Women who have inherited mutations in BRCA1 (17q21, chromosome 17: base pairs 43,044,294 to 43,125,482) or BRCA2 (13q12.3, chromosome 13: base pairs 32,315,479 to 32,399,671) have an increased risk of breast and ovarian cancers.^1,2 Little is known about how cancer risks differ by BRCA1 or BRCA2 (BRCA1/2) mutation type. An “ovarian cancer cluster region” (OCCR) has been reported in both BRCA1 and BRCA2 using small sample sets. For BRCA1, initially mutations after exon 11 were associated with a 20% lower ovarian cancer risk than mutations in exons 1 through 11.³ Following that observation, Thompson et al⁴ reported an increased risk of ovarian vs breast cancer specifically was associated with mutations in the central portion of exon 11. This association was attributed to both a decrease in breast cancer risk and an increase in ovarian cancer risk in this region. Mutations in exon 11 of BRCA2 also have been associated with higher ovarian vs breast cancer risk than in other regions of the gene.⁵ It was hypothesized that this risk variation might be explained by the failure of BRCA1/2 exon 11 truncating mutations to trigger nonsense-mediated messenger RNA (mRNA) decay (NMD) because of their extremely large size, contrary to truncating mutations in smaller exons. However, this postulate was not supported by the measures of the relative amounts of mRNA transcript encoded by BRCA1/2 alleles.^6,7 Murine models of different mutations in BRCA1/2 also suggest that genotype-phenotype correlations exist.^8,9 Quiz Ref ID To our knowledge, no study has reported whether BRCA1/2 mutation type is associated with differences in breast and ovarian cancer risk. Thus, we evaluated whether BRCA1 and BRCA2 mutation type or location is associated with variation in breast and ovarian cancer risk.

Paul Pharoah and colleagues report the results of a large genome-wide association study of ovarian cancer. They identify new susceptibility loci for different epithelial ovarian cancer histotypes and use integrated analyses of genes and regulatory features at each locus to predict candidate susceptibility genes, including OBFC1. To identify common alleles associated with different histotypes of epithelial ovarian cancer (EOC), we pooled data from multiple genome-wide genotyping projects totaling 25,509 EOC cases and 40,941 controls. We identified nine new susceptibility loci for different EOC histotypes: six for serous EOC histotypes (3q28, 4q32.3, 8q21.11, 10q24.33, 18q11.2 and 22q12.1), two for mucinous EOC (3q22.3 and 9q31.1) and one for endometrioid EOC (5q12.3). We then performed meta-analysis on the results for high-grade serous ovarian cancer with the results from analysis of 31,448 BRCA1 and BRCA2 mutation carriers, including 3,887 mutation carriers with EOC. This identified three additional susceptibility loci at 2q13, 8q24.1 and 12q24.31. Integrated analyses of genes and regulatory biofeatures at each locus predicted candidate susceptibility genes, including OBFC1, a new candidate susceptibility gene for low-grade and borderline serous EOC.

BRCA1-associated breast and ovarian cancer risks can be modified by common genetic variants. To identify further cancer risk-modifying loci, we performed a multi-stage GWAS of 11,705 BRCA1 carriers (of whom 5,920 were diagnosed with breast and 1,839 were diagnosed with ovarian cancer), with a further replication in an additional sample of 2,646 BRCA1 carriers. We identified a novel breast cancer risk modifier locus at 1q32 for BRCA1 carriers (rs2290854, P = 2.7×10⁻⁸, HR = 1.14, 95% CI: 1.09–1.20). In addition, we identified two novel ovarian cancer risk modifier loci: 17q21.31 (rs17631303, P = 1.4×10⁻⁸, HR = 1.27, 95% CI: 1.17–1.38) and 4q32.3 (rs4691139, P = 3.4×10⁻⁸, HR = 1.20, 95% CI: 1.17–1.38). The 4q32.3 locus was not associated with ovarian cancer risk in the general population or BRCA2 carriers, suggesting a BRCA1-specific association. The 17q21.31 locus was also associated with ovarian cancer risk in 8,211 BRCA2 carriers (P = 2×10⁻⁴). These loci may lead to an improved understanding of the etiology of breast and ovarian tumors in BRCA1 carriers. Based on the joint distribution of the known BRCA1 breast cancer risk-modifying loci, we estimated that the breast cancer lifetime risks for the 5% of BRCA1 carriers at lowest risk are 28%–50% compared to 81%–100% for the 5% at highest risk. Similarly, based on the known ovarian cancer risk-modifying loci, the 5% of BRCA1 carriers at lowest risk have an estimated lifetime risk of developing ovarian cancer of 28% or lower, whereas the 5% at highest risk will have a risk of 63% or higher. Such differences in risk may have important implications for risk prediction and clinical management for BRCA1 carriers. BRCA1 mutation carriers have increased and variable risks of breast and ovarian cancer. To identify modifiers of breast and ovarian cancer risk in this population, a multi-stage GWAS of 14,351 BRCA1 mutation carriers was performed. Loci 1q32 and TCF7L2 at 10q25.3 were associated with breast cancer risk, and two loci at 4q32.2 and 17q21.31 were associated with ovarian cancer risk. The 4q32.3 ovarian cancer locus was not associated with ovarian cancer risk in the general population or in BRCA2 carriers and is the first indication of a BRCA1-specific risk locus for either breast or ovarian cancer. Furthermore, modeling the influence of these modifiers on cumulative risk of breast and ovarian cancer in BRCA1 mutation carriers for the first time showed that a wide range of individual absolute risks of each cancer can be estimated. These differences suggest that genetic risk modifiers may be incorporated into the clinical management of BRCA1 mutation carriers.

