Dataset Information

Combined effect of CCND1 and COMT polymorphisms and increased breast cancer risk.

ABSTRACT: Estrogens are crucial tumorigenic hormones, which impact the cell growth and proliferation during breast cancer development. Estrogens are metabolized by a series of enzymes including COMT, which converts catechol estrogens into biologically non-hazardous methoxyestrogens. Several studies have also shown the relationship between estrogen and cell cycle progression through activation of CCND1 transcription.In this study, we have investigated the independent and the combined effects of commonly occurring CCND1 (Pro241Pro, A870G) and COMT (Met108/158Val) polymorphisms to breast cancer risk in two independent Caucasian populations from Ontario (1228 breast cancer cases and 719 population controls) and Finland (728 breast cancer cases and 687 population controls). Both COMT and CCND1 polymorphisms have been previously shown to impact on the enzymatic activity of the coded proteins.Here, we have shown that the high enzymatic activity genotype of CCND1High (AA) was associated with increased breast cancer risk in both the Ontario [OR: 1.3, 95%CI (1.0-1.69)] and the Finland sample [OR: 1.4, 95%CI (1.01-1.84)]. The heterozygous COMTMedium (MetVal) and the high enzymatic activity of COMTHigh (ValVal) genotype was also associated with breast cancer risk in Ontario cases, [OR: 1.3, 95%CI (1.07-1.68)] and [OR: 1.4, 95%CI (1.07-1.81)], respectively. However, there was neither a statistically significant association nor increased trend of breast cancer risk with COMTHigh (ValVal) genotypes in the Finland cases [OR: 1.0, 95%CI (0.73-1.39)]. In the combined analysis, the higher activity alleles of the COMT and CCND1 is associated with increased breast cancer risk in both Ontario [OR: 2.22, 95%CI (1.49-3.28)] and Finland [OR: 1.73, 95%CI (1.08-2.78)] populations studied. The trend test was statistically significant in both the Ontario and Finland populations across the genotypes associated with increasing enzymatic activity.Using two independent Caucasian populations, we have shown a stronger combined effect of the two commonly occurring CCND1 and COMT genotypes in the context of breast cancer predisposition.

SUBMITTER: Onay UV

PROVIDER: S-EPMC2254632 | biostudies-literature | 2008 Jan

REPOSITORIES: biostudies-literature

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Combined effect of CCND1 and COMT polymorphisms and increased breast cancer risk.

Onay Ummiye V UV Aaltonen Kirsimari K Briollais Laurent L Knight Julia A JA Pabalan Noel N Kilpivaara Outi O Andrulis Irene L IL Blomqvist Carl C Nevanlinna Heli H Ozcelik Hilmi H

BMC cancer 20080114

<h4>Background</h4>Estrogens are crucial tumorigenic hormones, which impact the cell growth and proliferation during breast cancer development. Estrogens are metabolized by a series of enzymes including COMT, which converts catechol estrogens into biologically non-hazardous methoxyestrogens. Several studies have also shown the relationship between estrogen and cell cycle progression through activation of CCND1 transcription.<h4>Methods</h4>In this study, we have investigated the independent and ...[more]

PMID: 18194538

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Project description:BACKGROUND:Texture patterns have been shown to improve breast cancer risk segregation in addition to area-based mammographic density. The additional value of texture pattern scores on top of volumetric mammographic density measures in a large screening cohort has never been studied. METHODS:Volumetric mammographic density and texture pattern scores were assessed automatically for the first available digital mammography (DM) screening examination of 51,400 women (50-75 years of age) participating in the Dutch biennial breast cancer screening program between 2003 and 2011. The texture assessment method was developed in a previous study and validated in the current study. Breast cancer information was obtained from the screening registration system and through linkage with the Netherlands Cancer Registry. All screen-detected breast cancers diagnosed at the first available digital screening examination were excluded. During a median follow-up period of 4.2 (interquartile range (IQR) 2.0-6.2) years, 301 women were diagnosed with breast cancer. The associations between texture pattern scores, volumetric breast density measures and breast cancer risk were determined using Cox proportional hazard analyses. Discriminatory performance was assessed using c-indices. RESULTS:The median age of the women at the time of the first available digital mammography examination was 56 years (IQR 51-63). Texture pattern scores were positively associated with breast cancer risk (hazard ratio (HR) 3.16 (95% CI 2.16-4.62) (p value for trend <0.001), for quartile (Q) 4 compared to Q1). The c-index of texture was 0.61 (95% CI 0.57-0.64). Dense volume and percentage dense volume showed positive associations with breast cancer risk (HR 1.85 (95% CI 1.32-2.59) (p value for trend <0.001) and HR 2.17 (95% CI 1.51-3.12) (p value for trend <0.001), respectively, for Q4 compared to Q1). When adding texture measures to models with dense volume or percentage dense volume, c-indices increased from 0.56 (95% CI 0.53-0.59) to 0.62 (95% CI 0.58-0.65) (p < 0.001) and from 0.58 (95% CI 0.54-0.61) to 0.60 (95% CI 0.57-0.63) (p = 0.054), respectively. CONCLUSIONS:Deep-learning-based texture pattern scores, measured automatically on digital mammograms, are associated with breast cancer risk, independently of volumetric mammographic density, and augment the capacity to discriminate between future breast cancer and non-breast cancer cases.

Dataset Information

Combined effect of CCND1 and COMT polymorphisms and increased breast cancer risk.

Publications

Combined effect of CCND1 and COMT polymorphisms and increased breast cancer risk.

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