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Tamoxifen is widely used in adjuvant therapy for breast cancer patients, but up to one-third of patients recur within 15 years after surgery even with its regular use. Low plasma levels of (Z)-endoxifen, the most active tamoxifen metabolite, have been studied as a possible predictor of treatment failure. Here, we evaluated plasma (Z)-endoxifen as a predictor of response to adjuvant treatment in breast cancer patients. Methods: One hundred forty nine patients were selected from a prospective cohort of consecutive newly diagnosed breast cancer patients recruited at a national referral center for treatment of cancer in Curitiba, Southern Brazil. Inclusion criteria were breast cancer women on stage I - III, positive hormone receptor tumors, operable, undergoing or not (neo)adjuvant chemotherapy, and signed for adjuvant tamoxifen for at least five years. At diagnosis, peripheral blood samples were collected for CYP2D6 genotyping for *1 *2, *3, *4, *5, *6, *7, *8, *9, *10, *17, *29 and *41 and subsequent metabolic activity scores according to phenotypes assigned for each allele (poor metabolizer PM; intermediate, IM; extensive, EM and ultrarapid metabolizer, UM). After the tamoxifen initiation, patients were evaluated at months 3, 6, and 12 for adherence and drug interactions, and plasma (Z)-endoxifen quantification. They were followed from April 2014 to April 2019. The study's primary objective was to evaluate whether (Z)-endoxifen plasma levels predict early recurrence in patients on adjuvant tamoxifen. The secondary aim was to evaluate an association between (Z)-endoxifen levels and clinical and phenotypic CYP2D6 metabolism variables. A Cox model estimated hazard ratios (HR) comparing recurrence free survival (RFS) according to (Z)-endoxifen plasma levels. The survival was compared using the Kaplan-Meier method and the log-rank test. Results: The median follow-up period was 52.3 months and at that point, there were 20 recurrences of 149 patients. At 3 months there were no cases of low adherence to tamoxifen. The (Z)-endoxifen levels were established by quartiles, with the first lower quartile being used as a cutoff (14.72nM). High (Z)-endoxifen levels at 3 months (>14.72nM) were detected in 75.8% (n = 113) of cases and low levels (≤14.72nM) in 24.2% (n = 36). There was no statistically significant difference between the groups with low or high (Z)-endoxifen levels regarding clinical and pathological variables, but there was a higher CYP2D6 PM/IM frequency in the low (Z)-endoxifen levels group (p Citation Format: Thais Almeida, Werner Schroth, Jeanine Marie Nardin, Thomas Mürdter, Solane Picolotto, Reiner Hoppe, Jenifer Primon Kogin, Elisa Daniele Gaio, Angela Dasenbrock, Raquel Cristina Skrsypcsak, Lucia Noronha, Hiltrud Brauch, José Claudio Casali-da-Rocha. Endoxifen predicts early recurrence in breast cancer: A Brazilian prospective study [abstract]. In: Proceedings of the 2021 San Antonio Breast Cancer Symposium; 2021 Dec 7-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2022;82(4 Suppl):Abstract nr P1-07-08.

Supplementary Table 1. Sample Size of each participated study, by case-control status and genotype platform. Supplementary Table 2. Association between fourteen environmental factors and the risk of breast cancer. Supplementary Table 3. Interactions between genes and fourteen environmental factors.

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.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.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).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.Our study suggests a limited role of gene–environment interactions in breast cancer risk.

Funding and acknowledgements.

Quantile-Quantile plot (Q-Q plot) of the aMiSTi p-values for each set of the GxE interactions.

Evidence linking coding germline variants in breast cancer (BC)-susceptibility genes other than BRCA1, BRCA2, and CHEK2 with contralateral breast cancer (CBC) risk and breast cancer-specific survival (BCSS) is scarce. The aim of this study was to assess the association of protein-truncating variants (PTVs) and rare missense variants (MSVs) in nine known (ATM, BARD1, BRCA1, BRCA2, CHEK2, PALB2, RAD51C, RAD51D, and TP53) and 25 suspected BC-susceptibility genes with CBC risk and BCSS. Hazard ratios (HRs) and 95% confidence intervals (CIs) were estimated with Cox regression models. Analyses included 34,401 women of European ancestry diagnosed with BC, including 676 CBCs and 3,449 BC deaths; the median follow-up was 10.9 years. Subtype analyses were based on estrogen receptor (ER) status of the first BC. Combined PTVs and pathogenic/likely pathogenic MSVs in BRCA1, BRCA2, and TP53 and PTVs in CHEK2 and PALB2 were associated with increased CBC risk [HRs (95% CIs): 2.88 (1.70-4.87), 2.31 (1.39-3.85), 8.29 (2.53-27.21), 2.25 (1.55-3.27), and 2.67 (1.33-5.35), respectively]. The strongest evidence of association with BCSS was for PTVs and pathogenic/likely pathogenic MSVs in BRCA2 (ER-positive BC) and TP53 and PTVs in CHEK2 [HRs (95% CIs): 1.53 (1.13-2.07), 2.08 (0.95-4.57), and 1.39 (1.13-1.72), respectively, after adjusting for tumor characteristics and treatment]. HRs were essentially unchanged when censoring for CBC, suggesting that these associations are not completely explained by increased CBC risk, tumor characteristics, or treatment. There was limited evidence of associations of PTVs and/or rare MSVs with CBC risk or BCSS for the 25 suspected BC genes. The CBC findings are relevant to treatment decisions, follow-up, and screening after BC diagnosis.

