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

项目摘要 大多数耐药研究模型都是在实验室从癌细胞系发展而来的；然而，他们的派生 生物史与患者的病史是不同的。随着创新方法的出现，发展 患者衍生的癌症模型(PDMC)，新的机会可以建立不同的模型阵列 代表个别患者的临床经验-使识别肿瘤的特征 患者组织中的药物反应和耐药性是潜在的。我们假设PDMC可以用来识别 乳腺癌有效新疗法，以及对有效和无效队列的分析 响应性PDMC可用于识别预测治疗反应或耐药的标志物。这个 这项建议的目标是利用大量和多样化的乳房PDMC库来筛选乳房的新疗法 癌症，重点是目前的NCI-IND药物。我们将首先使用患者衍生的有机化合物(PDO)进行 高通量筛选NCI-IND药物作为单一药物和两种药物的组合。每种药物和 药物组合将在来自100名不同患者的高危和转移性乳腺肿瘤的PDO上进行测试。 有效的“铅”疗法将在患者来源的异种移植(PDX)模型中得到验证，该模型来源于一个子集 在这些患者中，包括基于PDO分析的预测应答者和无应答者。重要的是 所有PDX模型上可用的基因组数据将被用来识别蛋白质组、基因表达 和/或与应答者或无应答者相关的突变生物标记物。初级阶段 这项研究的结果将是确定使用PDMCs作为乳腺癌的新的NCI-IND治疗方案 临床前工具(1)评估100名不同患者的多种药物和药物组合的疗效 肿瘤模型，以及(2)确定“铅”疗法的反应和无反应乳腺癌的特征， 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.