Integrative DNA methylome analysis of pan-cancer biomarkers in cancer discordant monozygotic twin-pairs

Clinical Epigenetics

Volumn 8, Issue 1, 2016, Pages 1-16

  Roos, Leonie ^a   van Dongen, Jenny ^b   Bell, Christopher G ^a,c,d   Burri, Andrea ^e   Deloukas, Panos ^f   Boomsma, Dorret I ^b   Spector, Tim D ^a   Bell, Jordana T ^a  

^a KING'S COLLEGE LONDON   (United Kingdom)

^b VU UNIVERSITY AMSTERDAM   (Netherlands)

^c UNIVERSITY OF SOUTHAMPTON   (United Kingdom)

^d UNIVERSITY OF SOUTHAMPTON   (United Kingdom)

^e UNIVERSITY OF ZURICH   (Switzerland)

^f QUEEN MARY UNIVERSITY OF LONDON   (United Kingdom)

Author keywords

Biomarker; Cancer; Discordant monozygotic twins; DNA methylation; Epigenetics; Twin study

Indexed keywords

DNA; PANCANCER BIOMARKER; SPACER DNA; TUMOR MARKER; UNCLASSIFIED DRUG; GENETIC MARKER;

ADULT; AGED; ARTICLE; BREAST CANCER; CANCER DIAGNOSIS; CANCER EPIDEMIOLOGY; CLINICAL ARTICLE; COLON CANCER; CONTROLLED STUDY; CPG ISLAND; DIAGNOSTIC VALUE; DNA METHYLATION; DNA METHYLATION ASSAY; DNA METHYLOME; ENDOMETRIUM CANCER; ENHANCER REGION; EPIGENETICS; FEMALE; FOLLOW UP; GENE EXPRESSION; GENE REPLICATION; GENETIC ASSOCIATION; GENETIC EPIDEMIOLOGY; HUMAN; HUMAN TISSUE; LYMPHOBLASTOID CELL; MELANOMA; MONOZYGOTIC TWINS; NEOPLASM; ONCOGENE AXL; ONCOGENE COL11A2; ONCOGENE LINC00340; ONCOGENE SASH1; OVARY CANCER; PANCREAS CANCER; PRIORITY JOURNAL; PROMOTER REGION; SIGNAL TRANSDUCTION; SKIN; THYROID CANCER; TUMOR SUPPRESSOR GENE; TWIN DISCORDANCE; UTERINE CERVIX CANCER; ADVERSE EFFECTS; AGE; BREAST TUMOR; COLON TUMOR; ENDOMETRIUM TUMOR; GENETIC MARKER; GENETICS; MALE; MIDDLE AGED; OVARY TUMOR; PANCREAS TUMOR; RISK FACTOR; SKIN TUMOR; SMOKING; THYROID TUMOR; TWINS; UTERINE CERVIX TUMOR;

ADULT; AGE FACTORS; AGED; BREAST NEOPLASMS; COLONIC NEOPLASMS; DISEASES IN TWINS; DNA METHYLATION; ENDOMETRIAL NEOPLASMS; EPIGENOMICS; FEMALE; GENETIC MARKERS; HUMANS; MALE; MELANOMA; MIDDLE AGED; NEOPLASMS; OVARIAN NEOPLASMS; PANCREATIC NEOPLASMS; RISK FACTORS; SKIN NEOPLASMS; SMOKING; THYROID NEOPLASMS; TWINS, MONOZYGOTIC; UTERINE CERVICAL NEOPLASMS;

EID: 85001875348     PISSN: 18687075     EISSN: 18687083     Source Type: Journal    
DOI: 10.1186/s13148-016-0172-y     Document Type: Article

References (78)

