Polymorphisms in genes of melatonin biosynthesis and signaling support the light-at-night hypothesis for breast cancer.

Light-at-night triggers the decline of pineal gland melatonin biosynthesis and secretion and is an IARC-classified probable breast-cancer risk factor. We applied a large-scale molecular epidemiology approach to shed light on the putative role of melatonin in breast cancer. We investigated associations between breast-cancer risk and polymorphisms at genes of melatonin biosynthesis/signaling using a study population of 44,405 women from the Breast Cancer Association Consortium (22,992 cases, 21,413 population-based controls). Genotype data of 97 candidate single nucleotide polymorphisms (SNPs) at 18 defined gene regions were investigated for breast-cancer risk effects. We calculated adjusted odds ratios (ORs) and 95% confidence intervals (CI) by logistic regression for the main-effect analysis as well as stratified analyses by estrogen- and progesterone-receptor (ER, PR) status. SNP-SNP interactions were analyzed via a two-step procedure based on logic regression. The Bayesian false-discovery probability (BFDP) was used for all analyses to account for multiple testing. Noteworthy associations (BFDP < 0.8) included 10 linked SNPs in tryptophan hydroxylase 2 (TPH2) (e.g. rs1386492: OR = 1.07, 95% CI 1.02-1.12), and a SNP in the mitogen-activated protein kinase 8 (MAPK8) (rs10857561: OR = 1.11, 95% CI 1.04-1.18). The SNP-SNP interaction analysis revealed noteworthy interaction terms with TPH2- and MAPK-related SNPs (e.g. rs1386483R ∧ rs1473473D ∧ rs3729931D: OR = 1.20, 95% CI 1.09-1.32). In line with the light-at-night hypothesis that links shift work with elevated breast-cancer risks our results point to SNPs in TPH2 and MAPK-genes that may impact the intricate network of circadian regulation.

A genome-wide gene-based gene-environment interaction study of breast cancer in more than 90,000 women.

Background: Genome-wide association studies (GWAS) have identified more than 200 susceptibility loci for breast cancer, but these variants explain less than a fifth of the disease risk. Although gene-environment interactions have been proposed to account for some of the remaining heritability, few studies have empirically assessed this. Methods: We obtained genotype and risk factor data from 46,060 cases and 47,929 controls of European ancestry from population-based studies within the Breast Cancer Association Consortium (BCAC). We built gene expression prediction models for 4,864 genes with a significant (P<0.01) heritable component using the transcriptome and genotype data from the Genotype-Tissue Expression (GTEx) project. We leveraged predicted gene expression information to investigate the interactions between gene-centric genetic variation and 14 established risk factors in association with breast cancer risk, using a mixed-effects score test. Results: After adjusting for number of tests using Bonferroni correction, no interaction remained statistically significant. The strongest interaction observed was between the predicted expression of the C13orf45 gene and age at first full-term pregnancy (PGXE=4.44×10-6). Conclusion: In this transcriptome-informed genome-wide gene-environment interaction study of breast cancer, we found no strong support for the role of gene expression in modifying the associations between established risk factors and breast cancer risk. Impact: Our study suggests a limited role of gene-environment interactions in breast cancer risk.

Genome-wide interaction analysis of menopausal hormone therapy use and breast cancer risk among 62,370 women.

Use of menopausal hormone therapy (MHT) is associated with increased risk for breast cancer. However, the relevant mechanisms and its interaction with genetic variants are not fully understood. We conducted a genome-wide interaction analysis between MHT use and genetic variants for breast cancer risk in 27,585 cases and 34,785 controls from 26 observational studies. All women were post-menopausal and of European ancestry. Multivariable logistic regression models were used to test for multiplicative interactions between genetic variants and current MHT use. We considered interaction p-values < 5 × 10-8 as genome-wide significant, and p-values < 1 × 10-5 as suggestive. Linkage disequilibrium (LD)-based clumping was performed to identify independent candidate variants. None of the 9.7 million genetic variants tested for interactions with MHT use reached genome-wide significance. Only 213 variants, representing 18 independent loci, had p-values < 1 × 105. The strongest evidence was found for rs4674019 (p-value = 2.27 × 10-7), which showed genome-wide significant interaction (p-value = 3.8 × 10-8) with current MHT use when analysis was restricted to population-based studies only. Limiting the analyses to combined estrogen-progesterone MHT use only or to estrogen receptor (ER) positive cases did not identify any genome-wide significant evidence of interactions. In this large genome-wide SNP-MHT interaction study of breast cancer, we found no strong support for common genetic variants modifying the effect of MHT on breast cancer risk. These results suggest that common genetic variation has limited impact on the observed MHT-breast cancer risk association.

Cancer-Associated Intermediate Conductance Ca2+-Activated K⁺ Channel KCa3.1.

