Display options
Cite
Aoki Y, Nojima M, Suzuki H, et al. Genomic vulnerability to LINE-1 hypomethylation is a potential determinant of the clinicogenetic features of multiple myeloma. Genome Med. 2012;4(12):101doi: 10.1186/gm402.
Aoki, Y., Nojima, M., Suzuki, H., Yasui, H., Maruyama, R., Yamamoto, E., Ashida, M., Itagaki, M., Asaoku, H., Ikeda, H., Hayashi, T., Imai, K., Mori, M., Tokino, T., Ishida, T., Toyota, M., & Shinomura, Y. (2012). Genomic vulnerability to LINE-1 hypomethylation is a potential determinant of the clinicogenetic features of multiple myeloma. Genome medicine, 4(12), 101. https://doi.org/10.1186/gm402
Aoki, Yuka, et al. "Genomic vulnerability to LINE-1 hypomethylation is a potential determinant of the clinicogenetic features of multiple myeloma." Genome medicine vol. 4,12 (2012): 101. doi: https://doi.org/10.1186/gm402
Aoki Y, Nojima M, Suzuki H, Yasui H, Maruyama R, Yamamoto E, Ashida M, Itagaki M, Asaoku H, Ikeda H, Hayashi T, Imai K, Mori M, Tokino T, Ishida T, Toyota M, Shinomura Y. Genomic vulnerability to LINE-1 hypomethylation is a potential determinant of the clinicogenetic features of multiple myeloma. Genome Med. 2012 Dec 22;4(12):101. doi: 10.1186/gm402. eCollection 2012. PMID: 23259664; PMCID: PMC4064317.
Copy Download .nbib Format: NLM
Share it on

Genome Med. 2012 Dec 22;4(12):101. doi: 10.1186/gm402. eCollection 2012.

Genomic vulnerability to LINE-1 hypomethylation is a potential determinant of the clinicogenetic features of multiple myeloma.

Genome medicine

Yuka Aoki, Masanori Nojima, Hiromu Suzuki, Hiroshi Yasui, Reo Maruyama, Eiichiro Yamamoto, Masami Ashida, Mitsuhiro Itagaki, Hideki Asaoku, Hiroshi Ikeda, Toshiaki Hayashi, Kohzoh Imai, Mitsuru Mori, Takashi Tokino, Tadao Ishida, Minoru Toyota, Yasuhisa Shinomura

Affiliations

  1. First Department of Internal Medicine, Sapporo Medical University School of Medicine, S1, W16, Chuo-Ku, Sapporo 060-8543, Japan.
  2. Department of Public Health, Sapporo Medical University School of Medicine, S1, W17, Chuo-ku, Sapporo 060-8556, Japan.
  3. Department of Molecular Biology, Sapporo Medical University School of Medicine, S1, W17, Chuo-ku, Sapporo 060-8556, Japan.
  4. First Department of Internal Medicine, Sapporo Medical University School of Medicine, S1, W16, Chuo-Ku, Sapporo 060-8543, Japan ; Department of Regional Health Care and Medicine, Sapporo Medical University School of Medicine, S1, W17, Chuo-ku, Sapporo 060-8556, Japan.
  5. Department of Hematology, Hiroshima Red Cross and Atomic-bomb Survivors Hospital, 1-9-6 Senda-cho, Hiroshima 730-8619, Japan.
  6. Department of Clinical Laboratory, Hiroshima Red Cross and Atomic-bomb Survivors Hospital, 1-9-6 Senda-cho, Naka-ku, Hiroshima 730-8619, Japan.
  7. Institute of Medical Science, University of Tokyo, 4-6-1 Shirokanedai, Minato-ku, Tokyo 108-8639, Japan.
  8. Division of Medical Genome Sciences, Research Institute for Frontier Medicine, Sapporo Medical University School of Medicine, S1, W17, Chuo-ku, Sapporo 060-8556, Japan.

PMID: 23259664 PMCID: PMC4064317 DOI: 10.1186/gm402

Abstract

BACKGROUND: The aim of this study was to clarify the role of global hypomethylation of repetitive elements in determining the genetic and clinical features of multiple myeloma (MM).

METHODS: We assessed global methylation levels using four repetitive elements (long interspersed nuclear element-1 (LINE-1), Alu Ya5, Alu Yb8, and Satellite-α) in clinical samples comprising 74 MM samples and 11 benign control samples (7 cases of monoclonal gammopathy of undetermined significance (MGUS) and 4 samples of normal plasma cells (NPC)). We also evaluated copy-number alterations using array-based comparative genomic hybridization, and performed methyl-CpG binding domain sequencing (MBD-seq).