1. International Agency for Research on Cancer. World Cancer Report 2014. WHO Press; 2014
2. Gulland A. Global cancer prevalence is growing at “alarming pace”, says WHO. BMJ. 2014;348:g1338.
3. Siegel R, Ma J, Zou Z, Jemal A. Cancer statistics, 2014. CA Cancer J Clin. 2014;64:9–29.
4. Hanash SM, Baik CS, Kallioniemi O. Emerging molecular biomarkers—blood-based strategies to detect and monitor cancer. Nat Rev Clin Oncol. 2011;8:142–50.
5. Heyn H, Esteller M. DNA methylation profiling in the clinic: applications and challenges. Nat Rev Genet. 2012;13:679–92.
6. Ogino S, Lochhead P, Chan AT, Nishihara R, Cho E, Wolpin BM, et al. Molecular pathological epidemiology of epigenetics: emerging integrative science to analyze environment, host, and disease. Mod Pathol. 2013;26:465–84.
7. Bell JT, Pai AA, Pickrell JK, Gaffney DJ, Pique-Regi R, Degner JF, et al. DNA methylation patterns associate with genetic and gene expression variation in HapMap cell lines. Genome Biol. 2011;12:R10.
8. Zeilinger S, Kühnel B, Klopp N, Baurecht H, Kleinschmidt A, Gieger C, et al. Tobacco smoking leads to extensive genome-wide changes in DNA methylation. PLoS ONE. 2013;8.
9. Tobi EW, Goeman JJ, Monajemi R, Gu H, Putter H, Zhang Y, et al. DNA methylation signatures link prenatal famine exposure to growth and metabolism. Nat Commun. 2014;5.
10. Horvath S. DNA methylation age of human tissues and cell types. Genome Biol. 2013;14:R115.
11. Shah S, McRae AF, Marioni RE, Harris SE, Gibson J, Henders AK, et al. Genetic and environmental exposures constrain epigenetic drift over the human life course. Genome Res. 2014;24:gr.176933.114.
12. Feil R, Fraga MF. Epigenetics and the environment: emerging patterns and implications. Nat Rev Genet. 2012;13:97–109.
13. Liu Y, Aryee MJ, Padyukov L, Fallin MD, Hesselberg E, Runarsson A, et al. Epigenome-wide association data implicate DNA methylation as an intermediary of genetic risk in rheumatoid arthritis. Nat Biotechnol. 2013;31:142–7.
14. Talens RP, Christensen K, Putter H, Willemsen G, Christiansen L, Kremer D, et al. Epigenetic variation during the adult lifespan: cross-sectional and longitudinal data on monozygotic twin pairs. Aging Cell. 2012;11:694–703.
15. Breitling LP, Yang R, Korn B, Burwinkel B, Brenner H. Tobacco-smoking-related differential DNA methylation: 27 K discovery and replication. Am J Hum Genet. 2011;88:450–7.
16. Elliott HR, Tillin T, McArdle WL, Ho K, Duggirala A, Frayling TM, et al. Differences in smoking associated DNA methylation patterns in South Asians and Europeans. Clin Epigenetics. 2014;6:4.
17. Joubert BR, Håberg SE, Nilsen RM, Wang X, Vollset SE, Murphy SK, et al. 450K epigenome-wide scan identifies differential DNA methylation in newborns related to maternal smoking during pregnancy. Environ Health Perspect. 2012;120:1425–31.
18. Wan ES, Qiu W, Baccarelli A, Carey VJ, Bacherman H, Rennard SI, et al. Cigarette smoking behaviors and time since quitting are associated with differential DNA methylation across the human genome. Hum Mol Genet. 2012;21:3073–82.
19. Baylin SB, Jones PA. A decade of exploring the cancer epigenome—biological and translational implications. Nat Rev Cancer. 2011;11:726–34.
20. Esteller M. Epigenetics in cancer. N Engl J Med. 2008;358:1148–59.
21. Yi JM, Guzzetta AA, Bailey VJ, Downing SR, Neste LV, Chiappinelli KB, et al. Novel methylation biomarker panel for the early detection of pancreatic cancer. Clin Cancer Res. 2013;19:6544–55.
22. Anjum S, Fourkala E-O, Zikan M, Wong A, Gentry-Maharaj A, Jones A, et al. A BRCA1-mutation associated DNA methylation signature in blood cells predicts sporadic breast cancer incidence and survival. Genome Med. 2014;6:47.
