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Cellular Oncology

, Volume 40, Issue 3, pp 293–297 | Cite as

Epigenetic sampling effects: nephrectomy modifies the clear cell renal cell cancer methylome

  • Christophe Van Neste
  • Alexander Laird
  • Fiach O’Mahony
  • Wim Van Criekinge
  • Dieter Deforce
  • Filip Van Nieuwerburgh
  • Thomas Powles
  • David J. HarrisonEmail author
  • Grant D. Stewart
  • Tim De Meyer
Report
  • 206 Downloads

Abstract

Purpose

Currently, it is unclear to what extent sampling procedures affect the epigenome. Here, this phenomenon was evaluated by studying the impact of artery ligation on DNA methylation in clear cell renal cancer.

Methods

DNA methylation profiles between vascularised tumour biopsy samples and devascularised nephrectomy samples from two individuals were compared. The relevance of significantly altered methylation profiles was validated in an independent clinical trial cohort.

Results

We found that six genes were differentially methylated in the test samples, of which four were linked to ischaemia or hypoxia (REXO1L1, TLR4, hsa-mir-1299, ANKRD2). Three of these genes were also found to be significantly differentially methylated in the validation cohort, indicating that the observed effects are genuine.

Conclusion

Tissue ischaemia during normal surgical removal of tumour can cause epigenetic changes. Based on these results, we conclude that the impact of sampling procedures in clinical epigenetic studies should be considered and discussed, particularly after inducing hypoxia/ischaemia, which occurs in most oncological surgery procedures through which tissues are collected for translational research.

Keywords

Hypoxia Cancer epigenetics DNA methylation Sampling effects 

Notes

Author’s contributions

Conception and design: DJH, AL, GDS, TDM, TP. Development of methodology: CVN, GDS, DJH, TP, TDM. Acquisition of data (acquired and managed patients, provided facilities, etc.): GDS, FOM, AL, DJH, TP. Analysis and interpretation of data (e.g., statistical analysis, biostatistics, computational analysis): CVN, TDM, GDS, DJH. Writing, review, and/or revision of the manuscript: CVN, AL, FOM, WVC, DD, FVN, TP, DJH, GDS, TDM. Study supervision: GDS, DJH, TDM, WVC.

Compliance with ethical standards

All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards. Permission to use tissue was obtained from local research ethics committees.

Funding

This work was supported by the Chief Scientist Office, Scotland (ETM37; GDS, DJH), Cancer Research UK (Experimental Cancer Medicine Centre; TP, London, DJH, Edinburgh), Medical Research Council (AL, DJH), Royal College of Surgeons of Edinburgh Robertson Trust (AL), Melville Trust AL), Renal Cancer Research Fund (GDS, DJH), Kidney Cancer Scotland (GDS) and an educational grant from Pfizer (TP). CVN and TDM were funded by Ghent University Multidisciplinary Research Partnership ‘Bioinformatics: from nucleotides to networks’.

Conflict of interest

The authors declare that they have no conflict of interest.

Informed consent

Informed consent was obtained from all participants included in the study.

Supplementary material

13402_2016_313_MOESM1_ESM.pdf (20 kb)
ESM 1 (PDF 20 kb)

