Skip to main content
SpringerLink
Log in

Analyzing DNA Methylation Patterns During Tumor Evolution

  • Protocol
  • First Online:
Cancer Systems Biology

Part of the book series: Methods in Molecular Biology ((MIMB,volume 1711))

Abstract

Epigenetic modifications play a key role in cellular development and tumorigenesis. Recent large-scale genomic studies have shown that mutations in players of the epigenetic machinery and concomitant perturbation of epigenomic patterning are frequent events in tumors. Among epigenetic marks, DNA methylation is one of the best studied. Hyper- and hypo-methylation events of specific regulatory elements (such as promoters and enhancers) are sometimes thought to be correlated with expression of nearby genes. High-throughput bisulfite converted sequencing is currently the technology of choice for studying DNA methylation in base-pair resolution and on whole-genome scale. Such broad and high-resolution coverage investigations of the epigenome provide unprecedented opportunities to analyze DNA methylation patterns, which are correlated with tumorigenesis, tumor evolution, and tumor progression. However, few computational pipelines are available to the public to perform systematic DNA methylation analysis. Utilizing open source tools, we here describe a comprehensive computational methodology to thoroughly analyze DNA methylation patterns during tumor evolution based on bisulfite converted sequencing data, including intra-tumor methylation heterogeneity.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution

Institutional subscriptions

References

  1. Dawson MA, Kouzarides T (2012) Cancer epigenetics: from mechanism to therapy. Cell 150:12–27

    Article  CAS  PubMed  Google Scholar 

  2. Clozel T, Yang S, Elstrom RL, Tam W, Martin P, Kormaksson M, Banerjee S, Vasanthakumar A, Culjkovic B, Scott DW, Wyman S, Leser M, Shaknovich R, Chadburn A, Tabbo F, Godley LA, Gascoyne RD, Borden KL, Inghirami G, Leonard JP, Melnick A, Cerchietti L (2013) Mechanism-based epigenetic chemosensitization therapy of diffuse large B-cell lymphoma. Cancer Discov 3:1002–1019. https://doi.org/10.1158/2159-8290.CD-13-0117

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  3. Shaknovich R, Melnick A (2011) Epigenetics and B-cell lymphoma. Curr Opin Hematol 18:293–299. https://doi.org/10.1097/MOH.0b013e32834788cf

    Article  PubMed  PubMed Central  Google Scholar 

  4. Pan H, Jiang Y, Boi M, Tabbò F, Redmond D, Nie K, Ladetto M, Chiappella A, Cerchietti L, Shaknovich R, Melnick AM, Inghirami GG, Tam W, Elemento O (2015) Epigenomic evolution in diffuse large B-cell lymphomas. Nat Commun 6:6921

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  5. Lin P-CC, Giannopoulou EG, Park K, Mosquera JM, Sboner A, Tewari AK, Garraway LA, Beltran H, Rubin MA, Elemento O (2013) Epigenomic alterations in localized and advanced prostate cancer. Neoplasia 15:373–383. https://doi.org/10.1593/neo.122146

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  6. Pike BL, Greiner TC, Wang X, Weisenburger DD, Hsu Y-H, Renaud G, Wolfsberg TG, Kim M, Weisenberger DJ, Siegmund KD, Ye W, Groshen S, Mehrian-Shai R, Delabie J, Chan WC, Laird PW, Hacia JG (2008) DNA methylation profiles in diffuse large B-cell lymphoma and their relationship to gene expression status. Leukemia 22:1035–1043. https://doi.org/10.1038/leu.2008.18

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  7. Esteller M (2002) CpG island hypermethylation and tumor suppressor genes: a booming present, a brighter future. Oncogene 21:5427–5440

    Article  CAS  PubMed  Google Scholar 

  8. Shaknovich R, Geng H, Johnson NA, Tsikitas L, Cerchietti L, Greally JM, Gascoyne RD, Elemento O, Melnick A (2010) DNA methylation signatures define molecular subtypes of diffuse large B-cell lymphoma. Blood 116:e81–e89

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  9. Akalin A, Garrett-Bakelman FE, Kormaksson M, Busuttil J, Zhang L, Khrebtukova I, Milne TA, Huang Y, Biswas D, Hess JL, Allis CD, Roeder RG, Valk PJM, Löwenberg B, Delwel R, Fernandez HF, Paietta E, Tallman MS, Schroth GP, Mason CE, Melnick A, Figueroa ME (2012) Base-pair resolution DNA methylation sequencing reveals profoundly divergent epigenetic landscapes in acute myeloid leukemia. PLoS Genet 8:e1002781. https://doi.org/10.1371/journal.pgen.1002781

