Research Project 1: Identification and validation of efficacious therapies for breast cancer using patient-derived specimens

项目摘要 大多数耐药性的研究模型都是在实验室中从癌细胞系中开发的;然而，它们的衍生物 生物学病史与患者的病史不同。随着创新方法的出现， 患者来源的癌症模型（PDMC），新的机会可用于建立各种各样的模型 代表个体患者的临床经验-能够识别肿瘤的特征， 是患者组织中药物反应和耐药性的基础。我们假设PDMC可以用来识别 有效的乳腺癌新疗法，以及对有反应和无反应的患者队列的分析， 响应的PDMC可用于鉴定预测治疗响应或抗性的标志物。的 该提案的目标是利用大量不同的乳腺PDMC库来筛选乳腺癌的新疗法， 癌症，重点是目前的NCI-IND药物。我们将首先使用患者源性类器官（PDO）进行 高通量筛选NCI-IND药物作为单一药剂和两种药剂的组合。每种药物和 将在来自100名不同患者的高风险和转移性乳腺肿瘤的PDO上测试药物组合。 有效的“先导”疗法随后将在源自亚组的患者源性异种移植物（PDX）模型中进行验证。 包括基于PDO测定的预测应答者和无应答者。重要的是， 所有PDX模型上的基因组数据将用于识别蛋白质组、基因表达 和/或与应答者或非应答者相关的突变生物标志物。主 这项研究的结果将是确定新的NCI-IND乳腺癌治疗方案，使用PDMC作为 临床前工具，以（1）在100名不同患者中评估许多药物和药物组合的疗效 肿瘤模型，和（2）识别“先导”疗法的应答和非应答乳腺癌的特征， 以便为未来的临床试验设计提供信息。

Project Summary Most research models of drug resistance are developed in the lab from cancer cell lines; however, their derived biological history is distinct from what occurs in patients. With the emergence of innovative methods to develop patient-derived models of cancer (PDMC), new opportunities are available to establish a diverse array of models representing individual patients’ clinical experiences – enabling identification of the features of tumors that underlie drug response and resistance in patient tissues. We hypothesize that PDMCs can be used to identify effective new therapies for breast cancer, and that analysis of cohorts of responding and non- responding PDMCs can be used to identify markers that predict treatment response or resistance. The goal of this proposal is to utilize a large and diverse bank of breast PDMCs to screen for new therapies for breast cancer, with a focus on current NCI-IND agents. We will first use patient-derived organoids (PDOs) to conduct high throughput screens of NCI-IND drugs as single agents and in combinations of two agents. Each drug and drug combination will be tested on PDOs from high-risk and metastatic breast tumors from 100 different patients. Effective “lead” therapies will then be validated in patient-derived xenograft (PDX) models derived from a subset of those patients, to include predicted responders and non-responders based on PDO assays. Importantly, genomic data that is available on all of the PDX models will be utilized to identify proteomic, gene expression and/or mutational biomarkers associated with responders or non-responders, for each lead therapy. The primary outcome of this study will be to identify new NCI-IND treatment regimens for breast cancer using PDMCs as a pre-clinical tool to (1) evaluate the efficacy of many drugs and drug combinations across 100 different patients’ tumor models, and (2) identify the features of responding and non-responding breast cancers for “lead” therapies, in order to inform future clinical trial design.