Skip to main content
SpringerLink
Log in

A six-CpG panel with DNA methylation biomarkers predicting treatment response of chemoradiation in esophageal squamous cell carcinoma

  • Original Article—Alimentary Tract
  • Published:
Journal of Gastroenterology Aims and scope Submit manuscript

Abstract

Background

Prognosis of esophageal squamous cell carcinoma (ESCC) patients remains poor, and the chemoradiotherapy (CRT) applied to ESCC patients often failed. Therefore, development of biomarkers to predict CRT response is immensely important for choosing the best treatment strategy of an individual patient.

Methods

The methylation array and pyrosequencing methylation assay were performed in pre-treatment endoscopic biopsies to identify probes with differential CpG methylation levels between good and poor CRT responders in a cohort of 12 ESCC patients. Receiver operating characteristic curves and multivariate logistic regressions were conducted to build the risk score equation of selected CpG probes in another cohort of 91 ESCC patients to predict CRT response. Kaplan–Meier analysis was used to estimate progression-free survival or time-to-progression of patients predicted with good and poor CRT responses.

Results

Nine differentially methylated CpG probes were identified to be associated with CRT response. A risk score equation comprising six CpG probes located in IFNGR2, KCNK4, NOTCH4, NPY, PAX6, and SOX17 genes were built. The risk score was derived from the sum of each probe multiplied by its corresponding coefficient. Such a risk score has a good prediction performance in discriminating poor CRT responders from good responders (AUC: 0.930). Moreover, poor CRT responders predicted by risk score significantly had poorer prognosis in terms of shorter progression-free survival and time-to-progression (p = 0.004–0.008).

Conclusion

We established a proof-of-concept CRT response prediction panel consisting of six-CpG methylation biomarkers in identifying ESCC patients who are at high risk of CRT failure and need intensive care.

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

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5

Similar content being viewed by others

Abbreviations

AUC:

Area under the curve

CI:

Confidence interval

CRT:

Chemoradiotherapy

ESCC:

Esophageal squamous cell carcinoma

EUS:

Endoscopic ultrasonography

ROC:

Receiver operating characteristic

HR:

Hazard ratio

References

  1. Siegel RL, Miller KD, Jemal A. Cancer Statistics, 2015. CA Cancer J Clin. 2015;65:5–29.

    Article  PubMed  Google Scholar 

  2. Khuroo MS, Zargar SA, Mahajan R, et al. High incidence of oesophageal and gastric cancer in Kashmir in a population with special personal and dietary habits. Gut. 1992;33:11–5.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  3. Enzinger PC, Mayer RJ. Esophageal cancer. N Engl J Med. 2003;349:2241–52.

    Article  CAS  PubMed  Google Scholar 

  4. Sakaeda T, Yamamori M, Kuwahara A, et al. Pharmacokinetics and pharmacogenomics in esophageal cancer chemoradiotherapy. Adv Drug Deliv Rev. 2009;61:388–401.

    Article  CAS  PubMed  Google Scholar 

  5. Chang WL, Lin FC, Yen CJ, et al. Tumor length assessed by miniprobe endosonography can predict the survival of the advanced esophageal squamous cell carcinoma with stricture receiving concurrent chemoradiation. Dis Esophagus. 2011;24:590–5.

    Article  PubMed  Google Scholar 

  6. van Hagen P, Hulshof MC, van Lanschot JJ, et al. Preoperative chemoradiotherapy for esophageal or junctional cancer. N Engl J Med. 2012;366:2074–84.

    Article  PubMed  Google Scholar 

  7. Stahl M, Stuschke M, Lehmann N, et al. Chemoradiation with and without surgery in patients with locally advanced squamous cell carcinoma of the esophagus. J Clin Oncol. 2005;23:2310–7.

    Article  PubMed  Google Scholar 

  8. Bedenne L, Michel P, Bouché O, et al. Chemoradiation followed by surgery compared with chemoradiation alone in squamous cancer of the esophagus: FFCD 9102. J Clin Oncol. 2007;25:1160–8.

