Optical imaging to predict cell-level genetic heterogeneity and treatment sensitivity in colorectal cancer

光学成像预测结直肠癌的细胞水平遗传异质性和治疗敏感性

• 批准号: 10518168
• 负责人: Dustin A Deming
• 金额: $ 60.12万
• 依托单位: UNIVERSITY OF WISCONSIN-MADISON
• 依托单位国家: 美国
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-06-08 至 2025-05-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10518168
• 关键词: 3-Dimensional; Aftercare; Age; Applications Grants; Architecture; Biopsy; Cancer Biology; Cancer Etiology; Cancer Model; Cancer Patient; Cell Communication; Cells; Cessation of life; Chemotherapy and/or radiation; Clinical; Clinical Treatment; Clinical Trials; Clonal Evolution; Coenzymes; Colorectal Cancer; Complex; Correlation Studies; Data; Development; Diameter; Disease; Disease Resistance; Dose; Enrollment; Ethnic Origin; Exposure to; Fluorescence; Fluorouracil; Future; Gender; Generations; Genes; Genetic; Genetic Heterogeneity; Genotype; Goals; Heterogeneity; Human; Image; Imaging technology; Individual; Investigational Therapies; Lymphocyte Count; Magnetic Resonance Imaging; Malignant Neoplasms; Measures; Metabolic; Metabolism; Methods; Modality; Modeling; Molecular; Molecular Evolution; Molecular Profiling; Multivariate Analysis; Mus; Mutation; NADH; Neoadjuvant Therapy; Oncology; Operative Surgical Procedures; Optics; Organoids; Pathologic; Patient imaging; Patient-Focused Outcomes; Patients; Pharmaceutical Preparations; Pilot Projects; Population Density; Prediction of Response to Therapy; Primary Neoplasm; Prior Therapy; Protocols documentation; Race; Radiation; Radiation therapy; Rectal Cancer; Regimen; Registries; Research Technics; Sampling; Secondary to; Staging; Stromal Neoplasm; System; Techniques; Technology; Testing; Therapeutic; Time; Toxic effect; Toxicity due to chemotherapy; Transgenic Organisms; Tumor-Infiltrating Lymphocytes; Xenograft procedure; anticancer treatment; cancer cell; chemotherapy; clinical imaging; clinical predictors; cohort; colon cancer patients; driver mutation; effective therapy; improved; in vivo; individual patient; individualized medicine; interest; metabolic imaging; metastatic colorectal; mortality; novel; optical imaging; parent grant; patient response; personalized medicine; predict clinical outcome; predicting response; prospective; response; screening; side effect; single cell analysis; standard care; standard of care; tool; treatment response; tumor

PROJECT SUMMARY/ABSTRACT Across all cancers a significant problem in oncology is the current lack of reliable means to predict response to anti-cancer treatments for individual patients. Specifically in locally advanced rectal cancer (LARC), it is known that patients can benefit from chemotherapy, radiation, and operative management. However, not all of these therapies may be required for each individual patient. With standard practices, patients are exposed to the toxicities of all of these modalities without knowing the necessity of each. In addition, for some patients they require escalation of therapies beyond these due to resistant disease. A method to predict treatment response is urgently needed to better tailor the neoadjuvant treatment paradigm for individual patients and this is the goal of this proposal. The long-term objective of this proposal is to utilize optical metabolic imaging (OMI) of patient- derived colorectal cancer (CRC) organoid cultures to predict sensitivity to therapeutic regimens. This proposal develops novel cellular-level imaging technologies to predict treatment response in individual cancer patients using optical metabolic imaging (OMI) of organoids cultures from their own tumors. Since tumor genetics can have profound impacts on cellular metabolism, a better understanding of the underlying mechanisms by which tumor genetics alter OMI in the pre- and post-treatment settings is needed. In addition, assessment of cell-level heterogeneity within patient samples is required to fully predict the treatment response. To interrogate these mechanistic inquiries, we have generated multiple tools and research techniques. Our data to date indicate that OMI in primary CRCs and other tumor types predicts in vivo drug response in mice and patients. In this proposal, we test the hypothesis that OMI of patient-derived organoid cultures will predict treatment response for patients with CRC undergoing chemotherapy and/or radiation. In this extension proposal, we build on the prior aims to assess the use of OMI to evaluate clonal evolution and correlate these studies with molecular evolution of these cells. Additionally, we further validate the OMI response thresholds to predict treatment response identified in our initial aims with an additional cohort of CRC patients. Finally, we will perform a multivariate analysis to evaluate multiple OMI parameters in combination with change in organoid diameter, response on clinical imaging, pre-treatment clinical stage, age, gender, race/ethnicity, clinical treatment dose intensity, tumor infiltrating lymphocyte counts, and the molecular profile as predictors of clinical outcomes for these CRC patients. Overall, these additional aims represent logical extensions of the initial aims and will be key to further supporting the incorporation of OMI of patient-derived organoids into future prospective clinical trials.

项目总结/摘要 在所有癌症中，肿瘤学中的一个重要问题是目前缺乏可靠的方法来预测对化疗的反应。 针对个别患者的抗癌治疗。特别是在局部晚期直肠癌（LARC）中，已知 患者可以从化疗、放疗和手术治疗中获益。然而，并非所有这些 可能需要针对每个个体患者进行治疗。在标准实践中，患者暴露于 所有这些方式的毒性，而不知道每一个的必要性。此外，对于一些患者， 由于耐药疾病，需要升级治疗。预测治疗反应的方法 迫切需要更好地为个体患者定制新辅助治疗模式，这是我们的目标。 这一提议。该提案的长期目标是利用患者的光学代谢成像（OMI）， 衍生的结直肠癌（CRC）类器官培养物来预测对治疗方案的敏感性。这项建议 开发新的细胞水平成像技术，以预测个体癌症患者的治疗反应 使用光学代谢成像（OMI）从他们自己的肿瘤中培养类器官。由于肿瘤遗传学可以 对细胞代谢有着深远的影响，更好地了解其潜在的机制， 肿瘤遗传学改变OMI在治疗前和治疗后的设置是必要的。此外，评估细胞水平 需要患者样品内的异质性来完全预测治疗反应。审问这些 机械查询，我们已经产生了多种工具和研究技术。我们迄今为止的数据表明， 原发性CRC和其他肿瘤类型中的OMI可预测小鼠和患者的体内药物反应。 在这个提议中，我们检验了患者源性类器官培养物的OMI将预测治疗的假设。 接受化疗和/或放疗的CRC患者的反应。在这个扩展建议中，我们建立 在先前的目的是评估使用OMI来评估克隆进化，并将这些研究与分子生物学相关联。 这些细胞的进化。此外，我们进一步验证了OMI反应阈值，以预测治疗 在我们最初的目标中，我们确定了一个额外的CRC患者队列。最后，我们将执行一个 多变量分析以评估多个OMI参数与类器官直径变化的组合， 临床影像学缓解、治疗前临床分期、年龄、性别、人种/种族、临床治疗剂量 强度、肿瘤浸润淋巴细胞计数和分子特征作为 这些CRC患者。总的来说，这些额外的目标代表了最初目标的逻辑延伸，将是关键 进一步支持将患者源性类器官的OMI纳入未来的前瞻性临床试验。