Network analyses identify liver-specific targets for treating liver diseases

Molecular Systems Biology

Volumn 13, Issue 8, 2017, Pages

  Lee, Sunjae ^a   Zhang, Cheng ^a   Liu, Zhengtao ^a   Klevstig, Martina ^b   Mukhopadhyay, Bani ^c   Bergentall, Mattias ^b   Cinar, Resat ^c   Ståhlman, Marcus ^b   Sikanic, Natasha ^a   Park, Joshua K ^c   Deshmukh, Sumit ^a   Harzandi, Azadeh M ^a   Kuijpers, Tim ^a   Grøtli, Morten ^b   Elsässer, Simon J ^d   Piening, Brian D ^e   Snyder, Michael ^e   Smith, Ulf ^b   Nielsen, Jens ^a,f   Bäckhed, Fredrik ^b   Kunos, George ^c   Uhlen, Mathias ^a   Boren, Jan ^b   Mardinoglu, Adil ^a,f   more..

^a ROYAL INSTITUTE OF TECHNOLOGY   (Sweden)

^b UNIVERSITY OF GOTHENBURG   (Sweden)

^c NATIONAL INSTITUTE ON ALCOHOL ABUSE AND ALCOHOLISM   (United States)

^d KAROLINSKA INSTITUTE   (Sweden)

^e STANFORD UNIVERSITY   (United States)

^f CHALMERS UNIVERSITY OF TECHNOLOGY   (Sweden)

Author keywords

co expression; co regulation; HCC; metabolism; NAFLD

Indexed keywords

FATTY ACID SYNTHASE; PATATIN LIKE PHOSPHOLIPASE DOMAIN CONTAINING 3; PHOSPHOLIPASE; PROPROTEIN CONVERTASE 9; PYRUVATE KINASE; PYRUVATE KINASE LIVER AND RED BLOOD CELL; UNCLASSIFIED DRUG; FASN PROTEIN, HUMAN;

AMINO ACID METABOLISM; ANIMAL EXPERIMENT; ANIMAL MODEL; ARTICLE; CELL GROWTH; CHOLESTEROL METABOLISM; CONTROLLED STUDY; FAT CONTENT; FATTY ACID METABOLISM; FATTY ACID SYNTHESIS; GENE EXPRESSION; GENE EXPRESSION PROFILING; HEP-G2 CELL LINE; HUMAN; HUMAN CELL; HUMAN TISSUE; LIPID HOMEOSTASIS; LIPID METABOLISM; LIPOGENESIS; LIVER CELL; LIVER CELL CARCINOMA; LIVER METABOLISM; LIVER TISSUE; MALE; MOUSE; NONALCOHOLIC FATTY LIVER; NONHUMAN; PATHOGENESIS; PREDICTION; PRIORITY JOURNAL; PROTEIN PROTEIN INTERACTION; PROTEIN TARGETING; PROTEOMICS; RNA SPLICING; SKELETAL MUSCLE; SUBCUTANEOUS FAT; TRANSCRIPTOMICS; ANIMAL; ANTIBODY SPECIFICITY; CELL CULTURE; CHEMISTRY; DRUG EFFECTS; GENE EXPRESSION REGULATION; GENE REGULATORY NETWORK; GENETICS; K-562 CELL LINE; LIVER; LIVER TUMOR; MOLECULARLY TARGETED THERAPY; PROCEDURES; SEQUENCE ANALYSIS; SYSTEMS BIOLOGY;

ANIMALS; CARCINOMA, HEPATOCELLULAR; CELLS, CULTURED; FATTY ACID SYNTHASE, TYPE I; GENE EXPRESSION PROFILING; GENE EXPRESSION REGULATION; GENE REGULATORY NETWORKS; HEP G2 CELLS; HUMANS; K562 CELLS; LIVER; LIVER NEOPLASMS; MICE; MOLECULAR TARGETED THERAPY; NON-ALCOHOLIC FATTY LIVER DISEASE; ORGAN SPECIFICITY; PROTEIN INTERACTION MAPS; SEQUENCE ANALYSIS, RNA; SYSTEMS BIOLOGY;

EID: 85028357254     PISSN: None     EISSN: 17444292     Source Type: Journal    
DOI: 10.15252/msb.20177703     Document Type: Article

References (57)