23. Heyn H, Carmona FJ, Gomez A, Ferreira HJ, Bell JT, Sayols S, et al. DNA methylation profiling in breast cancer discordant identical twins identifies DOK7 as novel epigenetic biomarker. Carcinogenesis. 2013;34:102–8.
24. Lim U, Flood A, Choi S, Albanes D, Cross AJ, Schatzkin A, et al. Genomic methylation of leukocyte DNA in relation to colorectal adenoma among asymptomatic women. Gastroenterology. 2008;134:47–55.
25. Langevin SM, Houseman EA, Accomando WP, Koestler DC, Christensen BC, Nelson HH, et al. Leukocyte-adjusted epigenome-wide association studies of blood from solid tumor patients. Epigenetics. 2014;9:884–95.
26. Teschendorff AE, Menon U, Gentry-Maharaj A, Ramus SJ, Gayther SA, Apostolidou S, et al. An epigenetic signature in peripheral blood predicts active ovarian cancer. PLoS ONE. 2009;4:e8274.
27. The Cancer Genome Atlas Research Network, Weinstein JN, Collisson EA, Mills GB, Shaw KRM, Ozenberger BA, et al. The Cancer Genome Atlas pan-cancer analysis project. Nat Genet. 2013;45:1113–20.
28. Witte T, Plass C, Gerhauser C. Pan-cancer patterns of DNA methylation. Genome Med. 2014;6.
29. Gevaert O, Tibshirani R, Plevritis SK. Pancancer analysis of DNA methylation-driven genes using MethylMix. Genome Biol. 2015;16.
30. Roos L, Spector TD, Bell CG. Using epigenomic studies in monozygotic twins to improve our understanding of cancer. Epigenomics. 2014;6:299–309.
31. Gordon L, Joo JE, Powell JE, Ollikainen M, Novakovic B, Li X, et al. Neonatal DNA methylation profile in human twins is specified by a complex interplay between intrauterine environmental and genetic factors, subject to tissue-specific influence. Genome Res. 2012;22:1395–406.
32. Wong CCY, Meaburn EL, Ronald A, Price TS, Jeffries AR, Schalkwyk LC, et al. Methylomic analysis of monozygotic twins discordant for autism spectrum disorder and related behavioural traits. Mol Psychiatry. 2014;19:495–503.
33. Bell JT, Tsai P-C, Yang T-P, Pidsley R, Nisbet J, Glass D, et al. Epigenome-wide scans identify differentially methylated regions for age and age-related phenotypes in a healthy ageing population. PLoS Genet. 2012;8:e1002629.
34. Grundberg E, Meduri E, Sandling JK, Hedman AK, Keildson S, Buil A, et al. Global analysis of DNA methylation variation in adipose tissue from twins reveals links to disease-associated variants in distal regulatory elements. Am J Hum Genet. 2013;93:876–90.
35. Leconet W, Larbouret C, Chardès T, Thomas G, Neiveyans M, Busson M, et al. Preclinical validation of AXL receptor as a target for antibody-based pancreatic cancer immunotherapy. Oncogene. 2014;33:5405–14.
36. Bansal N, Mishra PJ, Stein M, DiPaola RS, Bertino JR. Axl receptor tyrosine kinase is up-regulated in metformin resistant prostate cancer cells. Oncotarget 2015, 6:15321.
37. Martinelli E, Martini G, Cardone C, Troiani T, Liguori G, Vitagliano D, et al. AXL is an oncotarget in human colorectal cancer. Oncotarget. 2015;5.
38. Cheung N-KV, Dyer MA. Neuroblastoma: developmental biology, cancer genomics and immunotherapy. Nat Rev Cancer. 2013;13:397–411.
39. Cicek MS, Koestler DC, Fridley BL, Kalli KR, Armasu SM, Larson MC, et al. Epigenome-wide ovarian cancer analysis identifies a methylation profile differentiating clear-cell histology with epigenetic silencing of the HERG K+ channel. Hum Mol Genet. 2013;22:3038–47.
40. Jaffe AE, Murakami P, Lee H, Leek JT, Fallin MD, Feinberg AP, et al. Bump hunting to identify differentially methylated regions in epigenetic epidemiology studies. Int J Epidemiol. 2012;41:200–9.