We assessed the PREDICT v 2.2 for prognosis of breast cancer patients with pathogenic germline BRCA1 and BRCA2 variants, using follow-up data from 5453 BRCA1/2 carriers from the Consortium of Investigators of Modifiers of BRCA1/2 (CIMBA) and the Breast Cancer Association Consortium (BCAC). PREDICT for estrogen receptor (ER)-negative breast cancer had modest discrimination for BRCA1 carrier patients overall (Gönen & Heller unbiased concordance 0.65 in CIMBA, 0.64 in BCAC), but it distinguished clearly the high-mortality group from lower risk categories. In an analysis of low to high risk categories by PREDICT score percentiles, the observed mortality was consistently lower than the expected mortality, but the confidence intervals always included the calibration slope. Altogether, our results encourage the use of the PREDICT ER-negative model in management of breast cancer patients with germline BRCA1 variants. For the PREDICT ER-positive model, the discrimination was slightly lower in BRCA2 variant carriers (concordance 0.60 in CIMBA, 0.65 in BCAC). Especially, inclusion of the tumor grade distorted the prognostic estimates. The breast cancer mortality of BRCA2 carriers was under-estimated at the low end of the PREDICT score distribution, whereas at the high end, the mortality was over-estimated. These data suggest that BRCA2 status should also be taken into consideration with tumor characteristics, when estimating the prognosis of ER-positive breast cancer patients.

Background: It is not known whether modifiable lifestyle factors that predict survival after invasive breast cancer differ by subtype. Methods: We analyzed data for 121,435 women diagnosed with breast cancer from 67 studies in the Breast Cancer Association Consortium with 16,890 deaths (8,554 breast cancer specific) over 10 years. Cox regression was used to estimate associations between risk factors and 10-year all-cause mortality and breast cancer–specific mortality overall, by estrogen receptor (ER) status, and by intrinsic-like subtype. Results: There was no evidence of heterogeneous associations between risk factors and mortality by subtype (Padj > 0.30). The strongest associations were between all-cause mortality and BMI ≥30 versus 18.5–25 kg/m2 [HR (95% confidence interval (CI), 1.19 (1.06–1.34)]; current versus never smoking [1.37 (1.27–1.47)], high versus low physical activity [0.43 (0.21–0.86)], age ≥30 years versus 0– Conclusions: We confirm associations between modifiable lifestyle factors and 10-year all-cause mortality. There was no strong evidence that associations differed by ER status or intrinsic-like subtype. Impact: Given the large dataset and lack of evidence that associations between modifiable risk factors and 10-year mortality differed by subtype, these associations could be cautiously used in prognostication models to inform patient-centered care.

Background: 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. Methods: 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-8 as genome-wide significant, and p-values-5 as suggestive. Linkage disequilibrium (LD)-based clumping was performed to identify independent candidate variants.Results: 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-values5. The strongest evidence was found for rs4674019 (p-value=2.27x10-7), which showed genome-wide significant interaction (p-value=3.8x10-8) 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. Conclusions: 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.

Aim: Tamoxifen (TAM) resistance remains a clinical issue in breast cancer. The authors previously reported that 15-hydroxyprostaglandin dehydrogenase (HPGD) was significantly downregulated in tamoxifen-resistant (TAMr) breast cancer cell lines. Here, the authors investigated the relationship between HPGD expression, TAM resistance and prediction of outcome in breast cancer. Methods: HPGD overexpression and silencing studies were performed in isogenic TAMr and parental human breast cancer cell lines to establish the impact of HPGD expression on TAM resistance. HPGD expression and clinical outcome relationships were explored using immunohistochemistry and in silico analysis. Results: Restoration of HPGD expression and activity sensitised TAMr MCF-7 cells to TAM and 17β-oestradiol, whilst HPGD silencing in parental MCF-7 cells reduced TAM sensitivity. TAMr cells released more prostaglandin E2 (PGE2) than controls, which was reduced in TAMr cells stably transfected with HPGD. Exogenous PGE2 signalled through the EP4 receptor to reduce breast cancer cell sensitivity to TAM. Decreased HPGD expression was associated with decreased overall survival in ERα-positive breast cancer patients. Conclusions: HPGD downregulation in breast cancer is associated with reduced response to TAM therapy via PGE2-EP4 signalling and decreases patient survival. The data offer a potential target to develop combination therapies that may overcome acquired tamoxifen resistance.

Background and purpose Pore-forming α subunits of the voltage- and Ca2+ -activated K+ channel with large conductance (BKα) promote malignant phenotypes of breast tumour cells. Auxiliary subunits such as the leucine-rich repeat containing 26 (LRRC26) protein, also termed BKγ1, may be required to permit activation of BK currents at a depolarized resting membrane potential that frequently occur in non-excitable tumour cells. Experimental approach Anti-tumour effects of BKα loss were investigated in breast tumour-bearing MMTV-PyMT transgenic BKα knockout (KO) mice, primary MMTV-PyMT cell cultures, and in a syngeneic transplantation model of breast cancer derived from these cells. The therapeutic relevance of BK channels in the context of endocrine treatment was assessed in human breast cancer cell lines expressing either low (MCF-7) or high (MDA-MB-453) levels of BKα and BKγ1, as well as in BKα-negative MDA-MB-157. Key results BKα promoted breast cancer onset and overall survival in preclinical models. Conversely, lack of BKα and/or knockdown of BKγ1 attenuated proliferation of murine and human breast cancer cells in vitro. At low concentrations, tamoxifen and its major active metabolites stimulated proliferation of BKα/γ1-positive breast cancer cells, independent of the genomic signalling controlled by the oestrogen receptor. Finally, tamoxifen increased the relative survival time of BKα KO but not of wild-type tumour cell recipient mice. Conclusion and implications Breast cancer initiation, progression, and tamoxifen sensitivity depend on functional BK channels thereby providing a rationale for the future exploration of the oncogenic actions of BK channels in clinical outcomes with anti-oestrogen therapy.

