A Patient-Centric Approach to Advance Functional Precision Oncology

以患者为中心的方法推进功能性精准肿瘤学

• 批准号: 10721205
• 负责人: CHRISTOPHER J KEMP
• 金额: $ 109.88万
• 依托单位: FRED HUTCHINSON CANCER CENTER
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-09-22 至 2028-08-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10721205
• 关键词: Acceleration; Adjuvant Chemotherapy; Affect; Anatomy; Area; Biliary Tract Cancer; Biological Assay; Biological Markers; Biology; Cancer Biology; Cancer Etiology; Cancer Patient; Cells; Chemicals; Clinic; Clinical; Clinical Laboratory Improvement Amendments; Clinical Oncology; Clinical Research; Clinical Trials; Clustered Regularly Interspaced Short Palindromic Repeats; Computational Biology; Computing Methodologies; Credentialing; Data; Data Set; Dependence; Derivation procedure; Development; Drug Combinations; Drug Screening; Drug Targeting; Drug resistance; Drug usage; Environment; Epigenetic Process; Evolution; Future; Gene Expression; Genetic; Genetic Markers; Genomics; Goals; In Situ; Lethal Genes; Letters; Malignant Neoplasms; Malignant neoplasm of ovary; Malignant neoplasm of pancreas; Methodology; Methods; Modeling; Molecular Genetics; Molecular Profiling; Multiomic Data; Mutation; Neoadjuvant Therapy; Oncogenic; Oncologist; Oncology; Organoids; Outcome; Pancreatic Ductal Adenocarcinoma; Patient-Focused Outcomes; Patients; Pharmaceutical Preparations; Phenotype; Poly(ADP-ribose) Polymerase Inhibitor; Proteomics; Public Domains; Recording of previous events; Research; Resistance; Resistance development; Resource Sharing; Resources; Role; Sampling; Serous; Site; Stable Disease; Surgical Oncology; System; Technology; Testing; Translating; Translations; Treatment Failure; Validation; Work; cancer genetics; cancer type; chemotherapeutic agent; chemotherapy; clinically relevant; computerized tools; computing resources; drug development; drug resistance development; drug sensitivity; effective therapy; epigenetic profiling; epigenomic profiling; functional genomics; gemcitabine; genetic analysis; improved; individual patient; innovation; insight; mortality; neoplastic cell; new therapeutic target; novel; pancreatic cancer patients; patient response; pre-clinical; precision medicine; precision oncology; predictive modeling; pressure; prospective; protein degradation; refractory cancer; small molecule; small molecule inhibitor; standard of care; targeted agent; targeted treatment; therapeutically effective; tool; tumor; tumor heterogeneity

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.

项目摘要/摘要 耐药性的发展是癌症治疗失败和死亡率的主要原因。虽然 关于肿瘤细胞对给定药物具有抗性的机制知之甚少，翻译 这是有效的治疗溶液仍然是未满足的临床需求。在这里，我们建议开拓使用 患者衍生的肿瘤器官（PDTO）作为识别和验证新目标和有效的平台 在卵巢癌，胰腺癌和其他肿瘤类型中克服耐药性的药物。在我们的 初步研究，我们表明pDTO在遗传和表型上与之相匹配。 被得出，可用于研究肿瘤异质性，肿瘤的表型后果 进化和耐药性。使用已批准的临床实验室改进修订（CLIA） 高复杂性测定，我们表明PDTO药物敏感性与已知遗传相一致 生物标志物，回顾性治疗史和前瞻性患者反应。衍生的肿瘤类器官 从产生原位耐药性的患者中表现出对这些药物的体内耐药性，但 还表现出对其他替代肿瘤药物的敏感性。其他初步研究表明稳定 用从类器官药物筛查的药物治疗的患者的疾病或肿瘤消退。在这里，我们 提议结合源自给定患者的PDTO的药物筛查和分子分析 不同的解剖肿瘤部位以及治疗前后，以阐明药物的机械基础 敏感性或耐药性，并确定新的靶标和有效药物以治疗转移性药物抗药性 癌症。随附的计算预测模型，这些模型集成了大型公共数据集以及 机械目标验证的创新方法，包括CRIS，靶向蛋白质降解 技术和表观遗传分析将用于优先级和促进目标和相关的目标 具有最大临床潜力的生物标志物。我们方法背后的理由是确定目标和 直接在具有已知临床病史和结果的患者衍生样品中的有效药物将显着 增强我们的发现的翻译。该提议很重要，因为它将证明 PDTO既是目标发现和验证的研究工具，又是临床上有用的平台 指南功能精确医学。开发的发现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速临床前药物和药物靶向的发展，并将 转化为临床研究。该提案的模型，方法和预期结果很高 响应PAR-21-274的要求。