Kaikki aineistot
Lisää
Background: An increased risk of breast cancer is associated with high serum concentrations of oestradiol and testosterone in postmenopausal women, but little is known about how these hormones affect response to endocrine therapy for breast cancer prevention or treatment. We aimed to assess the effects of serum oestradiol and testosterone concentrations on the efficacy of the aromatase inhibitor anastrozole for the prevention of breast cancer in postmenopausal women at high risk. Methods: In this case-control study we used data from the IBIS-II prevention trial, a randomised, controlled, double-blind trial in postmenopausal women aged 40–70 years at high risk of breast cancer, conducted in 153 breast cancer treatment centres across 18 countries. In the trial, women were randomly assigned (1:1) to receive anastrozole (1 mg/day, orally) or placebo daily for 5 years. In this pre-planned case-control study, the primary analysis was the effect of the baseline oestradiol to sex hormone binding globulin (SHBG) ratio (oestradiol–SHBG ratio) on the development of all breast cancers, including ductal carcinoma in situ (the primary endpoint in the trial). Cases were participants in whom breast cancer was reported after trial entry and until the cutoff on Oct 22, 2019, and who had valid blood samples and no use of hormone replacement therapy within 3 months of trial entry or during the trial. For each case, two controls without breast cancer were selected at random, matched on treatment group, age (within 2 years), and follow-up time (at least that of the matching case). For each treatment group, we applied a multinominal logistic regression likelihood-ratio trend test to assess what change in the proportion of cases was associated with a one-quartile change in hormone ratio. Controls were used only to determine quartile cutoffs. Profile likelihood 95% CIs were used to indicate the precision of estimates. A secondary analysis also investigated the effect of the baseline testosterone–SHBG ratio on breast cancer development. We also assessed relative benefit of anastrozole versus placebo (calculated as 1 – the ratio of breast cancer cases in the anastrozole group to cases in the placebo group). The trial was registered with ISRCTN (number ISRCTN31488319) and completed recruitment on Jan 31, 2012, but long-term follow-up is ongoing. Findings: 3864 women were recruited into the trial between Feb 2, 2003, and Jan 31, 2012, and randomly assigned to receive anastrozole (n=1920) or placebo (n=1944). Median follow-up time was 131 months (IQR 106–156), during which 85 (4·4%) cases of breast cancer in the anastrozole group and 165 (8·5%) in the placebo group were identified. No data on gender, race, or ethnicity were collected. After exclusions, the case-control study included 212 participants from the anastrozole group (72 cases, 140 controls) and 416 from the placebo group (142 cases, 274 controls). A trend of increasing breast cancer risk with increasing oestradiol–SHBG ratio was found in the placebo group (trend per quartile 1·25 [95% CI 1·08 to 1·45], p=0·0033), but not in the anastrozole group (1·06 [0·86 to 1·30], p=0·60). A weaker effect was seen for the testosterone–SHBG ratio in the placebo group (trend 1·21 [1·05 to 1·41], p=0·011), but again not in the anastrozole group (trend 1·18 [0·96 to 1·46], p=0·11). A relative benefit of anastrozole was seen in quartile 2 (0·55 [95% CI 0·13 to 0·78]), quartile 3 (0·54 [0·22 to 0·74], and quartile 4 (0·56 [0·23 to 0·76]) of oestradiol–SHBG ratio, but not in quartile 1 (0·18 [–0·60 to 0·59]). Interpretation: These results suggest that serum hormones should be measured more routinely and integrated into risk management decisions. Measuring serum hormone concentrations is inexpensive and might help clinicians differentiate which women will benefit most from an aromatase inhibitor. Funding: Cancer Research UK, National Health and Medical Research Council (Australia), Breast Cancer Research Foundation, and DaCosta Fund.
Background The likelihood of recurrence in patients with breast cancer who have HER2-positive tumors is relatively high, although trastuzumab is a remarkably effective drug in this setting. Signal transducer and activator of transcription 3 protein (STAT3), a transcription factor that is persistently tyrosine-705 phosphorylated (pSTAT3) in response to numerous oncogenic signaling pathways, activates downstream proliferative and anti-apoptotic pathways. We hypothesized that pSTAT3 expression in HER2-positive breast cancer will confer trastuzumab resistance. Methods We integrated reverse phase protein array (RPPA) and gene expression data from patients with HER2-positive breast cancer treated with trastuzumab in the adjuvant setting. Results We show that a pSTAT3-associated gene signature (pSTAT3-GS) is able to predict pSTAT3 status in an independent dataset (TCGA; AUC = 0.77, P = 0.02). This suggests that STAT3 induces a characteristic set of gene expression changes in HER2-positive cancers. Tumors characterized as high pSTAT3-GS were associated with trastuzumab resistance (log rank P = 0.049). These results were confirmed using data from the prospective, randomized controlled FinHer study, where the effect was especially prominent in HER2-positive estrogen receptor (ER)-negative tumors (interaction test P = 0.02). Of interest, constitutively activated pSTAT3 tumors were associated with loss of PTEN, elevated IL6, and stromal reactivation. Conclusions This study provides compelling evidence for a link between pSTAT3 and trastuzumab resistance in HER2-positive primary breast cancers. Our results suggest that it may be valuable to add agents targeting the STAT3 pathway to trastuzumab for treatment of HER2-positive breast cancer.