One-third of early breast cancer patients with estrogen receptor (ER) positive tumors treated with the selective estrogen receptor modulator tamoxifen either relapse or die from the disease in the following decade. Improvement of tamoxifen efficacy requires a better knowledge of factors determining outcome of which the medication-taking behavior, i.e. adherence, is a strong suspect. Discontinuation and non-adherence to tamoxifen are frequent and result in increased mortality. Commonly used methods to assess drug adherence such as prescription-refill patterns infer that the medication is taken exactly as prescribed yet, partial adherence or actual use of the medication cannot be controlled. An objective surrogate of tamoxifen adherence is the monitoring of drug concentrations in the patients’ plasma including the parent drug and its active metabolite (Z)-endoxifen (endoxifen), however individual concentrations depend on pharmacogene polymorphisms particularly those of the liver enzyme cytochrome P450 2D6 (CYP2D6). Patients without CYP2D6 variants have normal enzyme function (extensive metabolizer, EM) and achieve high endoxifen concentrations compared to patients with variants conferring absent activity (poor metabolizer, PM) or reduced activity (intermediate metabolizer, IM) who have significantly lower plasma concentrations of the active metabolite. A putative threshold of 5.9 ng/mL endoxifen has been proposed suggesting that patients with endoxifen concentration above or below threshold have lower or higher risk for recurrence, assuming that low endoxifen exposure in the tumor likely results in incomplete inhibition of ER-dependent growth signaling. During tamoxifen treatment it is therefore important that patients achieve clinically relevant endoxifen levels while at the same time avoid confounders of which adherence is a prime candidate. To this end, we investigated patients’ ability to achieve relevant plasma concentrations during tamoxifen treatment in relation to their CYP2D6 metabolizer status and their tamoxifen adherence behavior. Our prospective study included 192 Brazilian breast cancer patients treated with 20 mg tamoxifen daily. Two-thirds of the patients were premenopausal. Plasma levels of tamoxifen and its metabolites were measured by LC-MS/MS at 3, 6 and 12 months of treatment. Adherence to tamoxifen was evaluated by the questionnaire-based Morisky medication adherence scale. CYP2D6 polymorphisms were determined by MALDI-TOF mass spectrometry and real-time PCR. Adherence to tamoxifen decreased from 74% at month 3 to 64% at month 12, and explained 47% of the variability of tamoxifen plasma concentrations (P Citation Format: Jose Claudio Casali da Rocha, Jeanine M Nardin, Werner Schroth, Thais A Almeida, Thomas Mürdter, Solange Picolotto, Evelyn CL Vendramini, Reiner Hoppe, Jenifer P Kogin, Diandra Miqueleto, Silvia DR Moraes, Matthias Schwab, Roberto F Pecoits-Filho, Hiltrud Brauch. The influences of adherence to tamoxifen and CYP2D6 pharmacogenetics on plasma concentrations of the active metabolite (Z)-endoxifen in breast cancer [abstract]. In: Proceedings of the 2019 San Antonio Breast Cancer Symposium; 2019 Dec 10-14; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2020;80(4 Suppl):Abstract nr P2-11-12.

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. 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. 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). 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. Our study suggests a limited role of gene–environment interactions in breast cancer risk.

Adherence to treatment and use of co-medication, but also molecular factors such as CYP2D6 genotype, affect tamoxifen metabolism, with consequences for early breast cancer prognosis. In a prospective study of 149 tamoxifen-treated early-stage breast cancer patients from Brazil followed up for 5 years, we investigated the association between the active tamoxifen metabolite (Z)-endoxifen at 3 months and event-free survival (EFS) adjusted for clinico-pathological factors. Twenty-five patients (16.8%) had recurred or died at a median follow-up of 52.3 months. When we applied a putative 15 nM threshold used in previous independent studies, (Z)-endoxifen levels below the threshold showed an association with shorter EFS in univariate analysis (p = 0.045) and after adjustment for stage (HR 2.52; 95% CI 1.13–5.65; p = 0.024). However, modeling of plasma concentrations with splines instead of dichotomization did not verify a significant association with EFS (univariate analysis: p = 0.158; adjusted for stage: p = 0.117). Hence, in our small exploratory study, the link between impaired tamoxifen metabolism and early breast cancer recurrence could not be unanimously demonstrated. This inconsistency justifies larger modeling studies backed up by mechanistic pharmacodynamic analyses to shed new light on this suspected association and the stipulation of an appropriate predictive (Z)-endoxifen threshold.

