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Aberrant methylation of tumour suppressor genes WT1, GATA5 and PAX5 in hepatocellular carcinoma

  • Martin Mžik , Marcela Chmelařová , Stanislav John , Jan Laco , Ondřej Slabý , Igor Kiss , Lucia Bohovicová , Vladimír Palička and Jana Nekvindová ORCID logo EMAIL logo
Published/Copyright: May 12, 2016
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Clinical Chemistry and Laboratory Medicine (CCLM)
From the journal Clinical Chemistry and Laboratory Medicine (CCLM) Volume 54 Issue 12

Abstract

Background:

Aberrant hypermethylation of tumour suppressor genes (TSGs) occurring in hepatocellular carcinoma (HCC) could provide a mean of molecular characterisation of this cancer. The aim of this study was to investigate promoter methylation and gene expression of selected TSGs in HCC to identify candidate genes for further validation as potential biomarkers.

Methods:

Methylation-specific multiplex ligation-dependent probe amplification method was used to measure the methylation status of 25 TSGs in 49 HCC samples and 36 corresponding non-cancerous liver tissue samples. Relative expression of the differentially methylated genes was assessed at the mRNA level using quantitative PCR.

Results:

We observed a significantly higher methylation in genes WT1, PAX5, PAX6, PYCARD and GATA5 in HCC compared with control samples. The expression of PAX5 was significantly decreased by methylation; conversely methylation of WT1 was associated with higher mRNA levels. Methylation of GATA5 was significantly associated with overall survival and methylation of WT1 and PAX5 significantly varied between patients with ALBI score 1 vs. 2+3. Moreover, PAX5 was significantly more methylated in patients with tumour grade 2+3 vs. grade 1, and methylation of the PAX5 correlated with the patient’s age at the time of diagnosis.

Conclusions:

HCC evince aberrant promoter methylation of WT1, PAX5, PAX6, PYCARD and GATA5 genes. Correlation between GATA5, WT1 and PAX5 methylation and clinical/histological parameters is suggestive of applicability of these markers in non-invasive (epi)genetic testing in HCC.

Keywords: DNA methylation; hepatocellular carcinoma (HCC); methylation-specific multiplex ligation-dependent probe amplification (MS-MLPA); promoter; tumour suppressor gene
Corresponding author: Jana Nekvindová, PhD, Institute of Clinical Biochemistry and Diagnostics, University Hospital Hradec Kralove, Sokolska 581, 500 05 Hradec Kralove, Czech Republic, Phone: (+420) 495 832 767

Acknowledgments:

The authors are grateful to Ian McColl MD, PhD for language correction of the manuscript and to Ivana Bubancova, MSc. for help with qPCR.

  1. Author contributions: All the authors have accepted responsibility for the entire content of this submitted manuscript and approved submission.

  2. Research funding: This work has been supported by MH CZ – DRO (UHHK, 00179906), by the program PRVOUK P37/11 and by program SVV 260181.

  3. Employment or leadership: None declared.

  4. Honorarium: None declared.

  5. Competing interest: The funding organisation(s) played no role in the study design; in the collection, analysis, and interpretation of data; in the writing of the report; or in the decision to submit the report for publication.

References

1. El-Serag HB. Hepatocellular carcinoma. N Engl J Med 2011;365:1118–27.10.1056/NEJMra1001683Search in Google Scholar

2. Forner A, Llovet JM, Bruix J. Hepatocellular carcinoma. Lancet 2012;379:1245–55.10.1016/S0140-6736(11)61347-0Search in Google Scholar

3. Dumitrescu RG. Epigenetic targets in cancer epidemiology. Methods Mol Biol 2009;471:457–67.10.1007/978-1-59745-416-2_23Search in Google Scholar

4. Farazi PA, DePinho RA. Hepatocellular carcinoma pathogenesis: from genes to environment. Nat Rev Cancer 2006;6:674–87.10.1038/nrc1934Search in Google Scholar

5. Raggi C, Invernizzi P. Methylation and liver cancer. Clin Res Hepatol Gastroenterol 2013;37:564–71.10.1016/j.clinre.2013.05.009Search in Google Scholar

6. Lee S, Lee HJ, Kim JH, Lee HS, Jang JJ, Kang GH. Aberrant CpG island hypermethylation along multistep hepatocarcinogenesis. Am J Pathol 2003;163:1371–8.10.1016/S0002-9440(10)63495-5Search in Google Scholar

7. Sceusi EL, Loose DS, Wray CJ. Clinical implications of DNA methylation in hepatocellular carcinoma. HPB (Oxford) 2011;13:369–76.10.1111/j.1477-2574.2011.00303.xSearch in Google Scholar PubMed PubMed Central

