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Ovarian cancer is the fifth leading cause of cancer death in women. Ovarian cancers display a high degree of complex genetic alterations involving many oncogenes and tumor suppressor genes. Analysis of the association between genetic alterations and clinical endpoints such as survival will lead to improved patient management via genetic stratification of patients into clinically relevant subgroups. In this study, we aim to define subgroups of high-grade serous ovarian carcinomas that differ with respect to prognosis and overall survival. Genome-wide DNA copy number alterations (CNAs) were measured in 72 clinically annotated, high-grade serous tumors using high-resolution oligonucleotide arrays. Two clinically annotated, independent cohorts were used for validation. Unsupervised hierarchical clustering of copy number data derived from the 72 patient cohort resulted in two clusters with significant difference in progression free survival (PFS) and a marginal difference in overall survival (OS). GISTIC analysis of the two clusters identified altered regions unique to each cluster. Supervised clustering of two independent large cohorts of high-grade serous tumors using the classification scheme derived from the two initial clusters validated our results and identified 8 genomic regions that are distinctly different among the subgroups. These 8 regions map to 8p21.3, 8p23.2, 12p12.1, 17p11.2, 17p12, 19q12, 20q11.21 and 20q13.12; and harbor potential oncogenes and tumor suppressor genes that are likely to be involved in the pathogenesis of ovarian carcinoma. We have identified a set of genetic alterations that could be used for stratification of high-grade serous tumors into clinically relevant treatment subgroups.

Alterations in stromal tissue components can inhibit or promote epithelial tumorigenesis. Decorin (DCN) and lumican (LUM) show reduced stromal expression in serous epithelial ovarian cancer (sEOC). We hypothesized that common variants in these genes associate with risk. Associations with sEOC among Caucasians were estimated with odds ratios (OR) among 397 cases and 920 controls in two U.S.-based studies (discovery set), 436 cases and 1,098 controls in Australia (replication set 1) and a consortium of 15 studies comprising 1,668 cases and 4,249 controls (replication set 2). The discovery set and replication set 1 (833 cases and 2,013 controls) showed statistically homogeneous (Pheterogeneity≥0.48) decreased risks of sEOC at four variants: DCN rs3138165, rs13312816 and rs516115, and LUM rs17018765 (OR = 0.6 to 0.9; Ptrend = 0.001 to 0.03). Results from replication set 2 were statistically homogeneous (Pheterogeneity≥0.13) and associated with increased risks at DCN rs3138165 and rs13312816, and LUM rs17018765: all ORs = 1.2; Ptrend≤0.02. The ORs at the four variants were statistically heterogeneous across all 18 studies (Pheterogeneity≤0.03), which precluded combining. In post-hoc analyses, interactions were observed between each variant and recruitment period (Pinteraction≤0.003), age at diagnosis (Pinteraction = 0.04), and year of diagnosis (Pinteraction = 0.05) in the five studies with available information (1,044 cases, 2,469 controls). We conclude that variants in DCN and LUM are not directly associated with sEOC, and that confirmation of possible effect modification of the variants by non-genetic factors is required.

BackgroundA sensitive assay to identify biomarkers using non-invasively collected clinical specimens is ideal for breast cancer detection. While there are other studies showing disease biomarkers in saliva for breast cancer, our study tests the hypothesis that there are breast cancer discriminatory biomarkers in saliva using de novo discovery and validation approaches. This is the first study of this kind and no other study has engaged a de novo biomarker discovery approach in saliva for breast cancer detection. In this study, a case-control discovery and independent preclinical validations were conducted to evaluate the performance and translational utilities of salivary transcriptomic and proteomic biomarkers for breast cancer detection.Methodology/principal findingsSalivary transcriptomes and proteomes of 10 breast cancer patients and 10 matched controls were profiled using Affymetrix HG-U133-Plus-2.0 Array and two-dimensional difference gel electrophoresis (2D-DIGE), respectively. Preclinical validations were performed to evaluate the discovered biomarkers in an independent sample cohort of 30 breast cancer patients and 63 controls using RT-qPCR (transcriptomic biomarkers) and quantitative protein immunoblot (proteomic biomarkers). Transcriptomic and proteomic profiling revealed significant variations in salivary molecular biomarkers between breast cancer patients and matched controls. Eight mRNA biomarkers and one protein biomarker, which were not affected by the confounding factors, were pre-validated, yielding an accuracy of 92% (83% sensitive, 97% specific) on the preclinical validation sample set.ConclusionsOur findings support that transcriptomic and proteomic signatures in saliva can serve as biomarkers for the non-invasive detection of breast cancer. The salivary biomarkers possess discriminatory power for the detection of breast cancer, with high specificity and sensitivity, which paves the way for prediction model validation study followed by pivotal clinical validation.

