METABOLITE BIOIMARKERS IN THE DEVELOPMENT OF ESOPHAGEAL ADENOCARCINOMA

食管腺癌发生过程中的代谢生物标志物

• 批准号: 8726352
• 负责人: THOMAS L VAUGHAN
• 金额: $ 18.46万
• 依托单位: FRED HUTCHINSON CANCER RESEARCH CENTER
• 依托单位国家: 美国
• 财政年份: 2013
• 资助国家: 美国
• 起止时间: 2013-09-01 至 2016-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8726352
• 关键词: Age; Amino Acids; Barrett Esophagus; Barrett' s Adenocarcinoma; Biological Assay; Biological Markers; Blood; Body mass index; Cancerous; Carbon; Caucasoid Race; Classification; Clinical; Data; Development; Discriminant Analysis; Disease; Disease Progression; Distal; Dysplasia; Early Diagnosis; Energy Metabolism; Epigenetic Process; Esophageal; Esophageal Adenocarcinoma; Foundations; Future; Gastroesophageal reflux disease; Gender; Genetic; Grant; Group Identifications; High-Risk Cancer; Incidence; Individual; International; Investigation; Laboratories; Least-Squares Analysis; Link; Lipids; Malignant Neoplasms; Maps; Mass Spectrum Analysis; Measures; Metabolic; Metabolic Pathway; Methods; Modeling; Molecular Weight; Monitor; Nuclear Magnetic Resonance; Nucleotides; Obesity; Pathway interactions; Patients; Performance; Population; Population Group; Population Heterogeneity; Premalignant; Proteins; ROC Curve; Receiver Operating Characteristics; Reflux; Resources; Risk; Risk Factors; Sample Size; Sampling; Sensitivity and Specificity; Serum; Smoking; Staging; Statistical Models; Stratification; Systems Biology; Testing; Urine; Validation; Work; aqueous; base; biobank; candidate marker; carcinogenesis; clinical risk; high risk; insight; lipid metabolism; male; metabolomics; novel; predictive modeling; public health relevance; research study; sex; tool; validation studies

DESCRIPTION (provided by applicant): The incidence of esophageal adenocarcinoma (EA) in the US has increased 300% over recent decades while median survival remains an abysmal 10 months. Several major risk factors have been defined for EA and its precursor, Barrett's esophagus (BE), including reflux, Caucasian race, male gender, obesity, and smoking, but a key challenge remains the identification of individuals at highest risk, since most with reflux do not develop BE, and most with BE do not progress to EA. While a number of genetic, epigenetic, and protein-based biomarkers have been evaluated for their ability to detect or predict disease progression, the development of novel clinical tests has been hampered by technical complexities of the required assays, limited sensitivity/specificity of the marker panels and lack of validation studies. Based on our preliminary data, we anticipate that metabolomics, the quantification of low molecular weight metabolites, offers a favorable alternative approach for identifying effective biomarkers to aid in risk stratification for those at risk of EA. Numerou studies have established that cellular energy metabolism is fundamentally altered in a broad spectrum of cancers, and increasing evidence indicates that cancer-associated metabolic changes are detectable in blood and urine. In this proposal, we hypothesize that serum-based metabolites can distinguish multiple stages of disease progression along the pathway from gastroesophageal reflux (GERD) to BE to EA. Using advanced profiling methods and a well-characterized biorepository, this collaborative proposal seeks to identify and validate novel metabolite markers linked to these disease states. In Aim 1, global metabolic profiling will be conducted on a set of 60 patient serum samples distributed across case type (GERD, BE, high- grade dysplasia/EA) to identify an expanded pool of candidate metabolite biomarkers that differ significantly across two or all of these conditions. In Aim 2, this targeted profiling of this set f metabolites plus a previously-identified panel of 28 candidates will be conducted on a larger set of 240 patient samples. Based on validated candidate markers identified, statistical models for sample classification (BE-GERD and HGD/EA-BE) will be constructed using partial least-squares discriminant analysis, and model performance estimated by Monte Carlo cross-validation. Successful completion of these aims will lay the groundwork for generating novel non-invasive tools for stratifying patients at risk of EA according to their likelihood of disease progression. Such tools have the potential to increase early detection and reduce unnecessary surveillance, by focusing intensive clinical monitoring on those at highest risk of cancer. These investigations will set the stage for larger-scale future studies, which will leverage the extensiv resources of the international Barrett's and Esophageal Adenocarcinoma (BEACON) consortium to validate our findings across population groups and identify key modifying factors that may enhance the accuracy and applicability of our predictive models.

描述（由申请人提供）：近几十年来，美国食管腺癌 (EA) 的发病率增加了 300%，而中位生存期仍然只有 10 个月。 EA 及其前身巴雷特食管 (BE) 的几个主要危险因素已被定义，包括反流、白人种族、男性、肥胖和吸烟，但关键挑战仍然是识别最高风险的个体，因为大多数反流患者不会发展为 BE，而大多数 BE 患者也不会进展为 EA。虽然已经评估了许多遗传、表观遗传和基于蛋白质的生物标志物检测或预测疾病进展的能力，但由于所需测定的技术复杂性、标志物组的敏感性/特异性有限以及缺乏验证研究，新型临床测试的发展受到阻碍。根据我们的初步数据，我们预计代谢组学（低分子量代谢物的定量）为识别有效的生物标志物提供了一种有利的替代方法，以帮助对有 EA 风险的人进行风险分层。大量研究已经证实，细胞能量代谢在多种癌症中发生了根本性改变，并且越来越多的证据表明，在血液和尿液中可以检测到与癌症相关的代谢变化。在该提案中，我们假设基于血清的代谢物可以区分从胃食管反流 (GERD) 到 BE 到 EA 的疾病进展的多个阶段。该合作提案利用先进的分析方法和特征良好的生物样本库，旨在识别和验证与这些疾病状态相关的新型代谢标志物。在目标 1 中，将对分布在不同病例类型（GERD、BE、高度不典型增生/EA）的一组 60 名患者血清样本进行全局代谢分析，以识别在两种或所有这些病症中显着差异的候选代谢生物标志物的扩展库。在目标 2 中，将对这组 f 代谢物以及先前确定的 28 名候选物进行有针对性的分析，将对更大的 240 名患者样本进行分析。基于确定的经过验证的候选标记，将使用偏最小二乘判别分析构建样本分类统计模型（BE-GERD 和 HGD/EA-BE），并通过蒙特卡罗交叉验证估计模型性能。这些目标的成功完成将为开发新型非侵入性工具奠定基础，这些工具可根据疾病进展的可能性对处于 EA 风险的患者进行分层。通过将密集的临床监测重点放在癌症风险最高的人群上，此类工具有可能增加早期发现并减少不必要的监测。这些调查将为未来更大规模的研究奠定基础，这些研究将利用国际巴雷特氏病和食管腺癌 (BEACON) 联盟的广泛资源来验证我们在不同人群中的研究结果，并确定可能提高我们预测模型的准确性和适用性的关键修改因素。