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

基本信息

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
项目类别：
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

项目摘要

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.

概括超过 90% 的癌症相关死亡是由转移（癌症从其起源扩散）引起的。当大多数癌症转移在临床上变得可见时，疾病已经发展得太远，无法从癌症转移中获益。早期干预措施，例如手术或放射治疗，因此需要新的方法来进行特定的诊断。非常需要生物标志物来改善治疗结果，例如。细胞外基质 (ECM) 改变、基质成分或免疫成分表现出关键的决定因素在此，该提案的主要目标是汇聚癌症的转移扩散。疾病大厅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开始侵入时，它们会向细胞外改变。申请人着手通过异常蛋白水解活性来分析基质，该活性可用作生物标志物。以某种方式通过转录组学和方法鉴定转移性结直肠癌 (CRC) 中表达的蛋白酶为了提高检测灵敏度，建议将蛋白水解活性整合到蛋白质组分析中。通过重新设计 ECM 靶向纳米抗体来制定酶激活传感器库非凡的肿瘤功效靶向最大目标信号生成（目标 1）。特异性，这些基于活动的传感器的多重性将广泛扩展用于疾病分类使用基于 CRISPR-Cas 的核酸条形码读数对体内 DNA 条形码进行初步研究。透露它们可以作为尿液报告仪进行无创检测，但也可以实现便携式检测纸上谈兵（目标 2）之外，疾病分层和治疗监测也至关重要。因此，将评估新型传感器的非侵入性肿瘤监测和治疗方法。疾病重演转移性 CRC 模型的成像（目标 3）。将提供肿瘤激活响应、基因编码跟踪 (TARGET) 平台可以 1) 推出新的转移特异性肿瘤微环境中的生物学，2）提供一种完全非侵入性的追踪方法肿瘤转移，3) 提供了验证新疗法的管道，这是目前无法实现的该项目需要跨多个领域的创新整合。组建了一支出色的团队来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 Tyler Jacks 博士（麻省理工学院，肿瘤遗传学）， Richard Hynes 博士（麻省理工学院，细胞外基质）、Frank Gertler 博士（麻省理工学院，细胞运动）和 Shawn Chen 博士（NIH，治疗诊断学）在指导委员会的培训期间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的未来原理。这个模块化平台的研究可以应用于其他疾病领域。候选人的长期目标是在癌症背景下开发多尺度工程工具。