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Interactions Between Obesity and One-Carbon Metabolism Genes in Predicting Prostate Cancer Outcomes Among White and Black Patients

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Abstract

Background

One-carbon metabolism genes are linked to several cancers, but the association with prostate cancer (PCa) is less clear. Studies examining the relationship have not accounted for obesity, a risk factor for advanced PCa and altered methylation patterns. We hypothesized that obesity could moderate the association between one-carbon metabolism genes and PCa outcomes.

Methods

We conducted secondary data analyses of the Study of Clinical Outcomes, Risk and Ethnicity. Obesity was included as a primary exposure and modifier (interacting with genetic polymorphisms) in the analytic models. We used logistic regression to determine associations of common one-carbon metabolism genotypes with odds of high stage (T3/T4) and high grade (Gleason score ≥ 7). We used Cox regression to examine associations of genotypes with biochemical recurrence.

Results

There were 808 patients (632 White and 176 Black.) Among White men, we observed associations of TCN2_R259P with increased odds of high stage (OR = 0.64, 95% CI = 0.41–1.00), but no significant interactions with obesity. Among Black men, the SCL19A1_61bpdel and CBS_68bpINS variants were associated with high grade (OR = 2.61, 95% CI = 1.39–4.89 and OR = 0.29, 95% CI = 0.09–0.91, respectively.) Both the CBS_68bpINS and MTHFR_E429A variants interacted with obesity in Black men, where the highest risk for biochemical failure and odds of high grade, respectively, occurred among obese patients with variants.

Conclusions

We observed associations of one-carbon metabolism genes with different associations by race. We also observed interactions with obesity related to PCa outcomes in Black men only. Therefore, the involvement of one-carbon metabolism on PCa was dependent upon obesity status for Black men. These novel results could help identify patients that might benefit from effective weight management targeting one-carbon metabolism effects.

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Data Availability

Data can be obtained by contacting the corresponding author or director of the SCORE Study, Dr. Timothy Rebbeck (Harvard University).

References

  1. ACS: Cancer facts and figures 2019. In. Atlanta: American Cancer Society; 2019. https://www.cancer.org/research/cancer-facts-statistics/all-cancer-facts-figures/cancer-factsfigures-2019.html. Accessed 2020

  2. Cancer Stat facts: lung and bronchus cancer https://seer.cancer.gov/statfacts/html/lungb.html. Accessed 2020

  3. Wu Y, Sarkissyan M, Vadgama JV. Epigenetics in breast and prostate cancer. Methods Mol Biol. 2015;1238:425–66.

    Article  Google Scholar 

  4. Singh S, Plaga A, Shukla GC. Racial disparities: disruptive genes in prostate carcinogenesis. Front Biosci. 2017;9:244–53.

    Article  Google Scholar 

  5. Freedland SJ, Isaacs WB. Explaining racial differences in prostate cancer in the United States: sociology or biology? Prostate. 2005;62(3):243–52.

    Article  Google Scholar 

  6. Zhang S, Lin J, Jiang J, Chen Y, Tang W, Liu L. Association between methylenetetrahydrofolate reductase tagging polymorphisms and susceptibility of hepatocellular carcinoma: a case-control study. Biosci Rep. 2019. https://doi.org/10.1042/BSR20192517.

    Article  PubMed  PubMed Central  Google Scholar 

  7. Figueiredo JC, Levine AJ, Crott JW, Baurley J, Haile RW. Folate-genetics and colorectal neoplasia: what we know and need to know next. Mol Nutr Food Res. 2013;57(4):607–27.

    Article  CAS  Google Scholar 

  8. Kim YI. Role of the MTHFR polymorphisms in cancer risk modification and treatment. Future Oncol. 2009;5(4):523–42.

    Article  CAS  Google Scholar 

  9. Luo WP, Li B, Lin FY, Yan B, Du YF, Mo XF, et al. Joint effects of folate intake and one-carbon-metabolizing genetic polymorphisms on breast cancer risk: a case-control study in China. Sci Rep. 2016;6:29555.