1. Agren R, Bordel S, Mardinoglu A, Pornputtapong N, Nookaew I, Nielsen J (2012) Reconstruction of genome-scale active metabolic networks for 69 human cell types and 16 cancer types using INIT. PLoS Comput Biol 8: e1002518
2. Agren R, Mardinoglu A, Asplund A, Kampf C, Uhlen M, Nielsen J (2014) Identification of anticancer drugs for hepatocellular carcinoma through personalized genome-scale metabolic modeling. Mol Syst Biol 10: 721
3. Anders S, Huber W (2010) Differential expression analysis for sequence count data. Genome Biol 11: R106
4. Aragones G, Auguet T, Armengol S, Berlanga A, Guiu-Jurado E, Aguilar C, Martinez S, Sabench F, Porras JA, Ruiz MD, Hernandez M, Sirvent JJ, Del Castillo D, Richart C (2016) PNPLA3 expression is related to liver steatosis in morbidly obese women with non-alcoholic fatty liver disease. Int J Mol Sci 17: 630
5. Björnson E, Mukhopadhyay B, Asplund A, Pristovsek N, Cinar R, Romeo S, Uhlen M, Kunos G, Nielsen J, Mardinoglu A (2015) Stratification of hepatocellular carcinoma patients based on acetate utilization. Cell Rep 13: 2014–2026
6. Bordbar A, Monk JM, King ZA, Palsson BO (2014) Constraint-based models predict metabolic and associated cellular functions. Nat Rev Genet 15: 107–120
7. Dorn C, Riener MO, Kirovski G, Saugspier M, Steib K, Weiss TS, Gabele E, Kristiansen G, Hartmann A, Hellerbrand C (2010) Expression of fatty acid synthase in nonalcoholic fatty liver disease. Int J Clin Exp Pathol 3: 505–514
8. Elsemman IE, Mardinoglu A, Shoaie S, Soliman TH, Nielsen J (2016) Systems biology analysis of hepatitis C virus infection reveals the role of copy number increases in regions of chromosome 1q in hepatocellular carcinoma metabolism. Mol BioSyst 12: 1496–1506
9. Giannone FA, Baldassarre M, Domenicali M, Zaccherini G, Trevisani F, Bernardi M, Caraceni P (2012) Reversal of liver fibrosis by the antagonism of endocannabinoid CB1 receptor in a rat model of CCl(4)-induced advanced cirrhosis. Lab Invest 92: 384–395
10. GTEx (2013) The genotype-tissue expression (GTEx) project. Nat Genet 45: 580–585
11. Harriman G, Greenwood J, Bhat S, Huang X, Wang R, Paul D, Tong L, Saha AK, Westlin WF, Kapeller R, Harwood HJ Jr (2016) Acetyl-CoA carboxylase inhibition by ND-630 reduces hepatic steatosis, improves insulin sensitivity, and modulates dyslipidemia in rats. Proc Natl Acad Sci USA 113: E1796–E1805
12. Hezode C, Roudot-Thoraval F, Nguyen S, Grenard P, Julien B, Zafrani ES, Pawlotsky JM, Dhumeaux D, Lotersztajn S, Mallat A (2005) Daily cannabis smoking as a risk factor for progression of fibrosis in chronic hepatitis C. Hepatology 42: 63–71
13. Huang DW, Sherman BT, Lempicki RA (2009) Systematic and integrative analysis of large gene lists using DAVID bioinformatics resources. Nat Protoc 4: 44–57
14. Hyötyläinen T, Jerby L, Petäjä EM, Mattila I., Jäntti S, Auvinen P, Gastaldelli A, Yki-Järvinen H, Ruppin E, Orešič M (2016) Genome-scale study reveals reduced metabolic adaptability in patients with non-alcoholic fatty liver disease. Nat Commun 7: 8994
15. Jeong WI, Osei-Hyiaman D, Park O, Liu J, Batkai S, Mukhopadhyay P, Horiguchi N, Harvey-White J, Marsicano G, Lutz B, Gao B, Kunos G (2008) Paracrine activation of hepatic CB1 receptors by stellate cell-derived endocannabinoids mediates alcoholic fatty liver. Cell Metab 7: 227–235
16. Jourdan T, Demizieux L, Gresti J, Djaouti L, Gaba L, Verges B, Degrace P (2012) Antagonism of peripheral hepatic cannabinoid receptor-1 improves liver lipid metabolism in mice: evidence from cultured explants. Hepatology 55: 790–799
17. Kampf C, Mardinoglu A, Fagerberg L, Hallström B, Edlund K, Nielsen J, Uhlen M (2014) The human liver-specific proteome defined by transcriptomics and antibody-based profiling. Faseb J 28: 2901–2914
18. Kew MC (2010) Epidemiology of chronic hepatitis B virus infection, hepatocellular carcinoma, and hepatitis B virus-induced hepatocellular carcinoma. Pathol Biol (Paris) 58: 273–277
