Targeting intratumor heterogeneity in breast cancer

 描述（由申请人提供）：肿瘤内异质性是理解和治疗癌症的主要障碍。我们分析了乳腺肿瘤的细胞遗传和表型异质性，发现较高的治疗前遗传多样性预示着治疗耐药性，远处转移是最多样化的。我们还开发了一个克隆异质性的实验模型，并表明多克隆肿瘤生长更快，更具转移性，肿瘤驱动克隆可以是通过非细胞自主机制起作用的次要亚群，显性克隆可以胜过肿瘤驱动次要克隆，导致肿瘤崩溃，并且癌症治疗加剧了克隆竞争，可能导致无意中加速疾病进展。这些数据质疑了目前关于如何定义临床样本中的癌症驱动事件以及如何基于这些知识设计治疗的观点。基于我们的初步数据，我们假设肿瘤内的克隆异质性驱动转移进展和治疗抗性，并且理解肿瘤内克隆相互作用的分子和细胞机制将改善乳腺癌患者的临床管理。本提案的目标是使用应用于临床样本和实验模型的多学科方法来测试这些假设。我们将利用我们已经开发的乳腺癌克隆异质性模型，并将从患者样本中产生新的模型。我们将分析原发性和转移性肿瘤在未受干扰的状态下和治疗后的组成，并研究克隆相互作用促进肿瘤发生的分子和细胞机制，使用全面的分子和数学方法。我们将探索非细胞自主肿瘤驱动因素和克隆干扰在临床乳腺肿瘤中的作用，方法是使用综合和单细胞分析方法结合异种移植模型中的机制研究，分析不同进展阶段的肿瘤以及治疗前和治疗后样本。我们将为异质性肿瘤设计新的治疗策略。肿瘤进展是遵循达尔文原则的体细胞进化。尽管被普遍接受，但目前研究和治疗癌症的方法并没有利用和建立在这些进化原则的基础上。拟议的研究将通过对实验和临床乳腺肿瘤的综合分析来解决这一空白。我们的研究结果将有助于设计更有效的治疗策略的异质性肿瘤。

 DESCRIPTION (provided by applicant): Intratumor heterogeneity is a major obstacle toward understanding and treatment of cancers. We have analyzed cellular genetic and phenotypic heterogeneity in breast tumors and found that higher pre-treatment genetic diversity predicts therapy resistance and distant metastases are the most diverse. We also developed an experimental model of clonal heterogeneity and shown that polyclonal tumors grow faster and are more metastatic, the tumor-driver clone can be a minor subpopulation acting via non-cell-autonomous mechanisms, a dominant clone can outcompete the tumor-driver minor clone leading to tumor collapse, and that cancer therapies intensify clonal competition potentially leading to inadvertent acceleration of disease progression. These data questions current views of how to define cancer-driving events in clinical samples and how to design treatment based on this knowledge. Based on our preliminary data we hypothesize that clonal heterogeneity within tumors drives metastatic progression and therapeutic resistance and that understanding the molecular and cellular mechanisms underlying clonal interactions within tumors will improve the clinical management of breast cancer patients. The goal of this proposal is to test these hypotheses using a multidisciplinary approach applied to clinical samples and experimental models. We will utilize a model of clonal heterogeneity of breast cancer that we have developed and will generate new ones from patient samples. We will analyze the composition of primary and metastatic tumors in unperturbed states and following therapies and investigate molecular and cellular mechanisms by which clonal interactions promote tumorigenesis using comprehensive molecular and mathematical approaches. We will explore the role of non-cell-autonomous tumor drivers and clonal interference in clinical breast tumors by analyzing tumors at different progression stages and pre- and post-treatment samples using comprehensive and single cell profiling approaches coupled with mechanistic studies in xenograft models. We will design novel treatment strategies for heterogeneous tumors. Tumor progression is a somatic evolution following Darwinian principles. Despite being universally accepted, current approaches to the study and treatment of cancers do not utilize and build on these evolutionary principles. The proposed studies will address this void by the combined analysis of experimental and clinical breast tumors. Our results will help the design of more effective therapeutic strategies for heterogeneous tumors.