Systematic integration of molecular profiles identifies miR-22 as a regulator of lipid and folate metabolism in breast cancer cells

Oncogene

Volumn 35, Issue 21, 2016, Pages 2766-2776

  Koufaris, C ^a,b   Valbuena, G N ^a   Pomyen, Y ^a,c   Tredwell, G D ^a   Nevedomskaya, E ^d   Lau, C H E ^a   Yang, T ^a   Benito, A ^a   Ellis, J K ^a   Keun, H C ^a  

^a HAMMERSMITH HOSPITAL   (United Kingdom)

^b CYPRUS INSTITUTE OF NEUROLOGY AND GENETICS   (Cyprus)

^c Chulabhorn Research Institute   (Thailand)

^d LEIDEN UNIVERSITY MEDICAL CENTER   (Netherlands)

Author keywords

[No Author keywords available]

Indexed keywords

ADENOSINE TRIPHOSPHATE CITRATE SYNTHASE; CELL ENZYME; FATTY ACID ELONGASE 6; FOLIC ACID; LIPID; MESSENGER RNA; METHENYLTETRAHYDROFOLATE CYCLOHYDROLASE; METHYLENETETRAHYDROFOLATE DEHYDROGENASE; MICRORNA 22; MYC PROTEIN; UNCLASSIFIED DRUG; MICRORNA; MIRN22 MICRORNA, HUMAN;

ARTICLE; BREAST CANCER; BREAST CANCER CELL LINE; CANCER CELL; CANCER PROGNOSIS; CARBON METABOLISM; CELL ELONGATION; CONTROLLED STUDY; DISEASE ASSOCIATION; DISEASE COURSE; FATTY ACID SYNTHESIS; FOLATE METABOLISM; GENE EXPRESSION; HUMAN; HUMAN CELL; IN VIVO STUDY; INTERACTIONS WITH RNA; LIPID METABOLISM; MALE; METABOLIC REGULATION; METABOLOMICS; MITOCHONDRIAL RESPIRATION; PRIORITY JOURNAL; RNA ANALYSIS; BREAST TUMOR; DOWN REGULATION; FEMALE; GENETICS; MCF-7 CELL LINE; METABOLISM; PATHOLOGY;

BREAST NEOPLASMS; DOWN-REGULATION; FEMALE; FOLIC ACID; HUMANS; LIPID METABOLISM; MCF-7 CELLS; MICRORNAS;

EID: 84971281712     PISSN: 09509232     EISSN: 14765594     Source Type: Journal    
DOI: 10.1038/onc.2015.333     Document Type: Article

References (74)

