Genome-wide association studies have identified breast cancer risk variants in over 150 genomic regions, but the mechanisms underlying risk remain largely unknown. These regions were explored by combining association analysis with in silico genomic feature annotations. We defined 205 independent risk-associated signals with the set of credible causal variants (CCVs) in each one. In parallel, we used a Bayesian approach (PAINTOR) that combines genetic association, linkage disequilibrium, and enriched genomic features to determine variants with high posterior probabilities of being causal. Potentially causal variants were significantly over-represented in active gene regulatory regions and transcription factor binding sites. We applied our INQUSIT Users may view, print, copy, and download text and data-mine the content in such documents, for the purposes of academic research, subject always to the full Conditions of use:
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Breast cancer susceptibility variants frequently show heterogeneity in associations by tumor subtype. To identify novel loci, we performed a genome-wide association study (GWAS) including 133,384 breast cancer cases and 113,789 controls, plus 18,908 BRCA1 mutation carriers (9,414 with breast cancer) of European ancestry, using both standard and novel methodologies that account for underlying tumor heterogeneity by estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER2) status and tumor grade. We identified 32 novel susceptibility loci (P<5.0x10 -8 ), 15 of which showed evidence for associations with at least one tumor feature (false discovery rate <0.05). Five loci showed associations (P<0.05) in opposite directions between luminal-and non-luminal subtypes. In-silico analyses showed these five loci contained cell-specific enhancers that differed between normal luminal and basal mammary cells. The genetic correlations between five intrinsic-like subtypes ranged from 0.35 to 0.80. The proportion of genome-wide chip heritability explained by all known susceptibility loci was 37.6% for triple-negative and 54.2% for luminal A-like disease. These findings provide an improved understanding of genetic predisposition to breast cancer subtypes and will inform the development of subtype-specific polygenic risk scores.
OBJECTIVE:A significant number of breast cancer patients, during their life with the diagnosis, experience emotional distress in the form of depression and anxiety. Psychological resilience is the ability of a person to protect his/her mental health when faced with adverse circumstances such as the cancer diagnosis. This study aims to assess the resilience in breast cancer patients and to explore whether depression affects the resilience.MATERIAL AND METHODS:Two hundred eighteen (218) women, treated for early breast cancer responded to Connor - Davidson Resilience Scale and Hospital Depression and Anxiety Scale, in order to assess the level of psychological resilience and the level of depression.RESULTS:There is a significant negative correlation between depression and resilience in our sample (r = - 0.562, p < 0.001). Individuals with higher levels of depression have lower levels of psychological resilience. There is no statistically significant correlation between the ages of the participants; time passed since diagnosis, cancer stage and resilience levels.CONCLUSION:This study shows that patients who are less depressed have higher levels of resilience and that psychological resilience may independently contribute to lower levels of depression among breast cancer patients. The level of psychological resilience may be a protective factor for depression and psychological distress.
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