Breast density and polymorphisms in genes coding for CYP1A2 and COMT: the Multiethnic Cohort

Curcumin inhibits human cancer cell growth and migration through downregulation of SVCT2

Curcumin is a natural polyphenol that is extracted from the rhizomes of the turmeric plant (Curcuma longa), a member of the ginger family. It has been used for centuries in traditional Indian and Chinese medicine for its medicinal properties, including anti-inflammatory, antioxidant and antitumor effects. SVCT2 (Solute Carrier Family 23 Member 2, also known as SLC23A2) is a protein that plays a role in the transport of Vitamin C (Ascorbic Acid) into cells. SVCT2 plays an important role in tumor progression and metastasis, however, the molecular mechanisms of curcumin on SVCT2 have not been studied to date. Curcumin treatment inhibited proliferation and migration of cancer cells in a dose dependent manner. We found that curcumin reduced the expression of SVCT2 in cancer cells with a wild type p53, but not in those with a mutant type of p53. SVCT2 downregulation also reduced the MMP2 activity. Taken together, our results indicate that curcumin inhibited human cancer cell growth and migration by regulating SVCT2 through a downregulating p53. These findings provide new insights into the molecular mechanisms of curcumin's anticancer effects and potential therapeutic strategies for the treatment of metastatic migration.

Genetic architecture of mammographic density as a risk factor for breast cancer: a systematic review

BACKGROUND

Mammography Density (MD) is a potential risk marker that is influenced by genetic polymorphisms and can subsequently modulate the risk of breast cancer. This qualitative systematic review summarizes the genes and biological pathways involved in breast density and discusses the potential clinical implications in view of the genetic risk profile for breast density.

METHODS

The terms related to "Common genetic variations" and "Breast density" were searched in Scopus, PubMed, and Web of Science databases. Gene pathways analysis and assessment of protein interactions were also performed.

RESULTS

Eighty-six studies including 111 genes, reported a significant association between mammographic density in different populations. ESR1, IGF1, IGFBP3, and ZNF365 were the most prevalent genes. Moreover, estrogen metabolism, signal transduction, and prolactin signaling pathways were significantly related to the associated genes. Mammography density was an associated phenotype, and eight out of 111 genes, including COMT, CYP19A1, CYP1B1, ESR1, IGF1, IGFBP1, IGFBP3, and LSP1, were modifiers of this trait.

CONCLUSION

Genes involved in developmental processes and the evolution of secondary sexual traits play an important role in determining mammographic density. Due to the effect of breast tissue density on the risk of breast cancer, these genes may also be associated with breast cancer risk.

Association of Catechol-O-methyltransferase polymorphism Val158Met and mammographic density: A meta-analysis

OBJECTIVES

The Val158Met polymorphism in catechol-O-methyltransferase (COMT) enzyme reduces the methylation of catechol estrogens, which may affect mammographic density. High mammographic density is a known risk factor of breast cancer. Our aim was to perform meta-analysis of the effect of COMT Val158Met polymorphism on mammographic density.

METHODS

Original studies reporting data on mammographic density, stratified by the presence of COMT Val158Met polymorphism, were identified and combined using genetic models Met/Val vs. Val/Val, Met/Met vs. Val/Val, Val/Met+Met/Met vs. Val/Val (dominant model) and Met/Met vs. Val/Met+Val/Val (recessive model). Subgroup analyses by breast cancer status, menopausal status and use of hormone replacement therapy (HRT) were also performed.

RESULTS

Eight studies were included in the meta-analysis. The overall effect in percent mammographic density was -1.41 (CI -2.86 to 0.05; P=0.06) in the recessive model. Exclusion of breast cancer patients increased the effect size to -1.93 (CI -3.49 to -0.37; P=0.02). The results suggested opposite effect of COMT Val158Met for postmenopausal users of HRT versus premenopausal women or postmenopausal non-users of HRT.

CONCLUSIONS

COMT Val158Met polymorphism may be associated with mammographic density at least in healthy women. Menopausal status and HRT should be taken into account in future studies to avoid masking of the underlying effects.

Polymorphisms in the estrogen receptor alpha gene (ESR1), daily cycling estrogen and mammographic density phenotypes

Background

Single nucleotide polymorphisms (SNPs) involved in the estrogen pathway and SNPs in the estrogen receptor alpha gene (ESR1 6q25) have been linked to breast cancer development, and mammographic density is an established breast cancer risk factor. Whether there is an association between daily estradiol levels, SNPs in ESR1 and premenopausal mammographic density phenotypes is unknown.