1. Schulze A Harris AL. How cancer metabolism is tuned for proliferation and vulnerable to disruption. Nature. 2012; 491: 364-373.
2. Vander Heiden MG, Cantley LC, Thompson CB. Understanding the Warburg effect: the metabolic requirements of cell proliferation. Science. 2009; 324: 1029-1033.
3. Anastasiou D, Yu Y, Israelsen WJ, Jiang JK, Boxer MB, Hong BS, et al. Pyruvate kinase M2 activators promote tetramer formation and suppress tumorigenesis. Nat Chem Biol. 2012; 8: 839-847.
4. Rohle D, Popovici-Muller J, Palaskas N, Turcan S, Grommes C, Campos C, et al. An inhibitor of mutant IDH1 delays growth and promotes differentiation of glioma cells. Science. 2013; 340: 626-630.
5. Frezza C, Zheng L, Folger O, Rajagopalan KN, MacKenzie ED, Jerby L, et al. Haem oxygenase is synthetically lethal with the tumour suppressor fumarate hydratase. Nature. 2011; 477: 225-228.
6. Bartel DP. MicroRNAs: target recognition and regulatory functions. Cell. 2009; 136: 215-233.
7. He L, Thomson JM, Hemann MT, Hernando-Monge E, Mu D, Goodson S, et al. A microRNA polycistron as a potential human oncogene. Nature. 2005; 435: 828-833.
8. Shimono Y, Zabala M, Cho RW, Lobo N, Dalerba P, Qian D, et al. Downregulation of miRNA-200c links breast cancer stem cells with normal stem cells. Cell. 2009; 138: 592-603.
9. Medina PP, Nolde M, Slack FJ. OncomiR addiction in an in vivo model of microRNA-21-induced pre-B-cell lymphoma. Nature. 2010; 467: 86-90.
10. Volinia S, Croce CM. Prognostic microRNA/mRNA signature from the integrated analysis of patients with invasive breast cancer. Proc Natl Acad Sci USA. 2013; 110: 7413-7417.
11. Vecchione A, Belletti B, Lovat F, Volinia S, Chiappetta G, Giglio S, et al. A microRNA signature defines chemoresistance in ovarian cancer through modulation of angiogenesis. Proc Natl Acad Sci USA. 2013; 110: 9845-9850.
12. Eichner LJ, Perry MC, Dufour CR, Bertos N, Park M, St-Pierre J, et al. miR-378() mediates metabolic shift in breast cancer cells via the PGC-1beta/ERRgamma transcriptional pathway. Cell Metab. 2010; 12: 352-361.
13. Zhu H, Shyh-Chang N, Segre AV, Shinoda G, Shah SP, Einhorn WS, et al. The Lin28/.let-7 axis regulates glucose metabolism. Cell. 2011; 147: 81-94.
14. Jiang S, Zhang LF, Zhang HW, Hu S, Lu MH, Liang S, et al. A novel miR-155/miR-143 cascade controls glycolysis by regulating hexokinase 2 in breast cancer cells. EMBO J. 2012; 31: 1985-1998.
15. Gao P, Tchernyshyov I, Chang TC, Lee YS, Kita K, Ochi T, et al. c-Myc suppression of miR-23a/b enhances mitochondrial glutaminase expression and glutamine metabolism. Nature. 2009; 458: 762-765.
16. Liu W, Le A, Hancock C, Lane AN, Dang CV, Fan TW, et al. Reprogramming of proline and glutamine metabolism contributes to the proliferative and metabolic responses regulated by oncogenic transcription factor c-MYC. Proc Natl Acad Sci USA. 2012; 109: 8983-8988.
17. Trygg J, Wold S. O2-PLS, a two-block (X-Y) latent variable regression (LVR) method with an integral OSC filter. J Chemometr. 2003; 17: 53-64.
18. Bylesjo M, Eriksson D, Kusano M, Moritz T, Trygg J. Data integration in plant biology: the O2PLS method for combined modeling of transcript and metabolite data. Plant J. 2007; 52: 1181-1191.
19. Rantalainen M, Cloarec O, Beckonert O, Wilson ID, Jackson D, Tonge R, et al. Statistically integrated metabonomic-proteomic studies on a human prostate cancer xenograft model in mice. J Proteome Res. 2006; 5: 2642-2655.