8. Shen J, Wang S, Zhang YJ, Kappil M, Wu HC, Kibriya MG, et al. Genome-wide DNA methylation profiles in hepatocellular carcinoma. Hepatology 2012;55:1799–808.10.1002/hep.25569Search in Google Scholar PubMed PubMed Central

9. Zhang P, Wen X, Gu F, Deng X, Li J, Dong J, et al. Methylation profiling of serum DNA from hepatocellular carcinoma patients using an Infinium Human Methylation 450 BeadChip. Hepatol Int 2013;7:893–900.10.1007/s12072-013-9437-0Search in Google Scholar PubMed

10. Villanueva A, Portela A, Sayols S, Battiston C, Hoshida Y, Méndez-González J. DNA methylation-based prognosis and epidrivers in hepatocellular carcinoma. Hepatology 2015;61:1945–56.10.1002/hep.27732Search in Google Scholar PubMed

11. van Vlodrop IJ, Niessen HE, Derks S, Baldewijns MM, van Criekinge W, Herman JG, et al. Analysis of promoter CpG island hypermethylation in cancer: location, location, location! Clin Cancer Res 2011;17:4225–31.10.1158/1078-0432.CCR-10-3394Search in Google Scholar PubMed

12. Mah WC, Thurnherr T, Chow PK, Chung AY, Ooi LL, Toh HC, et al. Methylation profiles reveal distinct subgroup of hepatocellular carcinoma patients with poor prognosis. PLoS One 2014;9:e104158.10.1371/journal.pone.0104158Search in Google Scholar PubMed PubMed Central

13. Dulaimi E, Hillinck J, Ibanez de Caceres I, Al-Saleem T, Cairns P. Tumour suppressor gene promoter hypermethylation in serum of breast cancer patients. Clin Cancer Res 2004;10:6189–93.10.1158/1078-0432.CCR-04-0597Search in Google Scholar PubMed

14. Warren JD, Xiong W, Bunker AM, Vaughn CP, Furtado LV, Roberts WL, et al. Septin 9 methylated DNA is a sensitive and specific blood test for colorectal cancer. BMC Med 2011;9:133.10.1186/1741-7015-9-133Search in Google Scholar PubMed PubMed Central

15. Kneip C, Schmidt B, Seegebarth A, Weickmann S, Fleischhacker M, Liebenberg V, et al. SHOX2 DNA methylation is a biomarker for the diagnosis of lung cancer in plasma. J Thorac Oncol 2011;6:1632–8.10.1097/JTO.0b013e318220ef9aSearch in Google Scholar PubMed

16. Song L, Yu H, Li Y. Diagnosis of lung cancer by SHOX2 gene methylation assay. Mol Diagn Ther 2015;19:159–67.10.1007/s40291-015-0144-5Search in Google Scholar PubMed

17. Dong X, He H, Zhang W, Yu D, Wang X, Chen Y. Combination of serum RASSF1A methylation and AFP is a promising non-invasive biomarker for HCC patient with chronic HBV infection. Diagn Pathol 2015;10:133.10.1186/s13000-015-0317-xSearch in Google Scholar PubMed PubMed Central

18. Huang G, Krocker JD, Kirk JL, Merwat SN, Ju H, Soloway RD, et al. Evaluation of INK4A promoter methylation using pyrosequencing and circulating cell-free DNA from patients with hepatocellular carcinoma. Clin Chem Lab Med 2014;52:899–909.10.1515/cclm-2013-0885Search in Google Scholar PubMed PubMed Central

19. Bosman FT, Carneiro F, Hruban RH, Theise ND, editors. WHO classification of tumours of the digestive system, 4th ed. Lyon: IARC, 2010.Search in Google Scholar

20. Sobin LH, Gospodarowicz MK, Wittekind C, editors. TNM Classification of Malignant Tumours, 7th ed. Oxford, UK: Wiley-Blackwell, 2009:47–50 (Czech ed. 2011).Search in Google Scholar

21. Moelans CB, Verschuur-Maes AH, van Diest PJ. Frequent promoter hypermethylation of BRCA2, CDH13, MSH6, PAX5, PAX6 and WT1 in ductal carcinoma in situ and invasive breast cancer. J Pathol 2011;225:222–31.10.1002/path.2930Search in Google Scholar PubMed

22. Ho CM, Huang CJ, Huang CY, Wu YY, Chang SF, Cheng WF. Promoter methylation status of HIN-1 associated with outcomes of ovarian clear cell adenocarcinoma. Mol Cancer 2012;11:53.10.1186/1476-4598-11-53Search in Google Scholar PubMed PubMed Central

23. Livak KJ, Schmittgen TD. Analysis of relative gene expression data using real-time quantitative PCR and the 2-[Delta][Delta]CT method. Methods 2001;25:402–8.10.1006/meth.2001.1262Search in Google Scholar PubMed