Objective: Adherence to treatment and use of co-medication, molecular factors such as CYP2D6 genotype affect tamoxifen metabolism with consequences for early breast cancer (BC) prognosis. CYP2D6 polymorphisms have been promoted as potential biomarkers, yet they only partially explain the variability of plasma (Z)-endoxifen concentrations. The objective of this study was to evaluate whether plasma (Z)-endoxifen levels predicted early BC events (recurrence or death) within 5 years in patients receiving adjuvant tamoxifen treatment. The secondary aim was to evaluate whether (Z)-endoxifen levels were associated with clinical, pathological, and phenotypic CYP2D6 metabolism variables. Methods: In a prospective study on 149 tamoxifen-treated early-stage BC patients from Brazil followed up for 5 years, we investigated the association between the active tamoxifen metabolite (Z)-endoxifen at 3 months and event-free survival (EFS) adjusted for clinicopathological factors. We apply this approach to patients from a Brazilian prospective cohort (Tamoxifen Adjuvant Interferers Study) Results: In all, 25 (16.8%) patients had recurred or died at a median follow-up of 52.3 months. When we applied a putative 15 nM threshold used in previous independent studies, (Z)-endoxifen levels below the threshold showed an association with shorter EFS in an univariate analysis (p=0.045) and after adjustment for stage (HR 2.52; 95%CI 1.13–5.65; p=0.024). However, modeling of plasma concentrations with splines instead of dichotomization did not verify a significant association with EFS (univariate analysis: p=0.158; adjusted for stage: p=0.117). Hence, in this small exploratory study, the link between impaired tamoxifen metabolism and early BC recurrence could not be unanimously demonstrated. This inconsistency justifies larger modeling studies backed up by mechanistic pharmacodynamic analyses to shed new light on this suspected association and the stipulation of an appropriate predictive (Z)-endoxifen threshold. Conclusion: As expected, significant associations with CYP2D6 metabolism phenotypes were detected. In individual and grouped (PM+IM vs. NM+UM) comparisons, PM and IM phenotypes had lower median (Z)-endoxifen levels (7.7 and 16.3 nM, respectively) than patients with NM or UM phenotypes (27.6 and 38.0 nM, respectively; p

BACKGROUNDProtein truncating variants in ATM, BRCA1, BRCA2, CHEK2 and PALB2 are associated with increased breast cancer risk, but risks associated with missense variants in these genes are uncertain.METHODSCombining 59,639 breast cancer cases and 53,165 controls, we sampled training (80%) and validation (20%) sets to analyze rare missense variants in ATM (1,146 training variants), BRCA1 (644), BRCA2 (1,425), CHEK2 (325) and PALB2 (472). We evaluated breast cancer risks according to five in-silico prediction-of-deleteriousness algorithms, functional protein domain, and frequency, using logistic regression models and also mixture models in which a subset of variants was assumed to be risk-associated.RESULTSThe most predictive in-silico algorithms were Helix (BRCA1, BRCA2 and CHEK2) and CADD (ATM). Increased risks appeared restricted to functional protein domains for ATM (FAT and PIK domains) and BRCA1 (RING and BRCT domains). For ATM, BRCA1 and BRCA2, data were compatible with small subsets (approximately 7%, 2% and 0.6%, respectively) of rare missense variants giving similar risk to those of protein truncating variants in the same gene. For CHEK2, data were more consistent with a large fraction (approximately 60%) of rare missense variants giving a lower risk (OR 1.75, 95% CI (1.47-2.08)) than CHEK2 protein truncating variants. There was little evidence for an association with risk for missense variants in PALB2. The best fitting models were well calibrated in the validation set.CONCLUSIONSThese results will inform risk prediction models and the selection of candidate variants for functional assays, and could contribute to the clinical reporting of gene panel testing for breast cancer susceptibility.

Tamoxifen efficacy in breast cancer is suspected to depend on adherence and intact drug metabolism. We evaluated the role of adherence behavior and pharmacogenetics on the formation rate of (Z)-endoxifen. In 192 Brazilian patients, we assessed plasma levels of tamoxifen and its metabolites at 3, 6, and 12 months of treatment (liquid-chromatography tandem mass spectrometry), adherence behavior (Morisky, Green, and Levine medication adherence scale), and cytochrome P450 2D6 (CYP2D6) and other pharmacogene polymorphisms (matrix-assisted laser-desorption-ionization time of flight) mass spectrometry, real-time polymerase chain reaction). Adherence explained 47% of the variability of tamoxifen plasma concentrations (P

BackgroundCopy number variants (CNVs) are pervasive in the human genome but potential disease associations with rare CNVs have not been comprehensively assessed in large datasets. We analysed rare CNVs in genes and non-coding regions for 86,788 breast cancer cases and 76,122 controls of European ancestry with genome-wide array data.ResultsGene burden tests detected the strongest association for deletions in BRCA1 (P= 3.7E-18). Nine other genes were associated with a p-value < 0.01 including known susceptibility genes CHEK2 (P= 0.0008), ATM (P= 0.002) and BRCA2 (P= 0.008). Outside the known genes we detected associations with p-values < 0.001 for either overall or subtype-specific breast cancer at nine deletion regions and four duplication regions. Three of the deletion regions were in established common susceptibility loci.ConclusionsThis is the first genome-wide analysis of rare CNVs in a large breast cancer case-control dataset. We detected associations with exonic deletions in established breast cancer susceptibility genes. We also detected suggestive associations with non-coding CNVs in known and novel loci with large effects sizes. Larger sample sizes will be required to reach robust levels of statistical significance.

