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

项目摘要/摘要 改善癌症患者的治疗策略需要改进的工具来更好地预测患者的反应， 建立克隆异质性模型，并为个别患者确定新的治疗方案。患者来源的癌症 有机化合物(PDCOS)是一项重大进步，提供了更具代表性的人类疾病模型，包括 在癌症中发现的分子改变、细胞间通讯和3D结构的维持。我们的 该组织拥有使用PDCOS预测不同癌症类型患者的治疗反应的重要经验。 然而，这些模型在用于翻译研究时面临着独特的挑战，包括(1)异质性 同一患者的有机物质之间；(2)需要样本固定或试剂的评估技术 这妨碍了克隆进化的时间进程研究，以及(3)缺乏单一有机化合物的评估和较低的生物多样性。 限制新药筛选的吞吐量培养技术。 我们已经开发了使用双光子(2P)显微镜的光学代谢成像(OMI)来测量治疗情况 无需试剂(例如，染料、标签)或固定即可进行反应。我们先前的研究表明，2P OMI 可以预测癌症患者的治疗反应。然而，2P显微镜成本高，产量低， 操作起来也很复杂。为了在PDCOS的多中心翻译研究中扩大OMI的使用，更多 需要易于获得的成像和分析方法来进行高通量/中通量药物筛选和 随着时间推移对有机物代谢异质性的评估。为了提高这项技术的可及性， 为了建立更多的实验室，促进PDCOS的广泛使用，我们开发了单光子广场(WF) OMI技术结合单有机物跟踪和前沿分割方法进行显著降低 与2P显微镜相比，降低了成本，降低了复杂性，并提高了吞吐量。 本方案的目标是验证可广泛应用于患者的PDCOS的WF OMI技术 治疗计划、异质性分析和新药开发。OMI非侵入式图像 在3D样品中使用代谢辅酶NAD(P)H和FAD的本征荧光进行响应。OMI 可以动态地量化治疗过程中不同种类的药物反应。我们已经并将继续 从转移性结直肠癌(CRC)患者中建立数百个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、识别 代谢/遗传异质性是靶向治疗抵抗的基础，并进行新药筛选 候选人。这项工作的完成将创造出实现高敏感性患者匹配药物的技术 在临床环境中进行筛选，预测个别患者的耐药性演变，并进行新药开发 在反映人类癌症多样性的样本中进行研究。

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.