24. Huang WY, Hsu SD, Huang HY, Sun YM, Chou CH, Weng SL, et al. MethHC: a database of DNA methylation and gene expression in human cancer. Nucleic Acids Res 2015;43:D856–61.10.1093/nar/gku1151Search in Google Scholar PubMed PubMed Central

25. Johnson PJ, Berhane S, Kagebayashi C, Satomura S, Teng M, Reeves HL, et al. Assessment of liver function in patient with hepatocellular carcinoma: a new evedence-based approach-the ALBI grade. J Clin Oncol 2015;33:550–8.10.1200/JCO.2014.57.9151Search in Google Scholar PubMed PubMed Central

26. Xia L, Gong Y, Zhang A, Cai S, Zeng Q. Loss of GATA5 expression due to gene promoter methylation induces growth and colony formation of hepatocellular carcinoma cells. Oncol Lett 2016;11:861–9.10.3892/ol.2015.3974Search in Google Scholar PubMed PubMed Central

27. Liu W, Li X, Chu ES, Go MY, Xu L, Zhao G, et al. Paired box gene 5 is a novel tumour suppressor in hepatocellular carcinoma through interaction with p53 signaling pathway. Hepatology 2011;53:843–53.10.1002/hep.24124Search in Google Scholar PubMed

28. Shitani M, Sasaki S, Akutsu N, Takagi H, Suzuki H, Nojima M, et al. Genome-wide analysis of DNA methylation identifies novel cancer-related genes in hepatocellular carcinoma. Tumour Biol 2012;33:1307–17.10.1007/s13277-012-0378-3Search in Google Scholar PubMed

29. Cheung KF, Ma X, Tian L, Zhao J, Go MY, Shen B, et al. Epigenetic inactivation of paired box gene 5, a novel tumour suppressor gene, through direct upregulation of p53 is associated with prognosis in gastric cancer patients. Oncogene 2012;31:3419–30.10.1038/onc.2011.511Search in Google Scholar PubMed

30. Jung M, Pfeifer GP. Aging and DNA methylation. BMC Biol 2015;13:7.10.1186/s12915-015-0118-4Search in Google Scholar PubMed PubMed Central

31. Qi XW, Zhang F, Wu H, Liu JL, Zong BG, Xu C, et al. Wilms’ tumor 1 (WT1) expression and prognosis in solid cancer patients: a systematic review and meta-analysis. Sci Rep 2015;5:8924.10.1038/srep08924Search in Google Scholar PubMed PubMed Central

32. Berasain C, Herrero JI, García-Trevijano ER, Avila MA, Esteban JI, Mato JM, et al. Expression of Wilms’ tumour suppressor in the liver with cirrhosis: relation to hepatocyte nuclear factor 4 and hepatocellular function. Hepatology 2003;38:148–57.10.1053/jhep.2003.50269Search in Google Scholar PubMed

33. Loeb DM, Evron E, Patel CB, Sharma PM, Niranjan B, Buluwela L, et al. Wilms’ tumour suppressor gene (WT1) is expressed in primary breast tumours despite tumour-specific promoter methylation. Cancer Res 2001;61:921–5.Search in Google Scholar

34. Perugorria MJ, Castillo J, Latasa MU, Goñi S, Segura V, Sangro B, et al. Wilms’ tumour 1 gene expression in hepatocellular carcinoma promotes cell dedifferentiation and resistance to chemotherapy. Cancer Res 2009;69:1358–67.10.1158/0008-5472.CAN-08-2545Search in Google Scholar PubMed

35. Sera T, Hiasa Y, Mashiba T, Tokumoto Y, Hirooka M, Konishi I, et al. Wilms’ tumour 1 gene expression is increased in hepatocellular carcinoma and associated with poor prognosis. Eur J Cancer 2008;44:600–8.10.1016/j.ejca.2008.01.008Search in Google Scholar PubMed

36. Jin SG, Kadam S, Pfeifer GP. Examination of the specificity of DNA methylation profiling techniques towards 5-methylcytosine and 5-hydroxymethylcytosine. Nucleic Acids Res 2010;38:e125.10.1093/nar/gkq223Search in Google Scholar PubMed PubMed Central

37. Bachman M, Uribe-Lewis S, Yang X, Williams M, Murrell A, Balasubramanian S. 5-Hydroxymethylcytosine is a predominantly stable DNA modification. Nat Chem 2014;6:1049–55.10.1038/nchem.2064Search in Google Scholar PubMed PubMed Central

38. Wu H, D’Alessio AC, Ito S, Wang Z, Cui K, Zhao K, et al. Genome-wide analysis of 5-hydroxymethylcytosine distribution reveals its dual function in transcriptional regulation in mouse embryonic stem cells. Genes Dev 2011;25:679–84.10.1101/gad.2036011Search in Google Scholar PubMed PubMed Central