Triple-negative breast cancer (TNBC) is a malignant subtype of breast cancer with the absence of targeted therapy, resulting in poor prognosis in patients. Chemotherapy remains the mainstay of treatment for TNBC; however, development of drug resistance is the main obstacle for successful treatments. In recent years, long non-coding RNA (lncRNA) has been implicated in multiple biological functions in various diseases, particularly cancers. Accumulating evidence suggested that lncRNA nuclear paraspeckle assembly transcript 1 (NEAT1) expression is dysregulated in many human cancers and thus is a useful prognostic marker for cancer patients. Nevertheless, the mechanism of how NEAT1 confers drug resistance in TNBC is still largely unknown. We performed lncRNA profiling by the LncRNA Profiler qPCR Array Kit in normal control (NC) and breast cancers (BC) blood samples and further validated in a larger cohort of samples by qRT-PCR. Gene expression level and localization were investigated by qRT-PCR, western blotting, and immunofluorescence staining. Flow cytometric analysis was carried out to detect cancer stem cells. Functional studies were performed both in vitro and in vivo xenograft model. Among 90 lncRNAs, NEAT1 was highly expressed in the blood samples of breast cancer patients than in NC. In particular, the expression of NEAT1 was higher in TNBC tissues than other subgroups. Functional studies revealed that NEAT1 conferred oncogenic role by regulating apoptosis and cell cycle progression in TNBC cells. We identified that knockdown of NEAT1 sensitized cells to chemotherapy, indicating the involvement in chemoresistance. Importantly, shNEAT1 reduced stem cell populations such as CD44+/CD24−, ALDH+, and SOX2+, implicating that NEAT1 was closely related to cancer stemness in TNBC. Our data highlighted the roles of NEAT1 chemoresistance and cancer stemness, suggesting that it could be used as a new clinical therapeutic target for treating TNBC patients especially those with drug resistance.

We previously showed microRNAs (miRNAs) in plasma are potential biomarkers for colorectal cancer detection. Here, we aimed to develop specific blood-based miRNA assay for breast cancer detection. TaqMan-based miRNA profiling was performed in tumor, adjacent non-tumor, corresponding plasma from breast cancer patients, and plasma from matched healthy controls. All putative markers identified were verified in a training set of breast cancer patients. Selected markers were validated in a case-control cohort of 170 breast cancer patients, 100 controls, and 95 other types of cancers and then blindly validated in an independent set of 70 breast cancer patients and 50 healthy controls. Profiling results showed 8 miRNAs were concordantly up-regulated and 1 miRNA was concordantly down-regulated in both plasma and tumor tissue of breast cancer patients. Of the 8 up-regulated miRNAs, only 3 were significantly elevated (p<0.0001) before surgery and reduced after surgery in the training set. Results from the validation cohort showed that a combination of miR-145 and miR-451 was the best biomarker (p<0.0001) in discriminating breast cancer from healthy controls and all other types of cancers. In the blind validation, these plasma markers yielded Receiver Operating Characteristic (ROC) curve area of 0.931. The positive predictive value was 88% and the negative predictive value was 92%. Altered levels of these miRNAs in plasma have been detected not only in advanced stages but also early stages of tumors. The positive predictive value for ductal carcinoma in situ (DCIS) cases was 96%. These results suggested that these circulating miRNAs could be a potential specific biomarker for breast cancer screening.