 微环境(TME)在不同的IC中变化，有助于免疫抑制、传播、 休眠和复发是未知的 我们假设高危IC的致癌驱动因素通过以下方式驱动肿瘤进展和复发 决定免疫环境和重塑细胞表面糖蛋白质组，增强耐受性细胞状态- 在与Michael Angelo和Michael合作的项目2和3中进行了进一步的功能评估 巴西克。此外，我们假设这些扩增产物具有内在的内分泌抵抗，从而有必要 新的治疗策略。我们在以下具体目标中测试这些假设：目标1-描述 在纵向BC队列中的TME，并评估IC、糖基转移酶表达、 治疗反应和复发。目的2-量化BC复发的动态和对临床的反应 跨IC的治疗。目的3-测定克隆动力学并确定靶向抗性的机制 以及来自原发和转移病变的高危ER+BC患者衍生的有机类物质的内分泌治疗。

Abstract/Project Summary While prognosis for early stage breast cancer (BC) has improved dramatically, 20-30% of patients recur at distant sites and ultimately succumb to their disease. To date, the spatial and temporal patterns of BC relapse have been difficult to predict. Moreover, when and how metastatic potential is determined is largely unknown. To address these questions, we have developed spatial computational and mathematical models of tumor progression to infer the ‘time’ of metastatic seeding. Application of these techniques to paired primary breast cancers with matched metastases, yielded quantitative evidence for early metastatic seeding, often 2- 4 years before the primary lesion is detectable (Nat Gen 2020), consistent with experimental and clinical data indicating that BC cells can disseminate early and persist. In parallel, we defined the rates and routes of relapse across 11 Integrative Clusters (ICs) in an analysis of 2,000 early-stage BCs with long-term follow-up (METABRIC cohort: Nature 2019; 2012). These include two triple negative BC subgroups with distinct relapse trajectories and four ER+/HER2- ICs (1, 2, 6 and 9) with high and persistent risk of relapse up to 20 years after diagnosis. Collectively, these high-risk subgroups account for 26% of all ER+/HER2- tumors and the majority of BC relapses. The pattern of copy number amplification (CNA) and overexpression in these high-risk ICs echoes that seen for HER2+ BC, each harboring druggable clonal genomic drivers. This breakthrough discovery led to a biomarker-driven clinical trial evaluating new targeted therapies in early-stage high-risk BC patients. However, the definitive drivers and mechanisms of progression in these subgroups have yet to be characterized. Moreover, how the local tissue microenvironment (TME) varies across the ICs and contributes to immune suppression, dissemination, dormancy and relapse is unknown We hypothesize that the oncogenic drivers of the high-risk ICs drive tumor progression and relapse by dictating immune contexture and remodeling the cell surface glycoproteome, potentiating tolerogenic cell states– as further functionally evaluated in Projects 2 and 3 in collaboration with Michael Angelo and Michael Bassik. Additionally, we hypothesize that these amplicons confer intrinsic endocrine resistance, necessitating new therapeutic strategies. We test these hypotheses in the following Specific Aims: Aim 1- Characterizes the TME in longitudinal BC cohorts and evaluate the association between IC, glycosyltransferase expression, response to therapy and relapse. Aim 2 - Quantifies the dynamics of BC relapse and the response to clinical therapies across the ICs. Aim 3 - Measures clonal dynamics and identify mechanisms of resistance to targeted and endocrine therapies in high-risk ER+ BC patient-derived organoids from primary and metastatic lesions.