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Retrospective studies provide conflicting interpretations of the effect of inherited genetic factors on the prognosis of patients with breast cancer. The primary aim of this study was to determine the effect of a germline BRCA1 or BRCA2 mutation on breast cancer outcomes in patients with young-onset breast cancer. We did a prospective cohort study of female patients recruited from 127 hospitals in the UK aged 40 years or younger at first diagnosis (by histological confirmation) of invasive breast cancer. Patients with a previous invasive malignancy (except non-melanomatous skin cancer) were excluded. Patients were identified within 12 months of initial diagnosis. BRCA1 and BRCA2 mutations were identified using blood DNA collected at recruitment. Clinicopathological data, and data regarding treatment and long-term outcomes, including date and site of disease recurrence, were collected from routine medical records at 6 months, 12 months, and then annually until death or loss to follow-up. The primary outcome was overall survival for all BRCA1 or BRCA2 mutation carriers (BRCA-positive) versus all non-carriers (BRCA-negative) at 2 years, 5 years, and 10 years after diagnosis. A prespecified subgroup analysis of overall survival was done in patients with triple-negative breast cancer. Recruitment was completed in 2008, and long-term follow-up is continuing. Between Jan 24, 2000, and Jan 24, 2008, we recruited 2733 women. Genotyping detected a pathogenic BRCA mutation in 338 (12%) patients (201 with BRCA1, 137 with BRCA2). After a median follow-up of 8·2 years (IQR 6·0–9·9), 651 (96%) of 678 deaths were due to breast cancer. There was no significant difference in overall survival between BRCA-positive and BRCA-negative patients in multivariable analyses at any timepoint (at 2 years: 97·0% [95% CI 94·5–98·4] vs 96·6% [95·8–97·3]; at 5 years: 83·8% [79·3–87·5] vs 85·0% [83·5–86·4]; at 10 years: 73·4% [67·4–78·5] vs 70·1% [67·7–72·3]; hazard ratio [HR] 0·96 [95% CI 0·76–1·22]; p=0·76). Of 558 patients with triple-negative breast cancer, BRCA mutation carriers had better overall survival than non-carriers at 2 years (95% [95% CI 89–97] vs 91% [88–94]; HR 0·59 [95% CI 0·35–0·99]; p=0·047) but not 5 years (81% [73–87] vs 74% [70–78]; HR 1·13 [0·70–1·84]; p=0·62) or 10 years (72% [62–80] vs 69% [63–74]; HR 2·12 [0·82–5·49]; p= 0·12). Patients with young-onset breast cancer who carry a BRCA mutation have similar survival as non-carriers. However, BRCA mutation carriers with triple-negative breast cancer might have a survival advantage during the first few years after diagnosis compared with non-carriers. Decisions about timing of additional surgery aimed at reducing future second primary-cancer risks should take into account patient prognosis associated with the first malignancy and patient preferences. Cancer Research UK, the UK National Cancer Research Network, the Wessex Cancer Trust, Breast Cancer Now, and the PPP Healthcare Medical Trust Grant.

Telomeres play a key role in the maintenance of chromosome integrity and stability, and telomere shortening is involved in initiation and progression of malignancies. A series of epidemiological studies have examined the association between shortened telomeres and risk of cancers, but the findings remain conflicting. A dataset composed of 11,255 cases and 13,101 controls from 21 publications was included in a meta-analysis to evaluate the association between overall cancer risk or cancer-specific risk and the relative telomere length. Heterogeneity among studies and their publication bias were further assessed by the χ(2)-based Q statistic test and Egger's test, respectively. The results showed that shorter telomeres were significantly associated with cancer risk (OR = 1.35, 95% CI = 1.14-1.60), compared with longer telomeres. In the stratified analysis by tumor type, the association remained significant in subgroups of bladder cancer (OR = 1.84, 95% CI = 1.38-2.44), lung cancer (OR = 2.39, 95% CI = 1.18-4.88), smoking-related cancers (OR = 2.25, 95% CI = 1.83-2.78), cancers in the digestive system (OR = 1.69, 95% CI = 1.53-1.87) and the urogenital system (OR = 1.73, 95% CI = 1.12-2.67). Furthermore, the results also indicated that the association between the relative telomere length and overall cancer risk was statistically significant in studies of Caucasian subjects, Asian subjects, retrospective designs, hospital-based controls and smaller sample sizes. Funnel plot and Egger's test suggested that there was no publication bias in the current meta-analysis (P = 0.532). The results of this meta-analysis suggest that the presence of shortened telomeres may be a marker for susceptibility to human cancer, but single larger, well-design prospective studies are warranted to confirm these findings.

Variation in sensitivity to radiation is an inherited genetic trait. This Perspective explores the possibility of genome-wide association studies to characterize genetic profiles that predict patient response to radiotherapy. A key challenge in radiotherapy is to maximize radiation doses to cancer cells while minimizing damage to surrounding healthy tissue. As severe toxicity in a minority of patients limits the doses that can be safely given to the majority, there is interest in developing a test to measure an individual's radiosensitivity before treatment. Variation in sensitivity to radiation is an inherited genetic trait and recent progress in genotyping raises the possibility of genome-wide studies to characterize genetic profiles that predict patient response to radiotherapy.

