Dr. Margarete Fischer-Bosch Institute of Clinical Pharmacology and University Tübingen, Stuttgart, Germany.
Citations 33
Supplementation of Tamoxifen with Low-Dose Endoxifen in Patients with Breast Cancer with Impaired Tamoxifen Metabolism (TAMENDOX): A Randomized Controlled Phase I/II Trial
Abstract Purpose :Tamoxifen undergoes bioactivation to its active metabolite (Z)-endoxifen, which blocks estrogen-dependent breast tumor growth at high potency. We tested the feasibility and safety of supplementing standard tamoxifen therapy with low-dose (Z)-endoxifen in patients with breast cancer with compromised tamoxifen bioactivation. Patients and Methods :We conducted a prospective, interventional, three group randomized trial including 235 patients with hormone receptor–positive breast cancer who received standard tamoxifen therapy (20 mg/day). Patients were stratified by CYP2D6 genotype (n = 78), defining poor, intermediate, and normal metabolizers, or by baseline (Z)-endoxifen plasma concentration (n = 78), defining ≤15, 15 to 25, and ≥25 nmol/L. Co-treatment with (Z)-endoxifen 3 and 1.5 mg/day or placebo was performed, respectively. A control group (n = 79) received placebo regardless of metabolizer phenotype. The primary endpoint was the number of patients with (Z)-endoxifen levels >32 nmol/L after 6 weeks of treatment. Adverse events were continuously monitored. Results: A higher proportion of patients in both intervention groups achieved target concentrations >32 nmol/L compared with control (P < 0.0001). At 3 mg (Z)-endoxifen supplementation, 92.3% of CYP2D6 poor metabolizer patients and all patients with baseline (Z)-endoxifen ≤15 nmol/L achieved the target concentration. At 1.5 mg (Z)-endoxifen supplementation, 88% of CYP2D6 intermediate metabolizer patients and 95% of patients with 15 to 25 nmol/L baseline (Z)-endoxifen levels achieved the target concentration. Similar proportions of patients receiving (Z)-endoxifen (6/80, 7.5%) or placebo (8/155, 5.2%) experienced grade 3 adverse events. Conclusions: Adding low-dose (Z)-endoxifen to standard tamoxifen is safe and provides a new approach to personalized antiestrogen treatment for patients with low endoxifen plasma levels.
Combined Associations of a Polygenic Risk Score and Classical Risk Factors With Breast Cancer Risk
Abstract We evaluated the joint associations between a new 313-variant PRS (PRS313) and questionnaire-based breast cancer risk factors for women of European ancestry, using 72 284 cases and 80 354 controls from the Breast Cancer Association Consortium. Interactions were evaluated using standard logistic regression and a newly developed case-only method for breast cancer risk overall and by estrogen receptor status. After accounting for multiple testing, we did not find evidence that per-standard deviation PRS313 odds ratio differed across strata defined by individual risk factors. Goodness-of-fit tests did not reject the assumption of a multiplicative model between PRS313 and each risk factor. Variation in projected absolute lifetime risk of breast cancer associated with classical risk factors was greater for women with higher genetic risk (PRS313 and family history) and, on average, 17.5% higher in the highest vs lowest deciles of genetic risk. These findings have implications for risk prevention for women at increased risk of breast cancer.
Transcriptome‐wide association study of breast cancer risk by estrogen‐receptor status
AbstractPrevious transcriptome‐wide association studies (TWAS) have identified breast cancer risk genes by integrating data from expression quantitative loci and genome‐wide association studies (GWAS), but analyses of breast cancer subtype‐specific associations have been limited. In this study, we conducted a TWAS using gene expression data from GTEx and summary statistics from the hitherto largest GWAS meta‐analysis conducted for breast cancer overall, and by estrogen receptor subtypes (ER+ and ER−). We further compared associations with ER+ and ER− subtypes, using a case‐only TWAS approach. We also conducted multigene conditional analyses in regions with multiple TWAS associations. Two genes, STXBP4 and HIST2H2BA, were specifically associated with ER+ but not with ER– breast cancer. We further identified 30 TWAS‐significant genes associated with overall breast cancer risk, including four that were not identified in previous studies. Conditional analyses identified single independent breast‐cancer gene in three of six regions harboring multiple TWAS‐significant genes. Our study provides new information on breast cancer genetics and biology, particularly about genomic differences between ER+ and ER− breast cancer.
Triple-Negative Breast Cancer Risk Genes Identified by Multigene Hereditary Cancer Panel Testing
AbstractEpidemiological, biological, and molecular data suggest links between endometriosis and endometrial cancer, with recent epidemiological studies providing evidence for an association between a previous diagnosis of endometriosis and risk of endometrial cancer. We used genetic data as an alternative approach to investigate shared biological etiology of these two diseases. Genetic correlation analysis of summary level statistics from genomewide association studies (GWAS) using LD Score regression revealed moderate but significant genetic correlation (rg = 0.23, P = 9.3 × 10−3), and SNP effect concordance analysis provided evidence for significant SNP pleiotropy (P = 6.0 × 10−3) and concordance in effect direction (P = 2.0 × 10−3) between the two diseases. Cross‐disease GWAS meta‐analysis highlighted 13 distinct loci associated at P ≤ 10−5 with both endometriosis and endometrial cancer, with one locus (SNP rs2475335) located within PTPRD associated at a genomewide significant level (P = 4.9 × 10−8, OR = 1.11, 95% CI = 1.07–1.15). PTPRD acts in the STAT3 pathway, which has been implicated in both endometriosis and endometrial cancer. This study demonstrates the value of cross‐disease genetic analysis to support epidemiological observations and to identify biological pathways of relevance to multiple diseases.
The BRCA2
c.68-7T > A variant is not pathogenic: A model for clinical calibration of spliceogenicity
Investigating the most likely causal variants identified by fine‐mapping analyses may improve the power to detect gene–environment interactions. We assessed the interplay between 70 single nucleotide polymorphisms identified by genetic fine‐scale mapping of susceptibility loci and 11 epidemiological breast cancer risk factors in relation to breast cancer. Analyses were conducted on up to 58,573 subjects (26,968 cases and 31,605 controls) from the Breast Cancer Association Consortium, in one of the largest studies of its kind. Analyses were carried out separately for estrogen receptor (ER) positive (ER+) and ER negative (ER–) disease. The Bayesian False Discovery Probability (BFDP) was computed to assess the noteworthiness of the results. Four potential gene–environment interactions were identified as noteworthy (BFDP < 0.80) when assuming a true prior interaction probability of 0.01. The strongest interaction result in relation to overall breast cancer risk was found between CFLAR‐rs7558475 and current smoking (ORint = 0.77, 95% CI: 0.67–0.88, pint = 1.8 × 10−4). The interaction with the strongest statistical evidence was found between 5q14‐rs7707921 and alcohol consumption (ORint =1.36, 95% CI: 1.16–1.59, pint = 1.9 × 10−5) in relation to ER– disease risk. The remaining two gene–environment interactions were also identified in relation to ER– breast cancer risk and were found between 3p21‐rs6796502 and age at menarche (ORint = 1.26, 95% CI: 1.12–1.43, pint =1.8 × 10−4) and between 8q23‐rs13267382 and age at first full‐term pregnancy (ORint = 0.89, 95% CI: 0.83–0.95, pint = 5.2 × 10−4). While these results do not suggest any strong gene–environment interactions, our results may still be useful to inform experimental studies. These may in turn, shed light on the potential interactions observed.
BRCA2
Hypomorphic Missense Variants Confer Moderate Risks of Breast Cancer