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Published in: Digestive Diseases and Sciences 8/2019

01-08-2019 | Colorectal Cancer | Original Article

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

Authors: Haoran Bi, Yupeng Liu, Rui Pu, Tingting Xia, Hongru Sun, Hao Huang, Lei Zhang, Yuanyuan Zhang, Ying Liu, Jing Xu, Jiesheng Rong, Yashuang Zhao

Published in: Digestive Diseases and Sciences | Issue 8/2019

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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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Literature
2.
go back to reference 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.CrossRefPubMed 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.CrossRefPubMed
7.
go back to reference Bardhan K, Liu K. Epigenetics and colorectal cancer pathogenesis. Cancers (Basel). 2013;5:676–713.CrossRef Bardhan K, Liu K. Epigenetics and colorectal cancer pathogenesis. Cancers (Basel). 2013;5:676–713.CrossRef
8.
go back to reference 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.CrossRefPubMedPubMedCentral 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.CrossRefPubMedPubMedCentral
9.
go back to reference Marsit C, Christensen B. Blood-derived DNA methylation markers of cancer risk. Adv Exp Med Biol. 2013;754:233–252.CrossRefPubMed Marsit C, Christensen B. Blood-derived DNA methylation markers of cancer risk. Adv Exp Med Biol. 2013;754:233–252.CrossRefPubMed
10.
go back to reference 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.CrossRefPubMedPubMedCentral 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.CrossRefPubMedPubMedCentral
12.
go back to reference 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.CrossRefPubMedPubMedCentral 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.CrossRefPubMedPubMedCentral
13.
go back to reference 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.CrossRef 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.CrossRef
14.
go back to reference 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.CrossRefPubMedPubMedCentral 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.CrossRefPubMedPubMedCentral
15.
go back to reference 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.CrossRefPubMedPubMedCentral 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.CrossRefPubMedPubMedCentral
17.
go back to reference 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.CrossRefPubMed 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.CrossRefPubMed
19.
go back to reference 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.CrossRefPubMed 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.CrossRefPubMed
20.
go back to reference 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.CrossRefPubMed 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.CrossRefPubMed
21.
go back to reference Shu XO, Yang G, Jin 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.CrossRefPubMed Shu XO, Yang G, Jin 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.CrossRefPubMed
22.
go back to reference 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.CrossRefPubMedPubMedCentral 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.CrossRefPubMedPubMedCentral
23.
go back to reference 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.CrossRefPubMed 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.CrossRefPubMed
24.
go back to reference Greenland S. Quantitative methods in the review of epidemiologic literature. Epidemiol Rev. 1987;9:1–30.CrossRefPubMed Greenland S. Quantitative methods in the review of epidemiologic literature. Epidemiol Rev. 1987;9:1–30.CrossRefPubMed
25.
go back to reference VanderWeele TJ, Ding P. Sensitivity analysis in observational research: introducing the E-value. Ann Intern Med. 2017;167:268–274.CrossRefPubMed VanderWeele TJ, Ding P. Sensitivity analysis in observational research: introducing the E-value. Ann Intern Med. 2017;167:268–274.CrossRefPubMed
26.
go back to reference Bingham S, Riboli E. Diet and cancer—the European prospective investigation into cancer and nutrition. Nat Rev Cancer. 2004;4:206.CrossRefPubMed Bingham S, Riboli E. Diet and cancer—the European prospective investigation into cancer and nutrition. Nat Rev Cancer. 2004;4:206.CrossRefPubMed
27.
go back to reference 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.CrossRefPubMed 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.CrossRefPubMed
28.
go back to reference 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.CrossRefPubMed 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.CrossRefPubMed
29.
go back to reference 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.CrossRefPubMed 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.CrossRefPubMed
30.
go back to reference Rosenbaum PR, Rubin DB. The central role of the propensity score in observational studies for causal effects. Biometrika. 1983;70:41–55.CrossRef Rosenbaum PR, Rubin DB. The central role of the propensity score in observational studies for causal effects. Biometrika. 1983;70:41–55.CrossRef
31.
go back to reference Lyon MF. Gene action in the X-chromosome of the mouse (Mus musculus L.). Nature.. 1961;190:372–373.CrossRefPubMed Lyon MF. Gene action in the X-chromosome of the mouse (Mus musculus L.). Nature.. 1961;190:372–373.CrossRefPubMed
32.
go back to reference 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.CrossRefPubMed 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.CrossRefPubMed
34.
go back to reference 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.CrossRefPubMed 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.CrossRefPubMed
35.
go back to reference 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.CrossRefPubMed 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.CrossRefPubMed
36.
Metadata
Title
CHST7 Gene Methylation and Sex-Specific Effects on Colorectal Cancer Risk
Authors
Haoran Bi
Yupeng Liu
Rui Pu
Tingting Xia
Hongru Sun
Hao Huang
Lei Zhang
Yuanyuan Zhang
Ying Liu
Jing Xu
Jiesheng Rong
Yashuang Zhao
Publication date
01-08-2019
Publisher
Springer US
Published in
Digestive Diseases and Sciences / Issue 8/2019
Print ISSN: 0163-2116
Electronic ISSN: 1573-2568
DOI
https://doi.org/10.1007/s10620-019-05530-9

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