Methods

We assessed estradiol in daily saliva samples throughout an entire menstrual cycle in 202 healthy premenopausal women in the Norwegian Energy Balance and Breast Cancer Aspects I study. DNA was genotyped using the Illumina Golden Gate platform. Mammograms were taken between days 7 and 12 of the menstrual cycle, and digitized mammographic density was assessed using a computer-assisted method (Madena). Multivariable regression models were used to study the association between SNPs in ESR1, premenopausal mammographic density phenotypes and daily cycling estradiol.

Results

We observed inverse linear associations between the minor alleles of eight measured SNPs (rs3020364, rs2474148, rs12154178, rs2347867, rs6927072, rs2982712, rs3020407, rs9322335) and percent mammographic density (p-values: 0.002–0.026), these associations were strongest in lean women (BMI, ≤23.6 kg/m^2.). The odds of above-median percent mammographic density (>28.5 %) among women with major homozygous genotypes were 3–6 times higher than those of women with minor homozygous genotypes in seven SNPs. Women with rs3020364 major homozygous genotype had an OR of 6.46 for above-median percent mammographic density (OR: 6.46; 95 % Confidence Interval 1.61, 25.94) when compared to women with the minor homozygous genotype. These associations were not observed in relation to absolute mammographic density. No associations between SNPs and daily cycling estradiol were observed. However, we suggest, based on results of borderline significance (p values: 0.025–0.079) that the level of 17β-estradiol for women with the minor genotype for rs3020364, rs24744148 and rs2982712 were lower throughout the cycle in women with low (<28.5 %) percent mammographic density and higher in women with high (>28.5 %) percent mammographic density, when compared to women with the major genotype.

Conclusion

Our results support an association between eight selected SNPs in the ESR1 gene and percent mammographic density. The results need to be confirmed in larger studies.

Electronic supplementary material

The online version of this article (doi:10.1186/s12885-016-2804-1) contains supplementary material, which is available to authorized users.

Lack of association between polymorphisms in the CYP1A2 gene and risk of cancer: evidence from meta-analyses

BACKGROUND

Polymorphisms in the CYP1A2 genes have the potential to affect the individual capacity to convert pre-carcinogens into carcinogens. With these comprehensive meta-analyses, we aimed to provide a quantitative assessment of the association between the published genetic association studies on CYP1A2 single nucleotide polymorphisms (SNPs) and the risk of cancer.

METHODS

We searched MEDLINE, ISI Web of Science and SCOPUS bibliographic online databases and databases of genome-wide association studies (GWAS). After data extraction, we calculated Odds Ratios (ORs) and 95% confidence intervals (CIs) for the association between the retrieved CYP1A2 SNPs and cancer. Random effect model was used to calculate the pooled ORs. Begg and Egger tests, one-way sensitivity analysis were performed, when appropriate. We conducted stratified analyses by study design, sample size, ethnicity and tumour site.

RESULTS

Seventy case-control studies and one GWA study detailing on six different SNPs were included. Among the 71 included studies, 42 were population-based case-control studies, 28 hospital-based case-control studies and one genome-wide association study, including total of 47,413 cancer cases and 58,546 controls. The meta-analysis of 62 studies on rs762551, reported an OR of 1.03 (95% CI, 0.96-1.12) for overall cancer (P for heterogeneity < 0.01; I(2) = 50.4%). When stratifying for tumour site, an OR of 0.84 (95% CI, 0.70-1.01; P for heterogeneity = 0.23, I(2) = 28.5%) was reported for bladder cancer for those homozygous mutant of rs762551. An OR of 0.79 (95% CI, 0.65-0.95; P for heterogeneity = 0.09, I(2) = 58.1%) was obtained for the bladder cancer from the hospital-based studies and on Caucasians.

CONCLUSIONS

This large meta-analysis suggests no significant effect of the investigated CYP1A2 SNPs on cancer overall risk under various genetic models. However, when stratifying according to the tumour site, our results showed a borderline not significant OR of 0.84 (95% CI, 0.70-1.01) for bladder cancer for those homozygous mutant of rs762551. Due to the limitations of our meta-analyses, the results should be interpreted with attention and need to be further confirmed by high-quality studies, for all the potential CYP1A2 SNPs.

