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Significance The major portion of hereditary breast cancer still remains unexplained, and many susceptibility loci are yet to be found. Exome sequencing of 24 high-risk familial BRCA1/2 -negative breast cancer patients and further genotyping of a large sample set of breast/ovarian cancer cases and controls was used to discover previously unidentified susceptibility alleles and genes. A significant association of a FANCM nonsense mutation with breast cancer, especially triple-negative breast cancer, identifies FANCM as a breast cancer susceptibility gene. Identification of such risk alleles is expected to improve cancer risk assessment for breast cancer patients and families, and may lead to improvements in the prevention, early diagnosis, and treatment of cancer. Inherited predisposition to breast cancer is known to be caused by loss-of-function mutations in BRCA1 , BRCA2 , PALB2 , CHEK2 , and other genes involved in DNA repair. However, most families severely affected by breast cancer do not harbor mutations in any of these genes. In Finland, founder mutations have been observed in each of these genes, suggesting that the Finnish population may be an excellent resource for the identification of other such genes. To this end, we carried out exome sequencing of constitutional genomic DNA from 24 breast cancer patients from 11 Finnish breast cancer families. From all rare damaging variants, 22 variants in 21 DNA repair genes were genotyped in 3,166 breast cancer patients, 569 ovarian cancer patients, and 2,090 controls, all from the Helsinki or Tampere regions of Finland. In Fanconi anemia complementation gene M ( FANCM ), nonsense mutation c.5101C>T (p.Q1701X) was significantly more frequent among breast cancer patients than among controls [odds ratio (OR) = 1.86, 95% CI = 1.26–2.75; P = 0.0018], with particular enrichment among patients with triple-negative breast cancer (TNBC; OR = 3.56, 95% CI = 1.81–6.98, P = 0.0002). In the Helsinki and Tampere regions, respectively, carrier frequencies of FANCM p.Q1701X were 2.9% and 4.0% of breast cancer patients, 5.6% and 6.6% of TNBC patients, 2.2% of ovarian cancer patients (from Helsinki), and 1.4% and 2.5% of controls. These findings identify FANCM as a breast cancer susceptibility gene, mutations in which confer a particularly strong predisposition for TNBC.

Immunohistochemical markers are often used to classify breast cancer into subtypes that are biologically distinct and behave differently. The aim of this study was to estimate mortality for patients with the major subtypes of breast cancer as classified using five immunohistochemical markers, to investigate patterns of mortality over time, and to test for heterogeneity by subtype. We pooled data from more than 10,000 cases of invasive breast cancer from 12 studies that had collected information on hormone receptor status, human epidermal growth factor receptor-2 (HER2) status, and at least one basal marker (cytokeratin [CK]5/6 or epidermal growth factor receptor [EGFR]) together with survival time data. Tumours were classified as luminal and nonluminal tumours according to hormone receptor expression. These two groups were further subdivided according to expression of HER2, and finally, the luminal and nonluminal HER2-negative tumours were categorised according to expression of basal markers. Changes in mortality rates over time differed by subtype. In women with luminal HER2-negative subtypes, mortality rates were constant over time, whereas mortality rates associated with the luminal HER2-positive and nonluminal subtypes tended to peak within 5 y of diagnosis and then decline over time. In the first 5 y after diagnosis the nonluminal tumours were associated with a poorer prognosis, but over longer follow-up times the prognosis was poorer in the luminal subtypes, with the worst prognosis at 15 y being in the luminal HER2-positive tumours. Basal marker expression distinguished the HER2-negative luminal and nonluminal tumours into different subtypes. These patterns were independent of any systemic adjuvant therapy. The six subtypes of breast cancer defined by expression of five markers show distinct behaviours with important differences in short term and long term prognosis. Application of these markers in the clinical setting could have the potential to improve the targeting of adjuvant chemotherapy to those most likely to benefit. The different patterns of mortality over time also suggest important biological differences between the subtypes that may result in differences in response to specific therapies, and that stratification of breast cancers by clinically relevant subtypes in clinical trials is urgently required.

The risk of breast cancer associated with CHEK2: c.1100delC is 2–threefold but higher in carriers with a family history of breast cancer than without, suggesting that other genetic loci in combination with CHEK2 :c.1100delC confer an increased risk in a polygenic model. Part of the excess familial risk has been associated with common low-penetrance variants. This study aimed to identify genetic loci that modify CHEK2 :c.1100delC-associated breast cancer risk by searching for candidate risk alleles that are overrepresented in CHEK2 :c.1100delC carriers with breast cancer compared with controls. We performed whole-exome sequencing in 28 breast cancer cases with germline CHEK2 :c.1100delC, 28 familial breast cancer cases and 70 controls. Candidate alleles were selected for validation in larger cohorts. One recessive synonymous variant, rs16897117, was suggested, but no overrepresentation of homozygous CHEK2 :c.1100delC carriers was found in the following validation. Furthermore, 11 non-synonymous candidate alleles were suggested for further testing, but no significant difference in allele frequency could be detected in the validation in CHEK2 :c.1100delC cases compared with familial breast cancer, sporadic breast cancer and controls. With this method, we found no support for a CHEK2 :c.1100delC-specific genetic modifier. Further studies of CHEK2 :c.1100delC genetic modifiers are warranted to improve risk assessment in clinical practice.

