Using implantable microdevices for deep phenotyping of multiple drug responses in brain tumor patients

胶质瘤是一种特别侵袭性的脑癌，预后很差，影响到大约20,000名新诊断的患者。 美国每年都有病人。人们对识别对已建立的疾病做出反应的预测性生物标志物很感兴趣 治疗，如替莫唑胺，并确定对新的单一和联合的反应和耐药性生物标志物 胶质瘤的治疗，因为有证据表明有效的辅助治疗策略可以提高存活率 患者的结果。目前几乎没有工具来识别这样的生物标志物并确定给药的优先顺序(S 以期最大限度地发挥药物治疗的效果。 我们将进行一项临床研究，在这项研究中，我们将测量肿瘤对20种不同疗法的反应， 32例患者。仅通过外科手术，可植入的微型装置(IMD)被放置到放置在肿瘤内的 在已经安排好的肿瘤切除过程中，肿瘤在手术期间保留在患者体内，并被取出 以及切除的肿瘤标本。IMD可以读出包括免疫组织化学在内的每种治疗方法， 转录、免疫和组织生物标记物，从而以最小的药物有效地执行20个生物标记物试验 每个患者的暴露水平是三倍重复。 这一项目将取得几项关键进展。第一，技术的安全性、可行性和临床集成性 工作流程将以统计意义重大的方式进行演示。这是建立更广泛的临床应用的关键 这项技术在外科手术环境中的应用。其次，我们将以回顾分析的方式研究IMD 替莫唑胺(TMZ)水库的读数可作为标准全身TMZ治疗的预测标志 每个患者6个月的有效率和无进展生存期。这将是胶质瘤的一个重大进步。 患者，因为TMZ是该病最常使用的辅助治疗，而MGMT启动子 甲基化状态仅是部分胶质瘤患者TMZ疗效的有限预测因子。第三，我们将使用 多重最先进的深层组织表型分析，以表征每个患者肿瘤的生物学反应 接触微型设备上的20种药物。这将产生一个全面的药物表型目录 在GBM患者中有20种不同的治疗方法，我们将使用这些数据来系统地识别耐药途径 可用的治疗方法。此外，通过检查肿瘤的遗传和生理变化，我们可以在体内进行关联 现有的肿瘤对多种药物的“组学”生物标记物。这解决了该领域的一个主要知识差距，因为 这样的数据集在传统的系统性临床试验中是不可行的。药物表型包括空间表型 转录组学和代谢组学，以确定肿瘤微环境中与 对每种治疗的高和低表型反应。这项研究将为证明局部肿瘤内瘤奠定基础 对多种药物微剂量的反应可用于有效筛查和量身定制脑胶质瘤的最佳治疗方案 病人。评估IMD对治疗选择的预测价值为作为精确度的更广泛使用打开了大门 改善神经胶质瘤预后的药物和药物开发工具。

Gliomas are a particularly aggressive type of brain cancer with poor prognosis that affect about 20,000 newly diagnosed patients in the US annually. There is high interest in identifying predictive biomarkers of response to established treatments such as Temozolomide, and to identify response and resistance biomarkers for new single and combinations treatments for gliomas, as there is evidence that an effective adjuvant treatment strategy can improve survival outcomes for patients. Few tools exist currently to identify such biomarkers and prioritize which agent(s) to administer to individual patients in order to maximize the impact of drug treatment. We will conduct a clinical study in which we measure the tumor responses to 20 distinct therapies across a cohort of 32 patients. Using only intrasurgical procedures, implantable microdevices (IMD) are placed into tumors placed into tumors during already scheduled tumor resections, remain in the patient for the duration of surgery, and are extracted along with the resected tumor specimen. IMDs enable readouts for each treatment that include immunohistochemical, transcriptomic, immune and tissue biomarkers, thereby effectively performing 20 biomarker trials at minute drug exposure levels in each patient with three-fold replicates. Several key advances will be achieved in this project. First, safety, feasibility and clinical integration of the technical workflow will be demonstrated in a statistically significant manner. This is key towards establishing broader clinical use for this technology in the intrasurgical setting. Secondly, we will examine in a retrospective analysis whether the IMD readout at Temozolomide (TMZ) reservoirs can serve as a predictive marker for standard systemic TMZ treatment response and progression-free survival at 6 months for each patient. This would constitute a major advance for glioma patients, as TMZ is the most frequently administered adjuvant treatment in this disease, and the MGMT promoter methylation status is only a limited predictor of TMZ efficacy for a subset of glioma patients. Third, we will use multiplexed state-of-the-art deep tissue phenotyping to characterize the biological response of each patient’s tumor exposed to each of 20 drugs on the microdevice. This will result in a comprehensive catalogue of drug phenotypes for 20 distinct therapies in GBM patients, and we will use this data to systematically identify resistance pathways to available therapies. In addition, by examining the tumor for genetic and physiologic changes, we can in vivo correlate existing ‘omic’ biomarkers of tumor response to multiple drugs. This addresses a major knowledge gap in the field, as such a dataset is not feasible to obtain with traditional systemic clinical trials. The drug phenotyping includes spatial transcriptomics and metabolomics to identify specific biomarkers in the tumor microenvironment that correlate with high and low phenotypic response to each therapy. This study will lay the ground work to prove that local intratumor response to microdoses of multiple agents can be used to effectively screen for and tailor optimal treatment for glioma patients. Assessing the predictive value of the IMD for therapy selection opens the door to broader use as a precision medicine and drug development tool to improve outcomes in glioma.