Association between the COMT Val158Met polymorphism and risk of cancer: evidence from 99 case-control studies

Catechol-O-methyltransferase (COMT) plays a central role in DNA repair and estrogen-induced carcinogenesis. Many recent epidemiologic studies have investigated the association between the COMT Val158Met polymorphism and cancer risk, but the results are inconclusive. In this study, we performed a meta-analysis to investigate the association between cancer susceptibility and COMT Val158Met in different genetic models. Overall, no significant associations were found between COMT Val158Met polymorphism and cancer risk (homozygote model: odds ratio [OR] =1.05, 95% confidence interval [CI] = [0.98, 1.13]; heterozygote model: OR =1.01, 95% CI = [0.98, 1.04]; dominant model: OR =1.02, 95% CI [0.97, 1.06], and recessive model: OR =1.03, 95% CI [0.97, 1.09]). In the subgroup analysis of cancer type, COMT Val158Met was significantly associated with increased risks of bladder cancer in recessive model, and esophageal cancer in homozygote model, heterozygote model, and dominant model. Subgroup analyses based on ethnicities, COMT Val158Met was significantly associated with increased risk of cancer in homozygote and recessive model among Asians. In addition, homozygote, recessive, and dominant models were significantly associated with increased cancer risk in the subgroup of allele-specific polymerase chain reaction genotyping. Significant associations were not observed when data were stratified by the source of the controls. In summary, this meta-analysis suggested that COMT Val158Met polymorphism might not be a risk factor for overall cancer risk, but it might be involved in cancer development at least in some ethnic groups (Asian) or some specific cancer types (bladder and esophageal cell cancer). Further evaluations of more preclinical and epidemiological studies are required.

A comprehensive evaluation of interaction between genetic variants and use of menopausal hormone therapy on mammographic density

INTRODUCTION

Mammographic density is an established breast cancer risk factor with a strong genetic component and can be increased in women using menopausal hormone therapy (MHT). Here, we aimed to identify genetic variants that may modify the association between MHT use and mammographic density.

METHODS

The study comprised 6,298 postmenopausal women from the Mayo Mammography Health Study and nine studies included in the Breast Cancer Association Consortium. We selected for evaluation 1327 single nucleotide polymorphisms (SNPs) showing the lowest P-values for interaction (P int) in a meta-analysis of genome-wide gene-environment interaction studies with MHT use on risk of breast cancer, 2541 SNPs in candidate genes (AKR1C4, CYP1A1-CYP1A2, CYP1B1, ESR2, PPARG, PRL, SULT1A1-SULT1A2 and TNF) and ten SNPs (AREG-rs10034692, PRDM6-rs186749, ESR1-rs12665607, ZNF365-rs10995190, 8p11.23-rs7816345, LSP1-rs3817198, IGF1-rs703556, 12q24-rs1265507, TMEM184B-rs7289126, and SGSM3-rs17001868) associated with mammographic density in genome-wide studies. We used multiple linear regression models adjusted for potential confounders to evaluate interactions between SNPs and current use of MHT on mammographic density.

RESULTS

No significant interactions were identified after adjustment for multiple testing. The strongest SNP-MHT interaction (unadjusted P int <0.0004) was observed with rs9358531 6.5kb 5' of PRL. Furthermore, three SNPs in PLCG2 that had previously been shown to modify the association of MHT use with breast cancer risk were found to modify also the association of MHT use with mammographic density (unadjusted P int <0.002), but solely among cases (unadjusted P int SNP×MHT×case-status <0.02).

CONCLUSIONS

The study identified potential interactions on mammographic density between current use of MHT and SNPs near PRL and in PLCG2, which require confirmation. Given the moderate size of the interactions observed, larger studies are needed to identify genetic modifiers of the association of MHT use with mammographic density.

Association between the CYP1A2 polymorphisms and risk of cancer: a meta-analysis

The previously published data on the association between CYP1A2*1C (rs2069514) and CYP1A2*1F (rs762551) polymorphisms and cancer risk have remained controversial. Hence, we performed a meta-analysis to investigate the association between CYP1A2*1F and CYP1A2*1C polymorphisms and cancer risk under different inheritance models. Overall, significant association was observed between CYP1A2*1F and cancer risk when all the eligible studies were pooled into the meta-analysis (dominant model: OR 1.08, 95 % CI 1.02-1.15; heterozygous model: OR 1.06, 95 % CI 1.01-1.12; additive model: OR 1.07, 95 % CI 1.02-1.13). In the further stratified and sensitivity analyses, for CYP1A2*1F polymorphism, significantly increased lung cancer risk and significantly decreased bladder cancer risk were observed in Caucasians. For CYP1A2*1C polymorphism, no significant association was found in overall and all subgroup analyses. In summary, this meta-analysis suggests that CYP1A2*1F polymorphism is associated with lung cancer and bladder cancer risk in Caucasians.