ABSTRACT Background Biallelic FANCM variants are linked to a Fanconi anemia‐like cancer predisposition syndrome, which includes early onset breast cancer, chemotherapy toxicity, and chromosome fragility. Additionally, heterozygous truncating variants have been linked to increased breast cancer risk. However, the published results have been inconsistent, and the risks and the functional effects associated with the variants also vary depending on the position in the gene, with N‐terminal truncating variants having a stronger effect. Compared to other FANCM variants studied, milder patient phenotypes and only late onset breast cancer have been reported for the homozygous C‐terminal c.5101C>T variant, which is enriched in Finland. Case We report here a Finnish patient, homozygous for the FANCM c.5101C>T p.(Gln1701*) variant, who manifested with early onset triple‐negative breast cancer, chemotherapy toxicity, and chromosome fragility. Homozygosity for c.5101C>T has previously been reported in two Finnish siblings with primary ovarian insufficiency and chromosome fragility. Conclusion These findings suggest that the C‐terminal FANCM variant c. 5101C>T may also be linked to a phenotype similar to the phenotype associated with N‐terminal truncating variants when inherited in a homozygous state.

Background Breast cancer survivors are at risk for contralateral breast cancer (CBC), with the consequent burden of further treatment and potentially less favorable prognosis. We aimed to develop and validate a CBC risk prediction model and evaluate its applicability for clinical decision-making. Methods We included data of 132,756 invasive non-metastatic breast cancer patients from 20 studies with 4682 CBC events and a median follow-up of 8.8 years. We developed a multivariable Fine and Gray prediction model (PredictCBC-1A) including patient, primary tumor, and treatment characteristics and BRCA1/2 germline mutation status, accounting for the competing risks of death and distant metastasis. We also developed a model without BRCA1/2 mutation status (PredictCBC-1B) since this information was available for only 6% of patients and is routinely unavailable in the general breast cancer population. Prediction performance was evaluated using calibration and discrimination, calculated by a time-dependent area under the curve (AUC) at 5 and 10 years after diagnosis of primary breast cancer, and an internal-external cross-validation procedure. Decision curve analysis was performed to evaluate the net benefit of the model to quantify clinical utility. Results In the multivariable model, BRCA1/2 germline mutation status, family history, and systemic adjuvant treatment showed the strongest associations with CBC risk. The AUC of PredictCBC-1A was 0.63 (95% prediction interval (PI) at 5 years, 0.52–0.74; at 10 years, 0.53–0.72). Calibration-in-the-large was -0.13 (95% PI: -1.62–1.37), and the calibration slope was 0.90 (95% PI: 0.73–1.08). The AUC of Predict-1B at 10 years was 0.59 (95% PI: 0.52–0.66); calibration was slightly lower. Decision curve analysis for preventive contralateral mastectomy showed potential clinical utility of PredictCBC-1A between thresholds of 4–10% 10-year CBC risk for BRCA1/2 mutation carriers and non-carriers. Conclusions We developed a reasonably calibrated model to predict the risk of CBC in women of European-descent; however, prediction accuracy was moderate. Our model shows potential for improved risk counseling, but decision-making regarding contralateral preventive mastectomy, especially in the general breast cancer population where limited information of the mutation status in BRCA1/2 is available, remains challenging.

Background Several susceptibility genes have been established for female breast cancer, of which mutations in BRCA1 and especially in BRCA2 are also known risk factors for male breast cancer (MBC). The role of other breast cancer genes in MBC is less well understood. Methods In this study, we have genotyped 68 MBC patients for the known breast or ovarian cancer associated mutations in the Finnish population in CHEK2, PALB2 , RAD51C , RAD51D, and FANCM genes. Results CHEK2 c.1100delC mutation was found in 4 patients (5.9%), which is significantly more frequent than in the control population (OR: 4.47, 95% CI 1.51–13.18, p  = 0.019). Four CHEK2 I157T variants were also detected, but the frequency did not significantly differ from population controls ( p  = 0.781). No RAD51C , RAD51D , PALB2 , or FANCM mutations were found. Conclusions These data suggest that the CHEK2 c.1100delC mutation is associated with an increased risk for MBC in the Finnish population.