Clare Turnbull and colleagues report discovery of 19 new susceptibility loci for testicular germ cell tumor (TGCT) and provide evidence for a network of physical interactions between TGCT risk variants and candidate causal genes. Their findings implicate widespread disruption of developmental transcriptional regulators in TGCT susceptibility, consistent with failed primordial germ cell differentiation as an initiating step in oncogenesis. Genome-wide association studies (GWAS) have transformed understanding of susceptibility to testicular germ cell tumors (TGCTs), but much of the heritability remains unexplained. Here we report a new GWAS, a meta-analysis with previous GWAS and a replication series, totaling 7,319 TGCT cases and 23,082 controls. We identify 19 new TGCT risk loci, roughly doubling the number of known TGCT risk loci to 44. By performing in situ Hi-C in TGCT cells, we provide evidence for a network of physical interactions among all 44 TGCT risk SNPs and candidate causal genes. Our findings implicate widespread disruption of developmental transcriptional regulators as a basis of TGCT susceptibility, consistent with failed primordial germ cell differentiation as an initiating step in oncogenesis 1 . Defective microtubule assembly and dysregulation of KIT–MAPK signaling also feature as recurrently disrupted pathways. Our findings support a polygenic model of risk and provide insight into the biological basis of TGCT.

Ana Vega and colleagues report the results of a three-stage genome-wide association study of radiotherapy toxicity following treatment for prostate cancer. They find that susceptibility to late radiation-induced toxicity is associated with variants in the TANC1 gene at 2q24.1. There is increasing evidence supporting the role of genetic variants in the development of radiation-induced toxicity 1 . However, previous candidate gene association studies failed to elucidate the common genetic variation underlying this phenotype 2 , which could emerge years after the completion of treatment 3 . We performed a genome-wide association study on a Spanish cohort of 741 individuals with prostate cancer treated with external beam radiotherapy (EBRT). The replication cohorts consisted of 633 cases from the UK 4 and 368 cases from North America 5 . One locus comprising TANC1 (lowest unadjusted P value for overall late toxicity = 6.85 × 10 −9 , odds ratio (OR) = 6.61, 95% confidence interval (CI) = 2.23–19.63) was replicated in the second stage (lowest unadjusted P value for overall late toxicity = 2.08 × 10 −4 , OR = 6.17, 95% CI = 2.25–16.95; P combined = 4.16 × 10 −10 ). The inclusion of the third cohort gave unadjusted P combined = 4.64 × 10 −11 . These results, together with the role of TANC1 in regenerating damaged muscle, suggest that the TANC1 locus influences the development of late radiation-induced damage.

Several studies have reported associations between radiation toxicity and single nucleotide polymorphisms (SNPs) in candidate genes. Few associations have been tested in independent validation studies. This prospective study aimed to validate reported associations between genotype and radiation toxicity in a large independent dataset. 92 (of 98 attempted) SNPs in 46 genes were successfully genotyped in 1613 patients: 976 received adjuvant breast radiotherapy in the Cambridge breast IMRT trial (ISRCTN21474421, n=942) or in a prospective study of breast toxicity at the Christie Hospital, Manchester, UK (n=34). A further 637 received radical prostate radiotherapy in the MRC RT01 multicentre trial (ISRCTN47772397, n=224) or in the Conventional or Hypofractionated High Dose Intensity Modulated Radiotherapy for Prostate Cancer (CHHiP) trial (ISRCTN97182923, n=413). Late toxicity was assessed 2 years after radiotherapy with a validated photographic technique (patients with breast cancer only), clinical assessment, and patient questionnaires. Association tests of genotype with overall radiation toxicity score and individual endpoints were undertaken in univariate and multivariable analyses. At a type I error rate adjusted for multiple testing, this study had 99% power to detect a SNP, with minor allele frequency of 0·35, associated with a per allele odds ratio of 2·2. None of the previously reported associations were confirmed by this study, after adjustment for multiple comparisons. The p value distribution of the SNPs tested against overall toxicity score was not different from that expected by chance. We did not replicate previously reported late toxicity associations, suggesting that we can essentially exclude the hypothesis that published SNPs individually exert a clinically relevant effect. Continued recruitment of patients into studies within the Radiogenomics Consortium is essential so that sufficiently powered studies can be done and methodological challenges addressed. Cancer Research UK, The Royal College of Radiologists, Addenbrooke's Charitable Trust, Breast Cancer Campaign, Cambridge National Institute of Health Research (NIHR) Biomedical Research Centre, Experimental Cancer Medicine Centre, East Midlands Innovation, the National Cancer Institute, Joseph Mitchell Trust, Royal Marsden NHS Foundation Trust, Institute of Cancer Research NIHR Biomedical Research Centre for Cancer.