Role of CYP1A2 1F polymorphism in cancer risk: evidence from a meta-analysis of 46 case-control studies

BACKGROUND

Emerging evidence showed that the common polymorphism (CYP1A2 1F, rs762551 C→A) in the promoter region of the CYP1A2 gene might be associated with susceptibility to cancer in humans. But individually published results were inconclusive. The aim of this meta-analysis is to investigate the association between CYP1A2 1F polymorphism and cancer risk.

METHODS

The Pubmed, Embase, Web of Science and Chinese BioMedical databases were searched for all articles published up to September 1st, 2012. Statistical analyses were performed using the STATA 12.0 software.

RESULTS

Forty-six case-control studies were included with a total of 22,993 cancer cases and 28,420 healthy controls. Meta-analysis results showed that the A allele of CYP1A2 1F polymorphism was associated with a decreased cancer risk (odds ratio [OR]=0.92, 95% confidence interval [CI]: 0.87-0.98, P=0.013). In the subgroup analysis by cancer types, the A allele of CYP1A2 1F polymorphism may increase the risk of breast cancer (OR=1.05, 95% CI: 1.01-1.10, P=0.024), and is also associated with a decreased risk of ovarian cancer (OR=0.70, 95% CI: 0.54-0.89, P=0.004). However, similar results were not found in lung, colorectal, bladder, endometrial, pancreatic and gastric cancers. Further subgroup analysis by ethnicity also showed a significant association between the A allele of CYP1A2 1F polymorphism and a decreased cancer risk among Caucasian populations (OR=0.91, 95% CI: 0.84-0.98, P=0.014); but no significant associations were observed among Asian populations.

CONCLUSIONS

Results from the current meta-analysis indicate that the A allele of CYP1A2 1F polymorphism may be associated with breast and ovarian cancer risk, especially among Caucasian populations.

Hormone metabolism genes and mammographic density in Singapore Chinese women

BACKGROUND

Female steroid hormone levels and exogenous hormone use influence breast cancer risk. We investigated the association between genetic variation in the hormone metabolism and signaling pathway and mammographic density, a strong predictor of breast cancer risk.

METHODS

We genotyped 161 SNPs in 15 hormone metabolism pathway gene regions and evaluated mammographic density in 2,038 Singapore Chinese women. Linear regression analysis was used to investigate single-nucleotide polymorphism (SNP) and mammographic density association. An overall pathway summary was obtained using the adaptive ranked truncated product test.

RESULTS

We did not find any of the individually tested SNPs to be associated with mammographic density after a multiple testing correction. There was no evidence of an overall effect on mammographic density of genetic variation in the hormone metabolism pathway.

CONCLUSIONS

In this cross-sectional study, genetic variation in hormone metabolism pathway was not associated with mammographic density in Singapore Chinese women.

IMPACT

Consistent with existing data from Caucasian populations, polymorphisms in hormone pathway genes are not likely to be strong predictors of mammographic density in Asian women.

Role of CYP1A2 polymorphisms in breast cancer risk in women

Cytochrome P4501A2 (CYP1A2) is a key enzyme in the etiology of breast cancer (BC). It is involved in breast carcinogen activation [aromatic (AAs) and heterocyclic amines (HAs), polycyclic aromatic hydrocarbons (PAHs)], in the production of beneficial oestrogen [2-hydroxyestrone (2-OHE1)] and in converting arachidonic acid (AAc) to epoxyeicosatrienoic acids (EETs), which have anti-inflammatory properties. Within a hospital-based case-control study, the effect of functional CYP1A2 variants [-3860G/A (rs2069514), -2467T/delT (rs3569413), -163C/A (rs762551)] and their interactions with environmental factors in BC risk was investigated. The study population included 125 BC cases and 43 non-cancer controls. Genotyping was performed in RT-PCR using Taqman assays. The gene-environment interaction was appraised using a case-only study design. We found that the -3860A variant, independently from environmental factors, as well as by interacting with fried foods (p=0.025) and indoor exposure to pollutants (p=0.050), reduced the risk of BC (p=0.025), whereas its interaction with coffee (p=0.045) increased the BC risk. This is the first study indicating that the -3860A variant, by decreasing CYP1A2 activity, modifies BC risk by interacting with environmental factors, thereby supporting the hypothesis that reduced CYP1A2 activity contributes to BC risk in different ways, for example, it may be protective by reducing the activation of pro-carcinogens such as AAs, HAs and PAHs, but would increase risk by reducing the beneficial formation of 2-OHE1 and EETs.

