Targeting intratumor heterogeneity in breast cancer

 描述(申请人提供)：肿瘤内的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，发现治疗前较高的遗传多样性预示着治疗耐药，而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作用的次要亚群，主导克隆可以竞争导致肿瘤崩溃的肿瘤驱动次要克隆，以及癌症治疗加剧克隆竞争可能导致无意中加速疾病进展。这些数据质疑了当前的观点，即如何在临床样本中定义癌症驱动事件，以及如何基于这些知识设计治疗。根据我们的初步数据，我们假设肿瘤内克隆的异质性驱动转移进展和治疗耐药，了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治疗。这项建议的目标是使用临床样本和实验模型的多学科方法来检验这些假设。我们将利用我们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。我们将分析原发和转移肿瘤在未受干扰状态和后续治疗中的组成，并使用综合的分子和数学方法研究克隆相互作用促进肿瘤发生的分子和细胞机制。我们将通过分析不同进展阶段的肿瘤以及治疗前后的样本，结合异种移植模型的机制研究，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。我们将为异质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联合分析来解决这一空白。我们的结果将有助于设计更有效的治疗异质性肿瘤的策略。

 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.