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  10. Meissner A, Gnirke A, Bell GW, Ramsahoye B, Lander ES, Jaenisch R (2005) Reduced representation bisulfite sequencing for comparative high-resolution DNA methylation analysis. Nucleic Acids Res 33:5868–5877

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  11. Sidow A, Spies N (2015) Concepts in solid tumor evolution. Trends Genet 31:208–214

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  12. Landau DA, Clement K, Ziller MJ, Boyle P, Fan J, Gu H, Stevenson K, Sougnez C, Wang L, Li S, Kotliar D, Zhang W, Ghandi M, Garraway L, Fernandes SM, Livak KJ, Gabriel S, Gnirke A, Lander ES, Brown JR, Neuberg D, Kharchenko PV, Hacohen N, Getz G, Meissner A, Wu CJ (2014) Locally disordered methylation forms the basis of intratumor methylome variation in chronic lymphocytic leukemia. Cancer Cell 26:813–825. https://doi.org/10.1016/j.ccell.2014.10.012

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  13. Andrews S (2010) FastQC: a quality control tool for high throughput sequence data. http://www.bioinformatics.babraham.ac.uk/projects/fastqc/ http://www.bioinformatics.babraham.ac.uk/projects/. doi: citeulike-article-id:11583827

  14. Krueger F (2012) Trim Galore!. http://www.bioinformatics.babraham.ac.uk/projects/trim_galore/

  15. Krueger F, Andrews SR (2011) Bismark: a flexible aligner and methylation caller for Bisulfite-Seq applications. Bioinformatics 27:1571–1572

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  16. Giannopoulou EG, Elemento O (2011) An integrated ChIP-seq analysis platform with customizable workflows. BMC Bioinformatics 12:277

    Article  PubMed  PubMed Central  Google Scholar 

  17. Goodarzi H, Elemento O, Tavazoie S (2009) Revealing global regulatory perturbations across human cancers. Mol Cell 36:900–911. https://doi.org/10.1016/j.molcel.2009.11.016

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  18. R Development Core Team (2011) R Foundation for Statistical Computing, Vienna AI 3-900051-07-0. R A Lang Environ Stat Comput 55:275–286

    Google Scholar 

  19. Lawrence M, Huber W, Pagès H, Aboyoun P, Carlson M, Gentleman R, Morgan MT, Carey VJ (2013) Software for computing and annotating genomic ranges. PLoS Comput Biol 9:e1003118

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  20. Xi Y, Li W (2009) BSMAP: whole genome bisulfite sequence MAPping program. BMC Bioinformatics 10:1–9

    Article  Google Scholar 

  21. Smith AD, Chung WY, Hodges E, Kendall J, Hannon G, Hicks J, Xuan Z, Zhang MQ (2009) Updates to the RMAP short-read mapping software. Bioinformatics 25:2841–2842

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  22. Li H, Ruan J, Durbin R (2008) Mapping short DNA sequencing reads and calling variants using mapping quality scores. Genome Res 18:1851–1858

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  23. Chen P-Y, Cokus SJ, Pellegrini M (2010) BS Seeker: precise mapping for bisulfite sequencing. BMC Bioinformatics 11:203

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  24. Kent WJ, Sugnet CW, Furey TS, Roskin KM, Pringle TH, Zahler AM, Haussler a D (2002) The Human Genome Browser at UCSC. Genome Res 12:996–1006. https://doi.org/10.1101/gr.229102

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  25. Aken BL, Ayling S, Barrell D, Clarke L, Curwen V, Fairley S, Fernandez-Banet J, Billis K, Garcia-Giron C, Hourlier T, Howe KL, Kahari AK, Kokocinski F, Martin FJ, Murphy DN, Nag R, Ruffier M, Schuster M, Tang YA, Vogel J-H, White S, Zadissa A, Flicek P, Searle SMJ (2016) The Ensembl gene annotation system. Database (Oxford) 2016:baw093. https://doi.org/10.1093/database/baw093

    Article  Google Scholar 

  26. Langmead B, Trapnell C, Pop M, Salzberg SL (2009) Ultrafast and memory-efficient alignment of short DNA sequences to the human genome. Genome Biol 10:1–25. https://doi.org/10.1186/gb-2009-10-3-r25. gb-2009-10-3-r25 [pii]\r

