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: 10630320
• 负责人: Jose Javier Bravo-Cordero
• 金额: $ 8.26万
• 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/10630320
• 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; Invaded; Lesion; Macrophage; 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; Shapes; Side; Somatic Mutation; Stream; Surgical Oncologist; Time; Training; Visualization; breast cancer progression; breast cancer survival; cancer cell; cancer invasiveness; cell behavior; cell motility; clinically relevant; experimental study; imaging modality; in vivo; innovation; intercalation; intravital imaging; intravital microscopy; malignant breast neoplasm; migration; mouse model; multi-photon; 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.

项目概要/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。然而，这无法解释致命的从头诊断 明显缺乏筛查可检测到的癌前病变的转移性疾病。积累证据 表明侵袭性癌症可能在没有延长且可检测的癌前阶段的情况下开始。此外， 增殖性病变并没有确定性进展，这表明许多早期癌症被过度治疗。 尽管早期发现率显着增加，但致死率也有类似的显着下降。 尚未观察到转移性疾病。有些人甚至认为许多筛查发现的早期病变 自发解决或消退。相比之下，最致命的癌症会逃避检测并事先转移 来检测。 假设：我们假设癌症进展与正常组织稳态一样，是随机的且受制于 明确的空间和微环境限制。 具体目标： 目标 1. 定义乳腺癌进展的稳态原则 HER2+乳腺癌小鼠模型。目标 2. 剖析 HER2 同工型在转移级联中的作用 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来可视化和 分析体内肿瘤生长速率。最先进的多光子实时成像将用于成像和量化 乳腺内肿瘤在空间和时间上的进展潜力以及微环境特征 （ECM、巨噬细胞、血管）。八周内的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侵袭性乳腺癌的进展和起源。 相关性：六十多年前，外科肿瘤学家试图解释为什么要早期进行手术干预 并没有改善乳腺癌的生存率，假设肿瘤和宿主之间的适应设定了 诊断前许多年的浸润性癌症的轨迹。支持者认为，早年的性格形成 肿瘤-TME适应的过程已经注定了一些肿瘤具有侵袭性和致命性。此外，许多 乳腺癌病变实际上可能会消退，这表明癌症进展可能是随机的。新颖的成像 需要模式和复杂的肿瘤谱系训练策略来解决这一具有挑战性的问题。我们的 在肿瘤过程中利用小鼠模型和高分辨率纵向成像进行实验 进展将决定癌症进展是否是确定性的，这为研究增加了重要价值 了解乳腺癌的进展。