Association of COMT Val158Met polymorphism and breast cancer risk: an updated meta-analysis

BACKGROUND

Catechol-O-methyltransferase (COMT) is one of the most important enzymes involved in estrogen metabolism and its functional genetic polymorphisms may be associated with breast cancer (BC) risk. Many epidemiological studies have been conducted to explore the association between the COMT Val158Met polymorphism and breast cancer risk. However, the results remain inconclusive. In order to derive a more precise estimation of this relationship, a large meta-analysis was performed in this study.

METHODS

Systematic searches of the PubMed, Embase and Cochrane Library were performed. Crude odds ratios (ORs) with 95% confidence intervals (CIs) were calculated to estimate the strength of the association.

RESULTS

A total of 56 studies including 34,358 breast cancer cases and 45,429 controls were included. Overall, no significant associations between the COMT Val158Met polymorphism and breast cancer risk were found for LL versus HH, HL versus HH, LL versus HL, recessive model LL versus HL+HH, and dominant model LL+HL versus HH. In subgroup analysis by ethnicity, source of controls, and menopausal status, there was still no significant association detected in any of the genetic models.

CONCLUSION

Our meta-analysis results suggest that the COMT Val158Met polymorphism may not contribute to breast cancer susceptibility.

VIRTUAL SLIDES

The virtual slides(s) for this article can be found here: http://www.diagnosticpathology.diagnomx.eu/vs4806123577708417.

Polymorphisms in genes involved in the estrogen pathway and mammographic density

Background

Single nucleotide polymorphisms (SNPs) in genes involved in the estrogen pathway appear to be associated with breast cancer risk and possibly with mammographic density (MD), but little is known of these associations among premenopausal women. This study examines the association of 11 polymorphisms in five estrogen-related genes (estrogen receptors alpha and beta (ERα, ERβ), 17β-hydroxysteroid dehydrogenase 1 (HSD17B1), catechol-O-methyltransferase (COMT), cytochrome P450 1B1 (CYP1B1)) with premenopausal MD. Effect modification of four estrogen-related factors (parity, age at menarche, hormonal derivatives use and body mass index (BMI)) on this relation is also assessed.

Methods

Polymorphisms were genotyped in 741 premenopausal Caucasian women whose MD was measured in absolute density (AD, cm²) and percent density using a computer-assisted method. Multivariate linear models were used to examine the associations (P_trend) and interactions (P_i).

Results

None of the SNPs showed a statistically significant association with AD. However, each additional rare allele of rs1056836 CYP1B1 was associated with a reduction in AD among nulliparous women (P_trend = 0.004), while no association was observed among parous women (P_trend = 0.62; P_i = 0.02). An increase in the number of rare alleles of the HSD17B1 SNP (rs598126 and rs2010750) was associated with an increase in AD among women who never used hormonal derivatives (P_trend = 0.06 and P_trend = 0.04, respectively), but with a decrease in AD among past hormonal derivatives users (P_trend = 0.04; P_i = 0.02 and P_trend = 0.08; P_i = 0.01, respectively). Moreover, a negative association of rs598126 HSD17B1 SNP with AD was observed among women with higher BMI (>median) (P_trend = 0.01; P_i = 0.02). A negative association between an increased number of rare alleles of COMT rs4680 SNP and AD was limited to women who never used hormonal derivatives (P_trend = 0.02; P_i = 0.03) or with late age at menarche (>median) (P_trend = 0.03; P_i = 0.02). No significant association was observed between polymorphisms in the ERα or ERβ genes and AD. Similar results, although less significant, were observed when MD was assessed in percent density.

