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

总结 胆道癌（BTC），包括胆囊癌和胆管癌，是第二大 全球常见的原发性肝胆癌。BTC具有高度致命性，约90%的患者在5分钟内死亡 诊断后几年。更好地了解BTC的病因对于设计具有成本效益的 预防战略，以减少这种致命癌症的发病率和死亡率。胆道是一个中枢神经系统 在脂溶性内源性和外源性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风险因素与代谢紊乱有关， 提示代谢紊乱在BTC发病机制中的重要作用。因此，系统地调查 循环代谢物可以提供关于BTC风险和生物学特性的生物标志物的有价值的信息。 BTC发病机制。在此，我们提出了一个强大的，多血统的研究，利用资源， 从全球17项大型前瞻性队列研究和5项大型遗传联盟/BTC研究， 鉴定和验证BTC风险代谢组学生物标志物。在目标1中，我们提出分析血液样品 在任何癌症诊断之前从750例事件病例和750例匹配对照中收集， 搜索血液代谢物组，以确定有希望的代谢物生物标志物用于复制。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 （GWAS）的BTC寻找其他有前途的代谢物生物标志物的复制。在目标3中，我们 量化从目标1和2中选出的50种有希望的代谢物，并评估其与BTC风险的相关性 总的来说，并通过其子网站，在一个独立的样本近2000例及其匹配的控制。最后， 在目标4中，我们将使用代谢物生物标志物、遗传风险变异和 传统风险因素。这是有史以来第一次进行系统地搜索血液的大型研究 代谢组学，以确定BTC的风险生物标志物，以及第一项整合代谢组学和基因组学数据的研究 BTC生物标记物研究。包括多祖先人群将使我们能够交叉验证研究 研究结果，并确定生物标志物关联的潜在种族差异。这项研究将提供大量 新的数据，以提高对BTC病因的理解，并确定BTC风险评估的生物标志物。

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.