Several tumor entities have been reported to overexpress KCa3.1 potassium channels due to epigenetic, transcriptional, or post-translational modifications. By modulating membrane potential, cell volume, or Ca2+ signaling, KCa3.1 has been proposed to exert pivotal oncogenic functions in tumorigenesis, malignant progression, metastasis, and therapy resistance. Moreover, KCa3.1 is expressed by tumor-promoting stroma cells such as fibroblasts and the tumor vasculature suggesting a role of KCa3.1 in the adaptation of the tumor microenvironment. Combined, this features KCa3.1 as a candidate target for innovative anti-cancer therapy. However, immune cells also express KCa3.1 thereby contributing to T cell activation. Thus, any strategy targeting KCa3.1 in anti-cancer therapy may also modulate anti-tumor immune activity and/or immunosuppression. The present review article highlights the potential of KCa3.1 as an anti-tumor target providing an overview of the current knowledge on its function in tumor pathogenesis with emphasis on vasculo- and angiogenesis as well as anti-cancer immune responses.

Long intergenic noncoding RNA 299 methylation in peripheral blood is a biomarker for triple-negative breast cancer.

AIM: To identify DNA methylation biomarkers in peripheral blood samples from triple-negative breast cancer (TNBC) patients. MATERIALS & METHODS: We conducted an epigenome-wide association study (EWAS): the most promising markers were identified in 233 TNBC case-control pairs (discovery set) and subsequently validated in an independent validation set (57 TNBC patients and 124 controls). RESULTS: cg06588802 (LINC00299/ID2) showed a higher methylation in TNBC patients compared with controls (discovery set: 3% increase, p-value = 0.0009; validation set: 2% increase, p-value = 0.01). Consistent results at four neighboring methylation probes and the strong negative correlation (rho = -0.93) with LINC00299 expression add plausibility to this result. CONCLUSION: Hypermethylation of LINC00299 in peripheral blood may constitute a useful circulating biomarker for TNBC.

Predicting Triple-Negative Breast Cancer Subtype Using Multiple Single Nucleotide Polymorphisms for Breast Cancer Risk and Several Variable Selection Methods.

INTRODUCTION: Studies of triple-negative breast cancer have recently been extending the inclusion criteria and incorporating additional molecular markers into the selection criteria, opening up scope for targeted therapies. The screening phases required for studies of this type are often prolonged, since the process of determining the molecular subtype and carrying out additional biomarker assessment is time-consuming. Parameters such as germline genotypes capable of predicting the molecular subtype before it becomes available from pathology might be helpful for treatment planning and optimizing the timing and cost of screening phases. This appears to be feasible, as rapid and low-cost genotyping methods are becoming increasingly available. The aim of this study was to identify single nucleotide polymorphisms (SNPs) for breast cancer risk capable of predicting triple negativity, in addition to clinical predictors, in breast cancer patients. METHODS: This cross-sectional observational study included 1271 women with invasive breast cancer who were treated at a university hospital. A total of 76 validated breast cancer risk SNPs were successfully genotyped. Univariate associations between each SNP and triple negativity were explored using logistic regression analyses. Several variable selection and regression techniques were applied to identify a set of SNPs that together improve the prediction of triple negativity in addition to the clinical predictors of age at diagnosis and body mass index (BMI). The most accurate prediction method was determined by cross-validation. RESULTS: The SNP rs10069690 (TERT, CLPTM1L) was the only significant SNP (corrected p = 0.02) after correction of p values for multiple testing in the univariate analyses. This SNP and three additional SNPs from the genes RAD51B, CCND1, and FGFR2 were selected for prediction of triple negativity. The addition of these SNPs to clinical predictors increased the cross-validated area under the curve (AUC) from 0.618 to 0.625. Age at diagnosis was the strongest predictor, stronger than any genetic characteristics. CONCLUSION: Prediction of triple-negative breast cancer can be improved if SNPs associated with breast cancer risk are added to a prediction rule based on age at diagnosis and BMI. This finding could be used for prescreening purposes in complex molecular therapy studies for triple-negative breast cancer.

SK4 channels modulate Ca2+ signalling and cell cycle progression in murine breast cancer.

Oncogenic signalling via Ca2+ -activated K+ channels of intermediate conductance (SK4, also known as KCa 3.1 or IK) has been implicated in different cancer entities including breast cancer. Yet, the role of endogenous SK4 channels for tumorigenesis is unclear. Herein, we generated SK4-negative tumours by crossing SK4-deficient (SK4 KO) mice to the polyoma middle T-antigen (PyMT) and epidermal growth factor receptor 2 (cNeu) breast cancer models in which oncogene expression is driven by the retroviral promoter MMTV. Survival parameters and tumour progression were studied in cancer-prone SK4 KO in comparison with wild-type (WT) mice and in a syngeneic orthotopic mouse model following transplantation of SK4-negative or WT tumour cells. SK4 activity was modulated by genetic or pharmacological means using the SK4 inhibitor TRAM-34 in order to establish the role of breast tumour SK4 for cell growth, electrophysiological signalling, and [Ca2+ ]i oscillations. Ablation of SK4 and TRAM-34 treatment reduced the SK4-generated current fraction, growth factor-dependent Ca2+ entry, cell cycle progression and the proliferation rate of MMTV-PyMT tumour cells. In vivo, PyMT oncogene-driven tumorigenesis was only marginally affected by the global lack of SK4, whereas tumour progression was significantly delayed after orthotopic implantation of MMTV-PyMT SK4 KO breast tumour cells. However, overall survival and progression-free survival time in the MMTV-cNeu mouse model were significantly extended in the absence of SK4. Collectively, our data from murine breast cancer models indicate that SK4 activity is crucial for cell cycle control. Thus, the modulation of this channel should be further investigated towards a potential improvement of existing antitumour strategies in human breast cancer.

