A Molecular Diagnostic Assay for Accurately Differentiating Melanoma from Benign Lesions

准确区分黑色素瘤和良性病变的分子诊断方法

• 批准号: 9926849
• 负责人: DAVID L HACHEY
• 金额: $ 94.45万
• 依托单位: FRONTIER DIAGNOSTICS, LLC
• 依托单位国家: 美国
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-08-01 至 2021-12-15
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9926849
• 关键词: Antigens; Area; Benign; Biological Assay; Biopsy; Caliber; Cells; Classification; Client; Clinical; Clinical Laboratory Improvement Amendments; Computer software; Custom; Data; Data Analyses; Detection; Development; Diagnosis; Diagnostic; Diagnostic Services; Digestion; Early Diagnosis; Ensure; Evaluation; Formalin; Goals; Gold; Image; Incentives; Informatics; Laboratories; Legal patent; Lesion; Mass Spectrum Analysis; Measures; Metadata; Methodology; Microscopic; Microtomy; Monitor; Nevus; Outcome; Paraffin Embedding; Pathologist; Pathology Report; Patient Care; Patients; Performance; Phase; Phase I Clinical Trials; Phase II Clinical Trials; Physical shape; Physicians; Preparation; Procedures; Proteins; Protocols documentation; Quality Control; Reagent; Reporting; Reproducibility; Research; Retrieval; Sampling; Secure; Security; Sensitivity and Specificity; Side; Skin; Skin Cancer; Small Business Innovation Research Grant; Software Tools; Spectrometry, Mass, Matrix-Assisted Laser Desorption-Ionization; Standardization; Statistical Data Interpretation; Technology; Testing; Time; Tissues; Training; Treatment Cost; United States; Validation; accurate diagnosis; analytical method; base; clinical diagnostics; cloud software; cohort; cost; cost effective; data acquisition; diagnosis standard; diagnostic assay; disease classification; follow-up; frontier; histopathological examination; instrumentation; interest; large datasets; machine learning algorithm; mass spectrometer; meetings; melanoma; molecular diagnostics; molecular imaging; mortality risk; operation; prototype; quality assurance; skin lesion; tissue preparation; web interface

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.

抽象的。 黑色素瘤是皮肤癌的第三大常见形式，估计有87,110例在 美国在2017年。当前的常规诊断方法利用微小评估 分区患者活检，但在某些情况下，诊断即使在专家中也可能是有争议的。总体 这个多相SBIR项目的目标是开发，验证和商业化Melanomap™，Frontier 使用基质辅助激光解吸/电离，诊断为诊断黑色素瘤的专利测定法 成像质谱（MALDI IMS）平台，并将此测定可用于美国病理学家 作为实验室开发的测试。 Maldi IMS是一种最先进的技术，生成了分子图像 在单个分析中，来自组织切片的成千上万生物分子。该测定使用福尔马林固定 石蜡嵌入（FFPE）活检中用于常规组织病理学诊断。拟议的测定法 病理学家选择皮肤活检的区域，用于通过远程Web界面进行分析。获得的IMS数据 从这些区域明确识别出恶性黑色素瘤或良性柳。 该提案的第一阶段将证明该技术平台的可行性以实现成本效益 在接受临床实验室接受的样本体积的患者皮肤活检中诊断黑色素瘤。 具体目标1侧重于在两个样本中开发可扩展和可靠的分析方案 准备和信息信息可以准确诊断出使用MALDI IMS诊断黑色素瘤。在特定目标2中，我们将测试 在特定目标1中开发的方法1在一系列具有已知临床结果的黑素细胞病变中 随后验证拟议测试的分类精度 在第二阶段，将在第一阶段制定的协议将集成到诊断服务工作流程中。这 阶段将专注于质量控制措施，面向云软件的客户，临床诊断报告以及 完成对最终评估验证的500名患者样本集的分析。该提案的特定目标3 （第二阶段的初始目标）将建立并将测试组织建立到标准工作流中，以提供 测试会议临床实验室改进修订的标准操作的标准操作绩效指标 （CLIA）标准。将开发协议以监视试剂，样品制备的可重复性， 和质谱仪每天的性能。特定目标4将扩展软件功能以包括 一个安全的Web界面，适用于订购测试的客户和执行测试的实验室。该软件将 满足法规合规性，进行统计分析，并生成和传达MALDI的报告 IMS分析。特定的目标5提案将初始评估中使用的样本集从特定目标2扩展到 在我们的临床合作者中包含一组300名患者样本，并提供5年或更长时间的随访数据。这 测试将由其他200个具有明确诊断的患者样本独立验证。

项目成果

Diagnosis of melanoma by imaging mass spectrometry: Development and validation of a melanoma prediction model.

• DOI: 10.1111/cup.14083
• 发表时间: 2021-12
• 期刊: Journal of cutaneous pathology
• 影响因子: 1.7
• 作者: Al-Rohil RN;Moore JL;Patterson NH;Nicholson S;Verbeeck N;Claesen M;Muhammad JZ;Caprioli RM;Norris JL;Kantrow S;Compton M;Robbins J;Alomari AK
• 通讯作者: Alomari AK