Epithelial ovarian cancer (EOC) is the leading cause of death from gynecological malignancy in the developed world, accounting for 4% of the deaths from cancer in women. We performed a three-phase genome-wide association study of EOC survival in 8,951 individuals with EOC (cases) with available survival time data and a parallel association analysis of EOC susceptibility. Two SNPs at 19p13.11, rs8170 and rs2363956, showed evidence of association with survival (overall P = 5 × 10⁻⁴ and P = 6 × 10⁻⁴, respectively), but they did not replicate in phase 3. However, the same two SNPs demonstrated genome-wide significance for risk of serous EOC (P = 3 × 10⁻⁹ and P = 4 × 10⁻¹¹, respectively). Expression analysis of candidate genes at this locus in ovarian tumors supported a role for the BRCA1-interacting gene C19orf62, also known as MERIT40, which contains rs8170, in EOC development.

This study was initiated to identify biomarkers with potential value for the early detection of poor-outcome breast cancer. Two sets of well-characterized tissues were utilized: one from breast cancer patients with favorable vs. poor outcome and the other from healthy women undergoing reduction mammaplasty. Over 46 differentially expressed genes were identified from a large list of potential targets by a) mining publicly available expression data (identifying 134 genes for quantitative PCR) and b) utilizing a commercial PCR array. Three genes show elevated expression in cancers with poor outcome and low expression in all other tissues, warranting further investigation as potential blood markers for early detection of cancers with poor outcome. Twelve genes showed lower expression in cancers with poor outcome than in cancers with favorable outcome but no differential expression between aggressive cancers and most healthy controls. These genes are more likely to be useful as prognostic tissue markers than as serum markers for early detection of aggressive disease. As a secondary finding was that, when histologically normal breast tissue was removed from a distant site in a breast with cancer, 7 of 38 specimens displayed a cancer-like expression profile, while the remaining 31 were genetically similar to the reduction mammaplasty control group. This finding suggests that some regions of ipsilateral histologically 'normal' breast tissue are predisposed to becoming malignant and that normal-appearing tissue with malignant signature might warrant treatment to prevent new primary tumors.

Background: A sensitive assay to identify biomarkers using non-invasively collected clinical specimens is ideal for breast cancer detection. While there are other studies showing disease biomarkers in saliva for breast cancer, our study tests the hypothesis that there are breast cancer discriminatory biomarkers in saliva using de novo discovery and validation approaches. This is the first study of this kind and no other study has engaged a de novo biomarker discovery approach in saliva for breast cancer detection. In this study, a case-control discovery and independent preclinical validations were conducted to evaluate the performance and translational utilities of salivary transcriptomic and proteomic biomarkers for breast cancer detection. Methodology/Principal Findings: Salivary transcriptomes and proteomes of 10 breast cancer patients and 10 matched controls were profiled using Affymetrix HG-U133-Plus-2.0 Array and two-dimensional difference gel electrophoresis (2DDIGE), respectively. Preclinical validations were performed to evaluate the discovered biomarkers in an independent sample cohort of 30 breast cancer patients and 63 controls using RT-qPCR (transcriptomic biomarkers) and quantitative protein immunoblot (proteomic biomarkers). Transcriptomic and proteomic profiling revealed significant variations in salivary molecular biomarkers between breast cancer patients and matched controls. Eight mRNA biomarkers and one protein biomarker, which were not affected by the confounding factors, were pre-validated, yielding an accuracy of 92% (83% sensitive, 97% specific) on the preclinical validation sample set. Conclusions: Our findings support that transcriptomic and proteomic signatures in saliva can serve as biomarkers for the non-invasive detection of breast cancer. The salivary biomarkers possess discriminatory power for the detection of breast cancer, with high specificity and sensitivity, which paves the way for prediction model validation study followed by pivotal clinical validation. [ABSTRACT FROM AUTHOR]

