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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.

BACKGROUNDGenetic testing for breast cancer susceptibility is widely used, but for many genes, evidence of an association with breast cancer is weak, underlying risk estimates are imprecise, and reliable subtype-specific risk estimates are lacking. METHODSWe used a panel of 34 putative susceptibility genes to perform sequencing on samples from 60,466 women with breast cancer and 53,461 controls. In separate analyses for protein-truncating variants and rare missense variants in these genes, we estimated odds ratios for breast cancer overall and tumor subtypes. We evaluated missense-variant associations according to domain and classification of pathogenicity. RESULTSProtein-truncating variants in 5 genes (ATM, BRCA1, BRCA2, CHEK2, and PALB2) were associated with a risk of breast cancer overall with a P value of less than 0.0001. Protein-truncating variants in 4 other genes (BARD1, RAD51C, RAD51D, and TP53) were associated with a risk of breast cancer overall with a P value of less than 0.05 and a Bayesian false-discovery probability of less than 0.05. For protein-truncating variants in 19 of the remaining 25 genes, the upper limit of the 95% confidence interval of the odds ratio for breast cancer overall was less than 2.0. For protein-truncating variants in ATM and CHEK2, odds ratios were higher for estrogen receptor (ER)-positive disease than for ER-negative disease; for protein-truncating variants in BARD1, BRCA1, BRCA2, PALB2, RAD51C, and RAD51D, odds ratios were higher for ER-negative disease than for ER-positive disease. Rare missense variants (in aggregate) in ATM, CHEK2, and TP53 were associated with a risk of breast cancer overall with a P value of less than 0.001. For BRCA1, BRCA2, and TP53, missense variants (in aggregate) that would be classified as pathogenic according to standard criteria were associated with a risk of breast cancer overall, with the risk being similar to that of protein-truncating variants. CONCLUSIONSThe results of this study define the genes that are most clinically useful for inclusion on panels for the prediction of breast cancer risk, as well as provide estimates of the risks associated with protein-truncating variants, to guide genetic counseling. (Funded by European Union Horizon 2020 programs and others.

BACKGROUND: We address the prognostic and predictive value of KRAS, PIK3CA and BRAF mutations for clinical outcomes in response to active agents in the treatment of metastatic colorectal cancer (mCRC). METHODS: We determined KRAS, BRAF and PIK3CA mutations in tumours from 168 patients treated for mCRC at two institutions. All patients received 5-FU-based first-line chemotherapy and treatment outcome was analysed retrospectively. RESULTS: KRAS, BRAF and PIK3CA mutations were present in 62 (37%), 13 (8%) and 26 (15%) cases, respectively. Multivariate analysis uncovered BRAF mutation as an independent prognostic factor for decreased survival (hazard ratio (HR) 4.0, 95% confidence interval (CI) 2.1 -7.6). In addition, patients with BRAF-mutant tumours had significantly lower progression-free survival (PFS: HR 4.0, 95% CI 2.2 -7.4) than those whose tumors that carried wild-type BRAF. Among 92 patients treated using chemotherapy and cetuximab as salvage therapy, KRAS mutation was associated with lack of response (P ¼ 0.002) and shorter PFS (P ¼ 0.09). BRAF (P ¼ 0.0005) and PIK3CA (P ¼ 0.01) mutations also predicted reduced PFS in response to cetuximab salvage therapy. CONCLUSIONS: These results underscore the potential of mutational profiling to identify CRCs with different natural histories or treatment responses. The adverse significance of BRAF mutation should inform patient selection and stratification in clinical trials.

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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:

BackgroundTo investigate the predictive significance of KRAS, BRAF, PIK3CA mutational status, AREG- EREG mRNA expression, PTEN protein expression and skin rash in metastatic colorectal cancer (mCRC) patients treated with cetuximab containing salvage chemotherapy.MethodsPrimary tumors from 112 mCRC patients were analyzed. The worst skin toxicity during treatment was recorded.Results KRAS, BRAF and PIK3CA mutations were present in 37 (33%), 8 (7.2%) and 11 (9.8%) cases, respectively, PTEN was lost in 21 (19.8%) cases, AREG and EREG were overexpressed in 48 (45%) and 51 (49%) cases. In the whole study population, time to tumor progression (TTP) and overall survival (OS) was significantly lower in patients with KRAS (p = 0.001 and p = 0.026, respectively) or BRAF (p = 0.001 and p<0.0001, respectively) mutant tumors, downregulation of AREG (p = 0.018 and p = 0.013, respectively) or EREG (p = 0.002 and p = 0.004, respectively) and grade 0-1 skin rash (p<0.0001 and p<0.0001, respectively). In KRAS wt patients TTP and OS was significantly lower in patients with BRAF (p = 0.0001 and p<0.0001, respectively) mutant tumors, downregulation of AREG (p = 0.021 and p = 0.004, respectively) or EREG (p = 0.0001 and p<0.0001, respectively) and grade 0-1 skin rash (p<0.0001 and p<0.0001, respectively). TTP was significantly lower in patients with PIK3CA mutations (p = 0.01) or lost PTEN (p = 0.002). Multivariate analysis revealed KRAS (Hazard Ratio [HR] 4.3, p<0.0001), BRAF mutation (HR: 5.1, p<0.0001), EREG low expression (HR: 1.6, p = 0.021) and absence of severe/moderate skin rash (HR: 4.0, p<0.0001) as independent prognostic factors for decreased TTP. Similarly, KRAS (HR 2.9, p = 0.01), BRAF mutation (HR: 3.0, p = 0.001), EREG low expression (HR: 1.7, p = 0.021), absecence of severe/moderate skin rash (HR: 3.7, p<0.0001) and the presence of undifferantited tumours (HR: 2.2, p = 0.001) were revealed as independent prognostic factors for decreased OS.ConclusionsThese results underscore that KRAS-BRAF mutations and EREG expression can be used as biomarkers to further select patients undergoing anti-EGFR treatment.

Objective. T cells play a major role in the pathogenesis of rheumatoid arthritis (RA).