Functional optical imaging for rapid, label-free predictions of treatment response and clonal evolution in patient-derived cancer organoids

功能光学成像可快速、无标记地预测患者来源的癌症类器官的治疗反应和克隆进化

• 批准号: 10657203
• 负责人: Dustin A Deming
• 金额: $ 68.22万
• 依托单位: MORGRIDGE INSTITUTE FOR RESEARCH, INC.
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-04-01 至 2028-03-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10657203
• 关键词: 3-Dimensional; Architecture; Cancer Patient; Cell Communication; Cell Line; Cells; Clinic; Clinical; Clonal Evolution; Coenzymes; Colorectal Cancer; Complex; Culture Techniques; Development; Disease model; Drug Screening; Drug resistance; Dyes; Epidermal Growth Factor Receptor; Epidermal Growth Factor Receptor Tyrosine Kinase Inhibitor; Evolution; Fluorescence; Genetic; Genetic Heterogeneity; Goals; Heterogeneity; Hour; Human; Image; Image Analysis; Imaging Device; Imaging Techniques; Label; Laboratories; Maintenance; Malignant Neoplasms; Measures; Metabolic; Methods; Microscopy; Modeling; Molecular; Monitor; Multivariate Analysis; Optics; Organoids; Patient imaging; Patients; Pharmaceutical Preparations; Photons; Prediction of Response to Therapy; Reader; Reagent; Receptor Inhibition; Resistance; Sampling; Techniques; Technology; Testing; Time; Translational Research; Work; cancer type; chemotherapy; clinical predictors; colon cancer patients; colorectal cancer treatment; cost; drug candidate; drug development; experience; high throughput screening; human model; improved; in vivo; individual patient; insight; metabolic imaging; metastatic colorectal; non-invasive imaging; novel; novel drug combination; novel therapeutics; optical imaging; patient response; predicting response; prevent; response; sample fixation; screening; targeted treatment; tool; translational study; treatment planning; treatment response; treatment strategy; tumor; tumor DNA; two-photon; validation studies

PROJECT SUMMARY / ABSTRACT Improved treatment strategies for patients with cancer require enhanced tools to better predict patient response, model clonal heterogeneity, and identify novel treatment options for individual patients. Patient-derived cancer organoids (PDCOs) are a major advance providing more representative models of the human disease, including the maintenance of molecular alterations, cell-cell communication, and the 3D architecture found in cancers. Our groups have significant experience using PDCOs to predict treatment response for patients across cancer types. These models, however, have unique challenges when used for translational studies, including (1) heterogeneity between organoids from the same patient, (2) assessment techniques that require sample fixation or reagents that prevent time-course studies of clonal evolution, and (3) lack of single organoid assessment and low- throughput culture techniques that limit screens for new drugs. We have developed optical metabolic imaging (OMI) using two-photon (2P) microscopy to measure treatment response without a need for reagents (e.g., dyes, labels) or fixation. Our prior studies demonstrated that 2P OMI can predict treatment response for patients with cancer. However, 2P microscopy is high cost, low throughput, and complex to operate. To expand the use of OMI across multi-center translational studies of PDCOs, more readily accessible imaging and analysis methods are needed for high/moderate throughput drug screening and assessments of organoid metabolic heterogeneity over time. To enhance the accessibility of this technology to more laboratories and facilitate the expanded use of PDCOs, we have developed a one-photon wide-field (WF) OMI technique with single-organoid tracking and leading-edge segmentation methods for significantly reduced cost, reduced complexity, and increased throughput compared to 2P microscopy. The goal of this proposal is to validate WF OMI techniques for PDCOs that can be widely used for patient treatment planning, heterogeneity analyses, and new drug development. OMI non-invasively images response in a 3D sample using the intrinsic fluorescence of the metabolic co-enzymes NAD(P)H and FAD. OMI can dynamically quantify heterogeneous drug response over a treatment time-course. We have and will continue to develop hundreds of PDCO lines from metastatic colorectal cancer (CRC) patients. These cultures will be used to validate new methods for more widely accessible OMI tools to predict patient response, identify metabolic/genetic heterogeneity that underlies resistance to targeted therapy, and perform screens of new drug candidates. The completion of this work will create technologies to perform high-sensitivity patient-matched drug screens in a clinical setting, predict the evolution of drug resistance for individual patients, and perform new drug development in samples that reflect the diversity of human cancers.

项目总结/摘要 改善癌症患者的治疗策略需要增强的工具来更好地预测患者的反应， 建立克隆异质性模型，并为个体患者确定新的治疗方案。患者源性癌症 类器官（PDCO）是一个重大进步，提供了更有代表性的人类疾病模型，包括 维持分子改变、细胞间通讯和癌症中发现的3D结构。我们 研究小组在使用PDCO预测不同癌症类型患者的治疗反应方面具有丰富的经验。 然而，这些模型在用于转化研究时具有独特的挑战，包括（1）异质性 来自同一患者的类器官之间，（2）需要样品固定或试剂的评估技术 这阻碍了克隆进化的时间进程研究，和（3）缺乏单一的类器官评估和低- 限制新药筛选的通量培养技术。 我们已经开发了光学代谢成像（OMI），使用双光子（2 P）显微镜来测量治疗 不需要试剂的响应（例如，染料、标签）或固定。我们以前的研究表明，2 P OMI 可以预测癌症患者的治疗反应。然而，2 P显微术成本高，通量低， 并且操作复杂。为了扩大OMI在多中心PDCO转化研究中的使用，更多 高/中通量药物筛选需要容易获得的成像和分析方法， 随时间推移的类器官代谢异质性评估。为了提高这项技术的可及性， 更多的实验室和促进PDCO的扩大使用，我们已经开发了一个单光子宽场（WF） OMI技术与单类器官跟踪和前沿分割方法相比， 与2 P显微镜相比，成本更低，复杂性更低，吞吐量更高。 本提案的目标是验证适用于PDCO的WF OMI技术，该技术可广泛用于患者 治疗计划、异质性分析和新药开发。OMI非侵入性图像 使用代谢辅酶NAD（P）H和FAD的固有荧光在3D样品中的响应。OMI 可以动态量化治疗时间过程中的异质药物反应。我们已经并将继续 从转移性结直肠癌（CRC）患者中开发数百个PDCO细胞系。这些文化将是 用于验证更广泛使用的OMI工具的新方法，以预测患者反应， 代谢/遗传异质性是靶向治疗耐药性的基础，并进行新药筛选 候选人这项工作的完成将创造技术，以执行高敏感性患者匹配的药物 在临床环境中进行筛选，预测个体患者的耐药性演变， 反映人类癌症多样性的样本的发展。