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

项目概要/摘要 背景：体细胞突变的逐步积累和细胞行为的进行性变化 为癌症筛查时代提供了理论基础。然而，这并不能解释致命性的重新诊断。 转移性疾病在明显缺乏屏幕可检测的癌前病变。越来越多的证据 表明侵袭性癌症可能在没有延长和可检测的癌前阶段的情况下开始。此外，本发明还提供了一种方法， 增殖性病变不能确定性地进展，这表明许多早期癌症被过度治疗。 虽然已经观察到早期检测的急剧增加，但致命的 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 自发地消退或退化。相比之下，最致命的癌症逃避检测和转移之前， 到侦查 假设：我们假设癌症的进展，像正常组织的稳态，是随机的和受控制的。 空间和微环境的限制。 具体目标：目标1。为了明确乳腺癌进展的自我平衡原则， HER 2+乳腺癌小鼠模型。目标2.分析HER 2亚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，我们将使用一个经过验证的癌症彩虹建模系统进行可视化， 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沿着微环境特征 (ECM巨噬细胞、血管）。八周的纵向成像将捕捉肿瘤的发生率， 在体内和免疫完整的小鼠模型中的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早期手术干预 并没有提高乳腺癌的存活率，假设肿瘤和宿主之间的适应性改变了乳腺癌的存活率。 在诊断前多年就有浸润性癌症的轨迹。支持者们认为， 肿瘤-TME适应性已经注定了一些肿瘤变得具有侵袭性和致命性。另外很多 乳腺癌病变实际上可能消退，这表明癌症进展可能是随机的。新的成像 需要模式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 利用小鼠模型和肿瘤过程中的高分辨率纵向成像的实验 进展将决定癌症进展是否是确定性的，增加了一个重要的价值， 了解乳腺癌的进展。

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.