Developing multiplexed microenvironmental sensors for precision diagnostics of cancer metastasis

开发用于癌症转移精确诊断的多重微环境传感器

• 批准号: 9891722
• 负责人: Liangliang Hao
• 金额: $ 10.13万
• 依托单位: MASSACHUSETTS INSTITUTE OF TECHNOLOGY
• 依托单位国家: 美国
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-12-01 至 2021-11-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9891722
• 关键词: Address; Analytical Chemistry; Anatomy; Architecture; Area; Bar Codes; Benchmarking; Biological; Biological Assay; Biological Markers; Biology; Biosensor; Blood; CRISPR/Cas technology; Cancer Etiology; Cancer Model; Career Mobility; Cause of Death; Characteristics; Clinic; Clinical; Clustered Regularly Interspaced Short Palindromic Repeats; Colorectal Cancer; Complement; Complex; DNA; Dependence; Detection; Development; Diagnosis; Diagnostic; Diagnostic Sensitivity; Diffuse; Disease; Disease stratification; Early Diagnosis; Emission-Computed Tomography; Engineering; Enzymes; Evaluation; Excision; Exhibits; Extracellular Matrix; Fostering; Future; Generations; Genetic; Goals; Homing; Human; Image; Imaging Device; Imaging Techniques; Immune; Immunoglobulin Fragments; In Vitro; Injectable; Intervention; Invaded; Investigation; Lesion; Libraries; Light; Malignant Neoplasms; Medical; Medical Imaging; Mentors; Modality; Molecular; Molecular Profiling; Monitor; Mutation; Neoplasm Metastasis; Non-Invasive Cancer Detection; Nucleic Acids; Oligonucleotides; Oncology; Operative Surgical Procedures; Organoids; Paper; Patients; Peptide Hydrolases; Peptides; Positron-Emission Tomography; Precision therapeutics; Primary Neoplasm; Property; Proteomics; Radiation; Recombinants; Reporter; Reporting; Research; Resources; Sampling; Sensitivity and Specificity; Signal Transduction; Site; Specificity; Survival Rate; Testing; Therapeutic; Time; Training; United States National Institutes of Health; Urine; Validation; Visualization; X-Ray Computed Tomography; base; cancer cell; cancer diagnosis; cancer type; cell motility; colorectal cancer metastasis; colorectal cancer screening; design; diagnostic biomarker; disease classification; experience; improved; in vivo; innovation; interdisciplinary approach; metastatic colorectal; molecular imaging; mortality; nanobodies; nanosensors; novel; novel strategies; novel therapeutics; personalized approach; personalized diagnostics; point-of-care diagnostics; portability; pre-clinical; precision medicine; programs; response; scaffold; sensor; technology development; theranostics; therapy outcome; tool; trafficking; transcriptomics; transplant model; treatment response; treatment strategy; tumor; tumor heterogeneity; tumor microenvironment; urinary