20. Kirwan GM, Johansson E, Kleemann R, Verheij ER, Wheelock AM, Goto S, et al. Building multivariate systems biology models. Anal Chem. 2012; 84: 7064-7071.
21. National Cancer Institute. Molecular Target Data - NCI/NIH Developmental Therapeutics Program Data 2013, Available from https://wiki.nci.nih.gov/display/.NCIDTPdata/Molecular+Target+Data
22. Sokilde R, Kaczkowski B, Podolska A, Cirera S, Gorodkin J, Moller S, et al. Global microRNA analysis of the NCI-60 cancer cell panel. Mol Cancer Ther. 2011; 10: 375-384.
23. O'Donnell KA, Wentzel EA, Zeller KI, Dang CV, Mendell JT. c-Myc-regulated microRNAs modulate E2F1 expression. Nature. 2005; 435: 839-843.
24. Chang TC, Yu D, Lee YS, Wentzel EA, Arking DE, West KM, et al. Widespread microRNA repression by Myc contributes to tumorigenesis. Nat Genet. 2008; 40: 43-50.
25. Marzi MJ, Puggioni EM, Dall'Olio V, Bucci G, Bernard L, Bianchi F, et al. Differentiation-Associated microRNAs antagonize the Rb-E2F pathway to restrict proliferation. J Cell Biol. 2012; 199: 77-95.
26. Pandey DP, Picard D. miR-22 inhibits estrogen signaling by directly targeting the estrogen receptor alpha mRNA. Mol Cell Biol. 2009; 29: 3783-3790.
27. Tsuchiya N, Izumiya M, Ogata-Kawata H, Okamoto K, Fujiwara Y, Nakai M, et al. Tumor suppressor miR-22 determines p53-dependent cellular fate through posttranscriptional regulation of p21. Cancer Res. 2011; 71: 4628-4639.
28. Song SJ, Poliseno L, Song MS, Ala U, Webster K, Ng C, et al. MicroRNA-Antagonism regulates breast cancer stemness and metastasis via TET-family-dependent chromatin remodeling. Cell. 2013; 154: 311-324.
29. Song SJ, Ito K, Ala U, Kats L, Webster K, Sun SM, et al. The oncogenic microRNA miR-22 targets the TET2 tumor suppressor to promote hematopoietic stem cell self-renewal and transformation. Cell Stem Cell. 2013; 13: 87-101.
30. Xu D, Takeshita F, Hino Y, Fukunaga S, Kudo Y, Tamaki A, et al. miR-22 represses cancer progression by inducing cellular senescence. J Cell Biol. 2011; 193: 409-424.
31. Zhang J, Yang Y, Yang T, Liu Y, Li A, Fu S, et al. microRNA-22, downregulated in hepatocellular carcinoma and correlated with prognosis, suppresses cell proliferation and tumourigenicity. Br J Cancer. 2010; 103: 1215-1220.
32. Huang ZP, Chen J, Seok HY, Zhang Z, Kataoka M, Hu X, et al. MicroRNA-22 regulates cardiac hypertrophy and remodeling in response to stress. Circ Res. 2013; 112: 1234-1243.
33. Xiong J, Du Q, Liang Z. Tumor-suppressive microRNA-22 inhibits the transcription of E-box-containing c-Myc target genes by silencing c-Myc binding protein. Oncogene. 2010; 29: 4980-4988.
34. Nagaraja AK, Creighton CJ, Yu Z, Zhu H, Gunaratne PH, Reid JG, et al. A link between mir-100 and FRAP1/mTOR in clear cell ovarian cancer. Mol Endocrinol. 2010; 24: 447-463.
35. Zaidi N, Swinnen JV, Smans K. ATP-citrate lyase: a key player in cancer metabolism. Cancer Res. 2012; 72: 3709-3714.
36. Migita T, Okabe S, Ikeda K, Igarashi S, Sugawara S, Tomida A, et al. Inhibition of ATP citrate lyase induces triglyceride accumulation with altered fatty acid composition in cancer cells. Int J Cancer. 2013; 135: 37-47.
37. Guillou H, Zadravec D, Martin PG, Jacobsson A. The key roles of elongases and desaturases in mammalian fatty acid metabolism: Insights from transgenic mice. Prog Lipid Res. 2010; 49: 186-199.
38. Kelleher JK, Masterson TM. Model equations for condensation biosynthesis using stable isotopes and radioisotopes. Am J Physiol. 1992; 262: E118-E125.