    Article  CAS  Google Scholar 

  10. Stevens VL, Rodriguez C, Sun J, Talbot JT, Thun MJ, Calle EE. No association of single nucleotide polymorphisms in one-carbon metabolism genes with prostate cancer risk. Cancer Epidemiol Biomark Prev. 2008;17(12):3612–4.

    Article  CAS  Google Scholar 

  11. Abedinzadeh M, Zare-Shehneh M, Neamatzadeh H, Abedinzadeh M, Karami H. Association between MTHFR C677T polymorphism and risk of prostate cancer: evidence from 22 studies with 10,832 cases and 11,993 controls. Asian Pac J Cancer Prev. 2015;16(11):4525–30.

    Article  Google Scholar 

  12. Fard-Esfahani P, Mohammadi Torbati P, Hashemi Z, Fayaz S, Golkar M. Analysis of relation between C677T genotype in MTHFR gene and prostatic cancer in Iranian males. Acta Med Iran. 2012;50(10):657–63.

    CAS  PubMed  Google Scholar 

  13. Jackson MD, Tulloch-Reid MK, McFarlane-Anderson N, Watson A, Seers V, Bennett FI, et al. Complex interaction between serum folate levels and genetic polymorphisms in folate pathway genes: biomarkers of prostate cancer aggressiveness. Genes Nutr. 2013;8(2):199–207.

    Article  CAS  Google Scholar 

  14. Herman M, Raman J, Dong S, Samadi D, Scherr D. Increasing body mass index negatively impacts outcomes following robotic radical prostatectomy. J Soc Laparoendosc Surg. 2007;11:438–42.

    Google Scholar 

  15. Calle E, Kaaks R. Overweight, Obesity and Cancer: epidemiological evidence and proposed mechanisms. Nat Rev. 2004;4:579–91.

    Article  CAS  Google Scholar 

  16. Demark-Wahnefried W, Rais-Bahrami S, Desmond RA, Gordetsky JB, Hunter GR, Yang ES, et al. Presurgical weight loss affects tumour traits and circulating biomarkers in men with prostate cancer. Br J Cancer. 2017;117(9):1303–13.

    Article  CAS  Google Scholar 

  17. Rodriguez C, Freedland S, Deka A, Jacobs E, McCullough M, Patel A, et al. Body mass index, weight change, and risk of prostate cancer in the Cancer Prevention Study II Nutrition Cohort. Cancer Epidemiol Biomark Prev. 2007;161(1):63–9.

    Article  Google Scholar 

  18. Spangler E, Zeigler-Johnson C, Coomes M, Malkowicz S, Wein A, Rebbeck T. Association of obesity with tumor characteristics and treatment failure of prostate cancer in African-American and European American men. J Urol. 2007;178:1939–45.

    Article  CAS  Google Scholar 

  19. Amling C, Riffenburgh R, Sun L, Moul J, Lance R, Kusuda L, et al. Pathologic variables and recurrence rates as related to obesity and race in men with prostate cancer undergoing radical prostatectomy. J Clin Oncol. 2004;22(3):439–45.

    Article  Google Scholar 

  20. Freedland S, Terris M, Presti J Jr, Amling C, Kane C, Trock B, et al. Obesity and biochemical outcome following radical prostatectomy for organ confined disease with negative surgical margins. J Urol. 2004;172(2):520–4.

    Article  Google Scholar 

  21. Zeigler-Johnson C, Spangler E, Jalloh M, Gueye S, Rennert H, Rebbeck T. Genetic susceptibility to prostate cancer in men of African descent: implications for global disparities in incidence and outcomes. Can J Urol. 2007;15(1):3872–82.

    Google Scholar 

  22. Bassett W, Cooperberg M, Sadetsky N, Silvia S, DuChane J, Pasta D, et al. Impact of obesity on prostate cancer recurrence after radical prostatectomy: Data from CaPSURE. Urology. 2005;66:1060–5.