References

  1. 1.
    A. Ferraro, Primary chromatin structures and their implications in cancer development. Cell Oncol 39, 195–210 (2016). doi: 10.1007/s13402-016-0276-6
  2. 2.
    V. Taucher, H. Mangge, J. Haybaeck, Non-coding RNAs in pancreatic cancer: challenges and opportunities for clinical application. Cell Oncol 39, 295–318 (2016). doi: 10.1007/s13402-016-0275-7
  3. 3.
    M. Vitiello, A. Tuccoli, L. Poliseno, Long non-coding RNAs in cancer: implications for personalized therapy. Cell Oncol 38, 17–28 (2015). doi: 10.1007/s13402-014-0180-x
  4. 4.
    K. Sharpe, G.D. Stewart, A. Mackay, C. Van Neste, C. Rofe, D. Berney, I. Kayani, A. Bex, E. Wan, F.C. O’Mahony, M. O’Donnell, S. Chowdhury, R. Doshi, C. Ho-Yen, M. Gerlinger, D. Baker, N. Smith, B. Davies, A. Sahdev, E. Boleti, T.D. Meyer, W.V. Criekinge, L. Beltran, Y.-J. Lu, D.J. Harrison, A.R. Reynolds, T. Powles, The effect of VEGF-targeted therapy on biomarker expression in sequential tissue from patients with metastatic clear cell renal cancer. Clin Cancer Res 19, 6924–6934 (2013). doi: 10.1158/1078-0432.ccr-13-1631 CrossRefPubMedGoogle Scholar
  5. 5.
    G.D. Stewart, F.C. O’Mahony, A. Laird, L. Eory, A.L.R. Lubbock, A. Mackay, J. Nanda, M. O’Donnell, P. Mullen, S.A. McNeill, A.C. Riddick, D. Berney, A. Bex, M. Aitchison, I.M. Overton, D.J. Harrison, T. Powles, Sunitinib treatment exacerbates intratumoral heterogeneity in metastatic renal cancer. Clin Cancer Res 21, 4212–4223 (2015). doi: 10.1158/1078-0432.ccr-15-0207 CrossRefPubMedGoogle Scholar
  6. 6.
    G.D. Stewart, F.C. O’Mahony, T. Powles, A.C.P. Riddick, D.J. Harrison, D. Faratian, What can molecular pathology contribute to the management of renal cell carcinoma? Nature Rev Urol 8, 255–265 (2011). doi: 10.1038/nrurol.2011.43 CrossRefGoogle Scholar
  7. 7.
    Confederation of Cancer Biobanks: Biobank Quality Standard - Collecting, Storing and Providing Human Biological Material and Data for Research (2014) http://ccb.ncri.org.uk/wp-content/uploads/2014/03/Biobank-quality-standard-Version-1.pdf
  8. 8.
    M.B. Freidin, N. Bhudia, E. Lim, A.G. Nicholson, W.O. Cookson, M.F. Moffatt, Impact of collection and storage of lung tumor tissue on whole genome expression profiling. J Mol Diagn 14, 140–148 (2012). doi: 10.1016/j.jmoldx.2011.11.002 CrossRefPubMedPubMedCentralGoogle Scholar
  9. 9.
    Q. Liu, L. Liu, Y. Zhao, J. Zhang, D. Wang, J. Chen, Y. He, J. Wu, Z. Zhang, Z. Liu, Hypoxia induces genomic DNA demethylation through the activation of HIF-1a and transcriptional upregulation of MAT2A in hepatoma cells. Mol Cancer Ther 10, 1113–1123 (2011). doi: 10.1158/1535-7163.mct-10-1010
  10. 10.
    W.G. Kaelin Jr., The von Hippel-Lindau tumour suppressor protein: O2 sensing and cancer. Nat Rev Cancer 8, 865–873 (2008). doi: 10.1038/nrc2502 CrossRefPubMedGoogle Scholar
  11. 11.
    R. Motzer, M. Michaelson, B. Redman, G. Hudes, G. Wilding, R. Figlin, M. Ginsberg, S. Kim, C. Baum, S. DePrimo, J. Li, C. Bello, C. Theuer, D. George, B. Rini, Activity of SU11248, a multitargeted inhibitor of vascular endothelial growth factor receptor and platelet-derived growth factor receptor, in patients with metastatic renal cell carcinoma. J Clin Oncol 24, 16–24 (2006). doi: 10.1200/JCO.2005.02257 CrossRefPubMedGoogle Scholar
  12. 12.
    N.W. Liu, T. Sanford, R. Srinivasan, J.L. Liu, K. Khurana, O. Aprelikova, V. Valero, C. Bechert, R. Worrell, P.A. Pinto, Y. Yang, M. Merino, W.M. Linehan, G. Bratslavsky, Impact of ischemia and procurement conditions on gene expression in renal cell carcinoma. Clin Cancer Res 19, 42–49 (2013). doi: 10.1158/1078-0432.ccr-12-2606 CrossRefPubMedGoogle Scholar
  13. 13.
    G. Stewart, T. Powles, C. Van Neste, A. Meynert, F. O’Mahony, A. Laird, D. Deforce, F. Van Nieuwerburgh, G. Trooskens, W. Van Criekinge, T. De Meyer, D.J. Harrison, Dynamic epigenetic changes to VHL occur with sunitinib in metastatic clear cell renal cancer. Oncotarget 7, 25241–25250 (2016). doi: 10.18632/oncotarget.8308 PubMedPubMedCentralGoogle Scholar
  14. 14.
    T. De Meyer, E. Mampaey, M. Vlemmix, S. Denil, G. Trooskens, J.-P. Renard, S. De Keulenaer, P. Dehan, G. Menschaert, W. Van Criekinge, Quality evaluation of methyl binding domain based kits for enrichment DNA-methylation sequencing. PLoS One 8, 59068 (2013). doi: 10.1371/journal.pone.0059068 CrossRefGoogle Scholar
  15. 15.
  16. 16.
    S. Hicks, R. Irizarry, Quantro: a data-driven approach to guide the choice of an appropriate normalization method. Genome Biol 16, 117 (2015). doi: 10.1186/s13059-015-0679-0 CrossRefPubMedPubMedCentralGoogle Scholar
  17. 17.
    C.W. Law, Y. Chen, W. Shi, G.K. Smyth, Voom: precision weights unlock linear model analysis tools for RNA-seq read counts. Genome Biol 15, 29 (2014). doi: 10.1186/gb-2014-15-2-r2 CrossRefGoogle Scholar
  18. 18.
    M. Esteller, Epigenetic gene silencing in cancer: the DNA hypermethylome. Hum Mol Genet 16, 50–59 (2007). doi: 10.1093/hmg/ddm018 CrossRefGoogle Scholar
  19. 19.
    P.-J. Volders, K. Verheggen, G. Menschaert, K. Vandepoele, L. Martens, J. Vandesompele, P. Mestdagh, An update on LNCipedia: a database for annotated human lncRNA sequences. Nucleic Acids Res 43, 174–180 (2014). doi: 10.1093/nar/gku1060 CrossRefGoogle Scholar
  20. 20.
    M.R. D’Apice, A. Novelli, A. di Masi, M. Biancolella, A. Antoccia, F. Gullotta, N. Licata, D. Minella, B. Testa, A.M. Nardone, G. Palmieri, E. Calabrese, L. Biancone, C. Tanzarella, M. Frontali, F. Sangiuolo, G. Novelli, F. Pallone, Deletion of REXO1L1 locus in a patient with malabsorption syndrome, growth retardation, and dysmorphic features: a novel recognizable microdeletion syndrome? BMC Med Genet 16, 20 (2015). doi: 10.1186/s12881-015-0164-3 CrossRefPubMedPubMedCentralGoogle Scholar
  21. 21.
    A. Greijer, P. van der Groep, D. Kemming, A. Shvarts, G. Semenza, G. Meijer, M. van de Wiel, J. Belien, P. van Diest, E. van der Wall, Up-regulation of gene expression by hypoxia is mediated predominantly by hypoxia-inducible factor 1 (hif-1). J Pathol 206, 291–304 (2005). doi: 10.1002/path.1778 CrossRefPubMedGoogle Scholar
  22. 22.
    H. Wu, G. Chen, K.R. Wyburn, J. Yin, P. Bertolino, J.M. Eris, S.I. Alexander, A.F. Sharland, S.J. Chadban, Tlr4 activation mediates kidney ischemia/reperfusion injury. J Clin Invest 117, 2847–2859 (2007). doi: 10.1172/jci31008 CrossRefPubMedPubMedCentralGoogle Scholar
  23. 23.
    Z. Liu, W. He, J. Gao, J. Luo, X. Huang, C. Gao, Computational prediction and experimental validation of a novel synthesized pan-pim inhibitor pi003 and its apoptosis-inducing mechanisms in cervical cancer. Oncotarget 6, 8019–8035 (2015). doi: 10.18632/oncotarget.3139 CrossRefPubMedPubMedCentralGoogle Scholar
  24. 24.
    M. Safran, I. Dalah, J. Alexander, N. Rosen, T.I. Stein, M. Shmoish, N. Nativ, I. Bahir, T. Doniger, H. Krug, A. Sirota-Madi, T. Olender, Y. Golan, G. Stelzer, A. Harel, D. Lancet, GeneCards version 3: the human gene integrator. Database (Oxford) 2010, baq020 (2010). doi: 10.1093/database/baq020 CrossRefGoogle Scholar
  25. 25.
    M.K. Miller, M.-L. Bang, C.C. Witt, D. Labeit, C. Trombitas, K. Watanabe, H. Granzier, A.S. McElhinny, C.C. Gregorio, S. Labeit, The muscle ankyrin repeat proteins: carp, ankrd2/arpp and darp as a family of titin filament-based stress response molecules. J Mol Biol 333, 951–964 (2003). doi: 10.1016/j.jmb.2003.09.012 CrossRefPubMedGoogle Scholar
  26. 26.
    M. Band, A. Joel, A. Avivi, The muscle ankyrin repeat proteins are hypoxia-sensitive: in vivo mrna expression in the hypoxia-tolerant blind subterranean mole rat, spalax ehrenbergi. J Mol Evol 70, 1–12 (2009). doi: 10.1007/s00239-009-9306-6 CrossRefPubMedGoogle Scholar