Conclusion

SNPs located in CYP1B1, COMT or HSD17B1 genes seem to be associated with MD in some strata of estrogen-related factors. Our findings suggest that modifying effects of estrogen-related factors should be considered when evaluating associations of polymorphisms in estrogen-related genes with premenopausal mammographic density.

Recording of hormone therapy and breast density in breast screening programs: summary and recommendations of the International Cancer Screening Network

Breast density and the use of hormone therapy (HT) for menopausal symptoms alter the risk of breast cancer and both factors influence screening mammography performance. The International Cancer Screening Network (ICSN) surveyed its 29 member countries and found that few programs record breast density or the use of HT among screening participants. This may affect the ability of programs to assess their effectiveness in reducing breast cancer mortality. Seven countries recorded the use of HT at screening, and some were able to link screening records to individual prescribing records of HT. Eight countries reported recording breast density at screening mammography for some or all women screened. The recommendations of the ICSN for recording information about breast density and HT are presented.

Lack of association of CYP1A2-164 A/C polymorphism with breast cancer susceptibility: a meta-analysis involving 17,600 subjects

Published data on the association between cytochrome P-450 1A2 (CYP1A2)-164 A/C polymorphism and breast cancer risk are inconclusive. To derive a more precise estimation of the relationship, a meta-analysis was performed. Medline, PubMed, Embase, and Web of Science were searched. Crude ORs with 95% CIs were used to assess the strength of association between CYP1A2-164 A/C polymorphism and breast cancer risk. The pooled ORs were performed for co-dominant model (AC versus AA, CC versus AA), dominant model (CC + AC versus AA), and recessive model (CC versus AA + AC), respectively. A total of 9 studies including 7,580 cases and 10,020 controls were involved in this meta-analysis. Overall, no significantly elevated breast cancer risk was found in all genetic models when all studies were pooled into the meta-analysis (AC versus AA: OR = 1.02, 95% CI = 0.92-1.13; CC versus AA: OR = 1.17, 95% CI = 0.83-1.64; dominant model: OR = 1.07, 95% CI = 0.93-1.23; and recessive model: OR = 1.13, 95% CI = 0.82-1.55). In the subgroup analysis by ethnicity or source of controls, there was still no significant association detected in all genetic models. In conclusion, upto date, there is still not enough evidence to indicate the association of CYP1A2-164 A/C polymorphism and breast cancer development.

Lack of association between catechol-O-methyltransferase Val108/158Met polymorphism and breast cancer risk: a meta-analysis of 25,627 cases and 34,222 controls

Epidemiological studies have evaluated the association between catechol-O-methyltransferase (COMT) Val108/158Met polymorphism and breast cancer risk. However, the results remain conflicting rather than conclusive. In order to derive a more precise estimation of the relationship, we performed this meta-analysis. Systematic searches of the PubMed and Medline databases were performed. A total of 41 studies including 25,627 cases and 34,222 controls were identified. Genotype distributions of COMT in the controls of all studies were in agreement with the Hardy-Weinberg equilibrium (HWE) except for three studies. When all 41 studies were pooled into the meta-analysis, there was no evidence for significant association between COMT Val108/158Met polymorphism and breast cancer risk (for Val/Met vs. Val/Val: OR = 0.99, 95% CI = 0.93-1.04; for Met/Met vs. Val/Val: OR = 0.96, 95% CI = 0.88-1.04; for dominant model: OR = 0.97, 95% CI = 0.92-1.03; for recessive model: OR = 0.97, 95% CI = 0.90-1.04). In the subgroup analyses by ethnicity, menopausal status, no significant associations were found in all genetic models. When sensitivity analyses were performed by excluding HWE-violating studies, all the results were not materially altered. In summary, the meta-analysis strongly suggests that COMT Val108/158Met polymorphism is not associated with increased breast cancer risk.