Summary More than 90% of all cancer-related deaths are caused by metastasis, the spread of cancer from its origin. By the time most cancer metastases become clinically visible, the disease has progressed too far to benefit from early-stage interventions such as surgery or radiation. Thus, new approaches accessing specific diagnostic biomarkers are highly desired to improve therapeutic outcomes. Microenvironmental signatures such as extracellular matrix (ECM) alterations, stromal composition, or immune components exhibit critical determinants of metastatic dissemination broadly across cancers. Herein, the main goal of this proposal is to converge the disease hall markers and rational design of biomolecular engineering to develop multidisciplinary approaches towards precision diagnostics of cancer metastasis. As metastases start to invade, they alter the extracellular matrix through aberrant proteolytic activities that could be leveraged as biomarkers. The applicant set out to systematically identify proteases expressed in metastatic colorectal cancer (CRC) by transcriptomic and proteomic analysis. To improve the detection sensitivity, it is proposed to integrate the proteolytic activity to formulate a library of enzyme activated sensors by reengineering the ECM targeting nanobody with extraordinarily tumor targeting efficacy for maximal on-target signal generation (Aim 1). To optimize the detection specificity, the multiplexity of these activity-based sensors will be extensively expanded for disease classification using CRISPR-Cas-based nucleic acid barcode readout. Preliminary investigation into the in vivo DNA barcodes revealed that they could be detected noninvasively as a urinary reporter, but could also enable portable detection on paper (Aim 2). Beyond initial diagnosis, disease stratification and treatment monitoring are critical to establishing a robust therapy. The novel sensors will thus be evaluated for noninvasive tumor monitoring and imaging in disease recapitulating metastatic CRC models (Aim 3). Successful completion of these three aims would offer a tumoral activation responsive, genetically encoded tracking (TARGET) platform can 1) unveil new biology at the metastasis-specific tumor microenvironment, 2) provide a completely noninvasive way to track tumor metastasis, and 3) offer a pipeline for validating novel therapies, which are currently unachievable by single modality agents. This project requires innovative integration across several fields. The candidate has assembled an exceptional team to help her achieve the goals of technology development and career transition, including her mentor Dr. Sangeeta Bhatia (MIT, medical engineering) and Drs. Tyler Jacks (MIT, tumor genetics), Dr. Richard Hynes (MIT, extracellular matrix), Dr. Frank Gertler (MIT, cell motility) and Dr. Shawn Chen (NIH, theranostics) on the mentoring committee. This training period will allow the candidate to gain experience in tumor microenvironment network, pre-clinical cancer models and analytical chemistry. In the future, the principles of this modular platform could apply to other disease areas. The research program here aligns well with the candidate’s long-term goal to develop multi-scale engineered tools in the context of cancer.

摘要 在所有与癌症相关的死亡中，90%以上是由转移造成的，转移是癌症从起源扩散而来。 当大多数癌症转移变得临床可见时，这种疾病已经进展得太远了，无法从中受益 早期干预，如手术或放射治疗。因此，访问特定诊断的新方法 生物标记物是改善治疗结果的迫切需要。微环境特征，如 细胞外基质(ECM)改变、基质成分或免疫成分显示出关键的决定因素 在癌症中广泛传播的转移性。在这里，这项建议的主要目标是将 疾病霍尔标志物和生物分子工程的合理设计发展多学科方法 癌症转移的精确诊断。当转移瘤开始侵入时，它们会改变细胞外 基质通过异常的蛋白分解活动，可以被用作生物标记物。申请者出发去 系统鉴定转移性结直肠癌(CRC)中表达的蛋白 蛋白质组学分析。为了提高检测灵敏度，建议将蛋白水解性结合到 通过对靶向纳米体的ECM进行重组来构建酶激活传感器文库 非凡的肿瘤靶向效能，可产生最大的靶向信号(目标1)。要优化检测 特异性，这些基于活动的传感器的多样性将被广泛扩展用于疾病分类 使用CRISPR-CAS为基础的核酸条形码读出。活体DNA条码的初步研究 据透露，它们可以作为尿路报告器进行非侵入性检测，但也可以进行便携式检测 纸面上(目标2)。除了最初的诊断，疾病分层和治疗监测对于 建立一种强有力的治疗方法。因此，这种新型传感器将被评估为非侵入性肿瘤监测和 重现转移性结直肠癌模型的疾病成像(目标3)。圆满完成这三个目标 将提供一个肿瘤激活响应性的、基因编码的跟踪(靶标)平台可以推出新的 生物学在肿瘤转移中的特异性微环境，2)提供了一种完全无创的追踪方式 肿瘤转移，以及3)提供了验证新疗法的管道，这些新疗法目前无法通过 单通道坐席。该项目需要跨多个领域的创新集成。候选人有 组建了一支出色的团队，帮助她实现了技术发展和职业转型的目标， 包括她的导师Sangeeta Bhatia博士(麻省理工学院医学工程)和Tyler Jack博士(麻省理工学院肿瘤遗传学)， 理查德·海因斯博士(麻省理工学院，细胞外基质)、弗兰克·格特勒博士(麻省理工学院，细胞运动学)和肖恩·陈博士(美国国立卫生研究院， Theranostics)在指导委员会。此培训期间将使应聘者获得以下方面的经验 肿瘤微环境网络、临床前癌症模型和分析化学。在未来，这些原则 这一模块化平台的设计可以应用于其他疾病领域。这里的研究计划与 候选人的长期目标是在癌症的背景下开发多尺度的工程工具。