41. Bonora E, Evangelisti C, Bonichon F, Tallini G, Romeo G. Novel germline variants identified in the inner mitochondrial membrane transporter TIMM44 and their role in predisposition to oncocytic thyroid carcinomas. Br J Cancer. 2006;95:1529–36.
42. Keita M, Wang Z-Q, Pelletier J-F, Bachvarova M, Plante M, Gregoire J, et al. Global methylation profiling in serous ovarian cancer is indicative for distinct aberrant DNA methylation signatures associated with tumor aggressiveness and disease progression. Gynecol Oncol. 2013;128:356–63.
43. Specht K, Harbeck N, Smida J, Annecke K, Reich U, Naehrig J, et al. Expression profiling identifies genes that predict recurrence of breast cancer after adjuvant CMF-based chemotherapy. Breast Cancer Res Treat. 2008;118:45–56.
44. Steegenga WT, Boekschoten MV, Lute C, Hooiveld GJ, de Groot PJ, Morris TJ, et al. Genome-wide age-related changes in DNA methylation and gene expression in human PBMCs. Age Dordr Neth. 2014;36:9648.
45. Marsit CJ, Koestler DC, Christensen BC, Karagas MR, Houseman EA, Kelsey KT. DNA methylation array analysis identifies profiles of blood-derived DNA methylation associated with bladder cancer. J Clin Oncol. 2011;29:1133–9.
46. Brooks AN, Choi PS, de Waal L, Sharifnia T, Imielinski M, Saksena G, et al. A pan-cancer analysis of transcriptome changes associated with somatic mutations in U2AF1 reveals commonly altered splicing events. PLoS ONE. 2014;9:e87361.
47. Kaminsky ZA, Tang T, Wang S-C, Ptak C, Oh GHT, Wong AHC, et al. DNA methylation profiles in monozygotic and dizygotic twins. Nat Genet. 2009;41:240–5.
48. Meng Q, Zheng M, Liu H, Song C, Zhang W, Yan J, et al. SASH1 regulates proliferation, apoptosis, and invasion of osteosarcoma cell. Mol Cell Biochem. 2012;373:201–10.
49. Zeller C, Hinzmann B, Seitz S, Prokoph H, Burkhard-Goettges E, Fischer J, et al. SASH1: a candidate tumor suppressor gene on chromosome 6q24.3 is downregulated in breast cancer. Oncogene. 2003;22:2972–83.
50. Rimkus C, Martini M, Friederichs J, Rosenberg R, Doll D, Siewert JR, et al. Prognostic significance of downregulated expression of the candidate tumour suppressor gene SASH1 in colon cancer. Br J Cancer. 2006;95:1419–23.
51. Grafodatskaya D, Choufani S, Ferreira JC, Butcher DT, Lou Y, Zhao C, et al. EBV transformation and cell culturing destabilizes DNA methylation in human lymphoblastoid cell lines. Genomics. 2010;95:73–83.
52. Çalışkan M, Pritchard JK, Ober C, Gilad Y. The effect of freeze-thaw cycles on gene expression levels in lymphoblastoid cell lines. PLoS ONE. 2014;9:e107166.
53. Joehanes R, Johnson AD, Barb JJ, Raghavachari N, Liu P, Woodhouse KA, et al. Gene expression analysis of whole blood, peripheral blood mononuclear cells, and lymphoblastoid cell lines from the Framingham Heart Study. Physiol Genomics. 2012;44:59–75.
54. Suzuki MM, Bird A. DNA methylation landscapes: provocative insights from epigenomics. Nat Rev Genet. 2008;9:465–76.
55. Bessette DC, Qiu D, Pallen CJ. PRL PTPs: mediators and markers of cancer progression. Cancer Metastasis Rev. 2008;27:231–52.
56. Dumaual CM, Sandusky GE, Soo HW, Werner SR, Crowell PL, Randall SK. Tissue-specific alterations of PRL-1 and PRL-2 expression in cancer. Am J Transl Res. 2012;4:83–101.
57. Hardy S, Wong NN, Muller WJ, Park M, Tremblay ML. Overexpression of the protein tyrosine phosphatase PRL-2 correlates with breast tumor formation and progression. Cancer Res. 2010;70:8959–67.
58. Jandaghi P, Hoheisel JD, Riazalhosseini Y. GHSR hypermethylation: a promising pan-cancer marker. Cell Cycle. 2015, 0(ja):00–00.