Introduction: Several common alleles have been shown to be associated with breast and/or ovarian cancer risk for BRCA1 and BRCA2 mutation carriers. Recent genome-wide association studies of breast cancer have identified eight additional breast cancer susceptibility loci: rs1011970 (9p21, CDKN2A/B), rs10995190 (ZNF365), rs704010 (ZMIZ1), rs2380205 (10p15), rs614367 (11q13), rs1292011 (12q24), rs10771399 (12p11 near PTHLH) and rs865686 (9q31.2). Methods: To evaluate whether these single nucleotide polymorphisms (SNPs) are associated with breast cancer risk for BRCA1 and BRCA2 carriers, we genotyped these SNPs in 12,599 BRCA1 and 7,132 BRCA2 mutation carriers and analysed the associations with breast cancer risk within a retrospective likelihood framework. Results: Only SNP rs10771399 near PTHLH was associated with breast cancer risk for BRCA1 mutation carriers \((per-allele hazard ratio (HR) = 0.87, 95% CI: 0.81 to 0.94, P-trend = 3 × 10^{-4})\). The association was restricted to mutations proven or predicted to lead to absence of protein expression \((HR = 0.82, 95% CI: 0.74 to 0.90, P-trend = 3.1 × 10^{-5}, P-difference = 0.03)\). Four SNPs were associated with the risk of breast cancer for BRCA2 mutation carriers: rs10995190, P-trend = 0.015; rs1011970, P-trend = 0.048; rs865686, 2df-P = 0.007; rs1292011 2df-P = 0.03. rs10771399 (PTHLH) was predominantly associated with estrogen receptor (ER)-negative breast cancer for BRCA1 mutation carriers \((HR = 0.81, 95% CI: 0.74 to 0.90, P-trend = 4 × 10^{-5})\) and there was marginal evidence of association with ER-negative breast cancer for BRCA2 mutation carriers (HR = 0.78, 95% CI: 0.62 to 1.00, P-trend = 0.049). Conclusions: The present findings, in combination with previously identified modifiers of risk, will ultimately lead to more accurate risk prediction and an improved understanding of the disease etiology in BRCA1 and BRCA2 mutation carriers.

Background: We previously reported significant associations between genetic variants in insulin receptor substrate 1 (IRS1) and breast cancer risk in women carrying BRCA1 mutations. The objectives of this study were to investigate whether the IRS1 variants modified ovarian cancer risk and were associated with breast cancer risk in a larger cohort of BRCA1 and BRCA2 mutation carriers., Methods: IRS1 rs1801123, rs1330645, and rs1801278 were genotyped in samples from 36 centers in the Consortium of Investigators of Modifiers of BRCA1/2 (CIMBA). Data were analyzed by a retrospective cohort approach modeling the associations with breast and ovarian cancer risks simultaneously. Analyses were stratified by BRCA1 and BRCA2 status and mutation class in BRCA1 carriers., Results: Rs1801278 (Gly972Arg) was associated with ovarian cancer risk for both BRCA1 (HR, 1.43; 95% confidence interval (CI), 1.06-1.92; P = 0.019) and BRCA2 mutation carriers (HR, 2.21; 95% CI, 1.39-3.52, P = 0.0008). For BRCA1 mutation carriers, the breast cancer risk was higher in carriers with class II mutations than class I mutations (class II HR, 1.86; 95% CI, 1.28-2.70; class I HR, 0.86; 95%CI, 0.69-1.09; P(difference), 0.0006). Rs13306465 was associated with ovarian cancer risk in BRCA1 class II mutation carriers (HR, 2.42; P = 0.03)., Conclusion: The IRS1 Gly972Arg single-nucleotide polymorphism, which affects insulin-like growth factor and insulin signaling, modifies ovarian cancer risk in BRCA1 and BRCA2 mutation carriers and breast cancer risk in BRCA1 class II mutation carriers., Impact: These findings may prove useful for risk prediction for breast and ovarian cancers in BRCA1 and BRCA2 mutation carriers., (©2012 AACR.)

