Metabolic perturbations prior to hepatocellular carcinoma diagnosis: Findings from a prospective observational cohort study.
hepatocellular carcinoma
prospective observational cohort
untargeted metabolomics
Journal
International journal of cancer
ISSN: 1097-0215
Titre abrégé: Int J Cancer
Pays: United States
ID NLM: 0042124
Informations de publication
Date de publication:
01 02 2021
01 02 2021
Historique:
received:
24
01
2020
revised:
16
06
2020
accepted:
26
06
2020
pubmed:
1
8
2020
medline:
25
6
2021
entrez:
1
8
2020
Statut:
ppublish
Résumé
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.
Substances chimiques
Biomarkers, Tumor
0
Types de publication
Journal Article
Observational Study
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
609-625Subventions
Organisme : Medical Research Council
ID : MR/N003284/1
Pays : United Kingdom
Organisme : Medical Research Council
ID : G0500300
Pays : United Kingdom
Organisme : Medical Research Council
ID : G1000143
Pays : United Kingdom
Organisme : Medical Research Council
ID : MC_UU_12015/1
Pays : United Kingdom
Organisme : Cancer Research UK
ID : 14136
Pays : United Kingdom
Organisme : Medical Research Council
ID : G0401527
Pays : United Kingdom
Organisme : Medical Research Council
ID : MC_UU_00006/1
Pays : United Kingdom
Organisme : Medical Research Council
ID : MR/M012190/1
Pays : United Kingdom
Informations de copyright
© 2020 UICC.
Références
Bray F, Ferlay J, Soerjomataram I, Siegel RL, Torre LA, Jemal A. Global cancer statistics 2018: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin. 2018;68(6):394-424.
Kew MC. Hepatocellular carcinoma: epidemiology and risk factors. J Hepatocell Carcinoma. 2014;1:115-125.
Blachier M, Leleu H, Peck-Radosavljevic M, Valla DC, Roudot-Thoraval F. The burden of liver disease in Europe: a review of available epidemiological data. J Hepatol. 2013;58(3):593-608.
McGlynn KA, Petrick JL, London WT. Global epidemiology of hepatocellular carcinoma: an emphasis on demographic and regional variability. Clin Liver Dis. 2015;19(2):223-238.
Kulik L, El-Serag HB. Epidemiology and management of hepatocellular carcinoma. Gastroenterology. 2019;156(2):477-491.
Trevisani F, Frigerio M, Santi V, Grignaschi A, Bernardi M. Hepatocellular carcinoma in non-cirrhotic liver: a reappraisal. Dig Liver Dis. 2010;42(5):341-347.
Desai A, Sandhu S, Lai JP, Sandhu DS. Hepatocellular carcinoma in non-cirrhotic liver: a comprehensive review. World J Hepatol. 2019;11(1):1-18.
Geh D, Rana FA, Reeves HL. Weighing the benefits of hepatocellular carcinoma surveillance against potential harms. J Hepatocell Carcinoma. 2019;6:23-30.
Assi N, Fages A, Vineis P, et al. A statistical framework to model the meeting-in-the-middle principle using metabolomic data: application to hepatocellular carcinoma in the EPIC study. Mutagenesis. 2015;30(6):743-753.
Beyoglu D, Idle JR. The metabolomic window into hepatobiliary disease. J Hepatol. 2013;59(4):842-858.
Le ML, Triba MN, Nahon P, et al. Nuclear magnetic resonance metabolomics and human liver diseases: the principles and evidence associated with protein and carbohydrate metabolism. Biomed Rep. 2017;6(4):387-395.
Huang Q, Tan Y, Yin P, et al. Metabolic characterization of hepatocellular carcinoma using nontargeted tissue metabolomics. Cancer Res. 2013;73(16):4992-5002.
Lu Y, Li N, Gao L, et al. Acetylcarnitine is a candidate diagnostic and prognostic biomarker of hepatocellular carcinoma. Cancer Res. 2016;76(10):2912-2920.
Luo P, Yin P, Hua R, et al. A large-scale, multicenter serum metabolite biomarker identification study for the early detection of hepatocellular carcinoma. Hepatology. 2018;67(2):662-675.
Kimhofer T, Fye H, Taylor-Robinson S, Thursz M, Holmes E. Proteomic and metabonomic biomarkers for hepatocellular carcinoma: a comprehensive review. Br J Cancer. 2015;112(7):1141-1156.