    Article  Google Scholar 

  23. Rebbeck TR, Weber AL, Walker AH, Stefflova K, Tran TV, Spangler E, et al. Context-dependent effects of genome-wide association study genotypes and macroenvironment on time to biochemical (prostate specific antigen) failure after prostatectomy. Cancer Epidemiol Biomark Prev. 2010;19(9):2115–23.

    Article  CAS  Google Scholar 

  24. Zeigler-Johnson C, Morales KH, Spangler E, Chang BL, Rebbeck TR. Relationship of early-onset baldness to prostate cancer in African-American men. Cancer Epidemiol Biomark Prev. 2013;22(4):589–96.

    Article  CAS  Google Scholar 

  25. Chen XL, Wang YM, Zhao F, Chen Z, Yang X, Sun C, et al. Methylenetetrahydrofolate reductase polymorphisms and colorectal cancer prognosis: a meta-analysis. J Gene Med. 2019;21(9):e3114.

    Article  CAS  Google Scholar 

  26. Collin SM, Metcalfe C, Zuccolo L, Lewis SJ, Chen L, Cox A, et al. Association of folate-pathway gene polymorphisms with the risk of prostate cancer: a population-based nested case-control study, systematic review, and meta-analysis. Cancer Epidemiol Biomark Prev. 2009;18(9):2528–39.

    Article  CAS  Google Scholar 

  27. Collin SM. Folate and B12 in prostate cancer. Adv Clin Chem. 2013;60:1–63.

    Article  CAS  Google Scholar 

  28. Qu YY, Zhou SX, Zhang X, Zhao R, Gu CY, Chang K, et al. Functional variants of the 5-methyltetrahydrofolate-homocysteine methyltransferase gene significantly increase susceptibility to prostate cancer: results from an ethnic Han Chinese population. Sci Rep. 2016;6:36264.

    Article  CAS  Google Scholar 

  29. Zhang X, Tang J, Shen N, Ren K. A single-nucleotide polymorphism (rs1805087) in the methionine synthase (METH) gene increases the risk of prostate cancer. Aging. 2018;10(10):2741–54.

    Article  CAS  Google Scholar 

  30. Lin VC, Lu TL, Yin HL, Yang SF, Lee YC, Liu CC, et al. Prognostic relevance of methylenetetrahydrofolate reductase polymorphisms for prostate cancer. Int J Mol Sci. 2016;17(12). https://doi.org/10.3390/ijms17121996.

  31. Tsai MY, Bignell M, Schwichtenberg K, Hanson NQ. High prevalence of a mutation in the cystathionine beta-synthase gene. Am J Hum Genet. 1996;59(6):1262–7.

    CAS  PubMed  PubMed Central  Google Scholar 

  32. Romano M, Marcucci R, Buratti E, Ayala YM, Sebastio G, Baralle FE. Regulation of 3′ splice site selection in the 844ins68 polymorphism of the cystathionine Beta -synthase gene. J Biol Chem. 2002;277(46):43821–9.

    Article  CAS  Google Scholar 

  33. Tsai MY, Yang F, Bignell M, Aras O, Hanson NQ. Relation between plasma homocysteine concentration, the 844ins68 variant of the cystathionine beta-synthase gene, and pyridoxal-5′-phosphate concentration. Mol Genet Metab. 1999;67(4):352–6.

    Article  CAS  Google Scholar 

  34. Levine AJ, Siegmund KD, Ervin CM, Diep A, Lee ER, Frankl HD, et al. The methylenetetrahydrofolate reductase 677C-->T polymorphism and distal colorectal adenoma risk. Cancer Epidemiol Biomark Prev. 2000;9(7):657–63.

    CAS  Google Scholar 

  35. Lopez-Cortes A, Cabrera-Andrade A, Salazar-Ruales C, Zambrano AK, Guerrero S, Guevara P, et al. Genotyping the high altitude mestizo ecuadorian population affected with prostate cancer. Biomed Res Int. 2017;2017:3507671.