    Article  CAS  PubMed  Google Scholar 

  9. Di Fiore F, Lecleire S, Rigal O, et al. Predictive factors of survival in patients treated with definitive chemoradiotherapy for squamous cell esophageal carcinoma. World J Gastroenterol. 2006;12:4185–90.

    Article  PubMed  PubMed Central  Google Scholar 

  10. Baylin SB, Esteller M, Rountree MR, et al. Aberrant patterns of DNA methylation, chromatin formation and gene expression in cancer. Hum Mol Genet. 2001;10:687–92.

    Article  CAS  PubMed  Google Scholar 

  11. Herman JG, Baylin SB. Gene silencing in cancer in association with promoter hypermethylation. N Engl J Med. 2003;349:2042–54.

    Article  CAS  PubMed  Google Scholar 

  12. Costello JF, Fruhwald MC, Smiraglia DJ, et al. Aberrant CpG-island methylation has non-random and tumour-type-specific patterns. Nat Genet. 2000;24:132–8.

    Article  CAS  PubMed  Google Scholar 

  13. Belinsky SA. Gene-promoter hypermethylation as a biomarker in lung cancer. Nat Rev Cancer. 2004;4:707–17.

    Article  CAS  PubMed  Google Scholar 

  14. Wilting RH, Dannenberg JH. Epigenetic mechanisms in tumorigenesis, tumor cell heterogeneity and drug resistance. Drug Resist Updat. 2012;15:21–38.

    Article  CAS  PubMed  Google Scholar 

  15. Su LJ, Mahabir S, Ellison GL, et al. Epigenetic contributions to the relationship between cancer and dietary intake of nutrients, bioactive food components, and environmental toxicants. Front Genet. 2012;2:91.

    Article  PubMed  PubMed Central  Google Scholar 

  16. Ivanova T, Zouridis H, Wu Y, et al. Integrated epigenomics identifies BMP4 as a modulator of cisplatin sensitivity in gastric cancer. Gut. 2013;62:22–33.

    Article  CAS  PubMed  Google Scholar 

  17. Chang WL, Wang WL, Chung TJ, et al. Response evaluation with endoscopic ultrasound and computed tomography in esophageal squamous cell carcinoma treated by definitive chemoradiotherapy. J Gastroenterol Hepatol. 2015;30:463–9.

    Article  PubMed  Google Scholar 

  18. Bibikova M, Lin Z, Zhou L, et al. High-throughput DNA methylation profiling using universal bead arrays. Genome Res. 2006;16:383–93.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  19. Vaissière T, Hung RJ, Zaridze D, et al. Quantitative analysis of DNA methylation profiles in lung cancer identifies aberrant DNA methylation of specific genes and its association with gender and cancer risk factors. Cancer Res. 2009;69:243–52.

    Article  PubMed  PubMed Central  Google Scholar 

  20. Vasiljević N, Wu K, Brentnall AR, et al. Absolute quantitation of DNA methylation of 28 candidate genes in prostate cancer using pyrosequencing. Dis Markers. 2011;30:151–61.

    Article  PubMed  Google Scholar 

  21. García-Tuñón I, Ricote M, Ruiz AA, et al. Influence of IFN-gamma and its receptors in human breast cancer. BMC Cancer. 2007;7:158.

    Article  PubMed  PubMed Central  Google Scholar 

  22. Wang F, Yang Y, Fu Z, et al. Differential DNA methylation status between breast carcinomatous and normal tissues. Biomed Pharmacother. 2014;68:699–707.

    Article  CAS  PubMed  Google Scholar 

  23. Lesage F, Barhanin J. Molecular physiology of pH-sensitive background K(2P) channels. Physiology (Bethesda). 2011;26:424–37.