Stepien M, Duarte-Salles T, Fedirko V, et al. Alteration of amino acid and biogenic amine metabolism in hepatobiliary cancers: findings from a prospective cohort study. Int J Cancer. 2016;138(2):348-360.
Fages A, Duarte-Salles T, Stepien M, et al. Metabolomic profiles of hepatocellular carcinoma in a European prospective cohort. BMC Med. 2015;13:242.
Loftfield E, Rothwell JA, Sinha R, et al. Prospective investigation of serum metabolites, coffee drinking, liver cancer incidence, and liver disease mortality. J Natl Cancer Inst. 2020;112(3):286-294.
His M, Viallon V, Dossus L, et al. Prospective analysis of circulating metabolites and breast cancer in EPIC. BMC Med. 2019;17(1):178.
Schmidt JA, Fensom GK, Rinaldi S, et al. Pre-diagnostic metabolite concentrations and prostate cancer risk in 1077 cases and 1077 matched controls in the European prospective investigation into cancer and nutrition. BMC Med. 2017;15(1):122.
Schmidt JA, Fensom GK, Rinaldi S, et al. Patterns in metabolite profile are associated with risk of more aggressive prostate cancer: a prospective study of 3,057 matched case-control sets from EPIC. Int J Cancer. 2020;146(3):720-730.
Carayol M, Leitzmann MF, Ferrari P, et al. Blood metabolic signatures of body mass index: a targeted metabolomics study in the EPIC cohort. J Proteome Res. 2017;16(9):3137-3146.
Schmidt JA, Rinaldi S, Ferrari P, et al. Metabolic profiles of male meat eaters, fish eaters, vegetarians, and vegans from the EPIC-Oxford cohort. Am J Clin Nutr. 2015;102(6):1518-1526.
Moore SC, Playdon MC, Sampson JN, et al. A metabolomics analysis of body mass index and postmenopausal breast cancer risk. J Natl Cancer Inst. 2018;110(6):588-597.
Jee SH, Kim M, Kim M, et al. Metabolomics profiles of hepatocellular carcinoma in a Korean prospective cohort: the Korean cancer prevention study-II. Cancer Prev Res (Phila). 2018;11(5):303-312.
Yu B, Zanetti KA, Temprosa M, et al. The consortium of metabolomics studies (COMETS): metabolomics in 47 prospective cohort studies. Am J Epidemiol. 2019;188(6):991-1012.
Scalbert A, Brennan L, Fiehn O, et al. Mass-spectrometry-based metabolomics: limitations and recommendations for future progress with particular focus on nutrition research. Metabolomics. 2009;5(4):435-458.
Riboli E, Kaaks R. The EPIC project: rationale and study design. European prospective investigation into cancer and nutrition. Int J Epidemiol. 1997;26(Suppl 1):S6-S14.
Riboli E, Hunt KJ, Slimani N, et al. European prospective investigation into cancer and nutrition (EPIC): study populations and data collection. Public Health Nutr. 2002;5(6B):1113-1124.
Lubin JH, Gail MH. Biased selection of controls for case-control analyses of cohort studies. Biometrics. 1984;40(1):63-75.
Wishart DS, Jewison T, Guo AC, et al. HMDB 3.0-the human metabolome database in 2013. Nucleic Acids Res. 2013;41:D801-D807.
Smith CA, O'Maille G, Want EJ, et al. METLIN: a metabolite mass spectral database. Ther Drug Monit. 2005;27(6):747-751.
Sumner LW, Amberg A, Barrett D, et al. Proposed minimum reporting standards for chemical analysis chemical analysis working group (CAWG) metabolomics standards initiative (MSI). Metabolomics. 2007;3(3):211-221.
Trichopoulos D, Bamia C, Lagiou P, et al. Hepatocellular carcinoma risk factors and disease burden in a European cohort: a nested case-control study. J Natl Cancer Inst. 2011;103(22):1686-1695.
Stepien M, Fedirko V, Duarte-Salles T, et al. Prospective association of liver function biomarkers with development of hepatobiliary cancers. Cancer Epidemiol. 2016;40:179-187.
Satriano L, Lewinska M, Rodrigues PM, Banales JM, Andersen JB. Metabolic rearrangements in primary liver cancers: cause and consequences. Nat Rev Gastroenterol Hepatol. 2019;16(12):748-766.