Copyright information

© International Society for Cellular Oncology 2017

Authors and Affiliations

  • Christophe Van Neste
    • 1
    • 2
  • Alexander Laird
    • 3
    • 4
    • 5
  • Fiach O’Mahony
    • 3
    • 4
  • Wim Van Criekinge
    • 6
  • Dieter Deforce
    • 1
  • Filip Van Nieuwerburgh
    • 1
  • Thomas Powles
    • 7
    • 8
  • David J. Harrison
    • 3
    • 4
    • 9
    Email author
  • Grant D. Stewart
    • 3
    • 4
  • Tim De Meyer
    • 6
  1. 1.Laboratory of Pharmaceutical BiotechnologyGhent UniversityGhentBelgium
  2. 2.Center for Medical GeneticsGhent UniversityGhentBelgium
  3. 3.Edinburgh Urological Cancer Group, Institute of Genetics and Molecular MedicineUniversity of EdinburghEdinburghUK
  4. 4.Scottish Collaboration On Translational Research into Renal Cell Cancer (SCOTRRCC)EdinburghUK
  5. 5.MRC Human Genetics Unit, Institute of Genetics and Molecular MedicineUniversity of EdinburghEdinburghUK
  6. 6.Biobix: Laboratory of Bioinformatics and Computational Genomics, Department of Mathematical Modeling, Statistics and BioninformaticsGhent UniversityGhentBelgium
  7. 7.Renal Cancer UnitThe Royal Free HospitalLondonUK
  8. 8.Centre for Experimental Cancer Medicine, Bart’s Cancer InstituteQueen Mary University of LondonLondonUK
  9. 9.School of MedicineUniversity of St AndrewsEdinburghUK

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