    Article  CAS  PubMed  Google Scholar 

  24. Lolicato M, Riegelhaupt PM, Arrigoni C, et al. Transmembrane helix straightening and buckling underlies activation of mechanosensitive and thermosensitive K(2P) channels. Neuron. 2014;84:1198–212.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  25. Qian C, Liu F, Ye B, et al. Notch4 promotes gastric cancer growth through activation of Wnt1/β-catenin signaling. Mol Cell Biochem. 2015;401:165–74.

    Article  CAS  PubMed  Google Scholar 

  26. Archer KJ, Mas VR, Maluf DG, et al. High-throughput assessment of CpG site methylation for distinguishing between HCV-cirrhosis and HCV-associated hepatocellular carcinoma. Mol Genet Genom. 2010;283:341–9.

    Article  CAS  Google Scholar 

  27. Rodríguez-Rodero S, Fernández AF, Fernández-Morera JL, et al. DNA methylation signatures identify biologically distinct thyroid cancer subtypes. J Clin Endocrinol Metab. 2013;98:2811–21.

    Article  PubMed  Google Scholar 

  28. Abe M, Watanabe N, McDonell N, et al. Identification of genes targeted by CpG island methylator phenotype in neuroblastomas, and their possible integrative involvement in poor prognosis. Oncology. 2008;74:50–60.

    Article  CAS  PubMed  Google Scholar 

  29. Roperch JP, Incitti R, Forbin S, et al. Aberrant methylation of NPY, PENK, and WIF1 as a promising marker for blood-based diagnosis of colorectal cancer. BMC Cancer. 2013;13:566.

    Article  PubMed  PubMed Central  Google Scholar 

  30. Walcher T, Xie Q, Sun J, et al. Functional dissection of the paired domain of Pax6 reveals molecular mechanisms of coordinating neurogenesis and proliferation. Development. 2013;140:1123–36.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  31. Shyr CR, Tsai MY, Yeh S, et al. Tumor suppressor PAX6 functions as androgen receptor co-repressor to inhibit prostate cancer growth. Prostate. 2010;70:190–9.

    PubMed  PubMed Central  Google Scholar 

  32. Zhou YH, Wu X, Tan F, et al. PAX6 suppresses growth of human glioblastoma cells. J Neurooncol. 2005;71:223–9.

    Article  CAS  PubMed  Google Scholar 

  33. Kornegoor R, Moelans CB, Verschuur-Maes AH, et al. Promoter hypermethylation in male breast cancer: analysis by multiplex ligation-dependent probe amplification. Breast Cancer Res. 2012;14:R101.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  34. Rauch TA, Wang Z, Wu X, et al. DNA methylation biomarkers for lung cancer. Tumour Biol. 2012;33:287–96.

    Article  CAS  PubMed  Google Scholar 

  35. Estey MP, Kim MS, Trimble WS. Septins. Curr Biol. 2011;21:R384–7.

    Article  CAS  PubMed  Google Scholar 

  36. Katoh M. Molecular cloning and characterization of human SOX17. Int J Mol Med. 2002;9:153–7.

    CAS  PubMed  Google Scholar 

  37. Fu DY, Wang ZM, Li-Chen, et al. Sox17, the canonical Wnt antagonist, is epigenetically inactivated by promoter methylation in human breast cancer. Breast Cancer Res Treat. 2010;119:601–12.

  38. Zhang W, Glöckner SC, Guo M, et al. Epigenetic inactivation of the canonical Wnt antagonist SRY-box containing gene 17 in colorectal cancer. Cancer Res. 2008;68:2764–72.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  39. Jia Y, Yang Y, Liu S, et al. SOX17 antagonizes WNT/beta-catenin signaling pathway in hepatocellular carcinoma. Epigenetics. 2010;5:743–9.

    Article  CAS  PubMed  Google Scholar 

  40. Kuo IY, Wu CC, Chang JM, et al. Low SOX17 expression is a prognostic factor and drives transcriptional dysregulation and esophageal cancer progression. Int J Cancer. 2014;135:563–73.