39. Rampal R, Alkalin A, Madzo J, Vasanthakumar A, Pronier E, Patel J, et al. DNA hydroxymethylation profiling reveals that WT1 mutations result in loss of TET2 function in acute myeloid leukemia. Cell Rep 2014;9:1841–55.10.1016/j.celrep.2014.11.004Search in Google Scholar PubMed PubMed Central

40. Wang D, Yang PN, Chen J, Zhou XY, Liu QJ, Li HJ, et al. Promoter hypermethylation may be an important mechanism of the transcriptional inactivation of ARRDC3, GATA5, and ELP3 in invasive ductal breast carcinoma. Mol Cell Biochem 2014;396:67–77.10.1007/s11010-014-2143-ySearch in Google Scholar PubMed

41. Li Y, Li Y, Liu Y, Xie P, Li F, Li G. PAX6, a novel target of microRNA-7, promotes cellular proliferation and invasion in human colorectal cancer cells. Dig Dis Sci 2014;59:598–606.10.1007/s10620-013-2929-xSearch in Google Scholar PubMed

Received: 2015-12-3
Accepted: 2016-4-11
Published Online: 2016-5-12
Published in Print: 2016-12-1

©2016 Walter de Gruyter GmbH, Berlin/Boston

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https://doi.org/10.1515/cclm-2015-1198
Keywords for this article
DNA methylation; hepatocellular carcinoma (HCC); methylation-specific multiplex ligation-dependent probe amplification (MS-MLPA); promoter; tumour suppressor gene

Articles in the same Issue

  1. Frontmatter
  2. Editorial
  3. Biomarkers, inflammation and cancer: where to go?
  4. Review
  5. Analysis, detection and quantitation of mixed cryoglobulins in HCV infection: brief review and case examples
  6. Mini Reviews
  7. Calcitonin measurement and immunoassay interference: a case report and literature review
  8. Exosomal non-coding RNAs: a promising cancer biomarker
  9. Opinion Paper
  10. Towards a new paradigm in laboratory medicine: the five rights
  11. EFLM Recommendation
  12. Recommendation for the review of biological reference intervals in medical laboratories
  13. IFCC Position Paper
  14. Assuring the quality of interpretative comments in clinical chemistry
  15. General Clinical Chemistry and Laboratory Medicine
  16. The effect of centrifugation speed and time on pre-analytical platelet activation
  17. An assessment of clinical laboratory performance for the determination of manganese in blood and urine
  18. Evaluation of antiphospholipid antibody assays using latent class analysis to address the lack of a reference standard
  19. Evaluation of the hypochromic erythrocyte and reticulocyte hemoglobin content provided by the Sysmex XE-5000 analyzer in diagnosis of iron deficiency erythropoiesis
  20. Cancer Diagnosis
  21. Identifying risk in the use of tumor markers to improve patient safety
  22. Association between Echinococcus granulosus infection and cancer risk – a pilot study in Cyprus
  23. Dynamic change of the systemic immune inflammation index predicts the prognosis of patients with hepatocellular carcinoma after curative resection
  24. Aberrant methylation of tumour suppressor genes WT1, GATA5 and PAX5 in hepatocellular carcinoma
  25. Cardiovascular Diseases
  26. High homocysteine and low folate plasma concentrations are associated with cardiovascular events but not bleeding during warfarin treatment
  27. Hemolysis and Coagulation
  28. Hemolysis rates in blood samples: differences between blood collected by clinicians and nurses and the effect of phlebotomy training
  29. Letters to the Editor
  30. Harmonisation of the laboratory testing process: need for a coordinated approach
  31. Pseudohyperkalemia due to severe leukocytosis: case presentation
  32. When obtaining a blood sample from the right arm was not the right thing to do: a case of elevated parathyroid hormone levels 27 years after thyroidectomy
  33. Raising awareness of assay compatibility with heparinized plasma
  34. Improved protocol for extraction of genomic DNA from formalin-fixed paraffin-embedded tissue samples without the use of xylene
  35. Effect of refrigeration, centrifugation, acidification, heat treatment and storage on urine calcium, magnesium and phosphate
  36. Letter in response to: Identifying risk in the use of tumor markers to improve patient safety
  37. Letter to the Editor in reply to Dayyani and Morgenstern’s comment on the article “Identifying risk in the use of tumor markers to improve patient safety”
  38. Level of red cell distribution width is affected by various factors
  39. Red blood cell distribution: an index without additional cost in estimating the prognosis of acute pancreatitis
  40. Testing of total 25(OH)vitamin D: agreement and discrepant cases between Cobas® 8000 and Liaison® XL methods
  41. Expression profiling and ontology analysis of circulating long non-coding RNAs in septic acute kidney injury patients
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