Identification of ovarian cancer plasma biomarkers

卵巢癌血浆生物标志物的鉴定

• 批准号: 7881494
• 负责人: DAVID W. SPEICHER
• 金额: $ 42.62万
• 依托单位: WISTAR INSTITUTE
• 依托单位国家: 美国
• 财政年份: 2009
• 资助国家: 美国
• 起止时间: 2009-07-01 至 2011-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7881494
• 关键词: Affect; Biological Assay; Biological Markers; Biological Models; Biological Process; Blood; Blood Volume; Cancer Model; Cancer Patient; Cancer cell line; Cell Line; Cells; Clinical Management; Collection; Conditioned Culture Media; Coupled; Culture Media; Cultured Cells; Data Analyses; Development; Diagnosis; Diagnostic; Disease; Disease Management; Early Diagnosis; Epithelial; Gel; Goals; Health Care Costs; Human; Human Cell Line; Hypoxia; Immune; Immunocompromised Host; Immunodeficient Mouse; In Vitro; Individual; Inflammatory Response; Lead; Malignant Neoplasms; Malignant neoplasm of ovary; Mass Spectrum Analysis; Methods; Modeling; Molecular; Morbidity - disease rate; Mouse Protein; Mus; Operative Surgical Procedures; Organ Culture Techniques; Ovarian; Ovarian Carcinoma; Ovary; Patients; Pattern; Peptides; Phase; Physiological; Plasma; Plasma Proteins; Primary Neoplasm; Protein Fragment; Proteins; Proteome; Public Health; Sampling; Serous; Specificity; Specimen; Staging; Survival Rate; Testing; Tumor Tissue; Tumor-Derived; Validation; Xenograft Model; Xenograft procedure; base; biosignature; candidate validation; cohort; improved; minimally invasive; mortality; mouse model; multiple reaction monitoring; neoplastic cell; novel; ovarian neoplasm; protein profiling; public health relevance; tumor; tumor specificity; tumor xenograft; validation studies

DESCRIPTION (provided by applicant): The overall goal of this application is to discover and validate multiple novel plasma protein biomarkers of human ovarian cancer. We will initially discover a substantial number of candidate biomarkers through parallel analysis of two complementary models of ovarian cancers and will subsequently validate the most promising candidate biomarkers in a human patient cohort. In Aim 1, we will use a xenograft model where human ovarian cancer cell lines are injected into both ovaries of NOD/SCID/3c-/- (NOG) mice and human primary tumors are allowed to grow prior to collection of the plasma. Several existing early passage serous cancer cell lines will be used and additional early passage cell lines will be derived from human ovarian tumors for this study. Low abundance plasma proteins will be identified using a 4-D protein profiling method that is capable of detecting many proteins in the low ng/ml to pg/ml range in plasma. Proteins secreted or shed by the human tumors will be unambiguously identified using high mass accuracy mass spectrometry coupled with rigorous data analysis to distinguish human and mouse proteins based on species-specific sequence differences. Low abundance human proteins that can be identified with >99% confidence and where repeat targeted LC-MS/MS analysis of the fraction can confirm the protein identification will be considered as candidate biomarkers. In Aim 2, we will analyze the secretome (shed and secreted proteins) from short term organ cultures using fresh ovarian tumors. The effects of normoxic and hypoxic conditions on protein shedding will be compared. In addition, the secretomes of short term organ culture, early passage established cultures from the same tumor and xenograft tumors from the same cell line will be compared to determine how different environmental and physiological context affects ovarian tumor cell protein shedding. In Aim 3, we will select the most promising candidate biomarkers from Aims 1 and 2 for validation analyses. Candidate biomarkers from the discovery studies in Aims 1 and 2 will be prioritized based upon: abundance in normal human plasma; specificity for ovarian tumors: consistency of shedding by different ovarian tumors, and biological function. The highest priority candidate biomarkers will be subsequently validated using multiplexed multiple reaction monitoring (MRM) mass spectrometry assays to quantify biomarker levels in plasma of ovarian patients and controls. Individual biomarkers as well as groups of biomarkers will be evaluated for their capacity to predict early stage ovarian cancers PUBLIC HEALTH RELEVANCE: Survival rates of ovarian cancer patients are about 90% if the disease is confined to the ovaries at diagnosis. Unfortunately, early stage ovarian tumors are usually asymptomatic and about 75% of cases are diagnosed after the cancer has spread. Recently developed powerful mass spectrometry-based plasma proteome analysis methods coupled with mouse ovarian cancer models provide unique opportunities to systematically discover many new ovarian cancer biomarker candidates that will lead to improved early diagnosis and clinical management of this disease.

描述（由申请人提供）：本申请的总体目标是发现并验证人类卵巢癌的多种新型血浆蛋白生物标志物。我们最初将通过对两种互补的卵巢癌模型进行并行分析来发现大量候选生物标志物，随后将在人类患者队列中验证最有希望的候选生物标志物。在目标 1 中，我们将使用异种移植模型，其中将人类卵巢癌细胞系注射到 NOD/SCID/3c-/- (NOG) 小鼠的两个卵巢中，并在收集血浆之前允许人类原发性肿瘤生长。本研究将使用几种现有的早期传代浆液性癌细胞系，并且将从人类卵巢肿瘤中衍生出其他早期传代细胞系。将使用 4-D 蛋白质分析方法来鉴定低丰度血浆蛋白质，该方法能够检测血浆中低 ng/ml 至 pg/ml 范围内的许多蛋白质。人类肿瘤分泌或脱落的蛋白质将通过高精度质谱分析和严格的数据分析来明确鉴定，以根据物种特异性序列差异区分人类和小鼠蛋白质。可以以 >99% 的置信度进行识别的低丰度人类蛋白质，并且对组分进行重复靶向 LC-MS/MS 分析可以确认蛋白质鉴定，将被视为候选生物标志物。在目标 2 中，我们将使用新鲜卵巢肿瘤来分析短期器官培养物的分泌组（脱落和分泌的蛋白质）。将比较常氧和低氧条件对蛋白质脱落的影响。此外，将比较短期器官培养物、来自同一肿瘤的早期传代建立的培养物和来自同一细胞系的异种移植肿瘤的分泌组，以确定不同的环境和生理背景如何影响卵巢肿瘤细胞蛋白脱落。在目标 3 中，我们将从目标 1 和 2 中选择最有希望的候选生物标志物进行验证分析。目标 1 和 2 中发现研究的候选生物标志物将根据以下因素进行优先排序： 正常人血浆中的丰度；卵巢肿瘤的特异性：不同卵巢肿瘤脱落的一致性以及生物学功能。随后将使用多重多反应监测（MRM）质谱分析来验证最高优先级的候选生物标志物，以量化卵巢患者和对照血浆中的生物标志物水平。将评估单个生物标志物以及生物标志物组预测早期卵巢癌的能力。 公共卫生相关性：如果诊断时疾病仅限于卵巢，则卵巢癌患者的生存率约为 90%。不幸的是，早期卵巢肿瘤通常无症状，约 75% 的病例是在癌症扩散后才被诊断出来的。最近开发的强大的基于质谱的血浆蛋白质组分析方法与小鼠卵巢癌模型相结合，为系统地发现许多新的卵巢癌生物标志物候选物提供了独特的机会，这将改善该疾病的早期诊断和临床管理。