Recording the natural history of cancer progression using a Crainbow model of HER2+ cancer

使用 HER2 癌症的 Crainbow 模型记录癌症进展的自然史

• 批准号: 10437462
• 负责人: Jose Javier Bravo-Cordero
• 金额: $ 9.98万
• 依托单位: ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-05-27 至 2024-03-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10437462
• 关键词: Award; Behavior; Biological Models; Blood Vessels; Breast; Cells; Data; Detection; Diagnosis; Disease; ERBB2 gene; Early Diagnosis; Extracellular Matrix; Fostering; Funding; Future; Homeostasis; Image; Imaging Techniques; Immune; Immune system; Indolent; Lesion; Malignant Neoplasms; Mammary Neoplasms; Mammary gland; Methodology; Methods; Modeling; Molecular; Monitor; Mus; Myoepithelial cell; Natural History; Neoplasm Metastasis; Neoplasms; Normal tissue morphology; Oncogenes; Operative Surgical Procedures; Outcome; Phase; Population; Primary Neoplasm; Protein Isoforms; Research Design; Research Infrastructure; Research Personnel; Resolution; Role; Rosaniline Dyes; Screening for cancer; Side; Somatic Mutation; Stream; Surgical Oncologist; Time; Training; base; breast cancer progression; breast cancer survival; cancer cell; cancer invasiveness; cell behavior; cell motility; clinically relevant; experimental study; imaging modality; in vivo; innovation; intravital imaging; intravital microscopy; macrophage; malignant breast neoplasm; migration; mouse model; multiphoton imaging; novel; premalignant; public health relevance; serial imaging; tumor; tumor growth; tumor microenvironment; tumor progression

PROJECT SUMMARY/ABSTRACT Background: The step-wise accumulation of somatic mutations and progressive changes to cell behavior provides a rationale for the cancer screening era. However, this fails to explain de novo diagnosis of lethal metastatic disease in the apparent absence of screen detectable precancerous lesions. Accumulating evidence suggests that invasive cancers may initiate without a prolonged and detectable precancerous phase. In addition, proliferative lesions do not deterministically progress, suggesting that many early cancers are overtreated. Although a dramatic increase in early-detection has been observed, a similar dramatic decrease in lethal metastatic disease has not been observed. Some have even argued that many screen-detected early lesions spontaneously resolve or regress. In contrast, the most lethal cancers escape detection and metastasize prior to detection. Hypothesis: We hypothesize that cancer progression, like normal tissue homeostasis, is stochastic and subject to defined spatial and microenvironmental constraints. Specific Aims: Aim 1. To define the homeostatic principles underlying the progression of breast cancer in a mouse model of HER2+ breast cancer. Aim 2. To dissect the role of HER2 isoforms on the metastatic cascade of breast tumors. Study design/Methods: Here we will use a proven cancer rainbow modeling system for visualizing and analyzing tumor growth rates in vivo. State-of-the-art multiphoton live imaging will be used to image and quantify tumor progression potential in space and time within the mammary gland along with microenvironmental features (ECM, macrophages, blood vessels). Longitudinal imaging over eight weeks will capture the rates of tumor progression and the origin of invasive breast cancers in an in vivo and immune intact mouse model. Relevance: More than six decades ago, surgical oncologists seeking to explain why earlier surgical intervention had not improved breast cancer survival, postulated that adaptations between the tumor and host set the trajectory of an invasive cancer many years before diagnosis. Proponents argued that the formative early years of tumor-TME adaptation had already destined some tumors to become invasive and lethal. In addition, many breast cancer lesions may actually regress suggesting that cancer progression may be stochastic. Novel imaging modalities and sophisticated tumor lineage training strategies are needed to solve this challenging problem. Our experiments utilizing mouse models and high-resolution longitudinal imaging during the course of tumor progression will determine whether cancer progression is deterministic or not, adding an important value towards understanding breast cancer progression.

项目摘要/摘要 背景：体细胞突变的逐步积累和细胞行为的渐进变化 为癌症筛查时代提供了理由。但是，这无法解释致命的从头诊断 转移性疾病在明显没有可检测到的癌前病变的情况下。积累证据 表明侵入性癌症可能在没有延长且可检测到的癌前阶段的情况下开始。此外， 增殖性病变并不确定性地进展，表明许多早期癌症过度处理。 尽管已经观察到早期检测的急剧增加，但致命的急剧下降类似 尚未观察到转移性疾病。有些人甚至认为许多筛查的早期病变 自发解决或退缩。相反，最致命的癌症逃脱了检测并转移 检测。 假设：我们假设癌症的进展，例如正常组织稳态，是随机的，受试者 定义的空间和微环境约束。 具体目的：目标1。定义乳腺癌进展的基础稳态原理 HER2+乳腺癌的小鼠模型。目标2。剖析HER2同工型在转移级联反应中的作用 乳腺肿瘤。 研究设计/方法：在这里，我们将使用经过验证的癌症彩虹建模系统可视化和 分析体内肿瘤生长速率。最先进的多光子实时成像将用于图像和量化 乳腺内空间和时间的肿瘤进展潜力以及微环境特征 （ECM，巨噬细胞，血管）。在八周内进行纵向成像将捕获肿瘤的发生率 在体内和免疫完整小鼠模型中的进展和侵入性乳腺癌的起源。 相关性：超过六十年前的手术肿瘤学家试图解释为什么早期手术干预 尚未改善乳腺癌的生存，假设肿瘤和宿主之间的适应 诊断前多年的侵入性癌症的轨迹。支持者辩称，成长的早期 肿瘤-TME的适应性已经注定了一些肿瘤，使其侵入性和致命性。此外，许多 乳腺癌病变实际上可能会退缩，这表明癌症的进展可能是随机的。小说成像 需要形态和复杂的肿瘤谱系训练策略来解决这个具有挑战性的问题。我们的 在肿瘤过程中利用小鼠模型和高分辨率纵向成像的实验 进展将确定癌症进展是否确定性，增加了重要的价值 了解乳腺癌的进展。