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CHST7 Gene Methylation and Sex-Specific Effects on Colorectal Cancer Risk

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Abstract

Background

X chromosome aberrations are involved in carcinogenesis and are associated with gender differences in cancer development. Abnormal DNA methylation also contributes to cancer. Carbohydrate Sulfotransferase 7 (CHST7), encoded by the X chromosome, is abnormally expressed during tumor development. However, its impact on colorectal cancer (CRC) and the effect of CHST7 methylation on sex-specific CRC risk remain unclear.

Aims

To investigate the effect of CHST7 methylation in white blood cells on CRC risk and to evaluate its impact on gender-specific differences.

Methods

CHST7 methylation in white blood cells was determined using methylation-sensitive high-resolution melting. A propensity score analysis was performed to control potential confounders. Furthermore, extensive sensitivity analyses were applied to assess the robustness of our findings. In addition, we validated the initial findings with a GEO dataset (GSE51032).

Results

CHST7 hypermethylation in white blood cells was associated with an increased CRC risk [odds ratio (OR)adj = 4.447, 95% confidence interval (CI) 2.662–7.430; p < 0.001]. The association was validated with the GEO dataset (ORadj = 2.802, 95% CI 1.235–6.360; p = 0.014). In particular, CHST7 hypermethylation significantly increased the CRC risk in females (ORadj = 7.704, 95% CI 4.222–14.058; p < 0.001) and younger patients (≤ 60 years) (ORadj = 5.755, 95% CI 2.540–13.038; p < 0.001). Subgroup analyses by tumor location and Duke’s stage also observed these associations.

Conclusion

CHST7 methylation in white blood cells is positively associated with CRC risk, especially in females, and may potentially serve as a blood-based predictive biomarker for CRC risk.

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References

  1. Siegel RL, Miller KD, Jemal A. Cancer statistics, 2018. CA Cancer J Clin. 2018;68:7–30.

    Article  PubMed  Google Scholar 

  2. Zheng ZX, Zheng RS, Zhang SW, Chen WQ. Colorectal cancer incidence and mortality in China, 2010. Asian Pac J Cancer Prev. 2014;15:8455–8460.

    Article  PubMed  Google Scholar 

  3. Worthley DL, Whitehall VL, Spring KJ, Leggett BA. Colorectal carcinogenesis: road maps to cancer. World J Gastroenterol. 2007;13:3784–3791.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  4. Jones PA, Baylin SB. The epigenomics of cancer. Cell. 2007;128:683–692.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  5. Robertson KD. DNA methylation and human disease. Nat Rev Genet. 2005;6:597–610.

    Article  CAS  PubMed  Google Scholar 

  6. Ashktorab H, Brim H. DNA Methylation and Colorectal Cancer. Curr Colorectal Cancer Rep. 2014;10:425–430.

    Article  PubMed  PubMed Central  Google Scholar 

  7. Bardhan K, Liu K. Epigenetics and colorectal cancer pathogenesis. Cancers (Basel). 2013;5:676–713.

    Article  CAS  Google Scholar 

  8. Terry MB, Delgado-Cruzata L, Vin-Raviv N, Wu HC, Santella RM. DNA methylation in white blood cells: association with risk factors in epidemiologic studies. Epigenetics. 2011;6:828–837.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  9. Marsit C, Christensen B. Blood-derived DNA methylation markers of cancer risk. Adv Exp Med Biol. 2013;754:233–252.

    Article  CAS  PubMed  Google Scholar 

  10. Li L, Choi JY, Lee KM, et al. DNA methylation in peripheral blood: a potential biomarker for cancer molecular epidemiology. J Epidemiol. 2012;22:384–394.

    Article  PubMed  PubMed Central  Google Scholar 

  11. Shivapurkar N, Gazdar AF. DNA methylation based biomarkers in non-invasive cancer screening. Curr Mol Med. 2010;10:123–132.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  12. Walters RJ, Williamson EJ, English DR, et al. Association between hypermethylation of DNA repetitive elements in white blood cell DNA and early-onset colorectal cancer. Epigenetics. 2013;8:748–755.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  13. Ally M, Al-Ghnaniem R, Pufulete M. The relationship between gene-specific DNA methylation in leukocytes and normal colorectal mucosa in subjects with and without colorectal tumors. Cancer Epidemiol Biomark Prev. 2009;18:922–928.

    Article  CAS  Google Scholar 

  14. De Angelis P, Clausen O, Schjølberg A, Stokke T. Chromosomal gains and losses in primary colorectal carcinomas detected by CGH and their associations with tumour DNA ploidy, genotypes and phenotypes. Br J Cancer. 1999;80:526–535.

    Article  PubMed  PubMed Central  Google Scholar 

  15. Ali R, Marafie M, Bitar M, et al. Gender-associated genomic differences in colorectal cancer: clinical insight from feminization of male cancer cells. Int J Mol Sci. 2014;15:17344–17365.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  16. Ross MT, Grafham DV, Coffey AJ, et al. The DNA sequence of the human X chromosome. Nature. 2005;434:325–337.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  17. Uchimura K, Fasakhany F, Kadomatsu K, et al. Diversity of N-acetylglucosamine-6-O-sulfotransferases: molecular cloning of a novel enzyme with different distribution and specificities. Biochem Biophys Res Commun. 2000;274:291–296.