Background Genome-wide association studies have identified 196 high confidence independent signals associated with breast cancer susceptibility. Variants within these signals frequently fall in distal regulatory DNA elements that control gene expression. Results We designed a Capture Hi-C array to enrich for chromatin interactions between the credible causal variants and target genes in six human mammary epithelial and breast cancer cell lines. We show that interacting regions are enriched for open chromatin, histone marks for active enhancers, and transcription factors relevant to breast biology. We exploit this comprehensive resource to identify candidate target genes at 139 independent breast cancer risk signals and explore the functional mechanism underlying altered risk at the 12q24 risk region. Conclusions Our results demonstrate the power of combining genetics, computational genomics, and molecular studies to rationalize the identification of key variants and candidate target genes at breast cancer GWAS signals.

Background Genetic variants identified through genome-wide association studies (GWAS) are predominantly non-coding and typically attributed to altered regulatory elements such as enhancers and promoters. However, the contribution of non-coding RNAs to complex traits is not clear. Results Using targeted RNA sequencing, we systematically annotated multi-exonic non-coding RNA (mencRNA) genes transcribed from 1.5-Mb intervals surrounding 139 breast cancer GWAS signals and assessed their contribution to breast cancer risk. We identify more than 4000 mencRNA genes and show their expression distinguishes normal breast tissue from tumors and different breast cancer subtypes. Importantly, breast cancer risk variants, identified through genetic fine-mapping, are significantly enriched in mencRNA exons, but not the promoters or introns. eQTL analyses identify mencRNAs whose expression is associated with risk variants. Furthermore, chromatin interaction data identify hundreds of mencRNA promoters that loop to regions that contain breast cancer risk variants. Conclusions We have compiled the largest catalog of breast cancer-associated mencRNAs to date and provide evidence that modulation of mencRNAs by GWAS variants may provide an alternative mechanism underlying complex traits.

Key Points The polygenic model for cancer susceptibility indicates that much of the inherited risk of cancer is due to multiple risk alleles, each with a low to moderate risk. The number of such alleles for any specific cancer is unknown, but might be in the hundreds or thousands. Although linkage studies have been highly successful in mapping the genes that underlie monogenic disorders, these studies are of limited use for investigating predisposition to polygenic disease, such as cancer. Genetic-association studies — or case–control studies — provide an efficient design for identifying common genetic variants that confer modest disease risks. Few convincing cancer-susceptibility alleles have been identified so far using the genetic-association study design. The limited success of these studies can be attributed mainly to the use of small study sizes — which provide insufficient statistical power and give a high rate of false positives — and limitations in the selection of candidate genes. The rapid acquisition of data on the occurrence of common single-nucleotide polymorphisms (SNPs) has made it possible to test for the association of a candidate gene or region with disease using a tagging-SNP approach. Several approaches can be used to increase the efficiency of candidate-gene association studies, such as improving the selection of candidate genes that are likely to be associated with cancer predisposition and enriching for genetic susceptibility by studying families with a history of cancer. A combination of cheaper genotyping technologies with efficient study design will make empirical, whole-genome studies a feasible prospect in the near future. Elucidating how multiple susceptibility alleles interact with each other and with lifestyle and environmental factors will be a key future challenge for the molecular and genetic epidemiology of cancer predisposition. Cancer is the result of complex interactions between inherited and environmental factors. Known genes account for a small proportion of the heritability of cancer, and it is likely that many genes with modest effects are yet to be found. Genetic-association studies have been widely used in the search for such genes, but success has been limited so far. Increased knowledge of the function of genes and the architecture of human genetic variation combined with new genotyping technologies herald a new era of gene mapping by association.

Background Family history, and genetic and non-genetic risk factors can stratify women according to their individual risk of developing breast cancer. The extent of overlap between these risk predictors is not clear. Methods In this case-only analysis involving 7600 Asian breast cancer patients diagnosed between age 30 and 75 years, we examined identification of high-risk patients based on positive family history, the Gail model 5-year absolute risk [5yAR] above 1.3%, breast cancer predisposition genes (protein-truncating variants [PTV] in ATM , BRCA1 , BRCA2 , CHEK2 , PALB2 , BARD1 , RAD51C , RAD51D , or TP53 ), and polygenic risk score (PRS) 5yAR above 1.3%. Results Correlation between 5yAR (at age of diagnosis) predicted by PRS and the Gail model was low ( r =0.27). Fifty-three percent of breast cancer patients ( n =4041) were considered high risk by one or more classification criteria. Positive family history, PTV carriership, PRS, or the Gail model identified 1247 (16%), 385 (5%), 2774 (36%), and 1592 (21%) patients who were considered at high risk, respectively. In a subset of 3227 women aged below 50 years, the four models studied identified 470 (15%), 213 (7%), 769 (24%), and 325 (10%) unique patients who were considered at high risk, respectively. For younger women, PRS and PTVs together identified 745 (59% of 1276) high-risk individuals who were not identified by the Gail model or family history. Conclusions Family history and genetic and non-genetic risk stratification tools have the potential to complement one another to identify women at high risk.