Developing multiplexed microenvironmental sensors for precision diagnostics of cancer metastasis

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。当大多数癌症转移变得临床可见时，疾病已经进展得太远，无法从手术或放射等早期干预中获益。因此，非常需要获得特异性诊断生物标志物的新方法来改善治疗结果。微环境特征，如细胞外基质（ECM）的改变，基质成分，或免疫成分表现出广泛的癌症转移性传播的关键决定因素。在此，该提案的主要目标是融合疾病标志物和生物分子工程的合理设计，以开发多学科方法来精确诊断癌症转移。当转移瘤开始侵入时，它们通过异常的蛋白水解活性改变细胞外基质，这些蛋白水解活性可以作为生物标志物。申请人着手通过转录组学和蛋白质组学分析系统地鉴定转移性结肠直肠癌（CRC）中表达的蛋白酶。为了提高检测灵敏度，提出了整合蛋白水解活性以通过重新工程化ECM靶向纳米抗体来配制酶激活传感器的文库，所述ECM靶向纳米抗体具有非常好的肿瘤靶向功效以产生最大的靶向信号（Aim 1）。为了优化检测特异性，这些基于活性的传感器的多重性将被广泛扩展，用于使用基于CRISPR-Cas的核酸条形码读出的疾病分类。对体内DNA条形码的初步研究表明，它们可以作为尿液报告基因进行非侵入性检测，但也可以在纸上进行便携式检测（目的2）。除了初步诊断，疾病分层和治疗监测是建立一个强大的治疗至关重要。因此，将在疾病重现转移性CRC模型中评价新型传感器的非侵入性肿瘤监测和成像（目的3）。这三个目标的成功完成将提供一个肿瘤激活响应的遗传编码跟踪（TARGET）平台，可以1）在转移特异性肿瘤微环境中揭示新的生物学，2）提供一种完全无创的方法来跟踪肿瘤转移，3）提供一个验证新疗法的管道，这是目前单一模式药物无法实现的。该项目需要在多个领域进行创新整合。这位候选人组建了一个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）和泰勒杰克斯博士（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）和Shawn Chen博士（NIH，治疗诊断学）。该培训期将使候选人获得肿瘤微环境网络，临床前癌症模型和分析化学方面的经验。将来，这种模块化平台的原理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保持一致，即在癌症背景下开发多尺度工程工具。

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.