DIAGNOSTIC TEST FOR METASTATIC KIDNEY CANCER

转移性肾癌的诊断测试

• 批准号: 9688628
• 负责人: STEPHEN CARRITHERS
• 金额: $ 30万
• 依托单位: LAGRANGE SCIENTIFIC, LLC
• 依托单位国家: 美国
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-09-14 至 2020-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9688628
• 关键词: Address; Adjuvant Therapy; Affect; Aging; Aldehydes; American; American Joint Committee on Cancer; Amines; Biological Markers; Biopsy; Blinded; Bromides; Calibration; Carboxylic Acids; Characteristics; Chemical Structure; Chemicals; Chlorides; Choking; Clear cell renal cell carcinoma; Clinical; Clinical Chemistry; Clinical Data; Clinical Trials; Complex; Complication; Computer software; Data; Databases; Development; Diagnosis; Diagnostic tests; Disease; Disease Progression; Enrollment; Ensure; Epidemiologist; Excision; FDA approved; Genomics; Goals; Health Care Research; Histology; Histopathology; Human; Image; Indolent; Intervention; Ions; Isotope Labeling; Ketones; Kidney Neoplasms; Label; Laboratories; Letters; Malignant Neoplasms; Mass Spectrum Analysis; Measures; Metabolic; Methodology; Methods; Modeling; Molecular Weight; Neoplasm Metastasis; Normal tissue morphology; Oncologist; Operative Surgical Procedures; Outcome; Pathologist; Patients; Performance; Pharmacotherapy; Phase; Phenols; Physicians; Plague; Preparation; Primary Neoplasm; Process; Proteomics; Protocols documentation; Regulatory Pathway; Renal carcinoma; Research Personnel; Resected; Risk; Running; Sampling; Sampling Studies; Series; Side; Signal Transduction; Small Business Innovation Research Grant; Staging; Statistical Methods; Surgeon; Survival Rate; TNM; Testing; Tissue Extracts; Tissues; Tumor Tissue; Update; Virginia; Vital Status; base; biobank; biomarker panel; biomarker validation; blind; cancer heterogeneity; clinical application; cohort; follow-up; hazard; high risk; human disease; human tissue; instrument; ionization; liquid chromatography mass spectrometry; medical schools; metabolic profile; metabolome; metabolomics; novel; patient population; phase 2 study; predictive marker; predictive test; prognostic; prognostic assays; prospective; research and development; research clinical testing; sugar; testing services; tumor; tumor heterogeneity; tumor progression

ABSTRACT The goal of this Phase I SBIR is to address the absence of measureable and targeted metabolite biomarkers in clear cell renal cell carcinoma (ccRCC) tissues that can predict disease metastasis. An estimated 69,990 Americans were diagnosed with kidney cancer in 2017, and approximately 14,400 died as a result of ccRCC, primarily due to metastasis of the cancer. Ultimately, we seek to identify those patients with more aggressive renal cancers that might benefit from more aggressive treatment. Patients with indolent ccRCC may choose less aggressive treatment while those with a greater risk of metastasis may elect adjuvant therapy that may include drug treatments. There are no diagnostic tests that predict post-surgical disease progression on the market. Our methodology will utilize novel liquid chromatography (LC) and mass spectrometry (MS) methods developed by our collaborators, along with several new methods we developed that will greatly increase quantitative accuracy and robustness. This will address a series of issues that have plagued the development of a reliable biomarker panel for the diagnosis of renal cancer progression and metastasis. A major problem with metabolomic studies to date is that the heterogeneity of cancer tissues is frequently overlooked. Thus, an important part of our approach includes normalization, calibration, and quantitation of metabolites in both discovery and targeted modes. Specifically, our method allows for the analysis of metabolites in small biopsies and will permit histopathology to be performed on exactly the same tissue. Whereas normalization and quantitation are usually addressed after data has been acquired, i.e. post- acquisition, we add pre-acquisition normalization, which will ensure that equal amounts of sample are injected for MS. Our use of chemical labeling and sample normalization will minimize the effects of ion suppression, signal saturation, column contamination, aging, and instrument performance drift. Essentially, the day-to-day and lab-to-lab variability, which frequently affect MS, will be minimized. In this proposal, we will utilize the Eastern Virginia Medical School Biorepository PROBE cohort, which houses over 300 renal tumors and associated clinical data, including treatment, vital status, imaging data, and longitudinal follow-up after primary tumor resection. The database accompanying the Biorepository is regularly updated, allowing us to identify those who “progressed” vs. those who are termed “non-progressors”. For this Phase I proof-of-concept study, tissues from 26 patients that developed metastasis will be analyzed and compared to 174 patients that did not develop metastasis (n=200 patients). All tumor tissues – primary and metastatic – will be paired with “normal” tumor-adjacent tissue from clear margins. In addition, larger numbers of patients in the cohort will be analyzed using available histopathological and staging data as surrogates for clinical outcome. A side benefit to this study is the prospective addition to our ccRCC bank for Phase II studies.

摘要 本I期SBIR的目标是解决缺乏可测量和靶向代谢物的问题 透明细胞肾细胞癌（ccRCC）组织中的生物标志物可以预测疾病转移。一个 据估计，2017年有69，990名美国人被诊断出患有肾癌，约有14，400人死于肾癌。 ccRCC的结果，主要是由于癌症的转移。最终，我们寻求识别这些患者， 可能从更积极的治疗中受益的更积极的肾癌。无痛症患者 ccRCC可能选择侵袭性较低的治疗，而转移风险较高的患者可能选择辅助治疗。 治疗，可能包括药物治疗。 市场上没有预测手术后疾病进展的诊断测试。我们 方法学将利用由以下公司开发的新型液相色谱（LC）和质谱（MS）方法： 我们的合作者，沿着我们开发的几种新方法，将大大提高定量 准确性和鲁棒性。这将解决一系列问题，一直困扰着发展一个可靠的 用于诊断肾癌进展和转移的生物标志物组。 迄今为止，代谢组学研究的一个主要问题是， 经常被忽视。因此，我们的方法的一个重要部分包括标准化，校准， 在发现和靶向模式下定量代谢物。具体来说，我们的方法允许 分析小活检中的代谢物，并将允许对完全相同的组织进行组织病理学检查。 组织.而标准化和定量通常是在获得数据之后，即， 采集时，我们添加采集前归一化，这将确保注入等量的样品 对于MS，我们使用化学标记和样品归一化将使离子抑制的影响最小化， 信号饱和、柱污染、老化和仪器性能漂移。基本上， 和实验室间的变异性，这经常影响MS，将被最小化。 在这项提案中，我们将利用东弗吉尼亚医学院的生物储存探针队列， 收藏了300多个肾肿瘤和相关的临床数据，包括治疗，生命状态，成像数据， 原发性肿瘤切除后的纵向随访。伴随生物储藏库的数据库定期 更新，使我们能够识别那些“进步”与那些被称为“非进步者”。为此 I期概念验证研究，将分析来自26名发生转移的患者的组织， 而174例患者未发生转移（n=200例患者）。所有肿瘤组织-原发性和 转移性-将与来自清晰边缘的“正常”肿瘤相邻组织配对。此外，更大的数字 将使用可用的组织病理学和分期数据作为以下指标的替代物， 临床结果。这项研究的一个附带好处是，我们的ccRCC库有望增加II期研究。