Genetic polymorphisms of estrogen metabolizing enzyme and breast cancer risk in Thai women

Estrogen and its metabolites are believed to play important roles in breast cancer, and its determinants include both genetic and lifestyle factors. The objective of the study is to investigate the association of breast cancer risk in Thailand with genetic polymorphisms in several genes involved in estrogen synthesis and metabolism. Five hundred and seventy patients with histopathologically confirmed breast cancer and 497 controls were included in the present study. Forty single nucleotide polymorphisms (SNPs) in the CYP1A1, CYP1A2, CYP1B1, CYP17, CYP19, CYP2C9, CYP2C19, AhR, ESR1, PGR, ERRG, COMT, HSD17B1, HSD17B2, EPHX1 and NQO1 genes were genotyped. Association of genotypes with breast cancer risk was evaluated using multivariate logistic regression, which suggested an altered risk for the following SNPs [gene, odds ratio (OR) and 95% confidence interval are shown]: heterozygote carriers of rs4917623 [CYP2C19, OR = 1.38 (1.04-1.84)], rs2066853 [AhR, OR = 1.34 (1.02-1.76)] and rs1857407 [ERRG, (OR = 0.72 (0.55-0.96)]; homozygote carriers of rs762551 [CYP1A2, OR = 2.75 (1.47-5.14)], rs4917623 [CYP2C19, OR = 1.48 (1.00-2.19) and rs945453 [ERRG, OR = 1.66 (1.04-2.65)]. In addition, a stratified analysis by menopausal status indicated that the association of the CYP1A2 (rs762551) and CYP17 (rs743572) polymorphisms with breast cancer risk were mainly evident in premenopausal, while ERRG (rs1857407) was significant in postmenopausal women. These findings suggest that CYP1A2, CYP2C19, AhR, ERRG and CYP17 polymorphisms may play an important role in estrogen metabolism and modify individual susceptibility to breast cancer in Thai women.

Do single nucleotide polymorphisms in xenobiotic metabolizing genes determine breast cancer susceptibility and treatment outcomes?

SNPs in CYP1A1, CYP2A1, CYP2B6, CYP2C, CYP2D6, CYP3A, GSTM1, GSTT1, GSTP1, SULT1A1, SULT1A2, UGT, and MTHFR are associated with breast cancer susceptibility; however, lack of such associations are also reported in some populations. The contradictory findings are explained on the basis of ethnic variation among populations and due to lack of proper sample size, detailed genotype-phenotype combinations and validation of gene expression studies at protein level. In this review, SNPs in these genes that have tremendous potential in identification of susceptible individuals, development of preventive strategies, treatment outcomes and their limitations are discussed.

Can genes for mammographic density inform cancer aetiology?

Mammographic density (MD) reflects variations in fat, stromal and epithelial tissues that are thought to be regulated by several genes. High MD is an established risk factor for breast cancer; therefore, genes that regulate MD may indirectly influence breast cancer. These genes might also be fewer in number and easier to identify than those for breast cancer risk outside of inherited predisposition syndromes. In this Perspective, we review the limited genetic studies of MD and propose future directions.

Coffee intake and CYP1A2*1F genotype predict breast volume in young women: implications for breast cancer

As breast volume may be associated with heart cancer risk, we studied the relationship between breast volume, CYP1A2*1F and coffee intake. Among healthy premenopausal non-hormone users, 3+ cups per day was associated with lower volume only in C-allele carriers (P_interaction=0.02), which is consistent with reports that coffee protects only C-allele carriers against breast cancer.

Breast cancer susceptibility loci and mammographic density

Introduction

Recently, the Breast Cancer Association Consortium (BCAC) conducted a multi-stage genome-wide association study and identified 11 single nucleotide polymorphisms (SNPs) associated with breast cancer risk. Given the high degree of heritability of mammographic density and its strong association with breast cancer, it was hypothesised that breast cancer susceptibility loci may also be associated with breast density and provide insight into the biology of breast density and how it influences breast cancer risk.

Methods

We conducted an analysis in the Nurses' Health Study (n = 1121) to assess the relation between 11 breast cancer susceptibility loci and mammographic density. At the time of their mammogram, 217 women were premenopausal and 904 women were postmenopausal. We used generalised linear models adjusted for covariates to determine the mean percentage of breast density according to genotype.

Results

Overall, no association between the 11 breast cancer susceptibility loci and mammographic density was seen. Among the premenopausal women, three SNPs (rs12443621 [TNRc9/LOC643714], rs3817198 [lymphocyte-specific protein-1] and rs4666451) were marginally associated with mammographic density (p < 0.10). All three of these SNPs showed an association that was consistent with the direction in which these alleles influence breast cancer risk. The difference in mean percentage mammographic density comparing homozygous wildtypes to homozygous variants ranged from 6.3 to 8.0%. None of the 11 breast cancer loci were associated with postmenopausal breast density.

Conclusion

Overall, breast cancer susceptibility loci identified through a genome-wide association study do not appear to be associated with breast cancer risk.