Simple Summary Breast cancer is the most common cancer in females worldwide. To date, many gene-environment interaction (GxE) studies have been conducted to better understand how genetic factors combine with environmental factors to influence risk. However, previous studies have not found or found only a few interactions by using SNPs which were discovered from genome-wide association studies and have been conducted, for the most part, within European populations. In this study, we focused on estrogen-related lifestyle factors that have been identified for breast cancer, including several well-established reproductive factors that are mediated by hormonal mechanisms. We aimed to examine whether there are any gene and environmental factor interactions related to estrogen exposure or metabolism using a candidate approach in Korean women. We found two interactions in this study, although they were not replicated in the independent large consortium data. These findings suggest specificity in Koreans for breast cancer risk. In this study we aim to examine gene-environment interactions (GxEs) between genes involved with estrogen metabolism and environmental factors related to estrogen exposure. GxE analyses were conducted with 1970 Korean breast cancer cases and 2052 controls in the case-control study, the Seoul Breast Cancer Study (SEBCS). A total of 11,555 SNPs from the 137 candidate genes were included in the GxE analyses with eight established environmental factors. A replication test was conducted by using an independent population from the Breast Cancer Association Consortium (BCAC), with 62,485 Europeans and 9047 Asians. The GxE tests were performed by using two-step methods in GxEScan software. Two interactions were found in the SEBCS. The first interaction was shown between rs13035764 of NCOA1 and age at menarche in the GE|2df model (p-2df = 1.2 x 10(-3)). The age at menarche before 14 years old was associated with the high risk of breast cancer, and the risk was higher when subjects had homozygous minor allele G. The second GxE was shown between rs851998 near ESR1 and height in the GE|2df model (p-2df = 1.1 x 10(-4)). Height taller than 160 cm was associated with a high risk of breast cancer, and the risk increased when the minor allele was added. The findings were not replicated in the BCAC. These results would suggest specificity in Koreans for breast cancer risk.

Purpose: Patients with estrogen receptor– and/or progesterone receptor–positive, early breast cancer benefit from hormonal treatment, yet high global death burdens due to high prevalence and long-term recurrence risk call for biomarkers to guide additional treatment approaches. Experimental Design: From a prospective, observational study of postmenopausal early breast cancer patients treated with tamoxifen or aromatase inhibitors, gene expression analyses of 612 tumors was performed using the NanoString Breast Cancer 360 panel to interrogate 23 breast cancer pathways. Candidate signatures associated with disease subtype and event-free survival (EFS) were obtained by cluster analysis, Cox modeling, and conditional inference trees, and were independently tested in 613 patients from BreastMark. Tumor-infiltrating lymphocytes (TIL) were assessed on tissue sections, and mutational burden was assessed in 36 tumors by whole-exome sequencing. Results: PAM50-derived classification distinguished lower-risk (Luminal A) from higher-risk subtypes (Luminal B, P = 0.04; HER2, P = 0.006; Basal, P = 0.008). In higher-risk patients, shorter EFS was associated with low androgen receptor [HR = 3.61; 95% confidence interval (CI), 1.72–7.56; P = 0.001] or high BRCAness signature expression (HR = 3.58; 95% CI, 1.19–10.7; P = 0.023). BRCAness was independently confirmed as a predictor of shorter EFS (HR = 2.64; 95% CI, 1.31–5.34; P = 0.007). About 13%–15% of patients, enriched for high-grade, higher-risk subtypes (P ≤ 0.0001), had strong expression of the Tumor Inflammation Signature (TIS) suggestive of an inhibited antitumor immune response. TIS scores were strongly associated with TIL numbers (P < 1e-30) but not with tumor mutation status. Conclusions: BRCA-related DNA repair deficiency and suppressed tumor immune responses may be clinically relevant predictors of endocrine therapy complementing treatment options in subgroups of hormone-sensitive early breast cancer.

Oncogenic signalling via Ca2+-activated K+ channels of intermediate conductance (SK4, also known as KCa3.1 or IK) has been implicated in different cancer entities including breast cancer. Yet, the role of endogenous SK4 channels for tumourigenesis 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 promotor MMTV. Survival parameters and tumour progression were studied in cancer-prone SK4 KO in comparison to wildtype (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 tumourigenesis 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 anti-tumour strategies in human breast cancer.

50 Years after the generation of the most studied human breast cancer cell line, MCF-7, many research results fundamentally changed patient outcomes for the better. The mortality of breast cancer in women has decreased significantly, especially in the last 30 years. But the total number of deaths is rising again in the last ten years. Considering that breast cancer is the most common cancer in women and the second most common cancer overall, with incidences of 24,2% and 11,6%, respectively, total numbers of new cases are in the millions every year. First line drugs for the treatment of breast cancer often target microtubules (e.g. Vinblastine and Paclitaxel) or induce DNA damage (e.g. Carboplatin and Cisplatin (CisPt)). In addition to these classic therapeutic drugs new compounds that specifically target cancer-driving molecular alterations have been developed. Among these is the group of BH3-mimetics. The efficacy of several BH3-mimetics is investigated in numerous clinical trials while the BCL-2 specific inhibitor ABT-199 (Venetoclax) is already approved for clinical application in chronic lymphatic leukemia (CLL), acute myeloid leukemia (AML) and small lymphocytic lymphoma (SLL). BH3-mimetics target the apoptosis machinery by interacting with anti-apoptotic Bcl-2 proteins, mimicking the function of pro-apoptotic BH3-only proteins. In turn, the pro-apoptotic potential of pore-forming BCL-2 effectors BAX, BAK and BOK is released inducing mitochondrial outer membrane permeabilization and cell death. Recently we reported synergistic cell death induction by ABT-199 in combination with the proteasome inhibitor Bortezomib (BOZ) in soft tissue sarcoma (STS) cells. ABT-199 and BOZ induce accumulation of BOK and the BH3-only protein NOXA (Muenchow et al. 2020). Here, we combined ABT-199, CisPt and Nutlin-3 in breast cancer cell lines that differ in expression of the estrogen receptor (ER) and p53 activity. Similar to the results in STS cells synergistic induction of apoptotic cell death was observed by FACS analysis of the mitochondrial membrane potential (TMRM) and exposure of phosphatidyl serine (Annexin-V). Western blot analysis revealed that ABT-199 induced accumulation of NOXA and MCL-1, irrespective of the ER status or p53 mutation. Simultaneous treatment with ABT-199 and CisPt or Nutlin-3 further increased expression of NOXA and MCL-1. Interestingly, qRT-PCR revealed enhanced expression of NOXA and MCL-1 mRNA in ABT-199 treated cells indicating transcriptional regulation. However, transcriptional induction of NOXA was also detected independent of p53 activity. Thus, combined therapeutic approaches using CisPt and ABT-199 should be effective irrespective of ER and p53 expression. Nevertheless, in p53 proficient tumors Nutlins might increase therapeutic efficacy. Citation Format: Benjamin Schaefer, Sandra Weller, Tobias Beigl, Kathrin Boepple, Reiner Hoppe, Klaus Schulze-Osthoff, Hans-Georg Kopp, Walter E. Aulitzky, Frank Essmann. Synergistic cell death induction in breast cancer cell lines by combining ABT-199 and cisplatin irrespective of estrogen receptor and p53 expression [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 1946.

