Desorption Electrospray Ionization Mass Spectrometry Imaging in Clinical Diagnost

描述(申请人提供)：将评估一种基于质谱学(MS)的组织诊断方法，以区分肾癌、膀胱癌和睾丸癌的存在、类型和分级。基于溶剂的解吸电喷雾电离(DESI)MS方法将被用于直接检查组织，由此产生的脂类衍生离子的分布将被用于表征组织的疾病状态。这将通过建立与不同疾病状态和级别的组织相关的脂质离子强度的典型模式的数据库来促进。独立的组织特征将由标准的组织病理学方法进行。将使用多元统计工具来评估DESI-MS成像数据，并将开发软件工具来将DESI分子图像与H&E染色的光学图像相关联。(这方面的工作将由统计学家和生物信息学专家Olga Vitek教授领导。)将特别注意在形态上非破坏性的DESI溶剂，因此允许在外科工作流程中的任何点插入DESI成像。这项工作背后的假设是，提供的关于组织中脂质分布的分子信息是恶性肿瘤的诊断，并补充了使用组织病理学对肿瘤边缘的评估。为了测试DESI-MS作为外科应用的诊断工具的能力，我们将在印第安纳大学医学院的病理实验室中安装一台配备了DESI的质谱仪。在那里，将与病理学家(梁成博士)合作，使用外科医生(蒂莫西·马斯特森博士)提供的样本进行DESI方法的测试。实验将分三个阶段进行：a)在不干扰外科干预中使用的标准程序的情况下，对切除的组织进行离线分析。组织将被喷洒一种溶剂，并对质谱图进行评估，以得出诊断结果(癌症及其级别；或正常)。这些结果将与标准组织病理学的诊断结果进行比较。B)在线组织切片成像将与标准病理检查并行使用，以验证DESI-MS在手术时间尺度上提供病理信息的能力。这些实验将被用来验证/无效Desi-MS成像，作为临床组织分析工作流程中用于肿瘤边缘评估的主要步骤。C)手术中切除组织的快速在线DESI分析将用于检查切除组织的表面是否没有肿瘤边缘。通过使用索引系统，任何未完全切除的癌症组织的位置都将在适合手术修复的时间尺度上进行定位。在为未来的发展做准备，其中MS将用于外科套件，小型质谱仪的性能将得到改进，以允许在单位分辨率下进行质量为1000Da的脂肪分析。

DESCRIPTION (provided by applicant): A method of tissue diagnosis based on mass spectrometry (MS) will be evaluated to distinguish the presence, type and grade of kidney, bladder and testicular cancers. The solvent-based method of desorption electrospray ionization (DESI) MS will be used to examine tissue directly and the resulting distribution of lipid-derived ions will be used to characterize the disease state of the tissue. This will be facilitated by building a data base of representative patterns of lipid ion intensities associated with tissue of different disease states and grades. Independent tissue characterization will be made by the standard methods of histopathology. Multivariate statistical tools will be used to evaluate the DESI-MS imaging data and software tools will be developed to correlate DESI molecular images with H&E stained optical images. (This aspect of the work will be led by Prof. Olga Vitek, a statistician and specialist in bioinformatics.) Special attention will be given to DESI solvents tht are morphologically non-destructive, so allowing DESI imaging to be inserted at any point in the surgical work-flow. The hypothesis underlying this effort is that the molecular information provided on lipid distributions in tissue is diagnostic of malignancy and complements the evaluation of tumor margins using histopathology. To test the capabilities of DESI-MS as a diagnostic tool for surgical applications, we will locate a DESI- equipped mass spectrometer in an Indiana University School of Medicine pathology laboratory. There, tests of the DESI method will be made in collaboration with a pathologist (Dr. Liang Cheng) using samples provided by a surgeon (Dr. Timothy Masterson). The experiments will occur in three stages: a) Off-line analysis of excised tissue without interfering with standard procedures used in surgical intervention. Tissue will be sprayed with a solvent and the mass spectra will be evaluated to reach a diagnosis (cancer, and its grade; or normal). These results will be compared with diagnoses obtained by standard histopathology. b) On-line tissue section imaging in parallel with standard pathology examination will be used to validate the capability of DESI-MS to yield pathological information on the time-scale of the surgery. These experiments will be used to validate/invalidate DESI-MS imaging as the primary step in clinical tissue- analysis workflow for tumor margin assessment. c) Rapid on-line DESI analysis of excised tissue during surgery will be used to check that the surface of resected tissue is clean of tumor margins. By using an indexing system the position of any incompletely removed cancerous tissue will be localized on a time scale suitable for surgical remediation. In preparation for future developments in which MS is utilized in the surgical suite, the performance of a small mass spectrometer will be improved to allow lipid analysis to mass 1000 Da at unit resolution.