Increased expression of miR-126 and miR-10a predict prolonged relapse-free time of primary oestrogen receptor-positive breast cancer following tamoxifen treatment.

BACKGROUND: Adjuvant tamoxifen is a valid treatment option for women with oestrogen receptor (ER)-positive breast cancer. However, up to 40% of patients experience distant or local recurrence or die. MicroRNAs have been suggested to be important prognosticators in breast cancer. This study aims to identify microRNAs with the potential to predict tamoxifen response. PATIENTS AND METHODS: We performed a global microRNA screen (1105 human microRNAs) in primary tumours of six matched pairs of postmenopausal, ER-positive breast cancer patients treated with tamoxifen, who were either recurrence free or had developed a recurrence (median follow up: 8.84 years; range: 1.28-12.7 years). Patients of this discovery set and the 81 patients of the validation set (median follow up: 8.64 years; range: 0.21-19.85 years) were treated at the Robert Bosch Hospital, Stuttgart, Germany, between 1986 and 2005. RESULTS: Out of the top 20 deregulated microRNAs (12 up-regulated, eight down-regulated) miR-126 (Hazard Ratio (HR) = 0.56, 95% confidence interval (CI): 0.38-0.83; Holm-adj. P = 0.022) and miR-10a (HR = 0.53, 95% CI: 0.33-0.85; Holm-adj. P = 0.031) were identified as significant predictors of tamoxifen outcome by multivariate Cox regression analysis in the independent validation set of 81 postmenopausal, ER-positive patients. Kaplan-Meier survival analyses based on cut-offs determined by receiver operating characteristics curves confirmed that a higher expression of miR-126 and miR-10a in the patients tumour was associated with longer relapse-free time (log-rank P = 0.037, P<0.0001, respectively). CONCLUSIONS: Our data suggest that miR-126 and miR-10a are independent predictors for tumour relapse in early postmenopausal breast cancer patients treated with adjuvant tamoxifen.

Omeprazole-induced acute interstitial nephritis is not related to CYP2C19 genotype or CYP2C19 phenotype.

AIM: Omeprazole-induced acute interstitial nephritis (OIAIN) is a rare adverse event. It is unknown if this is an idiosyncratic immune mediated reaction or if it relates to direct drug toxicity. Individuals who are homozygous for the variant alleles of CYP2C19 are poor metabolizers of omeprazole and have a greater exposure to the drug. The aim of this study was to determine the prevalence of the CYP2C19 poor metabolizer genotype and phenotype in patients with OIAIN. METHODS: Twenty patients were genotyped for the CYP2C19 variant alleles (2, 681G>A and 3, 636G>A) by RFLP-PCR analysis and eighteen phenotyped for CYP2C19 metabolizer status. RESULTS: The frequency of the CYP2C19 2 allelic variant was 12.5%, no 3 allelic variants were detected and no patient was a homozygous variant genotype. This was not different from the expected frequency. 33% of subjects were phenotypically CYP2C19 poor metabolizers. CONCLUSIONS: There was discordance between CYP2C19 genotype and phenotype. However, up to 45% of healthy elderly subjects have a poor metabolizer phenotype. Thus neither CYP2C19 poor metabolizer genotype nor phenotype is a risk factor for OIAIN.

Hydrolysis of dinitrobenzamide phosphate prodrugs: the role of alkaline phosphatase.

Phosphate prodrugs which undergo hydrolysis in vivo have been used to improve the solubility and pharmacokinetic properties of a number of drugs. Dinitrobenzamide mustards (DNBM) are examples of such drugs. We investigated the ability of purified alkaline phosphatase isoforms to dephosphorylate three DNBM phosphate prodrugs. In addition, the relative rate of dephosphorylation of these phosphate prodrugs in a number of tissues was determined. These phosphate prodrugs are indeed substrates for alkaline phosphatase, with time dependent formation of the hydrolysis product. Intestinal alkaline phosphatase (IAP) and placental alkaline phosphatase (PLAP) had the highest activity for these substrates and compound P2 was the most rapidly metabolised. Similarly, compound P2 had the shortest half life in mouse serum (t1/2 = 1.15 h) compared with P1 (t1/2 = 13.34 h) and P3 (t1/2 = 4.4 h). However, serum has very low dephosphorylase activity for these substrates compared with intestine and liver homogenates. In addition, there is little or no difference in the relative rate of dephosphorylation of each of the three compounds in mouse tissues in contrast to the pattern observed with purified alkaline phosphatase and mouse serum. Hence additional phosphatase enzymes may be involved in the metabolism of phosphate prodrugs in vivo.