Leonard SW, Paterson E, Atkinson JK, Ramakrishnan R, Cross CE, Traber MG. Studies in humans using deuterium-labeled alpha- and gamma-tocopherols demonstrate faster plasma gamma-tocopherol disappearance and greater gamma-metabolite production. Free Radic Biol Med. 2005;38(7):857-866.
Jiang Q, Christen S, Shigenaga MK, Ames BN. Gamma-tocopherol, the major form of vitamin E in the US diet, deserves more attention. Am J Clin Nutr. 2001;74(6):714-722.
Uray IP, Dmitrovsky E, Brown PH. Retinoids and rexinoids in cancer prevention: from laboratory to clinic. Semin Oncol. 2016;43(1):49-64.
Lai GY, Weinstein SJ, Albanes D, et al. Association of serum alpha-tocopherol, beta-carotene, and retinol with liver cancer incidence and chronic liver disease mortality. Br J Cancer. 2014;111(11):2163-2171.
Yuan JM, Gao YT, Ong CN, Ross RK, Yu MC. Prediagnostic level of serum retinol in relation to reduced risk of hepatocellular carcinoma. J Natl Cancer Inst. 2006;98(7):482-490.
Galli F, Piroddi M, Lannone A, Pagliarani S, Tomasi A, Floridi A. A comparison between the antioxidant and peroxynitrite-scavenging functions of the vitamin E metabolites alpha- and gamma-carboxyethyl-6-hydroxychromans. Int J Vitam Nutr Res. 2004;74(5):362-373.
Sanyal AJ, Chalasani N, Kowdley KV, et al. Pioglitazone, vitamin E, or placebo for nonalcoholic steatohepatitis. N Engl J Med. 2010;362(18):1675-1685.
Lasky-Su J, Dahlin A, Litonjua AA, et al. Metabolome alterations in severe critical illness and vitamin D status. Crit Care. 2017;21(1):193.
Fedirko V, Duarte-Salles T, Bamia C, et al. Prediagnostic circulating vitamin D levels and risk of hepatocellular carcinoma in European populations: a nested case-control study. Hepatology. 2014;60(4):1222-1230.
Luo P, Yin P, Hua R, Tan Y, Li Z, Qiu G, Yin Z, Xie X, Wang X, Chen W, Zhou L, Wang X, Li Y, Chen H, Gao L, Lu X, Wu T, Wang H, Niu J, Xu G. A Large-scale, multicenter serum metabolite biomarker identification study for the early detection of hepatocellular carcinoma. Hepatology. 2018;67(2):662-675. https://doi.org/10.1002/hep.29561.
Barcelos RP, Stefanello ST, Mauriz JL, Gonzalez-Gallego J, Soares FA. Creatine and the liver: metabolism and possible interactions. Mini Rev Med Chem. 2016;16(1):12-18.
Tian YE, Xie XU, Lin Y, Tan G, Zhong WU. Androgen receptor in hepatocarcinogenesis: recent developments and perspectives. Oncol Lett. 2015;9(5):1983-1988.
Kanda T, Yokosuka O. The androgen receptor as an emerging target in hepatocellular carcinoma. J Hepatocell Carcinoma. 2015;2:91-99.
De MN, Manno M, Villa E. Sex hormones and liver cancer. Mol Cell Endocrinol. 2002;193(1-2):59-63.
Park CB, Kim DJ, Moore MA, Takasuka N, Tsuda H. Promotion of liver lesion development in the Syrian hamster by dietary fat following multi-organ initiation is inhibited by DHEA-S administration. Asian Pac J Cancer Prev. 2000;1(4):329-332.
Duarte-Salles T, Fedirko V, Stepien M, et al. Dairy products and risk of hepatocellular carcinoma: the European prospective investigation into cancer and nutrition. Int J Cancer. 2014;135(7):1662-1672.
Ishikawa T. Branched-chain amino acids to tyrosine ratio value as a potential prognostic factor for hepatocellular carcinoma. World J Gastroenterol. 2012;18(17):2005-2008.
Rauschenbach MO, Zharova EI, Sergeeva TI, Ivanova VD, Probatova NA. Blastomogenic activity of p-hydroxyphenyllactic acid in mice. Cancer Res. 1975;35(3):577-585.
