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

 描述(申请人提供)：每一个癌症幸存者都害怕复发。虽然治疗后没有原发肿瘤是令人鼓舞的，但在每年一次的体检被诊断为转移性疾病后走出诊所，这在情感上是毁灭性的。大约90%的癌症致命性是由于转移--原发肿瘤细胞扩散到远处的器官。尽管原发乳腺癌的早期筛查方法和综合治疗方案大幅增加，但在过去20年里，美国转移性癌症复发患者的总体死亡率没有变化。临床上治疗转移性肿瘤的失败很大程度上是由于肿瘤转移的进化性质。为了在远处器官的不同组织微环境中存活和建立继发性肿瘤，播散性肿瘤细胞必须适应宿主环境(转移进化)。临床上，转移性肿瘤表现出与原发肿瘤截然不同的特征。因此，目前根据原发肿瘤的特点设计的癌症治疗方法很少有效。 突破性抗转移治疗的优化设计依赖于我们对早期转移演变过程中常见的和重要的功能特征的深入理解。在这项拟议的研究中，我们将以乳腺癌脑转移为模型系统，采用最先进的方法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的情况。这项由多学科团队联合开展的工作，包括癌症生物学家、计算生物学家、数学家和生物信息学家，将使我们能够：1)在单细胞水平上描绘脑转移瘤不同阶段的基因转录动态；2)通过实时活体成像和深部组织成像，可视化单个定植的转移瘤细胞的行为及其与微环境的相互作用；3)数学集成分子(RNA-seq)、行为(活体内)和结构(深部组织成像)信息，以确定乳腺癌脑转移过程中天然组织背景下的共同和功能重要的早期转移进化特征。 转变当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洞察力。在我们拟议的研究中，利用尖端测序和成像方式，我们将有能力系统地剖析早期转移行为的特征，并发现潜在的新治疗靶点，用于针对特定靶点转移进化量身定做的范式转换新辅助疗法。这项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治疗的蓝图。

 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.