Disruption of estrogen signaling with tamoxifen or aromatase inhibitors (AI) is the clinical standard for the treatment of estrogen receptor-positive breast cancer, yet resistance to antiestrogen therapies is inevitable. The long-term E2-deprived breast cancer models MCF-7:5C and MCF-7:2A mimic AI resistance and moreover are vulnerable to E2-induced apoptosis due to the reconfiguration of their survival signaling. E2-induced apoptosis which results from the accumulation of endoplasmic reticulum (ER), oxidative, and inflammatory stresses, is a new paradigm to subvert endocrine resistance, with sensors of the unfolded protein response (UPR) being important mediators of ER stress (Ariazi et al. 2011; Fan et al. 2013, 2015). Here we asked whether epigenetic modifications may play a role in this and investigated genome-wide changes of 5C and 2A DNA methylation patterns that occurred during E2 stimulation during a 72h time course with WS8 cells as a reference. Methylation patterns were established using the Illumina Infinium HumanMethylation450 BeadChip (Service XS, Leiden, NL), and raw intensities were normalized and filtered using the bioconductor minfi package. A linear model (bioconductor limma package) has been built to detect differentially methylated CpGs. F-statistics were calculated by empirical Bayes moderation of standard errors with "trend" and "robust" set “on”. We also performed whole-genome bisulfite sequencing (WGBS) in untreated cells using the Illumina HiSeq platform (GATC Biotech, Konstanz, DE) to obtain maximum baseline CpG coverage. Trimmed WGBS reads were aligned to the hg38 genome (Bismarck, PMC3102221), duplicates removed, and methylation levels extracted with MethylDackel (https://github.com/dpryan79/MethylDackel) with a 3x coverage threshold (Wreczycka et al. 2017). Raw methylation levels were smoothed and differential methylation called using the bsseq package (Hansen et al. 2012). At baseline, WGBS-derived profiles showed a 2-fold higher degree of hypomethylation (beta Citation Format: Reiner Hoppe, Siarhei Kandabarau, Ping Fan, Stefan Winter, Balkees Abderrahman, Heather Cunliffe, Werner Schroth, V. Craig Jordan, Hiltrud B. Brauch. Genome-wide DNA methylation changes in AI-resistant breast cancer models during E2-treatment [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 144.

Sophisticated wave propagation models are required for computing the 5G radio coverage as well as for the 5G radio channel analysis. The scenarios of interest range from large rural or suburban areas to dense urban city centers, and even complex indoor scenarios are relevant. For the detailed network planning the overall signal and interference situation needs to be computed. The ray-optical wave propagation models in the WinProp software have been extended to account for the specificities of the 5G frequency bands. Comparisons against various measurement campaigns verify the capability of the WinProp models to correctly predict the propagation characteristics also at mm wave bands.

The WinProp software has been added to the Electromagnetic Solver FEKO. WinProp includes sophisticated ray-optical and empirical wave propagation models for computing the radio coverage as well as for the radio channel analysis. The supported scenarios range from large rural or suburban areas to dense urban city centers, and even complex indoor scenarios can be predicted. For the detailed network planning modules for almost all air interfaces (incl. LTE, WLAN) are available, which compute the overall signal and interference situation by superposing the contributions from multiple transmitting sites.

Estrogen (ER) and/or progesterone (PR) receptor-positive, early breast cancer benefits from targeted therapy via long-term estrogen deprivation. Valid treatment options include the selective ER modulator tamoxifen (TAM) that interferes with estrogen-binding at the ER, and aromatase inhibitors (AI) that block the enzyme aromatase to prevent the conversion of androgens to estrogen. Both treatment principles are in clinical use however fail in about one third of the patients. The choice of endocrine treatment is currently not well supported by predictive tumor markers. Gene expression signatures covering critical breast cancer pathways were tested to predict TAM and AI associated outcomes in a prospectively collected postmenopausal, hormone-receptor positive, early breast cancer cohort (IKP211; 1200 patients, median follow up 5.5 years; DRKS00000605). RNA was extracted from formalin-fixed paraffin-embedded tumor sections of 631 patients and subjected to gene expression profiling with 770 genes across 23 key breast cancer pathways/processes (NanoString®BC360 panel) including the prognostic PAM50 signature for intrinsic subtype classification. Signatures were measured with the nCounter Digital Analyzer system (Nanostring) and revealed 60% Luminal A, 31% Luminal B, 6% HER2 enriched and 3% Basal-like tumor subtypes. Predefined signature scores (Nanostring) or single gene expression scores were analyzed in relation to breast cancer recurrence-free survival (EFS). PAM50 subtype designation and its derived Genomic Risk Score (ROR) were strongly associated with EFS of patients treated with AI (Log Rank P Citation Format: Werner Schroth, Reiner Hoppe, Florian Büttner, Stefan Winter, Siarhei Kandabarau, Jörg Kumbrink, Heather A. Brauer, Peter Fritz, Matthias Schwab, Thomas Mürdter, Hiltrud Brauch. Gene expression signatures for the prediction of endocrine treatment outcome in early-stage luminal breast cancer patients [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 464.

