Factors Modifying the Association Between Hormone-Replacement Therapy and Breast Cancer Risk

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UBC9 encodes a protein that conjugates small ubiquitin-related modifier (SUMO) to target proteins resulting in a change of their localization, activity or stability. Genetic variability may affect expression and activity of UBC9 and may have an impact on breast tumor progression. We investigated associations between UBC9 genotypes and histopathological parameters in 1,021 breast cancer cases of the GENICA collection using a single nucleotide polymorphism (SNP) tagging approach. Genotyping analyses were performed by TaqMan 1 allelic discrimination. Odds ratios (OR) and 95% confidence intervals (CI) were calculated by ordinal logistic regression. Multiple imputation based on HapMap data was applied to boost the power of the study. The study revealed significant associations of three UBC9 SNPs with histological grade (rs7187167, p trend 5 0.001; rs11248866, p trend 5 0.009; rs8052688, p trend 5 0.008). Model selection identified a recessive penetrance model for rs7187167 as the best representation of tumor grade (global p 5 0.001). This model did not improve by inclusion of additional SNPs in linkage disequilibrium. Imputation of SNPs in a 300 kb region around the genotyped SNPs supported rs7187167 as a major contributor to tumor grade. Compared with common allele carriers, rare homozygotes presented less frequently with high grade tumors (G3 vs. G1: OR 0.26, 95% CI 0.11-0.62; G3 vs. G2: OR 0.45, 95% CI 0.23-0.86). In addition to tumor size, nodal status and estrogen receptor status, multivariate analyses confirmed an independent role of rs7187167 as predictor of tumor grade (p 5 0.0003). The present results underline the value of genetic variation in UBC9 for breast cancer prognosis. ' 2009 UICC Key words: UBC9 polymorphisms; SUMOylation; breast cancer progression; tumor grade; multiple imputation Rapid and reversible post-translational protein modifications including phosphorylation, methylation, acetylation, glycosylation and ubiquitination are key elements in the regulation of many cellular processes. Another recently identified type of modification is small ubiquitin-related modifier (SUMO) conjugation or SUMOylation. SUMO plays an important role in the regulation of physical interactions. 1,2 By masking or adding interaction surfaces or by inducing conformational changes, it governs proteinprotein and protein-DNA interactions and in consequence can lead to changes in protein localization, activity or stability. Substrates of SUMO participate in diverse cellular processes, including transcriptional regulation, nuclear transport, cell cycle control and maintenance of genome integrity. SUMOylation is a multistep process involving maturation, activation and conjugation. 3 The SUMO-conjugating enzyme UBC9 (UBE2I) is essential for SUMOylation and transfers the activated SUMO to the target protein. This transfer is facilitated by SUMO ligases such as the protein inhibitors of activated STAT (PIAS) family proteins that together with UBC9 confer substrate specificity. 2 Due to the existence of SUMO isopeptidases, SUM...

Section: Study Populationmentioning

confidence: 99%

Common variants in the UBC9 gene encoding the SUMO‐conjugating enzyme are associated with breast tumor grade

Dünnebier¹,

Bermejo²,

Haas³

et al. 2009

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“…26,27 In addition, the study provides a comprehensive series of incident breast tumors suitable for the investigation of tumor-associated factors potentially relevant in breast tumorigenesis and tumor progression. Here, we describe GST (pi, mu, alpha) and CYP (1A1, 1A2, 3A4, 1B1, 2E1) isoenzyme expression in tumor tissues of this large collection of breast cancer cases and discuss their role in conjunction with known breast cancer prognostic factors.…”

mentioning

confidence: 99%

Expression of xenobiotic and steroid hormone metabolizing enzymes in human breast carcinomas