19. Khlaiphuengsin A, Kiatbumrung R, Payungporn S, Pinjaroen N, Tangkijvanich P (2015) Association of PNPLA3 polymorphism with hepatocellular carcinoma development and prognosis in viral and non-viral chronic liver diseases. Asian Pac J Cancer Prev 16: 8377–8382
20. Lee S, Zhang C, Kilicarslan M, Bluher M, Uhlen M, Nielsen J, Smith U, Serlie MJ, Boren J, Mardinoglu A (2016) Integrated network analysis reveals an association between plasma mannose levels and insulin resistance. Cell Metab 24: 172–184
21. Mardinoglu A, Nielsen J (2012) Systems medicine and metabolic modelling. J Intern Med 271: 142–154
22. Mardinoglu A, Agren R, Kampf C, Asplund A, Nookaew I, Jacobson P, Walley AJ, Froguel P, Carlsson LM, Uhlen M, Nielsen J (2013a) Integration of clinical data with a genome-scale metabolic model of the human adipocyte. Mol Syst Biol 9: 649
23. Mardinoglu A, Gatto F, Nielsen J (2013b) Genome-scale modeling of human metabolism – a systems biology approach. Biotechnol J 8: 985–996
24. Mardinoglu A, Agren R, Kampf C, Asplund A, Uhlen M, Nielsen J (2014a) Genome-scale metabolic modelling of hepatocytes reveals serine deficiency in patients with non-alcoholic fatty liver disease. Nat Commun 5: 3083
25. Mardinoglu A, Kampf C, Asplund A, Fagerberg L, Hallstrom BM, Edlund K, Bluher M, Ponten F, Uhlen M, Nielsen J (2014b) Defining the human adipose tissue proteome to reveal metabolic alterations in obesity. J Proteome Res 13: 5106–5119
26. Mardinoglu A, Nielsen J (2015) New paradigms for metabolic modeling of human cells. Curr Opin Biotech 34: 91–97
27. Mardinoglu A, Shoaie S, Bergentall M, Ghaffari P, Zhang C, Larsson E, Backhed F, Nielsen J (2015) The gut microbiota modulates host amino acid and glutathione metabolism in mice. Mol Syst Biol 11: 834
28. Mardinoglu A, Nielsen J (2016) Editorial: the impact of systems medicine on human health and disease. Front Physiol 7: 552
29. + and glutathione metabolism as intervention target in NAFLD. Mol Syst Biol 13: 916
30. Mardinoglu A, Boren J, Smith U, Uhlen M, Nielsen J (2017b) The employment of systems biology in gastroenterology and hepatology. Nat Rev Gastroenterol Hepatol In press
31. Mukhopadhyay B, Schuebel K, Mukhopadhyay P, Cinar R, Godlewski G, Xiong K, Mackie K, Lizak M, Yuan Q, Goldman D, Kunos G (2015) Cannabinoid receptor 1 promotes hepatocellular carcinoma initiation and progression through multiple mechanisms. Hepatology 61: 1615–1626
32. Nielsen J (2017) Systems biology of metabolism: a driver for developing personalized and precision medicine. Cell Metab 25: 572–579
33. O'Brien EJ, Monk JM, Palsson BO (2015) Using genome-scale models to predict biological capabilities. Cell 161: 971–987
34. Osei-Hyiaman D, DePetrillo M, Pacher P, Liu J, Radaeva S, Batkai S, Harvey-White J, Mackie K, Offertaler L, Wang L, Kunos G (2005) Endocannabinoid activation at hepatic CB1 receptors stimulates fatty acid synthesis and contributes to diet-induced obesity. J Clin Investig 115: 1298–1305
35. Osei-Hyiaman D, Liu J, Zhou L, Godlewski G, Harvey-White J, Jeong WI, Batkai S, Marsicano G, Lutz B, Buettner C, Kunos G (2008) Hepatic CB1 receptor is required for development of diet-induced steatosis, dyslipidemia, and insulin and leptin resistance in mice. J Clin Investig 118: 3160–3169
36. Pandey PR, Liu W, Xing F, Fukuda K, Watabe K (2012) Anti-cancer drugs targeting fatty acid synthase (FAS). Recent Pat Anticancer Drug Discov 7: 185–197
37. Petrick JL, Kelly SP, Altekruse SF, McGlynn KA, Rosenberg PS (2016) Future of hepatocellular carcinoma incidence in the United States forecast through 2030. J Clin Oncol 34: 1787–1794
38. Pons P, Latapy M (2005) Computing communities in large networks using random walks. ISCIS 3733: 284–293
39. Ruscica M, Ferri N, Macchi C, Meroni M, Lanti C, Ricci C, Maggioni M, Fracanzani AL, Badiali S, Fargion S, Magni P, Valenti L, Dongiovanni P (2016) Liver fat accumulation is associated with circulating PCSK9. Ann Med 48: 384–391