59. Akbani R, Ng PKS, Werner HMJ, Shahmoradgoli M, Zhang F, Ju Z, et al. A pan-cancer proteomic perspective on The Cancer Genome Atlas. Nat Commun. 2014;5.
60. Kandoth C, McLellan MD, Vandin F, Ye K, Niu B, Lu C, et al. Mutational landscape and significance across 12 major cancer types. Nature. 2013;502:333–9.
61. Zack TI, Schumacher SE, Carter SL, Cherniack AD, Saksena G, Tabak B, et al. Pan-cancer patterns of somatic copy number alteration. Nat Genet. 2013;45:1134–40.
62. Bauer M, Linsel G, Fink B, Offenberg K, Hahn AM, Sack U, et al. A varying T cell subtype explains apparent tobacco smoking induced single CpG hypomethylation in whole blood. Clin Epigenetics. 2015;7:1–11.
63. Tsai P-C, Bell JT. Power and sample size estimation for epigenome-wide association scans to detect differential DNA methylation. Int J Epidemiol 2015:dyv041.
64. Cohen J: Power Analysis for the Behavioral Sciences. 2nd edition.
65. Andrew T, Hart DJ, Snieder H, de Lange M, Spector TD, MacGregor AJ. Are twins and singletons comparable? A study of disease-related and lifestyle characteristics in adult women. Twin Res Hum Genet. 2001;4:464–77.
66. Dedeurwaerder S, Defrance M, Calonne E, Denis H, Sotiriou C, Fuks F. Evaluation of the Infinium Methylation 450K technology. Epigenomics. 2011;3:771–84.
67. Aryee MJ, Jaffe AE, Corrada-Bravo H, Ladd-Acosta C, Feinberg AP, Hansen KD, et al. Minfi: a flexible and comprehensive Bioconductor package for the analysis of Infinium DNA methylation microarrays. Bioinformatics. 2014;30:1363–9.
68. Schalkwyk LC, Pidsley R, Wong CC, Touleimat N, Defrance M, Teschendorff A, et al. wateRmelon: Illumina 450 Methylation Array Normalization and Metrics. 2013.
69. Butcher L. Illumina450ProbeVariants.db: annotation package combining variant data from 1000 genomes project for Illumina HumanMethylation450 Bead Chip probes. R package version 1.3.1. 2013.
70. Teschendorff AE, Marabita F, Lechner M, Bartlett T, Tegner J, Gomez-Cabrero D, et al. A beta-mixture quantile normalization method for correcting probe design bias in Illumina Infinium 450k DNA methylation data. Bioinforma Oxf Engl. 2013;29:189–96.
71. Houseman EA, Accomando WP, Koestler DC, Christensen BC, Marsit CJ, Nelson HH, et al. DNA methylation arrays as surrogate measures of cell mixture distribution. BMC Bioinformatics. 2012;13:86.
72. Grundberg E, Small KS, Hedman ÅK, Nica AC, Buil A, Keildson S, et al. Mapping cis- and trans-regulatory effects across multiple tissues in twins. Nat Genet. 2012;44:1084–9.
73. Houseman EA, Molitor J, Marsit CJ. Reference-free cell mixture adjustments in analysis of DNA methylation data. Bioinforma Oxf Engl. 2014;30:1431–9.
74. Zou J, Lippert C, Heckerman D, Aryee M, Listgarten J. Epigenome-wide association studies without the need for cell-type composition. Nat Methods. 2014;11:309–11.
75. Willemsen G, de Geus EJC, Bartels M, van Beijsterveldt CEMT, Brooks AI, Estourgie-van Burk GF, et al. The Netherlands twin register Biobank: a resource for genetic epidemiological studies. Twin Res Hum Genet. 2010;13:231–45.
76. Fortin J-P, Labbe A, Lemire M, Zanke BW, Hudson TJ, Fertig EJ, et al. Functional normalization of 450k methylation array data improves replication in large cancer studies. Genome Biol. 2014;15:503.
77. Ernst J, Kheradpour P, Mikkelsen TS, Shoresh N, Ward LD, Epstein CB, et al. Systematic analysis of chromatin state dynamics in nine human cell types. Nature. 2011;473:43–9.
78. Ernst J, Kellis M. Discovery and characterization of chromatin states for systematic annotation of the human genome. Nat Biotechnol 2010; 28:817–25.