    Article  Google Scholar 

  36. Friedman G, Goldschmidt N, Friedlander Y, Ben-Yehuda A, Selhub J, Babaey S, et al. A common mutation A1298C in human methylenetetrahydrofolate reductase gene: association with plasma total homocysteine and folate concentrations. J Nutr. 1999;129(9):1656–61.

    Article  CAS  Google Scholar 

  37. Kwabi-Addo B, Wang S, Chung W, Jelinek J, Patierno SR, Wang BD, et al. Identification of differentially methylated genes in normal prostate tissues from African American and Caucasian men. Clin Cancer Res. 2010;16(14):3539–47.

    Article  CAS  Google Scholar 

  38. Wang S, Dorsey TH, Terunuma A, Kittles RA, Ambs S, Kwabi-Addo B. Relationship between tumor DNA methylation status and patient characteristics in African-American and European-American women with breast cancer. PLoS One. 2012;7(5):e37928.

    Article  CAS  Google Scholar 

  39. Devaney JM, Wang S, Funda S, Long J, Taghipour DJ, Tbaishat R, et al. Identification of novel DNA-methylated genes that correlate with human prostate cancer and high-grade prostatic intraepithelial neoplasia. Prostate Cancer Prostatic Dis. 2013;16(4):292–300.

    Article  CAS  Google Scholar 

  40. Gohlke JH, Lloyd SM, Basu S, Putluri V, Vareed SK, Rasaily U, et al. Methionine-homocysteine pathway in African-American prostate cancer. JNCI Cancer Spectr. 2019;3(2):pkz019.

    Article  Google Scholar 

  41. Gross M, Ramirez C, Luthringer D, Nepomuceno E, Vollmer R, Burchette J, et al. Expression of androgen and estrogen related proteins in normal weight and obese prostate cancer patients. Prostate. 2009;69:520–7.

    Article  CAS  Google Scholar 

  42. Freedland S, Banez L, Sun L, Fitzsimons N, Moul J. Obese men have higher-grade and larger tumors: an analysis of the Duke Prostate Center database. Prostate Cancer Prostatic Dis. 2009;12:259–63.

    Article  CAS  Google Scholar 

  43. Al-Bayyari N, Hamadneh J, Hailat R, Hamadneh S. Total homocysteine is positively correlated with body mass index, waist-to-hip ratio, and fat mass among overweight reproductive women: a cross-sectional study. Nutr Res. 2017;48:9–15.

    Article  CAS  Google Scholar 

  44. Fowke JH, Motley SS. Statin use linked with a decrease in the conversion from high-grade prostatic intraepithelial neoplasia (HGPIN) to prostate cancer. Carcinogenesis. 2018;39(6):819–25.

    Article  CAS  Google Scholar 

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Acknowledgments

We would like to thank Dr. Timothy R. Rebbeck (Dana Farber Cancer Institute) for providing access to data from the SCORE study.

Funding

This study was funded by the Pennsylvania (PA) Department of Health. However, the PA Department of Health did not play a role in the study design, analysis, interpretation of results, or writing of the manuscript.

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SK assisted with drafting the manuscript, data analysis and interpretation, and manuscript revisions.

BKA contributed to the manuscript draft and revisions.

CZJ acquired data, was responsible for the study concept/design, analysis, and interpretation, and drafted the manuscript.

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Correspondence to Charnita Zeigler-Johnson.

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The authors declare that they have no conflicts of interest.

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This observational study based upon secondary data analysis of the Study of Clinical Outcomes, Risk and Ethnicity (SCORE) was approved by the Institutional Review Board (IRB) at Thomas Jefferson University (Philadelphia, PA). The IRB reference number is 16S.256. Informed consent was waived by the review board.

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Keith, S.W., Kwabi-Addo, B. & Zeigler-Johnson, C. Interactions Between Obesity and One-Carbon Metabolism Genes in Predicting Prostate Cancer Outcomes Among White and Black Patients. J. Racial and Ethnic Health Disparities 9, 305–314 (2022). https://doi.org/10.1007/s40615-020-00958-6

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