39. Lligona-Trulla L, Arduini A, Aldaghlas TA, Calvani M, Kelleher JK. Acetyl-L-carnitine flux to lipids in cells estimated using isotopomer spectral analysis. J Lipid Res. 1997; 38: 1454-1462.
40. Pike ST, Rajendra R, Artzt K, Appling DR. Mitochondrial C1-Tetrahydrofolate synthase (MTHFD1L) supports the flow of mitochondrial one-carbon units into the methyl cycle in embryos. J Biol Chem. 2010; 285: 4612-4620.
41. Patel JB, Appaiah HN, Burnett RM, Bhat-Nakshatri P, Wang G, Mehta R, et al. Control of EVI-1 oncogene expression in metastatic breast cancer cells through microRNA miR-22. Oncogene. 2011; 30: 1290-1301.
42. Kong LM, Liao CG, Zhang Y, Xu J, Li Y, Huang W, et al. A regulatory loop involving miR-22, Sp1, and c-Myc modulates CD147 expression in breast cancer invasion and metastasis. Cancer Res. 2014; 74: 3764-3778.
43. The Cancer Genome Atlas Network, Comprehensive molecular portraits of human breast tumours. Nature 2012 490 61-70.
44. Farazi TA, Horlings HM, Ten Hoeve JJ, Mihailovic A, Halfwerk H, Morozov P, et al. MicroRNA sequence and expression analysis in breast tumors by deep sequencing. Cancer Res. 2011; 71: 4443-4453.
45. Alvarez-Diaz S, Valle N, Ferrer-Mayorga G, Lombardia L, Herrera M, Dominguez O, et al. MicroRNA-22 is induced by vitamin D and contributes to its antiproliferative, antimigratory and gene regulatory effects in colon cancer cells. Hum Mol Genet. 2012; 21: 2157-2165.
46. Xu XD, Song XW, Li Q, Wang GK, Jing Q, Qin YW. Attenuation of microRNA-22 derepressed PTEN to effectively protect rat cardiomyocytes from hypertrophy. J Cell Physiol. 2012; 227: 1391-1398.
47. Nilsson R, Jain M, Madhusudhan N, Sheppard NG, Strittmatter L, Kampf C, et al. Metabolic enzyme expression highlights a key role for MTHFD2 and the mitochondrial folate pathway in cancer. Nat Commun. 2014; 5: 3128.
48. Jain M, Nilsson R, Sharma S, Madhusudhan N, Kitami T, Souza AL, et al. Metabolite profiling identifies a key role for glycine in rapid cancer cell proliferation. Science. 2012; 336: 1040-1044.
49. Fan J, Ye J, Kamphorst JJ, Shlomi T, Thompson CB, Rabinowitz JD. Quantitative flux analysis reveals folate-dependent NADPH production. Nature. 2014; 510: 298-302.
50. Shin M, Bryant JD, Momb J, Appling DR. Mitochondrial MTHFD2L Is a dual redox cofactor-specific methylenetetrahydrofolate dehydrogenase/methenyltetrahydrofolate cyclohydrolase expressed in both adult and embryonic tissues. J Biol Chem. 2014; 289: 15507-15517.
51. Wellen KE, Hatzivassiliou G, Sachdeva UM, Bui TV, Cross JR, Thompson CB. ATP-citrate lyase links cellular metabolism to histone acetylation. Science. 2009; 324: 1076-1080.
52. Doria ML, Ribeiro AS, Wang J, Cotrim CZ, Domingues P, Williams C, et al. Fatty acid and phospholipid biosynthetic pathways are regulated throughout mammary epithelial cell differentiation and correlate to breast cancer survival. FASEB J. 2014; 28: 4247-4264.
53. Muir K, Hazim A, He Y, Peyressatre M, Kim DY, Song X, et al. Proteomic and lipidomic signatures of lipid metabolism in NASH-Associated hepatocellular carcinoma. Cancer Res. 2013; 73: 4722-4731.
54. Christodoulou F, Raible F, Tomer R, Simakov O, Trachana K, Klaus S, et al. Ancient animal microRNAs and the evolution of tissue identity. Nature. 2010; 463: 1084-1088.
55. Gurha P, Abreu-Goodger C, Wang T, Ramirez MO, Drumond AL, van Dongen S, et al. Targeted deletion of microRNA-22 promotes stress-induced cardiac dilation and contractile dysfunction. Circulation. 2012; 125: 2751-2761.