Haas

Pierl

Harth

et al. 2006

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The potential to metabolize endogenous and exogenous substances may influence breast cancer development and tumor growth. Therefore, the authors investigated the protein expression of Glutathione S-transferase (GST) isoforms and cytochrome P450 (CYP) known to be involved in the metabolism of steroid hormones and endogenous as well as exogenous carcinogens in breast cancer tissue to obtain new information on their possible role in tumor progression. Expression of GST pi, mu, alpha and CYP1A1/2, 1A2, 3A4/5, 1B1, 2E1 was assessed by immunohistochemistry for primary breast carcinomas of 393 patients from the German GENICA breast cancer collection. The percentages of positive tumors were 50.1 and 44.5% for GST mu and CYP2E1, and ranged from 13 to 24.7% for CYP1A2, GST pi, CYP1A1/2, CYP3A4/5, CYP1B1. GST alpha was expressed in 1.8% of tumors. The authors observed the following associations between strong protein expression and histopathological characteristics: GST expression was associated with a better tumor differentiation (GST mu, p 5 0.018) and with reduced lymph node metastasis (GST pi, p 5 0.02). In addition, GST mu expression was associated with a positive estrogen receptor and progesterone receptor status (p < 0.001). CYP3A4/5 expression was associated with a positive nodal status (p 5 0.018). Expression of CYP1B1 was associated with poor tumor differentiation (p 5 0.049). Our results demonstrate that the majority of breast carcinomas expressed xenobiotic and drug metabolizing enzymes. They particularly suggest that GST mu and pi expression may indicate a better prognosis and that strong CYP3A4/5 and CYP1B1 expression may be key features of nonfavourable prognosis. ' 2006 Wiley-Liss, Inc.Key words: breast carcinoma; GST; CYP; immunohistochemistry; estrogen receptor; progesterone receptor The influence of exogenous and endogenous factors on tumor growth partly depends on the individual potential to metabolize these substances. Phase I and phase II enzymes are key players in the metabolism of a huge number of exogenous and endogenous compounds including steroid hormones. Usually, phase I and phase II are detoxification processes, but this metabolism can also lead to highly reactive electrophiles that can bind to macromolecules, e.g., proteins and DNA. Moreover, these enzymes are highly polymorphic, giving rise to variations in enzymatic activity.1 This may influence predisposition to cancer as well as tumor development and progression.2 Therefore, these enzymes are candidates for the investigation of a potential role in breast cancer.Glutathione S-transferases (GSTs) are phase II metabolizing isoenzymes. They facilitate clearance of endogenous hydrophobic compounds such as hormones, steroids, haem, bilirubin and bile acids. Furthermore, they are essential for metabolism of environmental carcinogens, drugs and pesticides by catalyzing the conjunction of reactive chemical intermediates to soluble glutathione conjugates.3 Seven classes of cytosolic GSTs are recognized in mammalian tissues (alpha, mu, pi, sigma, om...

“…32,33 In brief, 1,143 incident breast cancer cases and 1,155 population controls, matched in 5-year classes, participated in the study. The GENICA study was approved by the Ethics' Committee of the University of Bonn and all study participants gave written informed consent.…”

Section: Study Populationmentioning

confidence: 99%

Exploring the association between genetic variation in the SUMO isopeptidase gene USPL1 and breast cancer through integration of data from the population‐based GENICA study and external genetic databases

Bermejo

Kabisch

Dünnebier

et al. 2013

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Small ubiquitin-like modifier (SUMO) proteins are covalently attached to target proteins to modify their function. SUMO conjugation participates in processes tightly linked to tumorigenesis. Recently USPL1 (ubiquitin-specific peptidase-like (1) was identified as a SUMO isopeptidase. We report here on the first exploratory study investigating the relationship between genetic variability in USPL1 and breast cancer. Three potentially functional nonsynonymous coding SNPs (rs3742303, rs17609459, rs7984952) were genotyped in 1,021 breast cancer cases and 1,015 controls from the population-based GENICA study. We took advantage of multiple genotype imputation based on HapMap and the 1000 Genomes Project data to refine the association screening in the investigated region. Public genetic databases were also used to investigate the relationship