    Article  CAS  PubMed  Google Scholar 

  41. Liu MZ, McLeod HL, He FZ, et al. Epigenetic perspectives on cancer chemotherapy response. Pharmacogenomics. 2014;15:699–715.

    Article  PubMed  Google Scholar 

  42. Kneip C, Schmidt B, Seegebarth A, et al. SHOX2 DNA methylation is a biomarker for the diagnosis of lung cancer in plasma. J Thorac Oncol. 2011;6:1632–8.

    Article  PubMed  Google Scholar 

  43. Lange CP, Campan M, Hinoue T, et al. Genome-scale discovery of DNA-methylation biomarkers for blood-based detection of colorectal cancer. PLoS One. 2012;7(11):e50266.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgments

The authors thank Mr. Chien-Hsun Lin for technical support. This work was supported in part by the Ministry of Health and Welfare (DOH101-TD-PB-111-TM004 to BSS, DOH101-TD-PB-111-TM003 to PJL, DOH101-TD-PB-111-TM001 to YCW), and the Ministry of Science and Technology (MOST104-2314-B-006-082 to WLC, MOST104-2314-B-006-077-MY2 to WWL).

Author information

Author notes

    Authors and Affiliations

    1. Department of Internal Medicine, National Cheng Kung University Hospital, College of Medicine, National Cheng Kung University, Tainan, 701, Taiwan

      Wei-Lun Chang & Bor-Shyang Sheu

    2. Department of Surgery, National Cheng Kung University Hospital, College of Medicine, National Cheng Kung University, Tainan, 701, Taiwan

      Wu-Wei Lai

    3. Department of Basic Medical Sciences, College of Medicine, National Cheng Kung University, Tainan, 701, Taiwan

      I-Ying Kuo & Yi-Ching Wang

    4. Department of Pharmacology, College of Medicine, National Cheng Kung University, Tainan, 701, Taiwan

      Chien-Yu Lin & Yi-Ching Wang

    5. Institute of Clinical Medicine, College of Medicine, National Cheng Kung University, Tainan, 701, Taiwan

      Pei-Jung Lu

    6. Department of Internal Medicine, Tainan Hospital, Ministry of Health and Welfare, Tainan, 700, Taiwan

      Bor-Shyang Sheu

    Authors
    1. Wei-Lun Chang
      View author publications

      You can also search for this author in PubMed Google Scholar

    2. Wu-Wei Lai
      View author publications

      You can also search for this author in PubMed Google Scholar

    3. I-Ying Kuo
      View author publications

      You can also search for this author in PubMed Google Scholar

    4. Chien-Yu Lin
      View author publications

      You can also search for this author in PubMed Google Scholar

    5. Pei-Jung Lu
      View author publications

      You can also search for this author in PubMed Google Scholar

    6. Bor-Shyang Sheu
      View author publications

      You can also search for this author in PubMed Google Scholar

    7. Yi-Ching Wang
      View author publications

      You can also search for this author in PubMed Google Scholar

    Corresponding authors

    Correspondence to Bor-Shyang Sheu or Yi-Ching Wang.

    Ethics declarations

    Yes.

    Conflict of interest

    The authors declare no conflicts of interest.

    Additional information

    W.-L. Chang and W.-W. Lai contributed equally to this work.

    Electronic supplementary material

    Below is the link to the electronic supplementary material.

    Supplementary material 1 (PDF 570 kb)

    Rights and permissions

    Reprints and permissions

    About this article

    Check for updates. Verify currency and authenticity via CrossMark

    Cite this article

    Chang, WL., Lai, WW., Kuo, IY. et al. A six-CpG panel with DNA methylation biomarkers predicting treatment response of chemoradiation in esophageal squamous cell carcinoma. J Gastroenterol 52, 705–714 (2017). https://doi.org/10.1007/s00535-016-1265-2

    Download citation

    • Received:

    • Accepted:

    • Published:

    • Issue Date:

    • DOI: https://doi.org/10.1007/s00535-016-1265-2

    Keywords

    Search

    Navigation