Development of an Indicator Cell Assay for blood-based diagnosis of lung cancer

 描述(申请人提供)：我们正在开发指示细胞分析平台(ICAP)，这是一个广泛适用且廉价的基于血液的分析，可用于疾病的早期检测、疾病阶段分层、预后和对各种疾病的治疗干预反应。ICAP使用培养细胞作为生物传感器，利用细胞对正常或疾病受试者血清(或其他生物液)中存在的信号做出不同反应的能力，具有极高的敏感度，而不是依赖于直接检测血液中分子的传统检测方法。开发ICAP涉及将培养的细胞暴露于正常或疾病受试者的血清中，测量全球差异反应模式，并使用它来建立由少量特征组成的可靠的疾病分类器。部署ICAP涉及使用具有成本效益的工具仅测量作为疾病分类器特征的表达基因。指示细胞是根据疾病的应用来选择的，那些通常被选择的细胞与疾病病理有已知的关系。ICAP可以克服血液诊断的障碍，如血液成分的动态范围宽、特定标记物的丰度低和噪音水平高。这项提议的重点是启动基于血液的肺癌(LC)ICAP的开发。LC的血液生物标记物迫切需要与现有的成像工具结合使用，以提高诊断的准确性。我们的长期目标是开发一种基于血液的检测方法，用于临床应用于通过成像识别出不确定肺结节的患者，以区分LC患者和良性结节患者。这项检测将帮助良性结节患者避免侵入性活检，并将进一步的诊断测试集中在LC患者身上。对于这项I期研究，我们建议开发一种方法来可靠地区分LC和患者血清样本中的良性结节。具体地说，我们的目标是：1)确定最佳指标单元 2)开发基于ICAP的分类器，使用患者血清可靠地区分肺癌患者和良性结节患者；3)通过分析新的血清样本来验证该方法。如果我们成功地实现了稳健的分类，90%的盲目预测准确率和70%的灵敏度和特异度，该分析将得到优化，并在II期研究中用更大的队列进行验证。

 DESCRIPTION (provided by applicant): We are developing the Indicator Cell Assay Platform (iCAP), a broadly applicable and inexpensive blood- based assay that can be used for early detection of disease, disease stage stratification, prognosis and response to therapeutic intervention for a variety of diseases. The iCAP uses cultured cells as biosensors, capitalizing on the ability of cells to respond differently to signals present in the serum (or other biofluid) from normal or diseased subjects with exquisite sensitivity, as opposed to traditional assays that rely on direct detection of molecules in blood. Developing the iCAP involves exposing cultured cells to serum from normal or diseased subjects, measuring a global differential response pattern, and using it to build a reliable disease classifier comprised of a small number of features. Deploying the iCAP involves measuring only expression genes that are features of the disease classifier using cost-effective tools. Indicator cells are chosen based on the disease application, and those typically selected have known relationships to the disease pathology. The iCAP can overcome barriers to blood-based diagnostics like broad dynamic range of blood components, low abundance of specific markers, and high levels of noise. The focus of this proposal is to initiate development of the iCAP for blood-based diagnosis of lung cancer (LC). Blood biomarkers of LC are desperately needed for use in combination with existing imaging tools to improve diagnostic accuracy. Our long-term goal is to develop a blood-based assay for clinical use on patients that have indeterminate pulmonary nodules identified by imaging to distinguish those with LC from those with benign nodules. This assay will help patients with benign nodules avoid invasive biopsy and focus further diagnostic tests on those with LC. For this Phase I study, we propose to develop an assay to reliably distinguish LC from benign nodules from patient serum samples. Specifically, we aim to 1) identify optimal indicator cells for the assay, 2) develop an iCAP-based classifier to reliably distinguish patients with lung cancer from those with benign nodules using patient serum, and 3) validate the assay by analyzing new serum samples. If we successfully achieve robust classification with >90% blind predictive accuracy and 70% sensitivity and specificity, the assay will be optimized and validated with larger cohorts in a Phase II study.