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

神经胶质瘤是一种特别具有侵袭性的脑癌，预后较差，影响了大约 20,000 名新诊断的脑癌患者 美国每年都有患者。人们对识别已建立的反应的预测生物标志物非常感兴趣。 替莫唑胺等治疗方法，并确定新的单一药物和组合的反应和耐药生物标志物 神经胶质瘤的治疗，因为有证据表明有效的辅助治疗策略可以提高生存率 患者的结果。目前很少有工具可以识别此类生物标志物并优先考虑要施用的药物 以便最大限度地发挥药物治疗的影响。 我们将进行一项临床研究，测量一组受试者中 20 种不同疗法的肿瘤反应 32名患者。仅使用外科手术程序，将可植入微型设备 (IMD) 植入肿瘤中 在已安排的肿瘤切除术中，肿瘤在手术期间保留在患者体内并被取出 连同切除的肿瘤标本。 IMD 可读取每种治疗方法，包括免疫组织化学、 转录组、免疫和组织生物标志物，从而有效地在分钟内进行 20 个生物标志物试验 每个患者的暴露水平重复三倍。 该项目将取得几项关键进展。一、技术的安全性、可行性和临床结合性 工作流程将以统计上显着的方式进行演示。这是建立更广泛临床应用的关键 用于外科手术环境中的这项技术。其次，我们将回顾性分析 IMD 是否 替莫唑胺 (TMZ) 储库的读数可作为标准全身 TMZ 治疗的预测标记 每位患者 6 个月时的缓解和无进展生存期。这将构成神经胶质瘤的重大进展 患者，因为 TMZ 是该疾病最常用的辅助治疗方法，而 MGMT 启动子 甲基化状态只是 TMZ 对部分神经胶质瘤患者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来表征每位患者肿瘤的生物反应 暴露于微型装置上的 20 种药物中的每一种。这将产生一个全面的药物表型目录 GBM 患者有 20 种不同的疗法，我们将使用这些数据来系统地识别耐药途径 可用的疗法。此外，通过检查肿瘤的遗传和生理变化，我们可以在体内将 肿瘤对多种药物反应的现有“组学”生物标志物。这解决了该领域的一个主要知识空白，因为 通过传统的系统临床试验无法获得这样的数据集。药物表型分析包括空间 转录组学和代谢组学，以确定肿瘤微环境中与相关的特定生物标志物 对每种疗法的高和低表型反应。这项研究将为证明局部肿瘤内 对多种药物微剂量的反应可用于有效筛选和定制神经胶质瘤的最佳治疗 患者。评估 IMD 对治疗选择的预测价值为更广泛的应用打开了大门 改善神经胶质瘤治疗效果的医学和药物开发工具。

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.