Abstract The breast cancer risk variants identified in genome-wide association studies explain only a small fraction of the familial relative risk, and the genes responsible for these associations remain largely unknown. To identify novel risk loci and likely causal genes, we performed a transcriptome-wide association study evaluating associations of genetically predicted gene expression with breast cancer risk in 122,977 cases and 105,974 controls of European ancestry. We used data from the Genotype-Tissue Expression Project to establish genetic models to predict gene expression in breast tissue and evaluated model performance using data from The Cancer Genome Atlas. Of the 8,597 genes evaluated, significant associations were identified for 48 at a Bonferroni-corrected threshold of P < 5.82 × 10−6, including 14 genes at loci not yet reported for breast cancer. We silenced 13 genes and showed an effect for 11 on cell proliferation and/or colony-forming efficiency. Our study provides new insights into breast cancer genetics and biology.
Abstract Background: We examined the associations between germline variants and breast cancer mortality using a large meta-analysis of women of European ancestry. Methods: Meta-analyses included summary estimates based on Cox models of twelve datasets using ~10.4 million variants for 96,661 women with breast cancer and 7697 events (breast cancer-specific deaths). Oestrogen receptor (ER)-specific analyses were based on 64,171 ER-positive (4116) and 16,172 ER-negative (2125) patients. We evaluated the probability of a signal to be a true positive using the Bayesian false discovery probability (BFDP). Results: We did not find any variant associated with breast cancer-specific mortality at P < 5 × 10−8. For ER-positive disease, the most significantly associated variant was chr7:rs4717568 (BFDP = 7%, P = 1.28 × 10−7, hazard ratio [HR] = 0.88, 95% confidence interval [CI] = 0.84–0.92); the closest gene is AUTS2. For ER-negative disease, the most significant variant was chr7:rs67918676 (BFDP = 11%, P = 1.38 × 10−7, HR = 1.27, 95% CI = 1.16–1.39); located within a long intergenic non-coding RNA gene (AC004009.3), close to the HOXA gene cluster. Conclusions: We uncovered germline variants on chromosome 7 at BFDP < 15% close to genes for which there is biological evidence related to breast cancer outcome. However, the paucity of variants associated with mortality at genome-wide significance underpins the challenge in providing genetic-based individualised prognostic information for breast cancer patients.
Abstract Stratification of women according to their risk of breast cancer based on polygenic risk scores (PRSs) could improve screening and prevention strategies. Our aim was to develop PRSs, optimized for prediction of estrogen receptor (ER)-specific disease, from the largest available genome-wide association dataset and to empirically validate the PRSs in prospective studies. The development dataset comprised 94,075 case subjects and 75,017 control subjects of European ancestry from 69 studies, divided into training and validation sets. Samples were genotyped using genome-wide arrays, and single-nucleotide polymorphisms (SNPs) were selected by stepwise regression or lasso penalized regression. The best performing PRSs were validated in an independent test set comprising 11,428 case subjects and 18,323 control subjects from 10 prospective studies and 190,040 women from UK Biobank (3,215 incident breast cancers). For the best PRSs (313 SNPs), the odds ratio for overall disease per 1 standard deviation in ten prospective studies was 1.61 (95%CI: 1.57–1.65) with area under receiver-operator curve (AUC) = 0.630 (95%CI: 0.628–0.651). The lifetime risk of overall breast cancer in the top centile of the PRSs was 32.6%. Compared with women in the middle quintile, those in the highest 1% of risk had 4.37- and 2.78-fold risks, and those in the lowest 1% of risk had 0.16- and 0.27-fold risks, of developing ER-positive and ER-negative disease, respectively. Goodness-of-fit tests indicated that this PRS was well calibrated and predicts disease risk accurately in the tails of the distribution. This PRS is a powerful and reliable predictor of breast cancer risk that may improve breast cancer prevention programs.