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的主要原因。虽然 关于肿瘤细胞对给定药物产生耐药性的机制， 将其转化为有效的治疗解决方案仍然是未满足的临床需求。在这里，我们建议率先使用 患者来源的肿瘤类器官（PDTO）作为一个平台，以确定和验证新的目标和有效的 卵巢癌、胰腺癌和其他类型肿瘤的耐药性药物。在我们 初步研究表明，PDTO在遗传和表型上与肿瘤相匹配， 衍生并可用于研究肿瘤异质性，肿瘤 进化和抗药性。使用批准的临床实验室改进修正案（CLIA） 高复杂性试验，我们表明PDTO药物敏感性与已知的遗传学高度一致， 生物标志物、回顾性治疗史和前瞻性患者反应。肿瘤类器官来源 来自产生原位耐药性的患者，其表现出对这些相同药物的离体耐药性， 也显示出对其他替代肿瘤药物的敏感性。额外的初步研究显示稳定 用从类器官药物筛选鉴定的药物治疗的患者的疾病或肿瘤消退。这里我们 建议将联合收割机药物筛选和源自给定患者的PDTO的分子谱分析结合起来， 不同的解剖肿瘤部位和治疗前后，以阐明药物的机制基础 敏感性或耐药性，并确定新的目标和有效的药物，以治疗转移性，耐药性 癌的伴随而来的计算预测模型整合了大型公共数据集， 创新的机制靶向验证方法，包括CRISPR、靶向蛋白质降解 技术和表观遗传分析，将用于优先考虑和推进目标和相关的 具有最大临床潜力的生物标志物。我们的做法背后的基本原理是，确定目标和 直接在具有已知临床病史和结果的患者来源的样品中使用有效药物将显著 加强对我们调查结果的翻译。这一建议意义重大，因为它将证明 PDTO既是靶点发现和验证的研究工具，也是临床有用的平台， 引导功能性精准医疗。研究结果和开发的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点的开发， 转化为临床研究。该提案的模式、方法和预期成果非常重要， 符合PAR-21-274的要求。