One third of breast cancer patients treated with Aromatase Inhibitors (AI) or Tamoxifen acquire resistance leading to disease recurrence and death. The clinically observed AI resistance is mimicked by in vitro models MCF-7:5C and MCF-7:2A that are susceptible to apoptosis upon E2-treatment. These models have been instrumental to the current understanding of underlying mechanisms such as the reconfiguration of survival signaling, alterations of stress-related pathways (Ariazi et al. 2011; Fan et al. 2013, 2015), and changes in miRNA expression profiles (Hoppe et al. 2016). How the model phenotypes relate to a specific genomic background is poorly understood. In order to identify somatic variants indicative of AI resistance and potentially useful as novel therapeutic targets we performed NGS analyses of the 5C and 2A clones compared to the non-resistant WS8 and MCF-7 (ATCC). Whole genome/exome libraries were sequenced on Illumina HiSeq/NovaSeq platforms, respectively. Previously we reported first results from a preliminary analysis of gains and losses of variants in both resistant derivatives (Hoppe at al. AACR 2018). Here we report an updated analysis of raw reads trimmed and aligned to GRCh38 reference using BWAkit v 0.7.15. Duplicates were removed by Picard MarkDuplicates. Base quality scores were recalibrated using GATK4 BQSR. WGS and WES alignments were merged and tested for somatic variants using GATK4 Mutect2 (Tumor-only mode) with population variation data from gnomAD as a germline source. Called and filtered variants were uploaded to IVA for functional and clinical annotation. Copy number segments were modeled using both read- and allele-counts from WGS alignments by Gaussian-kernel binary-segmentation algorithm applied in GATK4 ModelSegments tool. To interpret copy number events causative for LOH we recovered germline variants and annotated CNVs that led to loss of the corresponding wild-type allele. In line with the COSMIC database we confirmed 461 mutated loci of which 228 were lost in both resistant derivatives. Examples of 5C-specific coding mutations classified as pathogenic include splice site alterations (i.e. SEMA3A), frameshifts (i.e. ARID1A), and stop gains (i.e. CACNA1S, CDH2, NOTCH4). 2A-specific mutations include for example a stop gain affecting ADGRV1. Copy number variation analyses revealed that both resistance models share prominent genetic defects such as amplified regions at Chr6q25.1 and Chr21q22.2. A 5C-specific aberration is a large Chr18 deletion affecting most of the q-arm, and a 2A-specific aberration is the amplification of most parts of Chr6q23.3-q24.3. We will present the status of this currently ongoing comparative genome analysis of AI resistance models and discuss the putative effects of homozygous mutations at loci with copy number aberrations within the context of AI resistance. Citation Format: Reiner Hoppe, Siarhei Kandabarau, Ping Fan, V. Craig Jordan, Heather Cunliffe, Hiltrud B. Brauch. Comparative whole genome analyses of breast cancer aromatase inhibitor resistance models [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 1689.

// Reiner Hoppe 1,2 , Ping Fan 3 , Florian Buttner 1,2,4 , Stefan Winter 1,2 , Amit K. Tyagi 3 , Heather Cunliffe 5 , V. Craig Jordan 3 and Hiltrud Brauch 1,2,4 1 Dr. Margarete Fischer-Bosch-Institute of Clinical Pharmacology, Stuttgart, Germany 2 University of Tubingen, Tubingen, Germany 3 Department of Breast Medical Oncology, MD Anderson Cancer Center, University of Texas, Houston, TX, USA 4 German Cancer Consortium (DKTK) and German Cancer Research Center (DKFZ), Heidelberg, Germany 5 Department of Pathology, Dunedin School of Medicine, University of Otago, Dunedin, New Zealand Correspondence to: Hiltrud Brauch, email: // Keywords : breast cancer, AI resistance, microRNA profiling, pathway enrichment, E 2 -inducible apoptosis Received : March 23, 2016 Accepted : September 02, 2016 Published : September 17, 2016 Abstract Aromatase inhibitor (AI) resistance during breast cancer treatment is mimicked by MCF-7:5C (5C) and MCF-7:2A (2A) cell lines that grow spontaneously. Survival signaling is reconfigured but cells are vulnerable to estradiol (E 2 )-inducible apoptosis. These model systems have alterations of stress related pathways including the accumulation of endoplasmic reticulum, oxidative, and inflammatory stress that occur prior to E 2 -induced apoptosis. We investigated miRNA expression profiles of 5C and 2A to characterize their AI resistance phenotypes. Affymetrix GeneChip miRNA2.0 arrays identified 184 miRNAs differentially expressed in 2A and 5C compared to E 2 -free wild-type MCF-7:WS8. In 5C, 34 miRNAs of the DLK1-DIO3 locus and miR-31 were overexpressed, whereas miR-222 was low. TCGA data revealed poor and favorable overall survival for low miR-31 and miR-222 levels, respectively (HR=3.0, 95% CI:1.9-4.8; HR=0.3, 95% CI:0.1-0.6). Targets of deregulated miRNAs were identified using CLIP-confirmed TargetScan predictions. KEGG enrichment analyses for 5C- and 2A-specific target gene sets revealed pathways associated with cell proliferation including insulin, mTOR, and ErbB signaling as well as immune response and metabolism. Key genes overrepresented in 5C- and 2A-specific pathway interaction networks including EGFR , IGF1R and PIK3R1 had lower protein levels in 5C compared to 2A and were found to be differentially modulated by respective miRNA sets. Distinct up-regulated miRNAs from the DLK1-DIO3 locus may cause these attenuative effects as they are predicted to interact with corresponding 3’ untranslated regions. These new miRNA profiles become an important regulatory database to explore E 2 -induced apoptotic mechanisms of clinical relevance for the treatment of resistant breast cancer.