Germline mutations in BRCA1 and BRCA2 are associated with increased risks of breast and ovarian cancer. A genome-wide association study (GWAS) identified six alleles associated with risk of ovarian cancer for women in the general population. We evaluated four of these loci as potential modifiers of ovarian cancer risk for BRCA1 and BRCA2 mutation carriers. Four single-nucleotide polymorphisms (SNPs), rs10088218 (at 8q24), rs2665390 (at 3q25), rs717852 (at 2q31), and rs9303542 (at 17q21), were genotyped in 12,599 BRCA1 and 7,132 BRCA2 carriers, including 2,678 ovarian cancer cases. Associations were evaluated within a retrospective cohort approach. All four loci were associated with ovarian cancer risk in BRCA2 carriers; rs10088218 per-allele hazard ratio (HR) = 0.81 (95% CI: 0.67-0.98) P-trend = 0.033, rs2665390 HR = 1.48 (95% CI: 1.21-1.83) P-trend = 1.8 × 10(-4), rs717852 HR = 1.25 (95% CI: 1.10-1.42) P-trend = 6.6 × 10(-4), rs9303542 HR = 1.16 (95% CI: 1.02-1.33) P-trend = 0.026. Two loci were associated with ovarian cancer risk in BRCA1 carriers; rs10088218 per-allele HR = 0.89 (95% CI: 0.81-0.99) P-trend = 0.029, rs2665390 HR = 1.25 (95% CI: 1.10-1.42) P-trend = 6.1 × 10(-4). The HR estimates for the remaining loci were consistent with odds ratio estimates for the general population. The identification of multiple loci modifying ovarian cancer risk may be useful for counseling women with BRCA1 and BRCA2 mutations regarding their risk of ovarian cancer., (© 2012 Wiley Periodicals, Inc.)

Background: Previously, small studies have found that BRCA1 and BRCA2 breast tumors differ in their pathology. Analysis of larger datasets of mutation carriers should allow further tumor characterization., Methods: We used data from 4,325 BRCA1 and 2,568 BRCA2 mutation carriers to analyze the pathology of invasive breast, ovarian, and contralateral breast cancers., Results: There was strong evidence that the proportion of estrogen receptor (ER)-negative breast tumors decreased with age at diagnosis among BRCA1 (P-trend = 1.2 × 10(-5)), but increased with age at diagnosis among BRCA2, carriers (P-trend = 6.8 × 10(-6)). The proportion of triple-negative tumors decreased with age at diagnosis in BRCA1 carriers but increased with age at diagnosis of BRCA2 carriers. In both BRCA1 and BRCA2 carriers, ER-negative tumors were of higher histologic grade than ER-positive tumors (grade 3 vs. grade 1; P = 1.2 × 10(-13) for BRCA1 and P = 0.001 for BRCA2). ER and progesterone receptor (PR) expression were independently associated with mutation carrier status [ER-positive odds ratio (OR) for BRCA2 = 9.4, 95% CI: 7.0-12.6 and PR-positive OR = 1.7, 95% CI: 1.3-2.3, under joint analysis]. Lobular tumors were more likely to be BRCA2-related (OR for BRCA2 = 3.3, 95% CI: 2.4-4.4; P = 4.4 × 10(-14)), and medullary tumors BRCA1-related (OR for BRCA2 = 0.25, 95% CI: 0.18-0.35; P = 2.3 × 10(-15)). ER-status of the first breast cancer was predictive of ER-status of asynchronous contralateral breast cancer (P = 0.0004 for BRCA1; P = 0.002 for BRCA2). There were no significant differences in ovarian cancer morphology between BRCA1 and BRCA2 carriers (serous: 67%; mucinous: 1%; endometrioid: 12%; clear-cell: 2%). CONCLUSIONS/IMPACT: Pathologic characteristics of BRCA1 and BRCA2 tumors may be useful for improving risk-prediction algorithms and informing clinical strategies for screening and prophylaxis.