Background Prediction of contralateral breast cancer (CBC) risk is challenging due to moderate performances of the known risk factors. We aimed to improve our previous risk prediction model (PredictCBC) by updated follow-up and including additional risk factors. Methods We included data from 207,510 invasive breast cancer patients participating in 23 studies. In total, 8225 CBC events occurred over a median follow-up of 10.2 years. In addition to the previously included risk factors, PredictCBC-2.0 included CHEK2 c.1100delC, a 313 variant polygenic risk score (PRS-313), body mass index (BMI), and parity. Fine and Gray regression was used to fit the model. Calibration and a time-dependent area under the curve (AUC) at 5 and 10 years were assessed to determine the performance of the models. Decision curve analysis was performed to evaluate the net benefit of PredictCBC-2.0 and previous PredictCBC models. Results The discrimination of PredictCBC-2.0 at 10 years was higher than PredictCBC with an AUC of 0.65 (95% prediction intervals (PI) 0.56–0.74) versus 0.63 (95%PI 0.54–0.71). PredictCBC-2.0 was well calibrated with an observed/expected ratio at 10 years of 0.92 (95%PI 0.34–2.54). Decision curve analysis for contralateral preventive mastectomy (CPM) showed the potential clinical utility of PredictCBC-2.0 between thresholds of 4 and 12% 10-year CBC risk for BRCA1/2 mutation carriers and non-carriers. Conclusions Additional genetic information beyond BRCA1/2 germline mutations improved CBC risk prediction and might help tailor clinical decision-making toward CPM or alternative preventive strategies. Identifying patients who benefit from CPM, especially in the general breast cancer population, remains challenging.

To identify genetic variants associated with breast cancer prognosis we conduct a meta-analysis of overall survival (OS) and disease-free survival (DFS) in 6042 patients from four cohorts. In young women, breast cancer is characterized by a higher incidence of adverse pathological features, unique gene expression profiles and worse survival, which may relate to germline variation. To explore this hypothesis, we also perform survival analysis in 2315 patients aged ≤ 40 years at diagnosis. Here, we identify two SNPs associated with early-onset DFS, rs715212 ( P meta  = 3.54 × 10 −5 ) and rs10963755 ( P meta  = 3.91 × 10 −4 ) in ADAMTSL1 . The effect of these SNPs is independent of classical prognostic factors and there is no heterogeneity between cohorts. Most importantly, the association with rs715212 is noteworthy (FPRP <0.2) and approaches genome-wide significance in multivariable analysis ( P multivariable  = 5.37 × 10 −8 ). Expression quantitative trait analysis provides tentative evidence that rs715212 may influence AREG expression ( P eQTL  = 0.035), although further functional studies are needed to confirm this association and determine a mechanism. Genetic variance can influence breast cancer prognosis. Here, the authors conduct a meta-analysis to explore genetic variance linked to breast cancer in young women, identifying a prognostic association with germline variation of ADAMTSL1.

Germline mutations in the BRCA1 and BRCA2 genes cause hereditary breast and ovarian cancer syndrome (HBOC). Mutations in these genes are usually inherited, and reports of de novo BRCA1/2 mutations are rare. To date, only one patient with low-level BRCA1 mutation mosaicism has been published. We report on a breast cancer patient with constitutional somatic mosaicism of a BRCA2 mutation. BRCA2 mutation c.9294C>G, p.(Tyr3098Ter) was detected in 20% of reads in DNA extracted from peripheral blood using next-generation sequencing (NGS). The BRCA2 mutation was subsequently observed at similar levels in normal breast tissue, adipose tissue, normal right fallopian tube tissue and ovaries of the patient, suggesting that this mutation occurred early in embryonic development. This is the first case to report constitutional mosaicism for a BRCA2 mutation and shows that BRCA2 mosaicism can underlie early-onset breast cancer. NGS for BRCA1/2 should be considered for patients whose tumors harbor a BRCA1/2 mutation and for individuals suggestive of genetic predisposition but without a family history of HBO.

MiR-34a acts as a candidate tumour suppressor gene, and its expression is reduced in several cancer types. We aimed to study miR-34a expression in breast cancer and its correlation with tumour characteristics and clinical outcome, and regulatory links with other genes. We analysed miR-34a expression in 1,172 breast tumours on TMAs. 25% of the tumours showed high, 43% medium and 32% low expression of miR-34a. High miR-34a expression associated with poor prognostic factors for breast cancer: positive nodal status (p = 0.006), high tumour grade (p<0.0001), ER-negativity (p = 0.0002), HER2-positivity (p = 0.0002), high proliferation rate (p<0.0001), p53-positivity (p<0.0001), high cyclin E (p<0.0001) and γH2AX (p<0.0001). However, multivariate analysis adjusting for conventional prognostic factors indicated that high miR-34a expression in fact associated with a lower risk of recurrence or death from breast cancer (HR = 0.63, 95% CI = 0.41-0.96, p = 0.031). Gene expression analysis by differential miR-34a expression revealed an expression signature with an effect on both the 5-year and 10-year survival of the patients (p<0.001). Functional genomic analysis highlighted a novel regulatory role of the transcription factor MAZ, apart from the known control by p53, on the expression of miR-34a and a number of miR-34a targets. Our findings suggest that while miR-34a expression activation is a marker of aggressive breast tumour phenotype it exerts an independent effect for a lower risk of recurrence or death from breast cancer. We also present an expression signature of 190 genes associated with miR-34a expression. Our analysis for regulatory loops suggest that MAZ and p53 transcription factors co-operate in modulating miR-34a, as well as miR-34a targets involved in several cellular pathways. Taken together, these results suggest that the network of genes co-regulated with and targeted by miR-34a form a group of down-stream effectors that maybe of use in predicting clinical outcome, and that highlight novel regulatory mechanisms in breast cancer.