Label-Free, Longitudinal, Multi-Metric Viability Imaging of 3D Tissue Spheroid Array

3D 组织球体阵列的无标记、纵向、多指标活力成像

• 批准号: 10295612
• 负责人: Jonghwan Lee
• 金额: $ 35.03万
• 依托单位: BROWN UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-07-09 至 2026-06-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10295612
• 关键词: 3-Dimensional; Address; Adopted; Biological Assay; Biopsy; Cancer Patient; Cell Adhesion; Cell Culture Techniques; Cell Nucleus; Cell Survival; Cells; Chemicals; Chemosensitivity Assay; Clinical Trials; Combined Modality Therapy; Cultured Cells; Data; Data Set; Development; Diffusion; Dimensions; Dose; Drug Combinations; Drug usage; End Point Assay; Ethanol; Fractals; Future; Genomics; Guidelines; Hour; Image; Imaging technology; In Vitro; Individual; Investigation; Label; Lung; Malignant Neoplasms; Malignant neoplasm of liver; Measurement; Measures; Medicine; Membrane; Metabolism; Methods; Microscopy; Oligomycins; Oncology; Optical Coherence Tomography; Optics; Outcome; Paclitaxel; Pancreas; Patient Monitoring; Patients; Pharmaceutical Preparations; Physicians; Pilot Projects; Population; Precision Medicine Initiative; Process; Research; Sampling; Sensitivity and Specificity; Series; Signal Transduction; Specificity; Surface; Techniques; Technology; Testing; Time; Tissue Engineering; Tissues; Toxicity Tests; Tumor Cell Line; Validation; Variant; attenuation; base; cancer therapy; cancer type; cell type; chemotherapy; clinical application; design; drug discovery; drug testing; image processing; imaging study; in vivo; individual patient; individualized medicine; innovation; longitudinal dataset; malignant breast neoplasm; neoplastic cell; novel strategies; optimal treatments; patient population; personalized medicine; precision medicine; precision oncology; prevent; response; statistics; three dimensional cell culture; tumor; tumor microenvironment

SUMMARY When selecting cancer therapy, physicians generally begin with first-line treatment options and monitor patient progress on a watch-and-wait basis, following a set of guidelines based on clinical trials from a large patient population. But this traditional method has been questioned on whether it provides individual patients with the optimal treatment. To better find a matching treatment individually, a concept called precision cancer medicine or personalized cancer medicine has been studied. Among other approaches, functional precision medicine directly tests chemotherapy options on tumor cells biopsied from a patient to find the best matching treatment for the specific patient. This promising approach, however, has not been widely adopted by clinicians because the tumor microenvironment in a lab differed from the one within the patient’s body, leading to inconsistent drug responses between the sample and patient, and the quantity of biopsied cells is generally insufficient for a reliable number of options to be tested. The first problem is being addressed by recent advances in three- dimensional (3D) cell culture techniques, which better mimic the body’s microenvironment in a lab. But the second problem, the limited number of testable options, is mainly due to limitations in the current assay techniques that assess chemosensitivity in 3D culture. With most current assays, a sample can only be tested once, and multiple drugs with different mechanisms of action cannot be simultaneously tested by a single assay. Combined, these limitations exponentially reduce the number of testable options when involving multiple assessment time points to design a sequential therapy or when increasing the number of drugs to test a combination therapy. Here, we will develop a new technique for the assessment of chemosensitivity in 3D culture, by maximizing the potential of a label-free 3D microscopy technology, called optical coherence tomography (OCT). The majority of prior OCT research measured only one or two types of signals and showed the signals corresponding to only a single type of cell viability disruption process in each study. But this approach has led to a concern about specificity (i.e., other types of processes than the one tested in the study can generate similar OCT signals). This low specificity, along with unclear mechanisms of viability assessment, have prevented OCT methods from being adopted for the promising concept of functional precision medicine. Therefore, we will develop at least 18 different types of OCT signals and establish their sensitivity and specificity to four major types of viability disruption processes. The feasibility of this approach has been strongly supported by a pilot study where we imaged and analyzed more than 6,000 3D-cultured cell spheroids. This R01 project will image and analyze up to 100,000+ spheroids for an unprecedentedly systemic investigation of the comprehensive range of OCT signal types.

概括 选择癌症治疗时，医生通常从一线治疗选择开始，并监测患者 根据一组基于大型患者的临床试验的准则，在等待中进展 人口。但是，这种传统方法已被质疑是否为单个患者提供 最佳治疗。为了更好地找到一种单独的匹配治疗，一个称为精密癌症医学的概念 或个性化癌症医学已研究。除其他方法外，功能精确医学 直接测试从患者活检的肿瘤细胞上的化学疗法选择，以找到最佳匹配治疗 对于特定患者。 但是，这种有希望的方法并未被临床医生广泛采用，因为肿瘤 与患者体内一个不同的实验室中的微环境，导致药物不一致 样本和患者之间的反应以及活检细胞的数量通常不足 可靠数量的要测试的选项。第三个问题是由三个进步解决的 尺寸（3D）细胞培养技术，可以更好地模仿实验室中人体的微环境。但是 第二个问题是有限的可测试选项，主要是由于当前测定中的限制 评估3D培养中化学敏度的技术。有了大多数当前评估，只能测试样本 一次，多种具有不同作用机制的药物不能简单地测试一个 测定。结合在一起，这些限制指数级减少涉及可测试选项的数量 多次评估时间点设计顺序治疗或增加测试的药物数量 组合疗法。 在这里，我们将开发一种新技术，用于评估3D培养的化学敏感性，通过最大化 无标签3D显微镜技术的潜力，称为光学相干断层扫描（OCT）。多数 先前的OCT研究仅测量了一种或两种信号，并显示了与 在每项研究中，只有单一类型的细胞活力破坏过程。但是这种方法引起了人们的关注 关于特异性（即，在研究中测试的过程以外的其他类型的过程可以产生相似的OCT 信号）。这种低的特异性以及不清楚的生存能力评估机制已阻止了OCT 被用于功能精确医学的承诺概念所采用的方法。 因此，我们将至少开发18种不同类型的OCT信号，并确定其敏感性和 对四种主要类型的可行性破坏过程的特异性。这种方法的可行性已经 通过一项试点研究的强烈支持，我们对6,000多个3D培养细胞进行了成像和分析 球体。这个R01项目将形象和分析多达100,000多个球体，以实现系统性 对OCT信号类型的综合范围进行研究。