56. Gurha P, Wang T, Larimore AH, Sassi Y, Abreu-Goodger C, Ramirez MO, et al. microRNA-22 promotes heart failure through coordinate suppression of PPAR/ERR-nuclear hormone receptor transcription. PLoS One. 2013; 8: e75882.
57. Tedeschi PM, Markert EK, Gounder M, Lin H, Dvorzhinski D, Dolfi SC, et al. Contribution of serine, folate and glycine metabolism to the ATP, NADPH and purine requirements of cancer cells. Cell Death Dis. 2013; 4: e877.
58. Lehtinen L, Ketola K, Makela R, Mpindi JP, Viitala M, Kallioniemi O, et al. Highthroughput RNAi screening for novel modulators of vimentin expression identifies MTHFD2 as a regulator of breast cancer cell migration and invasion. Oncotarget. 2013; 4: 48-63.
59. Polioudakis D, Bhinge AA, Killion PJ, Lee BK, Abell NS, Iyer VR. A MycmicroRNA network promotes exit from quiescence by suppressing the interferon response and cell-cycle arrest genes. Nucleic Acids Res. 2013; 41: 2239-2254.
60. Duarte NC, Becker SA, Jamshidi N, Thiele I, Mo ML, Vo TD, et al. Global reconstruction of the human metabolic network based on genomic and bibliomic data. Proc Natl Acad Sci USA. 2007; 104: 1777-1782.
61. Friedman RC, Farh KK, Burge CB, Bartel DP. Most mammalian mRNAs are conserved targets of microRNAs. Genome Res. 2009; 19: 92-105.
62. Trygg J. O2-PLS for qualitative and quantitative analysis in multivariate calibration. J Chemometr. 2002; 16: 283-293.
63. Stein SE. An integrated method for spectrum extraction and compound identification from gas chromatography/mass spectrometry data. J Am Soc Mass Spectrom. 1999; 10: 770-781.
64. Behrends V, Tredwell GD, Bundy JG. A software complement to AMDIS for processing GC-MS metabolomic data. Anal Biochem. 2011; 415: 206-208.
65. Millard P, Letisse F, Sokol S, Portais JC. IsoCor: correcting MS data in isotope labeling experiments. Bioinformatics. 2012; 28: 1294-1296.
66. Helton JC, Johnson JD, Sallaberry CJ, Storlie CB. Survey of sampling-based methods for uncertainty and sensitivity analysis. Reliab Eng Syst Safe. 2006; 91: 1175-1209.
67. Gyorffy B, Lanczky A, Eklund AC, Denkert C, Budczies J, Li Q, et al. An online survival analysis tool to rapidly assess the effect of 22,277 genes on breast cancer prognosis using microarray data of 1,809 patients. Breast Cancer Res Treat. 2010; 123: 725-731.
68. Robinson MD, Oshlack A. A scaling normalization method for differential expression analysis of RNA-seq data. Genome Biol. 2010; 11: R25.
69. Wilson CL, Miller CJ. Simpleaffy: a BioConductor package for Affymetrix Quality Control and data analysis. Bioinformatics. 2005; 21: 3683-3685.
70. Robinson MD, McCarthy DJ, Smyth GK. edgeR: a Bioconductor package for differential expression analysis of digital gene expression data. Bioinformatics. 2010; 26: 139-140.
71. Therneau TM. A Package for Survival Analysis in S 2013, Available from: http://.CRAN.R-project.org/package=survival
72. Lu TP, Lee CY, Tsai MH, Chiu YC, Hsiao CK, Lai LC, et al. miRSystem: an integrated system for characterizing enriched functions and pathways of microRNA targets. PLoS One. 2012; 7: e42390.
73. Meiri E, Levy A, Benjamin H, Ben-David M, Cohen L, Dov A, et al. Discovery of microRNAs and other small RNAs in solid tumors. Nucleic Acids Res. 2010; 38: 6234-6246.
74. Kuchen S, Resch W, Yamane A, Kuo N, Li Z, Chakraborty T, et al. Regulation of microRNA expression and abundance during lymphopoiesis. Immunity. 2010; 32: 828-839.