Breast cancers demonstrate substantial biological, clinical and etiological heterogeneity. We investigated breast cancer risk associations of eight susceptibility loci identified in GWAS and two putative susceptibility loci in candidate genes in relation to specific breast tumor subtypes. Subtypes were defined by five markers (ER, PR, HER2, CK5/6, EGFR) and other pathological and clinical features. Analyses included up to 30 040 invasive breast cancer cases and 53 692 controls from 31 studies within the Breast Cancer Association Consortium. We confirmed previous reports of stronger associations with ER+ than ER- tumors for six of the eight loci identified in GWAS: rs2981582 (10q26) (P-heterogeneity = 6.1 × 10(-18)), rs3803662 (16q12) (P = 3.7 × 10(-5)), rs13281615 (8q24) (P = 0.002), rs13387042 (2q35) (P = 0.006), rs4973768 (3p24) (P = 0.003) and rs6504950 (17q23) (P = 0.002). The two candidate loci, CASP8 (rs1045485, rs17468277) and TGFB1 (rs1982073), were most strongly related with the risk of PR negative tumors (P = 5.1 × 10(-6) and P = 4.1 × 10(-4), respectively), as previously suggested. Four of the eight loci identified in GWAS were associated with triple negative tumors (P ≤ 0.016): rs3803662 (16q12), rs889312 (5q11), rs3817198 (11p15) and rs13387042 (2q35); however, only two of them (16q12 and 2q35) were associated with tumors with the core basal phenotype (P ≤ 0.002). These analyses are consistent with different biological origins of breast cancers, and indicate that tumor stratification might help in the identification and characterization of novel risk factors for breast cancer subtypes. This may eventually result in further improvements in prevention, early detection and treatment.

International audienceThe 70-gene prognosis signature (van't Veer et al., Nature 415(6871):530–536, 2002) may improve the selection of lymph node-negative breast cancer patients for adjuvant systemic therapy. Optimal validation of prognostic classifiers is of great importance and we therefore wished to evaluate the prognostic value of the 70-gene prognosis signature in a series of relatively recently diagnosed lymph node negative breast cancer patients. We evaluated the 70-gene prognosis signature in an independent representative series of patients with invasive breast cancer ( = 123; <55 years; pT1-2N0; diagnosed between 1996 and 1999; median follow-up 5.8 years) by classifying these patients as having a good or poor prognosis signature. In addition, we updated the follow-up of the node-negative patients of the previously published validation-series (Van de Vijver et al., N Engl J Med 347(25):1999–2009, 2002;  = 151; median follow-up 10.2 years). The prognostic value of the 70-gene prognosis signature was compared with that of four commonly used clinicopathological risk indexes. The endpoints were distant metastasis (as first event) free percentage (DMFP) and overall survival (OS). The 5-year OS was 82 ± 5% in poor (48%) and 97 ± 2% in good prognosis signature (52%) patients (HR 3.4; 95% CI 1.2–9.6;  = 0.021). The 5-years DMFP was 78 ± 6% in poor and 98 ± 2% in good prognosis signature patients (HR 5.7; 95% CI 1.6–20;  = 0.007). In the updated series ( = 151; 60% poor vs. 40% good), the 10-year OS was 51 ± 5% and 94 ± 3% (HR 10.7; 95% CI 3.9–30;  < 0.01), respectively. The DMFP was 50 ± 6% in poor and 86 ± 5% in good prognosis signature patients (HR 5.5; 95% CI 2.5–12;  < 0.01). In multivariate analysis, the prognosis signature was a strong independent prognostic factor in both series, outperforming the clinicopathological risk indexes. The 70-gene prognosis signature is also an independent prognostic factor in node-negative breast cancer patients for women diagnosed in recent years

BackgroundCitizen science, scientific research conducted by non-specialists, has the potential to facilitate biomedical research using available large-scale data, however validating the results is challenging. The Cell Slider is a citizen science project that intends to share images from tumors with the general public, enabling them to score tumor markers independently through an internet-based interface.MethodsFrom October 2012 to June 2014, 98,293 Citizen Scientists accessed the Cell Slider web page and scored 180,172 sub-images derived from images of 12,326 tissue microarray cores labeled for estrogen receptor (ER). We evaluated the accuracy of Citizen Scientist's ER classification, and the association between ER status and prognosis by comparing their test performance against trained pathologists.FindingsThe area under ROC curve was 0.95 (95% CI 0.94 to 0.96) for cancer cell identification and 0.97 (95% CI 0.96 to 0.97) for ER status. ER positive tumors scored by Citizen Scientists were associated with survival in a similar way to that scored by trained pathologists. Survival probability at 15 years were 0.78 (95% CI 0.76 to 0.80) for ER-positive and 0.72 (95% CI 0.68 to 0.77) for ER-negative tumors based on Citizen Scientists classification. Based on pathologist classification, survival probability was 0.79 (95% CI 0.77 to 0.81) for ER-positive and 0.71 (95% CI 0.67 to 0.74) for ER-negative tumors. The hazard ratio for death was 0.26 (95% CI 0.18 to 0.37) at diagnosis and became greater than one after 6.5 years of follow-up for ER scored by Citizen Scientists, and 0.24 (95% CI 0.18 to 0.33) at diagnosis increasing thereafter to one after 6.7 (95% CI 4.1 to 10.9) years of follow-up for ER scored by pathologists.InterpretationCrowdsourcing of the general public to classify cancer pathology data for research is viable, engages the public and provides accurate ER data. Crowdsourced classification of research data may offer a valid solution to problems of throughput requiring human input.

eHealth interventions aimed at improving physical activity (PA) can reach large populations with few resources and demands on the population as opposed to centre-based interventions. Active Plus is a proven effective computer-tailored PA intervention for the older adult population focusing on PA in daily life. This manuscript describes the effects of the Active Plus intervention (N = 260) on PA of older adults with chronic illnesses (OACI), compared to a waiting list control group (N = 325). It was part of a larger randomized controlled trial (RCT) on the effects of the Active Plus intervention on cognitive functioning. OACI (≥65 years) with at least one chronic illness were allocated to one of the conditions. Intervention group participants received PA advice. Baseline and follow-up measurements were assessed after 6 and 12 months. Intervention effects on objectively measured light PA (LPA) and moderate-to-vigorous PA (MVPA) min/week were analysed with multilevel linear mixed-effects models adjusted for the clustered design. Intervention effects on self-reported MVPA min/week on common types of PA were analysed with two-part generalized linear mixed-effects models adjusted for the clustered design. The dropout rate was 19.1% after 6 months and 25.1% after 12 months. Analyses showed no effects on objectively measured PA. Active Plus increased the likelihood to perform self-reported cycling and gardening at six months and participants who cycled increased their MVPA min/week of cycling. Twelve months after baseline the intervention increased the likelihood to perform self-reported walking and participants who cycled at 12 months increased their MVPA min/week of cycling. Subgroup analyses showed that more vulnerable participants (higher degree of impairment, age or body mass index) benefitted more from the intervention on especially the lower intensity PA outcomes. In conclusion, Active Plus only increased PA behaviour to a limited extent in OACI 6 and 12 months after baseline measurements. The Active Plus intervention may yet be not effective enough by itself in OACI. A blended approach, where this eHealth intervention and face-to-face contact are combined, is advised to improve the effects of Active Plus on PA in this target group.