Purpose: Cell-based approaches were used to identify genetic markers predictive of patients' risk for poor response prior to chemotherapy., Experimental Design: We conducted genome-wide association studies (GWAS) to identify single-nucleotide polymorphisms (SNP) associated with cellular sensitivity to carboplatin through their effects on mRNA expression using International HapMap lymphoblastoid cell lines (LCL) and replicated them in additional LCLs. SNPs passing both stages of the cell-based study were tested for association with progression-free survival (PFS) in patients. Phase 1 validation was based on 377 ovarian cancer patients receiving at least four cycles of carboplatin and paclitaxel from the Australian Ovarian Cancer Study (AOCS). Positive associations were then assessed in phase 2 validation analysis of 1,326 patients from the Ovarian Cancer Association Consortium and The Cancer Genome Atlas., Results: In the initial GWAS, 342 SNPs were associated with carboplatin-induced cytotoxicity, of which 18 unique SNPs were retained after assessing their association with gene expression. One SNP (rs1649942) was replicated in an independent LCL set (Bonferroni adjusted P < 0.05). It was found to be significantly associated with decreased PFS in phase 1 AOCS patients (P(per-allele) = 2 × 10(-2)), with a stronger effect in the subset of women with optimally debulked tumors (P(per-allele) = 4 × 10(-3)). rs1649942 was also associated with poorer overall survival in women with optimally debulked tumors (P(per-allele) = 9 × 10(-3)). However, this SNP was not significant in phase 2 validation analysis with patients from numerous cohorts., Conclusion: This study shows the potential of cell-based, genome-wide approaches to identify germline predictors of treatment outcome and highlights the need for extensive validation in patients to assess their clinical effect., (©2011 AACR.)

Purpose: Secondary somatic BRCA1/2 mutations may restore BRCA1/2 protein in hereditary ovarian carcinomas. In cell lines, BRCA2 restoration mediates resistance to platinum chemotherapy and poly (ADP-ribose) polymerase (PARP) inhibitors. We assessed primary and recurrent BRCA1/2-mutated ovarian carcinomas to define the frequency of secondary mutations and correlate these changes with clinical outcomes., Methods: Neoplastic cells were isolated with laser capture microdissection, and DNA was sequenced at the site of the known germline BRCA1/2 mutation. When secondary mutations were found that restored wild-type sequence, haplotyping was performed using single nucleotide polymorphisms in tumor and paired lymphocyte DNA to rule out retention of the wild-type allele., Results: There were 64 primary and 46 recurrent ovarian carcinomas assessed. Thirteen (28.3%) of 46 (95% CI, 17.3% to 42.6%) recurrent carcinomas had a secondary mutation compared with two (3.1%) of 64 (95% CI, 1.0% to 10.7%) primary carcinomas (P = .0003, Fisher's exact test). Twelve (46.2%) of 26 (95% CI, 28.7% to 64.7%) platinum-resistant recurrences had secondary mutations restoring BRCA1/2, compared with one (5.3%) of 19 (95% CI, 1.2% to 24.8%) platinum-sensitive recurrences (P = .003, Fisher's exact test). Six (66.7%) of nine (95% CI, 34.8% to 87.8%) women with prior breast carcinoma had a recurrent carcinoma with a secondary mutation, compared with six (17.1%) of 35 (95% CI, 8.2% to 32.8%) with no history of breast carcinoma (P = .007, Fisher's exact test)., Conclusion: Secondary somatic mutations that restore BRCA1/2 in carcinomas from women with germline BRCA1/2 mutations predict resistance to platinum chemotherapy and may also predict resistance to PARP inhibitors. These mutations were detectable only in ovarian carcinomas of women whom have had previous chemotherapy, either for ovarian or breast carcinoma.