40. Salameh H, Hanayneh MA, Masadeh M, Naseemuddin M, Matin T, Erwin A, Singal AK (2016) PNPLA3 as a genetic determinant of risk for and severity of non-alcoholic fatty liver disease spectrum. J Clin Transl Hepatol 4: 175–191
41. Shaker M, Tabbaa A, Albeldawi M, Alkhouri N (2014) Liver transplantation for nonalcoholic fatty liver disease: new challenges and new opportunities. World J Gastroenterol 20: 5320–5330
42. Shoaie S, Ghaffari P, Kovatcheva-Datchary P, Mardinoglu A, Sen P, Pujos-Guillot E, de Wouters T, Juste C, Rizkalla S, Chilloux J, Hoyles L, Nicholson JK, Dore J, Dumas ME, Clement K, Backhed F, Nielsen J (2015) Quantifying diet-induced metabolic changes of the human gut microbiome. Cell Metab 22: 320–331
43. Subramanian A, Tamayo P, Mootha VK, Mukherjee S, Ebert BL, Gillette MA, Paulovich A, Pomeroy SL, Golub TR, Lander ES, Mesirov JP (2005) Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles. Proc Natl Acad Sci USA 102: 15545–15550
44. Teixeira-Clerc F, Julien B, Grenard P, Tran Van Nhieu J, Deveaux V, Li L, Serriere-Lanneau V, Ledent C, Mallat A, Lotersztajn S (2006) CB1 cannabinoid receptor antagonism: a new strategy for the treatment of liver fibrosis. Nat Med 12: 671–676
45. Thul PJ, Akesson L, Wiking M, Mahdessian D, Geladaki A, Ait Blal H, Alm T, Asplund A, Bjork L, Breckels LM, Backstrom A, Danielsson F, Fagerberg L, Fall J, Gatto L, Gnann C, Hober S, Hjelmare M, Johansson F, Lee S et al (2017) A subcellular map of the human proteome. Science 356: eaal3321
46. Uhlen M, Fagerberg L, Hallstrom BM, Lindskog C, Oksvold P, Mardinoglu A, Sivertsson A, Kampf C, Sjöstedt E, Asplund A, Lundberg E, Djureinovic D, Odeberg J, Habuka M, Tahmasebpoor S, Danielsson A, Edlund K, Szigyarto CA, Skogs M, Takanen JO et al (2015) Tissue-based map of the human proteome. Science 347: 1260419
47. Uhlen M, Hallstrom BM, Lindskog C, Mardinoglu A, Ponten F, Nielsen J (2016) Transcriptomics resources of human tissues and organs. Mol Syst Biol 12: 862
48. Varemo L, Scheele C, Broholm C, Mardinoglu A, Kampf C, Asplund A, Nookaew I, Uhlén M, Pedersen BK, Nielsen J (2015) Transcriptome and proteome driven reconstruction of the human myocyte metabolic model and its use for identification of metabolic markers for type 2 diabetes. Cell Rep 11: 921–933
49. Wang H, Chu W, Das SK, Ren Q, Hasstedt SJ, Elbein SC (2002) Liver pyruvate kinase polymorphisms are associated with type 2 diabetes in northern European Caucasians. Diabetes 51: 2861–2865
50. Yizhak K, Gabay O, Cohen H, Ruppin E (2013) Model-based identification of drug targets that revert disrupted metabolism and its application to ageing. Nat Commun 4: 2632
51. Yizhak K, Gaude E, Le Devedec S, Waldman YY, Stein GY, van de Water B, Frezza C, Ruppin E (2014a) Phenotype-based cell-specific metabolic modeling reveals metabolic liabilities of cancer. Elife 3: e03641
52. Yizhak K, Le Devedec SE, Rogkoti VM, Baenke F, de Boer VC, Frezza C, Schulze A, van de Water B, Ruppin E (2014b) A computational study of the Warburg effect identifies metabolic targets inhibiting cancer migration. Mol Syst Biol 10: 744
53. Yizhak K, Chaneton B, Gottlieb E, Ruppin E (2015) Modeling cancer metabolism on a genome scale. Mol Syst Biol 11: 817
54. Younossi ZM, Otgonsuren M, Henry L, Venkatesan C, Mishra A, Erario M, Hunt S (2015) Association of nonalcoholic fatty liver disease (NAFLD) with hepatocellular carcinoma (HCC) in the United States from 2004 to 2009. Hepatology 62: 1723–1730
55. Younossi ZM, Koenig AB, Abdelatif D, Fazel Y, Henry L, Wymer M (2016) Global epidemiology of nonalcoholic fatty liver disease-Meta-analytic assessment of prevalence, incidence, and outcomes. Hepatology 64: 73–84
56. Zhang C, Ji B, Mardinoglu A, Nielsen J, Hua Q (2015) Logical transformation of genome-scale metabolic models for gene level applications and analysis. Bioinformatics 31: 2324–2331
57. Zhang C, Lee S, Mardinoglu A, Hua Q (2016) Investigating the combinatory effects of biological networks on gene co-expression. Front Physiol 7: 160