(PQD-3) Spatiotemporal Molecular Interrogation of Early Metastatic Evolution In Situ

 描述（由申请人提供）：每个癌症幸存者都害怕复发。虽然治疗后没有原发性肿瘤是令人鼓舞的，但在每年一次的检查诊断为转移性疾病后走出诊所是一种情感上的破坏。大约90%的癌症致死率是由于转移-原发性肿瘤细胞扩散到远处器官。尽管原发性乳腺肿瘤的早期筛查方法和综合治疗方案急剧增加，但美国转移性癌症复发患者的总体死亡率在过去二十年中没有变化。治疗转移性肿瘤的临床失败主要是由于肿瘤转移的进化性质。为了在远端器官的不同组织微环境中存活并建立继发性肿瘤，播散性肿瘤细胞必须适应（转移性进化）宿主环境。临床上，转移性肿瘤表现出与原发性肿瘤截然不同的特征。因此，目前基于原发性肿瘤特征设计的癌症治疗方法很少有效。 突破性抗转移治疗的最佳设计依赖于我们对早期转移演变过程中常见和功能重要特征的深入理解。在这项拟议的研究中，我们将使用乳腺癌脑转移作为模型系统，并采取最先进的方法来跟踪和分析单个癌细胞从转移定植的初始时刻起在其精确的转移微环境中。这项由一个多学科团队，包括一位癌症生物学家、一位计算生物学家、一位数学家和一位生物信息学家的合作努力将使我们能够：1）在单细胞水平上描绘脑转移不同阶段基因转录的动态; 2）通过真实的图像可视化单个定殖转移性肿瘤细胞的行为及其与微环境的相互作用。时间活体成像和深部组织成像; 3）数学整合分子（RNA-seq）、行为（活体）和结构（深部组织成像）信息，以在其天然组织背景中识别乳腺癌脑转移期间常见的和功能上重要的早期转移性进化特征。 改变目前的临床治疗模式依赖于通过基础和临床前创新研究获得的新的深入机制见解。在我们提出的研究中利用尖端的测序和成像模式，我们将有能力系统地剖析早期转移行为的特征，并发现潜在的新的治疗靶点，用于针对特定靶点转移演变的范式转移新辅助治疗。本研究中提出的大胆和开创性尝试的概念验证将作为有效抗转移治疗的新类别辅助疗法的蓝图。

 DESCRIPTION (provided by applicant): Every single cancer survivor fears relapse. While being free of the primary tumor after treatment is encouraging, it is emotionally devastating to step out of the clinic after a yearly checkup with a diagnosis of metastatic disease. Approximately 90% of cancer lethality is due to metastasis - the spreading of primary tumor cells to distant organs. Despite a dramatic increase in early screening methods and comprehensive treatment regimens for primary breast tumors, the overall mortality of patients who relapsed with metastatic cancer in the US has not changed in the past two decades. Clinical failure in treating metastatic tumors is largely due to the evolutionary nature of tumor metastasis. In order to survive and establish secondary tumors in a different tissue microenvironment at distant organs, disseminated tumor cells have to adapt (metastatic evolution) to the host environment. Clinically, metastatic tumors exhibit drastically different characteristics from their primary counterpart. Therefore, current cancer treatments, designed based on the features of primary tumors, are rarely effective. Optimal design of breakthrough anti-metastasis therapies relies on our in-depth understanding of the common and functionally important traits during the early metastatic evolution. In this proposed study, we will use breast cancer brain metastasis as model system and take state-of-the-art approaches to trace and analyze a single cancer cell within its precise metastatic microenvironment from the initial moment of metastatic colonization. This collaborative effort from a multidisciplinary team, including a cancer biologist, a computational biologist, a mathematician and a bioinformatician will allow us to: 1) depict the dynamics of gene transcription during the different stages of brain metastasis at single cell level; 2) visualize th behavior of a single colonized metastatic tumor cell and its interaction with the microenvironment through real-time intravital imaging and deep tissue imaging; 3) mathematically integrate molecular (RNA-seq), behavioral (intravital) and structural (deep tissue imaging) information to identify the common and functionally important early metastatic evolutionary traits during the breast cancer brain metastasis in its native tissue context. Shifting the current clinical treatment model relies on new in-depth mechanistic insight obtained through basic and pre-clinical innovative research. Utilizing cutting-edge sequencing and imaging modality in our proposed study, we will have the capacity to systematically dissect traits of early metastatic behavior and discover potential novel therapeutic targets for paradigm-shifting novel adjuvant therapy tailored to specific target metastatic evolution. The conceptual validation from our bold and pioneering attempt proposed in this study will serves as a blueprint for a new category of adjuvant therapies for effective anti-metastasis treatment.