Background: Invasive ovarian cancer is a significant cause of gynecologic cancer mortality., Methods: We examined whether this mortality was associated with inherited variation in approximately 170 candidate genes/regions [993 single-nucleotide polymorphisms (SNPs)] in a multistage analysis based initially on 312 Mayo Clinic cases (172 deaths). Additional analyses used The Cancer Genome Atlas (TCGA; 127 cases, 62 deaths). For the most compelling gene, we immunostained Mayo Clinic tissue microarrays (TMA, 326 cases) and conducted consortium-based SNP replication analysis (2,560 cases, 1,046 deaths)., Results: The strongest initial mortality association was in HGF (hepatocyte growth factor) at rs1800793 (HR = 1.7, 95% CI = 1.3-2.2, P = 2.0 × 10(-5)) and with overall variation in HGF (gene-level test, P = 3.7 × 10(-4)). Analysis of TCGA data revealed consistent associations [e.g., rs5745709 (r(2) = 0.96 with rs1800793): TCGA HR = 2.4, CI = 1.4-4.1, P = 2.2 × 10(-3); Mayo Clinic + TCGA HR = 1.6, CI = 1.3-1.9, P = 7.0 × 10(-5)] and suggested genotype correlation with reduced HGF mRNA levels (P = 0.01). In Mayo Clinic TMAs, protein levels of HGF, its receptor MET (C-MET), and phospho-MET were not associated with genotype and did not serve as an intermediate phenotype; however, phospho-MET was associated with reduced mortality (P = 0.01) likely due to higher expression in early-stage disease. In eight additional ovarian cancer case series, HGF rs5745709 was not associated with mortality (HR = 1.0, CI = 0.9-1.1, P = 0.87)., Conclusions: We conclude that although HGF signaling is critical to migration, invasion, and apoptosis, it is unlikely that HGF genetic variation plays a major role in ovarian cancer mortality. Furthermore, any minor role is not related to genetically-determined expression., Impact: Our study shows the utility of multiple data types and multiple data sets in observational studies., (©2011 AACR.)

Purpose: An assay for the single-nucleotide polymorphism (SNP), rs61764370, has recently been commercially marketed as a clinical test to aid ovarian cancer risk evaluation in women with family histories of the disease. rs67164370 is in a 3'-UTR miRNA binding site of the KRAS oncogene and is a candidate for epithelial ovarian cancer (EOC) susceptibility. However, only one published article, analyzing fewer than 1,000 subjects in total, has examined this association., Experimental Design: Risk association was evaluated in 8,669 cases of invasive EOC and 10,012 controls from 19 studies participating in the Ovarian Cancer Association Consortium, and in 683 cases and 2,044 controls carrying BRCA1 mutations from studies in the Consortium of Investigators of Modifiers of BRCA1/2. Prognosis association was also examined in a subset of five studies with progression-free survival (PFS) data and 18 studies with all-cause mortality data., Results: No evidence of association was observed between genotype and risk of unselected EOC (OR = 1.02, 95% CI: 0.95-1.10), serous EOC (OR = 1.08, 95% CI: 0.98-1.18), familial EOC (OR = 1.09, 95% CI: 0.78-1.54), or among women carrying deleterious mutations in BRCA1 (OR = 1.09, 95% CI: 0.88-1.36). There was little evidence for association with survival time among unselected cases (HR = 1.10, 95% CI: 0.99-1.22), among serous cases (HR = 1.12, 95% CI = 0.99-1.28), or with PFS in 540 cases treated with carboplatin and paclitaxel (HR = 1.18, 95% CI: 0.93-1.52)., Conclusions: These data exclude the possibility of an association between rs61764370 and a clinically significant risk of ovarian cancer or of familial ovarian cancer. Use of this SNP for ovarian cancer clinical risk prediction, therefore, seems unwarranted., (©2011 AACR.)

Introduction: Previous studies have demonstrated that common breast cancer susceptibility alleles are differentially associated with breast cancer risk for BRCA1 and/or BRCA2 mutation carriers. It is currently unknown how these alleles are associated with different breast cancer subtypes in BRCA1 and BRCA2 mutation carriers defined by estrogen (ER) or progesterone receptor (PR) status of the tumour., Methods: We used genotype data on up to 11,421 BRCA1 and 7,080 BRCA2 carriers, of whom 4,310 had been affected with breast cancer and had information on either ER or PR status of the tumour, to assess the associations of 12 loci with breast cancer tumour characteristics. Associations were evaluated using a retrospective cohort approach., Results: The results suggested stronger associations with ER-positive breast cancer than ER-negative for 11 loci in both BRCA1 and BRCA2 carriers. Among BRCA1 carriers, single nucleotide polymorphism (SNP) rs2981582 (FGFR2) exhibited the biggest difference based on ER status (per-allele hazard ratio (HR) for ER-positive = 1.35, 95% CI: 1.17 to 1.56 vs HR = 0.91, 95% CI: 0.85 to 0.98 for ER-negative, P-heterogeneity = 6.5 × 10-6). In contrast, SNP rs2046210 at 6q25.1 near ESR1 was primarily associated with ER-negative breast cancer risk for both BRCA1 and BRCA2 carriers. In BRCA2 carriers, SNPs in FGFR2, TOX3, LSP1, SLC4A7/NEK10, 5p12, 2q35, and 1p11.2 were significantly associated with ER-positive but not ER-negative disease. Similar results were observed when differentiating breast cancer cases by PR status., Conclusions: The associations of the 12 SNPs with risk for BRCA1 and BRCA2 carriers differ by ER-positive or ER-negative breast cancer status. The apparent differences in SNP associations between BRCA1 and BRCA2 carriers, and non-carriers, may be explicable by differences in the prevalence of tumour subtypes. As more risk modifying variants are identified, incorporating these associations into breast cancer subtype-specific risk models may improve clinical management for mutation carriers.

