Stepien Magdalena, Keski-Rahkonen Pekka, Kiss Agneta, Robinot Nivonirina, Duarte-Salles Talita, Murphy Neil, Perlemuter Gabriel, Viallon Vivian, Tjønneland Anne, Rostgaard-Hansen Agnetha Linn, Dahm Christina C, Overvad Kim, Boutron-Ruault Marie-Christine, Mancini Francesca Romana, Mahamat-Saleh Yahya, Aleksandrova Krasimira, Kaaks Rudolf, Kühn Tilman, Trichopoulou Antonia, Karakatsani Anna, Panico Salvatore, Tumino Rosario, Palli Domenico, Tagliabue Giovanna, Naccarati Alessio, Vermeulen Roel C H, Bueno-de-Mesquita Hendrik Bastiaan, Weiderpass Elisabete, Skeie Guri, Ramón Quirós Jose, Ardanaz Eva, Mokoroa Olatz, Sala Núria, Sánchez Maria-Jose, Huerta José María, Winkvist Anna, Harlid Sophia, Ohlsson Bodil, Sjöberg Klas, Schmidt Julie A, Wareham Nick, Khaw Kay-Tee, Ferrari Pietro, Rothwell Joseph A, Gunter Marc, Riboli Elio, Scalbert Augustin, Jenab Mazda
Section of Nutrition and Metabolism, International Agency for Research on Cancer (IARC-WHO), Lyon, France.
Institut Universitari d'Investigació en Atenció Primària Jordi Gol (IDIAP Jordi Gol), Barcelona, Spain.
Int J Cancer. 2021 Feb 1;148(3):609-625. doi: 10.1002/ijc.33236. Epub 2020 Aug 28.
Hepatocellular carcinoma (HCC) development entails changes in liver metabolism. Current knowledge on metabolic perturbations in HCC is derived mostly from case-control designs, with sparse information from prospective cohorts. Our objective was to apply comprehensive metabolite profiling to detect metabolites whose serum concentrations are associated with HCC development, using biological samples from within the prospective European Prospective Investigation into Cancer and Nutrition (EPIC) cohort (>520 000 participants), where we identified 129 HCC cases matched 1:1 to controls. We conducted high-resolution untargeted liquid chromatography-mass spectrometry-based metabolomics on serum samples collected at recruitment prior to cancer diagnosis. Multivariable conditional logistic regression was applied controlling for dietary habits, alcohol consumption, smoking, body size, hepatitis infection and liver dysfunction. Corrections for multiple comparisons were applied. Of 9206 molecular features detected, 220 discriminated HCC cases from controls. Detailed feature annotation revealed 92 metabolites associated with HCC risk, of which 14 were unambiguously identified using pure reference standards. Positive HCC-risk associations were observed for N1-acetylspermidine, isatin, p-hydroxyphenyllactic acid, tyrosine, sphingosine, l,l-cyclo(leucylprolyl), glycochenodeoxycholic acid, glycocholic acid and 7-methylguanine. Inverse risk associations were observed for retinol, dehydroepiandrosterone sulfate, glycerophosphocholine, γ-carboxyethyl hydroxychroman and creatine. Discernible differences for these metabolites were observed between cases and controls up to 10 years prior to diagnosis. Our observations highlight the diversity of metabolic perturbations involved in HCC development and replicate previous observations (metabolism of bile acids, amino acids and phospholipids) made in Asian and Scandinavian populations. These findings emphasize the role of metabolic pathways associated with steroid metabolism and immunity and specific dietary and environmental exposures in HCC development.
肝细胞癌（HCC）的发生与肝脏代谢变化有关。目前关于HCC代谢紊乱的知识大多来自病例对照研究设计，前瞻性队列研究的信息较少。我们的目标是应用全面的代谢物谱分析来检测血清浓度与HCC发生相关的代谢物，使用欧洲癌症与营养前瞻性调查（EPIC）队列（超过520,000名参与者）中的生物样本，我们在其中确定了129例HCC病例，并与对照组进行1:1匹配。我们对癌症诊断前招募时采集的血清样本进行了基于高分辨率非靶向液相色谱-质谱的代谢组学分析。应用多变量条件逻辑回归，控制饮食习惯、饮酒、吸烟、体型、肝炎感染和肝功能障碍。进行了多重比较校正。在检测到的9206个分子特征中，有220个能够区分HCC病例和对照组。详细的特征注释揭示了92种与HCC风险相关的代谢物，其中14种使用纯参考标准明确鉴定。观察到N1-乙酰亚精胺、异吲哚酮、对羟基苯乳酸、酪氨酸、鞘氨醇、l,l-环（亮氨酰脯氨酰）、甘氨鹅脱氧胆酸、甘胆酸和7-甲基鸟嘌呤与HCC风险呈正相关。观察到视黄醇、硫酸脱氢表雄酮、甘油磷酸胆碱、γ-羧乙基羟基苯并二氢吡喃和肌酸与HCC风险呈负相关。在诊断前长达10年的时间里，病例组和对照组之间这些代谢物存在明显差异。我们的观察结果突出了HCC发生过程中代谢紊乱的多样性，并重复了之前在亚洲和斯堪的纳维亚人群中所做的观察（胆汁酸、氨基酸和磷脂的代谢）。这些发现强调了与类固醇代谢和免疫相关的代谢途径以及特定饮食和环境暴露在HCC发生中的作用。