RESULTS: Global levels of the repetitive-element methylation declined with the degree of malignancy of plasma cells (NPC>MGUS>MM), and there was a significant inverse correlation between the degree of genomic loss and the LINE-1 methylation levels. We identified 80 genomic loci as common breakpoints (CBPs) around commonly lost regions, which were significantly associated with increased LINE-1 densities. MBD-seq analysis revealed that average DNA-methylation levels at the CBP loci and relative methylation levels in regions with higher LINE-1 densities also declined during the development of MM. We confirmed that levels of methylation of the 5' untranslated region of respective LINE-1 loci correlated strongly with global LINE-1 methylation levels. Finally, there was a significant association between LINE-1 hypomethylation and poorer overall survival (hazard ratio 2.8, P = 0.015).

CONCLUSION: Global hypomethylation of LINE-1 is associated with the progression of and poorer prognosis for MM, possibly due to frequent copy-number loss.

Keywords: Common breakpoints; Global hypomethylation; LINE-1; Multiple myeloma; Repetitive elements

References

  1. Blood. 1997 Apr 1;89(7):2500-6 - PubMed
  2. Curr Pharm Biotechnol. 2006 Oct;7(5):381-93 - PubMed
  3. Blood. 2011 Jan 13;117(2):553-62 - PubMed
  4. Blood. 2002 Mar 15;99(6):2185-91 - PubMed
  5. Cancer Genet Cytogenet. 2006 Sep;169(2):143-9 - PubMed
  6. PLoS One. 2007 May 02;2(5):e399 - PubMed
  7. Oncogene. 2002 Oct 17;21(47):7266-76 - PubMed
  8. Cancer Epidemiol Biomarkers Prev. 2008 Oct;17(10):2555-64 - PubMed
  9. Mol Cancer. 2010 May 27;9:125 - PubMed
  10. Cancer Res. 2008 Jan 1;68(1):44-54 - PubMed
  11. Nature. 2004 May 20;429(6989):268-74 - PubMed
  12. Clin Cancer Res. 2009 Jul 1;15(13):4356-64 - PubMed
  13. Cancer Res. 2004 Jul 1;64(13):4472-80 - PubMed
  14. Blood. 2001 Jul 1;98(1):244-6 - PubMed
  15. Cancer Biol Ther. 2004 Dec;3(12):1225-31 - PubMed
  16. Cancer Cell. 2006 Apr;9(4):313-25 - PubMed
  17. Cell. 2010 Jun 25;141(7):1253-61 - PubMed
  18. Oncogene. 2010 Oct 28;29(43):5775-84 - PubMed
  19. Science. 2011 Feb 4;331(6017):593-6 - PubMed
  20. Gene. 2008 Aug 1;419(1-2):1-6 - PubMed
  21. Gynecol Oncol. 2011 Apr;121(1):24-31 - PubMed
  22. Blood. 2004 Aug 1;104(3):607-18 - PubMed
  23. Cancer Res. 2010 Sep 1;70(17):6934-44 - PubMed
  24. Nature. 2004 Aug 19;430(7002):857-64 - PubMed
  25. Br J Cancer. 2005 Mar 28;92(6):1165-72 - PubMed
  26. Nat Biotechnol. 2010 Oct;28(10):1106-14 - PubMed
  27. Blood. 2007 Apr 15;109(8):3489-95 - PubMed
  28. Int J Cancer. 2011 Jan 1;128(1):33-9 - PubMed
  29. Nat Rev Genet. 2009 Oct;10(10):691-703 - PubMed
  30. J Clin Oncol. 2009 Sep 20;27(27):4585-90 - PubMed
  31. Blood. 2010 Oct 14;116(15):e56-65 - PubMed
  32. Nucleic Acids Res. 2005 Dec 02;33(21):6823-36 - PubMed
  33. Int J Cancer. 2009 Aug 1;125(3):723-9 - PubMed
  34. Blood. 2007 Feb 1;109(3):1228-32 - PubMed
  35. Blood. 2010 Mar 25;115(12):2430-40 - PubMed
  36. Blood. 2006 Sep 15;108(6):2020-8 - PubMed
  37. Nature. 1983 Jan 6;301(5895):89-92 - PubMed
  38. PLoS One. 2011;6(8):e23332 - PubMed
  39. Carcinogenesis. 2009 Aug;30(8):1330-5 - PubMed
  40. Cancer Res. 2001 Sep 15;61(18):6640-8 - PubMed
  41. Proc Natl Acad Sci U S A. 2003 May 13;100(10):5956-61 - PubMed
  42. Int J Hematol. 2010 Jan;91(1):87-96 - PubMed
  43. Blood. 2011 Jan 6;117(1):211-20 - PubMed
  44. Nat Rev Genet. 2002 May;3(5):370-9 - PubMed
  45. PLoS Genet. 2010 Apr 22;6(4):e1000917 - PubMed
  46. Hum Genet. 1984;67(2):136-42 - PubMed
  47. Hum Mol Genet. 2009 Dec 1;18(23):4501-12 - PubMed
  48. J Natl Cancer Inst. 2008 Dec 3;100(23):1734-8 - PubMed
  49. Clin Cancer Res. 2010 Nov 1;16(21):5114-23 - PubMed
  50. Int J Cancer. 2009 Jan 1;124(1):81-7 - PubMed

Publication Types