Searching the blood metabolome to identify risk biomarkers for biliary tract cancer

摘要 胆道癌(BTC)是第二大癌症，包括胆囊癌和胆道癌 世界范围内常见的原发性肝胆癌。BTC是高度致命的，大约90%的患者在五年内死亡 在确诊数年后。更好地了解BTC的病因对于设计具有成本效益的BTC至关重要 预防战略，以减少这一致命癌症的发病率和死亡率。胆道起着中枢作用。 在脂溶性内源和外源化合物的代谢和吸收中的作用 维持正常的肝功能。许多已知的BTC危险因素与代谢紊乱有关， 提示代谢紊乱在BTC发病机制中具有重要作用。因此，系统地调查 循环代谢产物可以提供有关BTC风险的生物标志物和生物学上的有价值的信息 BTC的发病机制。在这里，我们提出了一个强大的，多血统的研究，使用资源 来自世界各地的17项大型前瞻性队列研究和5个大型遗传联盟/BTC研究，到 识别和验证代谢生物标记物的BTC风险。在目标1中，我们建议分析血液样本 在任何癌症诊断之前从750个事件病例和750个匹配的对照中收集，以系统地 搜索血液代谢组，以确定有希望的代谢物生物标志物进行复制。在目标2中，我们将使用 与循环代谢物相关的遗传变异和来自大型全基因组关联研究的数据 为复制寻找其他有希望的代谢物生物标记物。在《目标3》中，我们将 量化选自目标1和目标2的50种有希望的代谢物，并评估它们与BTC风险的关系 总体而言，按其子站点，在近2000个病例及其匹配的对照的独立样本中。最后， 在目标4中，我们将使用代谢物生物标记物、遗传风险变量和 传统的风险因素。这是有史以来第一次系统地搜索血液的大型研究 代谢组识别BTC的风险生物标记物，以及首次整合代谢组和基因组数据的研究 在BTC生物标记物研究中。包括多个祖先的人口将使我们能够交叉验证研究 发现并确定生物标记物关联中潜在的种族差异。这项研究将提供大量的 新的数据，以提高对BTC病因学的理解，并为BTC风险评估确定生物标志物。

Summary Biliary tract cancer (BTC), which includes cancers of the gallbladder and bile ducts, is the second most common primary hepatobiliary cancer worldwide. BTC is highly fatal, with ~90% of its patients dying within five years after diagnosis. A better understanding of the etiology of BTC is critical for designing cost-effective prevention strategies to reduce the morbidity and mortality of this fatal cancer. The biliary tract plays a central role in the metabolism and absorption of fat-soluble endogenous and exogenous compounds and in the maintenance of normal liver functions. Many known risk factors for BTC are related to metabolic disturbance, suggesting a significant role of metabolic perturbance in BTC pathogenesis. Thus, a systematic investigation of circulating metabolites could provide valuable information regarding biomarkers for BTC risk and biological mechanisms of BTC pathogenesis. Herein, we propose a well-powered, multi-ancestry study, using resources from 17 large prospective cohort studies around the world and five large genetic consortia/studies of BTC, to identify and validate metabolomic biomarkers for BTC risk. In Aim 1, we propose to analyze blood samples collected prior to any cancer diagnosis from 750 incident cases and 750 matched controls to systematically search the blood metabolome to identify promising metabolite biomarkers for replication. In Aim 2, we will use genetic variants associated with circulating metabolites and data from large genome-wide association studies (GWAS) of BTC to search for additional promising metabolite biomarkers for replication. In Aim 3, we will quantify 50 promising metabolites selected from Aims 1 and 2 and evaluate their associations with risk of BTC overall, and by its subsites, in an independent sample of nearly 2000 cases and their matched controls. Finally, in Aim 4, we will build risk prediction models for BTC using metabolite biomarkers, genetic risk variants and traditional risk factors. This is the first large study ever conducted to systematically search the blood metabolome to identify risk biomarkers for BTC, and the first study to integrate metabolomic and genomic data in BTC biomarker research. Including multi-ancestry populations will allow us to cross-validate research findings and identify potential racial differences in biomarker associations. This study will provide substantial novel data to improve the understanding of BTC etiology and identify biomarkers for BTC risk assessment.