    Article  Google Scholar 

  27. Langmead B, Salzberg SL (2012) Fast gapped-read alignment with Bowtie 2. Nat Methods 9:357–359

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  28. Ashburner M, Ball CA, Blake JA, Botstein D, Butler H, Cherry JM, Davis AP, Dolinski K, Dwight SS, Eppig JT, Harris MA, Hill DP, Issel-Tarver L, Kasarskis A, Lewis S, Matese JC, Richardson JE, Ringwald M, Rubin GM, Sherlock G (2000) Gene ontology: tool for the unification of biology. The Gene Ontology Consortium. Nat Genet 25:25–29

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  29. Shaffer AL, Wright G, Yang L, Powell J, Ngo V, Lamy L, Lam LT, Davis RE, Staudt LM (2006) A library of gene expression signatures to illuminate normal and pathological lymphoid biology. Immunol Rev 210:67–85. https://doi.org/10.1111/j.0105-2896.2006.00373.x

    Article  CAS  PubMed  Google Scholar 

  30. Kolde R (2012) Package ‘pheatmap’. Bioconductor:1–6

    Google Scholar 

  31. Kanehisa M, Sato Y, Kawashima M, Furumichi M, Tanabe M (2016) KEGG as a reference resource for gene and protein annotation. Nucleic Acids Res 44:D457–D462

    Article  CAS  PubMed  Google Scholar 

  32. Ogata H, Goto S, Sato K, Fujibuchi W, Bono H, Kanehisa M (1999) KEGG: Kyoto encyclopedia of genes and genomes. Nucleic Acids Res 27:29–34

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  33. 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 U S A 102:15545–15550

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  34. Lai AY, Fatemi M, Dhasarathy A, Malone C, Sobol SE, Geigerman C, Jaye DL, Mav D, Shah R, Li L, Wade PA (2010) DNA methylation prevents CTCF-mediated silencing of the oncogene BCL6 in B cell lymphomas. J Exp Med 207:1939–1950

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  35. Landan G, Cohen NM, Mukamel Z, Bar A, Molchadsky A, Brosh R, Horn-Saban S, Zalcenstein DA, Goldfinger N, Zundelevich A, Gal-Yam EN, Rotter V, Tanay A (2012) Epigenetic polymorphism and the stochastic formation of differentially methylated regions in normal and cancerous tissues. Nat Genet 44:1207–1214. https://doi.org/10.1038/ng.2442

    Article  CAS  PubMed  Google Scholar 

  36. Eichten SR, Stuart T, Srivastava A, Lister R, Borevitz JO (2016) DNA methylation profiles of diverse Brachypodium distachyon aligns with underlying genetic diversity. Genome Res 26:1520–1531. https://doi.org/10.1101/gr.205468.116

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  37. Li S, Garrett-Bakelman F, Perl AE, Luger SM, Zhang C, To BL, Lewis ID, Brown AL, D’Andrea RJ, Ross ME, Levine R, Carroll M, Melnick A, Mason CE (2014) Dynamic evolution of clonal epialleles revealed by methclone. Genome Biol 15:472

    Article  PubMed  PubMed Central  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Physiology and Biophysics, Institute for Precision Medicine, Institute for Computational Biomedicine, Weill Cornell Medical College, 1305 York Avenue, New York, NY, 10021, USA

    Heng Pan & Olivier Elemento

Authors
  1. Heng Pan
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Olivier Elemento
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Olivier Elemento .

Editor information

Editors and Affiliations

  1. NNF Center for Protein Research, University of Copenhagen, Copenhagen, Denmark

    Louise von Stechow

Rights and permissions

Reprints and permissions

Copyright information

© 2018 Springer Science+Business Media LLC

About this protocol

Check for updates. Verify currency and authenticity via CrossMark

Cite this protocol

Pan, H., Elemento, O. (2018). Analyzing DNA Methylation Patterns During Tumor Evolution. In: von Stechow, L. (eds) Cancer Systems Biology. Methods in Molecular Biology, vol 1711. Humana Press, New York, NY. https://doi.org/10.1007/978-1-4939-7493-1_3

Download citation

  • DOI: https://doi.org/10.1007/978-1-4939-7493-1_3

  • Published:

  • Publisher Name: Humana Press, New York, NY

  • Print ISBN: 978-1-4939-7492-4

  • Online ISBN: 978-1-4939-7493-1

  • eBook Packages: Springer Protocols

Publish with us

Policies and ethics

Search

Navigation