    Article  CAS  PubMed  Google Scholar 

  18. Stowell SR, Ju T, Cummings RD. Protein glycosylation in cancer. Annu Rev Pathol. 2015;10:473–510.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  19. Debeljak Z, Dundovic S, Badovinac S, et al. Serum carbohydrate sulfotransferase 7 in lung cancer and non-malignant pulmonary inflammations. Clin Chem Lab Med. 2018;56:1328–1335.

    Article  CAS  PubMed  Google Scholar 

  20. Cordero F, Ferrero G, Polidoro S, et al. Differentially methylated microRNAs in prediagnostic samples of subjects who developed breast cancer in the European Prospective Investigation into Nutrition and Cancer (EPIC-Italy) cohort. Carcinogenesis. 2015;36:1144–1153.

    Article  CAS  PubMed  Google Scholar 

  21. Shu XO, Yang G, ** F, et al. Validity and reproducibility of the food frequency questionnaire used in the Shanghai Women’s Health Study. Eur J Clin Nutr. 2004;58:17–23.

    Article  CAS  PubMed  Google Scholar 

  22. Austin PC. Balance diagnostics for comparing the distribution of baseline covariates between treatment groups in propensity-score matched samples. Stat Med. 2009;28:3083–3107.

    Article  PubMed  PubMed Central  Google Scholar 

  23. Elze MC, Gregson J, Baber U, et al. Comparison of propensity score methods and covariate adjustment: evaluation in 4 cardiovascular studies. J Am Coll Cardiol. 2017;69:345–357.

    Article  PubMed  Google Scholar 

  24. Greenland S. Quantitative methods in the review of epidemiologic literature. Epidemiol Rev. 1987;9:1–30.

    Article  CAS  PubMed  Google Scholar 

  25. VanderWeele TJ, Ding P. Sensitivity analysis in observational research: introducing the E-value. Ann Intern Med. 2017;167:268–274.

    Article  PubMed  Google Scholar 

  26. Bingham S, Riboli E. Diet and cancer—the European prospective investigation into cancer and nutrition. Nat Rev Cancer. 2004;4:206.

    Article  CAS  PubMed  Google Scholar 

  27. Riboli E, Hunt KJ, Slimani N, et al. European prospective investigation into cancer and nutrition (EPIC): study populations and data collection. Public Health Nutr. 2002;5:1113–1124.

    Article  CAS  PubMed  Google Scholar 

  28. Sanchez-Palencia A, Gomez-Morales M, Gomez-Capilla JA, et al. Gene expression profiling reveals novel biomarkers in nonsmall cell lung cancer. Int J Cancer. 2011;129:355–364.

    Article  CAS  PubMed  Google Scholar 

  29. Oliveira-Ferrer L, Hessling A, Trillsch F, Mahner S, Milde-Langosch K. Prognostic impact of chondroitin-4-sulfotransferase CHST11 in ovarian cancer. Tumour Biol. 2015;36:9023–9030.

    Article  CAS  PubMed  Google Scholar 

  30. Rosenbaum PR, Rubin DB. The central role of the propensity score in observational studies for causal effects. Biometrika. 1983;70:41–55.

    Article  Google Scholar 

  31. Lyon MF. Gene action in the X-chromosome of the mouse (Mus musculus L.). Nature.. 1961;190:372–373.

    Article  CAS  PubMed  Google Scholar 

  32. Dunford A, Weinstock DM, Savova V, et al. Tumor-suppressor genes that escape from X-inactivation contribute to cancer sex bias. Nat Genet. 2017;49:10–16.

    Article  CAS  PubMed  Google Scholar 

  33. Jones MJ, Goodman SJ, Kobor MS. DNA methylation and healthy human aging. Aging Cell. 2015;14:924–932.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  34. Lonning PE, Berge EO, Bjornslett M, et al. White blood cell BRCA1 promoter methylation status and ovarian cancer risk. Ann Intern Med. 2018;168:326–334.

    Article  PubMed  Google Scholar 

  35. Heiss JA, Brenner H. Impact of confounding by leukocyte composition on associations of leukocyte DNA methylation with common risk factors. Epigenomics. 2017;9:659–668.

    Article  CAS  PubMed  Google Scholar 

  36. Teschendorff AE, Menon U, Gentry-Maharaj A, et al. An epigenetic signature in peripheral blood predicts active ovarian cancer. PLoS ONE. 2009;4:e8274.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgments

This work was supported by the National Natural Science Foundation of China grants, Grant numbers 81473055 and 30972539.

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Correspondence to Yashuang Zhao.

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All procedures performed in studies involving human participants were in accordance with the ethical standards of the Institutional Research Board of Harbin Medical University and with the 1964 Declaration of Helsinki and its later amendments or comparable ethical standards.

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Bi, H., Liu, Y., Pu, R. et al. CHST7 Gene Methylation and Sex-Specific Effects on Colorectal Cancer Risk. Dig Dis Sci 64, 2158–2166 (2019). https://doi.org/10.1007/s10620-019-05530-9

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  • DOI: https://doi.org/10.1007/s10620-019-05530-9

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