Ultra-high content analyses of circulating and solid tumor cells: A diagnostic reference system for disease burden

循环肿瘤细胞和实体肿瘤细胞的超高内涵分析：疾病负担的诊断参考系统

• 批准号: 10259230
• 负责人: Michel Nederlof
• 金额: $ 22.37万
• 依托单位: QUANTITATIVE IMAGING SYSTEMS, LLC
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-08-16 至 2022-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10259230
• 关键词: Address; Age; Antibodies; Architecture; Biological; Biological Markers; Biology; Blood; Blood Tests; Blood specimen; Cancer Patient; Cataloging; Cations; Cell model; Cells; Clinical; Collaborations; Color; Colorectal Cancer; Complex; Computer software; Data Analyses; Derivation procedure; Detection; Development; Diagnostic; Disease; Disease Progression; Early Diagnosis; Ensure; Evaluation; Excision; Foundations; Goals; Gold; Health Sciences; Hybrid Cells; Image; Image Analysis; Immunofluorescence Immunologic; Indirect Immunofluorescence; Individual; Institutes; Label; Link; Malignant Neoplasms; Malignant neoplasm of pancreas; Maps; Methodology; Monitor; Neoplasm Metastasis; Oligonucleotides; Operative Surgical Procedures; Oregon; Pathologic; Patient Care; Patients; Pattern; Periodicity; Phase; Phenotype; Population; Prediction of Response to Therapy; Primary Neoplasm; Process; Proteins; Rectal Cancer; Research; Risk; Sampling; Signal Pathway; Signal Transduction; Small Business Innovation Research Grant; Solid Neoplasm; Specificity; Stains; System; Technology; Testing; Time; Tissue Model; Tissues; Translations; Tumor Tissue; Universities; Validation; Visual; Visualization; Work; antibody conjugate; base; biomarker identification; biomarker panel; burden of illness; cancer cell; cancer type; cell type; cellular imaging; clinical assay development; cohort; colon cancer patients; data visualization; high risk; imaging platform; imaging software; multiplexed imaging; neoplastic cell; novel; peripheral blood; personalized cancer therapy; prognostic assays; protein expression; prototype; spatial relationship; success; symposium; targeted treatment; tool; translational impact; treatment response; tumor; tumor progression; validation studies

ABSTRACT We propose to create a modular suite of products to facilitate highly multiplexed imaging and quantita- tive analyses of individual cells in intact tissue, and cells circulating in blood to be used to establish disease status. Our imaging software analyses platform supporting interactive data visualization will connect protein-based cellular features between tissue resident cells and disseminated cells to lever- age mechanisms of cancer cell dissemination to detect disease earlier, to identify risk for metastases, and to track response to treatment. Our goal is to develop an imaging software analyses platform, biomarker panels for highly multiplexed imaging using cyclic immunostaining and a newly discovered tumor cell population for translation to clinical assay development. Our suite of products will fill an unmet clinical need as no visual platforms exist that can link analyses of individual highly metastatic cells poised to escape the primary tumor with their disseminated counterparts in blood to inform disease status. Our technology has translational impact in developing a non-invasive biomarker for prognosti- cation and for monitoring treatment response in cancer patients. To ensure successful development of a visualization platform with translational potential, we will extend our close partnership with Oregon Health and Science University (OHSU) and strong collaborations at the Knight Cancer Institute for biologic analyses with translation to patient care. We will leverage a novel disseminated tumor popula- tion (i.e., circulating hybrid cells [CHCs]), discovered at OHSU, and a novel cyclic immunofluorescence (cyCIF) technology based on oligonucleotide conjugated antibodies. Currently, little functionality exists to optimally extract the wealth of phenotypic information from highly multiplexed cyCIF images of cells produced on ours or similar staining platforms. Herein, we introduce a novel tool to manage, process, and dynamically visualize such images, with superior single cell analytics even in complex tissue. The proposed labeling platform is the foundation for a new field of advanced multi-parametric analytics that can correlate architectural and functional aspects of intact tissue then apply these finding to corre- sponding cells from blood; a critical aspect of lethal tumor progression. In Phase I, a prototype imaging platform will be built and tested with an integral set of biomarkers for identification of CHC in blood and their corresponding hybrid cell in the primary tumor. Upon confirming feasibility, Phase II will focus on expansion of this technology to address three critical clinical questions: (1) Can cancer be reliably de- tected with a blood test? (2) Can occult metastatic disease be detected in early stage cancers? (3) Can a blood test aid in treatment monitoring to personalize cancer therapy? Successful completion of this work will result in biomarker panels and a software solution to answer these questions as demonstrated in pancreatic and colorectal cancers herein, that can be readily expanded to other cancer types.

抽象的 我们建议创建一个模块化产品套件，以促进高度多路复用的成像和定量 对完整组织中单个细胞的分析，以及用于建立血液中循环的细胞 疾病状况。我们的成像软件分析支持交互式数据可视化的平台将 将基于蛋白质的细胞特征与组织驻留细胞和传播细胞之间连接到杠杆 癌细胞传播的年龄机制早期检测疾病，以确定转移风险， 并跟踪对治疗的反应。我们的目标是开发成像软件分析平台， 使用环状免疫染色和新发现的生物标志物面板用于高度多路复用成像 肿瘤细胞种群转化为临床分析开发。我们的产品套件将填满未满足的 临床需求是由于没有可视平台可以连接单个高度转移细胞的分析 准备逃避原发性肿瘤，并在血液中传播的对应物为疾病提供信息 地位。我们的技术在为预后开发非侵入性生物标志物方面具有翻译影响 阳离子和监测癌症患者的治疗反应。确保成功发展 具有转化潜力的可视化平台，我们将扩展与俄勒冈州的密切合作伙伴关系 卫生与科学大学（OHSU）和骑士癌症研究所的强大合作 将生物学分析转化为患者护理。我们将利用一种新颖的传播肿瘤popula- 在OHSU发现的（即循环杂化细胞[CHC]）和一种新型的环状免疫荧光 （CYCIF）基于寡核苷酸共轭抗体的技术。目前，功能很少 从高度多路复用的Cycif图像中最佳提取大量表型信息 在我们的或类似的染色平台上生产。本文中，我们介绍了一种新颖的工具来管理，处理， 并在复杂的组织中，即使在复杂的组织中，也可以动态地可视化此类图像，并具有优质的单细胞分析。这 拟议的标签平台是一个新的高级多参数分析领域的基础 可以将完整组织的结构和功能方面相关联，然后将这些发现应用于 从血液中挥发细胞；致命肿瘤进展的关键方面。在第一阶段，原型成像 平台将通过一组不可或缺的生物标志物来建立和测试，以识别血液中的CHC和 它们在原发性肿瘤中相应的杂化细胞。确认可行性后，第二阶段将重点关注 该技术的扩展以解决三个关键的临床问题：（1）癌症可以可靠地解决 用血液检查？ （2）可以在早期癌症中检测到神秘转移性疾病吗？ （3）可以 治疗监测以个性化癌症治疗的血液测试？成功完成 工作将导致生物标志物面板和软件解决方案，以回答这些问题 在此处的胰腺和结直肠癌中，可以很容易地扩展到其他癌症类型。