A Patient-Centric Approach to Advance Functional Precision Oncology

项目摘要/摘要 耐药性的发展是癌症治疗失败和死亡的主要原因。虽然 关于肿瘤细胞对特定药物产生抗药性的机制，人们已经知道很多。 将其转化为有效的治疗方案仍然是一个未得到满足的临床需求。在这里，我们建议率先使用 患者来源的肿瘤有机化合物(PDTO)作为平台来识别和验证新的靶点和有效性 克服卵巢癌、胰腺癌和其他肿瘤类型的耐药性的药物。在我们的 初步研究表明，PDTO在基因和表型上与其来源的肿瘤相匹配 可用于研究肿瘤异质性、肿瘤的表型后果 进化和抗药性。使用临床实验室改进修正案(CLIA)获得批准 高复杂性分析，我们表明PDTO药物敏感性与已知基因高度一致 生物标志物、回溯性治疗历史和预期的患者反应。肿瘤有机化合物衍生 在体内产生耐药性的患者对同样的药物表现出体外耐药性，但 也表现出对其他肿瘤替代药物的敏感性。额外的初步研究表明情况稳定 使用有机类药物筛选确定的药物治疗的患者的疾病或肿瘤消退。在这里，我们 建议将药物筛选和来自特定患者的PDTO的分子图谱相结合 肿瘤不同解剖部位及治疗前后药物作用机制的探讨 敏感性或耐药性，并确定新的靶点和有效药物来治疗转移的、耐药的 癌症。随附的计算预测模型集成了大型公共数据集以及 机制靶标验证的创新方法，包括CRISPR、靶向蛋白质降解 将使用技术和表观遗传概况来确定和推进目标和相关的 最具临床潜力的生物标志物。我们方法背后的基本原理是识别目标和 在已知临床病史和结果的患者来源样本中直接使用有效药物将显著 加强对我们调查结果的翻译。这项建议意义重大，因为它将证明 PDTOS既是发现和验证靶点的研究工具，也是临床上有用的平台 引导功能精准医学。所开发的结果和方法可以很容易地应用于其他 癌症类型和临床挑战，将加快临床前药物和药物靶点的开发，并将 转化为临床研究。这项提案的模型、方法和预期结果是高度 响应PAR-21-274的要求。

PROJECT SUMMARY/ABSTRACT The development of drug resistance is a major cause of cancer treatment failure and mortality. Although much is known about the mechanisms by which tumor cells can become resistant to a given drug, translating this into effective therapeutic solutions remains an unmet clinical need. Here we propose to pioneer the use of patient derived tumor organoids (PDTOs) as a platform to identify and validate novel targets and effective drugs to overcome drug resistance in ovarian cancer, pancreatic cancer, and other tumor types. In our preliminary studies, we show that PDTOs genetically and phenotypically match the tumor from which they were derived and can be used to study the phenotypic consequences of tumor heterogeneity, tumor evolution, and drug resistance. Using a Clinical Laboratory Improvement Amendments (CLIA) approved high complexity assay, we show that PDTO drug sensitivities are highly concordant with known genetic biomarkers, retrospective treatment history and prospective patient responses. Tumor organoids derived from patients who developed in situ drug resistance demonstrate ex vivo resistance to those same drugs but also demonstrate sensitivity to other alternative oncology drugs. Additional preliminary studies show stable disease or tumor regression in patients treated with drugs identified from organoid drug screens. Here, we propose to combine drug screening and molecular profiling of PDTOs derived from a given patient from different anatomic tumor sites and before and after therapy to elucidate the mechanistic basis for drug sensitivity or resistance and to identify novel targets and effective drugs to treat metastatic, drug resistant cancers. Accompanying computational prediction models that integrate large public datasets as well as innovative methods of mechanistic target validation including CRISPR, targeted protein degradation technologies, and epigenetic profiling, will be used to prioritize and advance targets and associated biomarkers with greatest clinical potential. The rationale behind our approach is that identifying targets and effective drugs directly in patient derived samples with known clinical history and outcomes will significantly enhance translation of our findings. This proposal is significant because it will demonstrate the utility of PDTOs as both a research tool for target discovery and validation but also as a clinically useful platform to guide functional precision medicine. The findings and methods developed can be readily applied to other cancer types and clinical challenges, will accelerate preclinical drug and drug target development, and will translate to clinical studies. The models, approaches, and expected outcomes of this proposal are highly responsive to the requirements of PAR-21-274.