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

摘要 我们建议创建一套模块化的产品，以促进高度多路传输的成像和量化- 对完整组织中单个细胞和血液中循环细胞的动态分析将用于建立 疾病状况。我们的成像软件分析平台支持交互式数据可视化 将组织驻留细胞和播散细胞之间基于蛋白质的细胞特征连接到水平- 癌细胞扩散的年龄机制，以更早地发现疾病，识别转移的风险， 并追踪对治疗的反应。我们的目标是开发一个成像软件分析平台， 利用循环免疫染色进行高度多重成像的生物标记板和一种新发现的 肿瘤细胞群转化为临床检测方法的发展。我们的产品套件将填补未满足的需求 临床需要，因为不存在可以链接单个高转移细胞分析的可视平台 准备逃脱原发肿瘤与其在血液中播散的对应物告知疾病 状态。我们的技术在开发一种非侵入性生物标志物用于预测- 阳离子和监测癌症患者的治疗反应。为确保成功开发 作为一个具有翻译潜力的可视化平台，我们将扩大与俄勒冈州的密切合作伙伴关系 健康与科学大学(OHSU)与奈特癌症研究所的强大合作 生物学分析与病人护理的转换。我们将利用一种新的播散性肿瘤人群- OHSU发现的循环杂交细胞和一种新的循环免疫荧光 基于寡核苷酸结合抗体的(CyCIF)技术。目前，几乎没有什么功能存在 从高度多元化的细胞cyCIF图像中最佳地提取丰富的表型信息 在我们的或类似的染色平台上生产。在这里，我们介绍了一种新的工具来管理、处理 即使在复杂的组织中，也可以使用卓越的单细胞分析来动态可视化这些图像。这个 建议的标记平台是高级多参数分析的新领域的基础 可以将完整组织的结构和功能方面联系起来，然后将这些发现应用于相关的 血液中的应答细胞；致命肿瘤进展的关键方面。在第一阶段，原型成像 将建立一套完整的生物标志物平台并进行测试，以识别血液和 它们在原发肿瘤中的相应杂交细胞。在确认可行性后，第二阶段将重点放在 这项技术的扩展以解决三个关键的临床问题：(1)癌症能否可靠地消除 验血？(2)早期癌症能发现隐匿性转移疾病吗？(3)能 血液检测辅助治疗监测，以实现癌症治疗的个性化？成功完成这项工作 工作将产生生物标记物面板和软件解决方案，以回答这些问题，如演示 在这里的胰腺癌和结直肠癌中，它可以很容易地扩展到其他类型的癌症。

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.