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: 10063499
• 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 2022-11-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10063499
• 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; 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; detection sensitivity; diagnostic biomarker; diagnostic platform; disease classification; efficacy validation; experience; improved; in vivo; innovation; interdisciplinary approach; metastatic colorectal; molecular imaging; mortality; nanobodies; nanosensors; novel; novel strategies; novel therapeutics; organoid transplantation; 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.

总结 超过90%的癌症相关死亡是由转移引起的，即癌症从其起源扩散。 当大多数癌症转移在临床上可见时，疾病已经进展得太远而不能从中受益。 早期干预，如手术或放疗。因此，获得特定诊断的新方法 高度期望生物标志物来改善治疗结果。微环境特征，如 细胞外基质（ECM）改变、基质成分或免疫成分表现出关键决定因素 转移性扩散的可能性。在此，该提案的主要目标是将 疾病霍尔标记和生物分子工程的合理设计，以开发多学科方法 癌症转移的精确诊断。当转移瘤开始侵入时，它们改变了细胞外的 基质通过异常的蛋白水解活性，可以利用作为生物标志物。申请人着手 通过转录组学系统地鉴定转移性结肠直肠癌（CRC）中表达蛋白酶， 蛋白质组学分析为了提高检测灵敏度，建议整合蛋白水解活性， 通过重新工程化靶向ECM的纳米抗体来配制酶激活的传感器库， 对于最大的靶向信号产生（目标1），具有非常高的肿瘤靶向功效。为了优化检测 特异性，这些基于活动的传感器的多重性将被广泛扩展用于疾病分类 使用基于CRISPR-Cas的核酸条形码读数。体内DNA条形码的初步研究 显示它们可以作为尿液报告者非侵入性地检测，但也可以实现便携式检测 在纸上（目标2）。除初步诊断外，疾病分层和治疗监测对于 建立一个强有力的疗法因此，新型传感器将被评估用于非侵入性肿瘤监测， 在疾病再现转移性CRC模型中的成像（目的3）。圆满完成这三个目标 将提供一个肿瘤激活响应，遗传编码跟踪（目标）平台可以1）揭示新的 转移特异性肿瘤微环境的生物学，2）提供一种完全非侵入性的方法来跟踪 肿瘤转移，和3）提供了一个验证新疗法的管道，这是目前无法实现的， 单模态代理。该项目需要在多个领域进行创新整合。这位候选人有 组建了一支出色的团队，帮助她实现技术开发和职业转型的目标， 包括她的导师Sangeeta Bhatia博士（麻省理工学院，医学工程）和泰勒杰克斯博士（麻省理工学院，肿瘤遗传学）， 博士Richard Hynes（MIT，细胞外基质），Frank Gertler博士（MIT，细胞运动）和Shawn Chen博士（NIH， theranostics）在指导委员会。此培训期将使候选人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。今后，原则 这个模块化平台可以应用于其他疾病领域。这里的研究项目与 候选人的长期目标是在癌症背景下开发多尺度工程工具。