A Molecular Diagnostic Assay for Accurately Differentiating Melanoma from Benign Lesions

抽象的。 黑色素瘤是第三种最常见的皮肤癌，估计有87，110例新诊断病例， 美国在2017年。目前的常规诊断方法利用显微镜评价薄 切片的病人活检，但在某些情况下，诊断可能是有争议的，甚至在专家之间。整体 这个多阶段SBIR项目的目标是开发、验证和商业化MelanoMap™，Frontier 诊断的专利检测黑色素瘤的诊断使用基质辅助激光解吸/电离 成像质谱（MALDI IMS）平台，并将此检测方法提供给美国的病理学家。 作为实验室开发的测试。MALDI IMS是一种最先进的技术，可以生成 在一次分析中从组织切片中提取数十到数千个生物分子。该测定使用福尔马林固定的 常规组织病理学诊断中使用的石蜡包埋（FFPE）活检。所提出的测定方法具有 病理学家通过远程网络接口选择皮肤活检的区域进行分析。获取的IMS数据 从这些区域可以明确地识别恶性黑素瘤或良性痣。 本提案的第一阶段将证明这一技术平台的可行性，以实现成本效益 在临床实验室可接受的样本量下，从患者皮肤活检诊断黑素瘤。 具体目标1的重点是开发一个可扩展的和强大的分析协议，在这两个样品 制备和信息学，以准确诊断黑色素瘤与MALDI IMS。在具体目标2中，我们将测试 在特定目标1中开发的方法，用于具有已知临床结果的黑素细胞病变队列 并随后验证所提出的测试的分类准确性 在第二阶段，第一阶段制定的协议将被纳入诊断服务工作流程。这 阶段将侧重于质量控制措施、面向客户端的云软件、临床诊断报告， 完成对500名患者样本集的分析，以进行最终测定验证。本提案的具体目标3 （第二阶段的最初目标）将建立并实施测试组织，以提供标准工作流程， 符合临床实验室改进修正案的检测标准操作的性能指标 （CLIA）标准。将制定方案，以监测试剂、样品制备的重现性， 和质谱仪的性能。Specific Aim 4将扩展软件功能， 一个安全的网络界面，供客户订购测试和实验室执行测试。该软件将 满足法规遵从性，执行统计分析，并生成和传达MALDI报告 IMS分析。具体目标5建议将初始试验中使用的样本集从具体目标2扩展至 包括来自我们临床合作者的一组300名患者样本，具有5年或更长时间的随访数据。的 测试将通过另外200名具有明确诊断的患者样本进行独立验证。

Abstract. Melanoma is the third most common form of skin cancer with estimated 87,110 new cases diagnosed in the United States in the year 2017. Current routine diagnostic approaches utilize microscopic evaluation of thinly sectioned patient biopsies, but in certain cases diagnosis can be contentious even among experts. The overall goal of this multi-phase SBIR project is to develop, validate, and commercialize MelanoMap™, Frontier Diagnostics' patented assay for the diagnosis of melanoma using a matrix-assisted laser desorption/ionization imaging mass spectrometry (MALDI IMS) platform—and to have this assay available to pathologists in the U.S. as a laboratory developed test. MALDI IMS is a state-of-the-art technology that generates molecular images of tens to thousands of biomolecules from tissue sections in a single analysis. The assay uses formalin-fixed paraffin embedded (FFPE) biopsies used in routine histopathological diagnosis. The proposed assay has pathologists select regions of skin biopsies for analysis via a remote web interface. The acquired IMS data from those regions unambiguously identifies malignant melanoma or benign nevus. Phase I of this proposal will demonstrate the feasibility of this technology platform to achieve cost-effective diagnosis of melanoma from patient skin biopsies at sample volumes acceptable for a clinical laboratory. Specific Aim 1 focuses on the development of a scalable and robust analytical protocol in both sample preparation and informatics to accurately diagnose melanoma with MALDI IMS. In specific aim 2, we will test the methodology developed in Specific Aim 1 on a cohort of melanocytic lesions with known clinical outcome and subsequently validate the classification accuracy of the proposed test In Phase II, the protocols developed in Phase I will be integrated into a diagnostic service workflow. This phase will focus on quality control measures, client facing cloud software, clinical diagnostic reporting, and completing the analysis of a 500-patient sample set for final assay validation. Specific Aim 3 of this proposal (initial aim of Phase II) will establish and implement test tissues into standard workflows that will provide performance metrics for standard operation of a test meeting Clinical Laboratory Improvement Amendments (CLIA) standards. Protocols will be developed to monitor reagents, the reproducibility of sample preparation, and mass spectrometer performance on daily basis. Specific Aim 4 will expand software capabilities to include a secure web interface for clients ordering the test and the laboratory performing the test. The software will meet regulatory compliance, perform statistical analysis, and generate and communicate reports of the MALDI IMS analysis. Specific Aim 5 proposes to expand the sample set used in the initial assay from Specific Aim 2 to include a set of 300 patient samples from our clinical collaborators with 5 or more years follow-up data. The test will be independently validated by an additional 200 patient samples with definitive diagnoses.