Yang Y, Liu F, Wan Y. Simultaneous determination of 4-hydroxyphenyl lactic acid, 4-hydroxyphenyl acetic acid, and 3,4-hydroxyphenyl propionic acid in human urine by ultra-high performance liquid chromatography with fluorescence detection. J Sep Sci. 2017;40(10):2117-2122.
Medvedev A, Buneeva O, Glover V. Biological targets for isatin and its analogues: implications for therapy. Biol Theory. 2007;1(2):151-162.
Fedirko V, Tran HQ, Gewirtz AT, et al. Exposure to bacterial products lipopolysaccharide and flagellin and hepatocellular carcinoma: a nested case-control study. BMC Med. 2017;15(1):72.
Koch M, Freitag-Wolf S, Schlesinger S, et al. Serum metabolomic profiling highlights pathways associated with liver fat content in a general population sample. Eur J Clin Nutr. 2017;71(8):995-1001.
Sugimoto H, Sakurai S, Abe T, et al. Elevation of N1-acetylspermidine and putrescine in hepatic tissues of patients with fulminant hepatitis and liver cirrhosis. J Gastroenterol. 1994;29(2):159-163.
Xu H, Liu R, He B, Bi C, Bi K, Li Q. Polyamine Metabolites Profiling for Characterization of Lung and Liver Cancer Using an LC-Tandem MS Method with Multiple Statistical Data Mining Strategies: Discovering Potential Cancer Biomarkers in Human Plasma and Urine. Molecules. 2016;21(8):1040-1052. https://doi.org/10.3390/molecules21081040.
Grammatikos G, Muhle C, Ferreiros N, et al. Serum acid sphingomyelinase is upregulated in chronic hepatitis C infection and non alcoholic fatty liver disease. Biochim Biophys Acta. 2014;1841(7):1012-1020.
Hofmann AF. The continuing importance of bile acids in liver and intestinal disease. Arch Intern Med. 1999;159(22):2647-2658.
Trottier J, Bialek A, Caron P, et al. Metabolomic profiling of 17 bile acids in serum from patients with primary biliary cirrhosis and primary sclerosing cholangitis: a pilot study. Dig Liver Dis. 2012;44(4):303-310.
Safaei A, Arefi OA, Mohebbi SR, et al. Metabolomic analysis of human cirrhosis, hepatocellular carcinoma, non-alcoholic fatty liver disease and non-alcoholic steatohepatitis diseases. Gastroenterol Hepatol Bed Bench. 2016;9(3):158-173.
Yoshimoto S, Loo TM, Atarashi K, et al. Obesity-induced gut microbial metabolite promotes liver cancer through senescence secretome. Nature. 2013;499(7456):97-101.
Chen T, Xie G, Wang X, et al. Serum and urine metabolite profiling reveals potential biomarkers of human hepatocellular carcinoma. Mol Cell Proteomics. 2011;10(7):M110.
Tan Y, Yin P, Tang L, et al. Metabolomics study of stepwise hepatocarcinogenesis from the model rats to patients: potential biomarkers effective for small hepatocellular carcinoma diagnosis. Mol Cell Proteomics. 2012;11(2):M111.
Chao MR, Wang CJ, Yang HH, Chang LW, Hu CW. Rapid and sensitive quantification of urinary N7-methylguanine by isotope-dilution liquid chromatography/electrospray ionization tandem mass spectrometry with on-line solid-phase extraction. Rapid Commun Mass Spectrom. 2005;19(17):2427-2432.
Tamae K, Kawai K, Yamasaki S, et al. Effect of age, smoking and other lifestyle factors on urinary 7-methylguanine and 8-hydroxydeoxyguanosine. Cancer Sci. 2009;100(4):715-721.
Romaguera D, Vergnaud AC, Peeters PH, et al. Is concordance with World Cancer Research Fund/American Institute for Cancer Research guidelines for cancer prevention related to subsequent risk of cancer? Results from the EPIC study. Am J Clin Nutr. 2012;96(1):150-163.
Huang J, Weinstein SJ, Moore SC, et al. Serum metabolomic profiling of all-cause mortality: a prospective analysis in the alpha-tocopherol, beta-carotene cancer prevention (ATBC) study cohort. Am J Epidemiol. 2018;187(8):1721-1732.
Ivanisevic J, Zhu ZJ, Plate L, et al. Toward 'omic scale metabolite profiling: a dual separation-mass spectrometry approach for coverage of lipid and central carbon metabolism. Anal Chem. 2013;85(14):6876-6884.