Acquired endocrine resistance is a severe barrier in the anti-hormonal treatment of breast cancer and is responsible for its failure in about half of the treated patients. In vitro models of long-term estrogen deprived breast cancer cells serve as laboratory tools to explore new therapeutic strategies. The models MCF-7:5C and MCF-7:2A mimic clinical AI resistance but regress with E2 due to the reconfiguration of survival signaling known as E2-inducible apoptosis (5C rapid, 2A delayed reaction). Alterations of stress related pathways including the accumulation of endoplasmic reticulum stress, oxidative stress, and inflammatory stress that occur prior to E2-induced apoptosis (Ariazi et al. 2011; Fan et al. 2013, 2015; Sweeney et al. 2014) and specific miRNA expression profiles (Hoppe et al Oncotarget 2016) have been linked with these resistance and E2-inducible apoptosis phenotypes. Little is known on their underlying genetic variability. Here we compare the mutational profiles of 5C and 2A clones with those of the estradiol stimulated growth sensitive MCF-7:WS8 and standard MCF-7 (ATCC) cells. Whole genome libraries were sequenced on the Illumina HiSeq platform (2x150bp reads). Alignments were manually inspected (bcftools mpileup) to avoid false negative variant calling in poorly ( Citation Format: Reiner Hoppe, Siarhei Kandabarau, Ping Fan, V Craig Jordan, Hiltrud B. Brauch. Evolving genomes of breast cancer aromatase inhibitor resistance models [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 3432.

Long-term estrogen deprivation with tamoxifen or aromatase inhibitors (AI) is the basic principle of endocrine treatment of ER-positive breast cancer. Acquired resistance is however a major obstacle in treatment success. Based on clinical observations and in vitro as well as animal in vivo experiments it has been suggested that tumor cell clones evolve over time and become vulnerable to E2-induced apoptosis, thereby potentially providing a promising second line treatment option. In vitro, this vulnerability is mimicked in the AI-resistant breast cancer models MCF-7:5C and MCF-7:2A, which during long-term E2-deprivation reconfigure their survival signaling including endoplasmic reticulum, oxidative and inflammatory stress related pathways. E2-stimulation of these cells initiates an unfolded protein response which in turn triggers apoptosis through the intrinsic and subsequently extrinsic pathway (Jordan VC 2015). Recently, we identified miRNA profiles matching the biology of AI resistance and vulnerability to E2-induced apoptosis (Hoppe R et al. 2016). Here we investigate the modulatory role of miRNAs in E2-induced apoptosis through the identification of their global expression changes in E2-stimulated 5C and 2A models compared to MCF-7:WS8 reference. Each cell line was treated with 10-9 M E2 or vehicle over a 72h time course (6, 12, 24, 72 h). miRNA profiles were generated using Affymetrix GeneChip miRNA2.0 arrays. At each time point relative miRNA expression changes (E2/control) were evaluated resulting in a total of 72 (5C), 104 (2A) and 94 (WS8) differentially expressed miRNAs (FC > 1.5 or < 1/1.5, Pt-test < 0.05). Differential expression analyses between consecutive time points revealed 16 (5C), 43 (2A) and 27 (WS8) miRNAs (maximum absolute FC difference > 1.5, PF-test < 0.05). Differential area under the curve (dAUC) analyses at 6-72, 6-24, and 24-72 h mined the overall, early, and late-responding miRNAs of the different phenotypes (Ppermutation test < 0.05). Representative early down-regulated miRNA candidates potentially modulating E2-induced apoptosis in 5C cells are miR-543 and miR-432 of the DLK1-DIO3 locus on Chr. 14q32.31. Late responding up-regulated miRNA candidates are miR-150* and miR-149* the low expression of which in tumor tissues registered in The Cancer Genome Atlas (miRNA-Seq v. 3.1.17.0) was associated with worse outcome in all PAM50 breast cancer subtypes and Lum B, respectively (HR = 2.1, 95% CI: 1.4-3.2; P = 0.00017; HR = 6.8, 95% CI: 1.5-3.0; P = 0.0036). We are currently in the process to subject respective miRNA sets to functional enrichment analyses (KEGG, GO) and to correlate E2-responsive miRNA candidates with respective transcriptome signatures. In summary, we will present miRNAs matching to the biological processes inherent to E2-induced apoptosis. These may serve as potential targets for the amplification of the apoptotic trigger upon E2-treatment. Citation Format: Reiner Hoppe, Ping Fan, Stefan Winter, Florian Büttner, V. Craig Jordan, Hiltrud B. Brauch. Estrogen-responsive miRNAs as modulators of E2-induced apoptosis in AI-resistant breast cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 474. doi:10.1158/1538-7445.AM2017-474

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 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.