The known breast cancer susceptibility polymorphisms in FGFR2, TNRC9/TOX3, MAP3K1, LSP1, and 2q35 confer increased risks of breast cancer for BRCA1 or BRCA2 mutation carriers. We evaluated the associations of 3 additional single nucleotide polymorphisms (SNPs), rs4973768 in SLC4A7/NEK10, rs6504950 in STXBP4/COX11, and rs10941679 at 5p12, and reanalyzed the previous associations using additional carriers in a sample of 12,525 BRCA1 and 7,409 BRCA2 carriers. Additionally, we investigated potential interactions between SNPs and assessed the implications for risk prediction. The minor alleles of rs4973768 and rs10941679 were associated with increased breast cancer risk for BRCA2 carriers (per-allele HR = 1.10, 95% CI: 1.03-1.18, P = 0.006 and HR = 1.09, 95% CI: 1.01-1.19, P = 0.03, respectively). Neither SNP was associated with breast cancer risk for BRCA1 carriers, and rs6504950 was not associated with breast cancer for either BRCA1 or BRCA2 carriers. Of the 9 polymorphisms investigated, 7 were associated with breast cancer for BRCA2 carriers (FGFR2, TOX3, MAP3K1, LSP1, 2q35, SLC4A7, 5p12, P = 7 × 10(-11) - 0.03), but only TOX3 and 2q35 were associated with the risk for BRCA1 carriers (P = 0.0049, 0.03, respectively). All risk-associated polymorphisms appear to interact multiplicatively on breast cancer risk for mutation carriers. Based on the joint genotype distribution of the 7 risk-associated SNPs in BRCA2 mutation carriers, the 5% of BRCA2 carriers at highest risk (i.e., between 95th and 100th percentiles) were predicted to have a probability between 80% and 96% of developing breast cancer by age 80, compared with 42% to 50% for the 5% of carriers at lowest risk. Our findings indicated that these risk differences might be sufficient to influence the clinical management of mutation carriers.

Purpose: To measure circulating antigens, sandwich ELISA assays require two complementary affinity reagents. Mouse monoclonal antibodies (mAb) and polyclonal antibodies (pAb) are commonly used, but because their production is lengthy and costly, recombinant antibodies are emerging as an attractive alternative., Experimental Design: We developed a new class of recombinant antibodies called biobodies (Bb) and compared them to mAb for use in serodiagnosis. Bbs were secreted biotinylated in vivo by diploid yeast and used as affinity reagents after Ni purification. Bead-based assays for HE4 and mesothelin were developed using Bbs in combination with pAbs (Bb/pAb assays). To assess precision, reproducibility studies were done using four runs of 16 replicates at six analyte levels for each marker. Pearson correlations and receiver-operator characteristic analyses were done in 214 patient serum samples to directly compare the Bb/pAb assays to mAb assays. Diagnostic performance of the Bb/pAb assay was further assessed in an expanded set of 336 ovarian cancer cases and controls., Results: On average across analyte levels, Bb/pAb assays yielded within-run and between-run coefficients of variations of 11.7 and 23.8, respectively, for HE4 and 14.0 and 14.5, respectively, for mesothelin. In the subset (n = 214), Pearson correlations of 0.95 for HE4 and 0.92 for mesothelin were observed between mAb and Bb/pAb assays. The area under the curves for the mAb and Bb/pAb assays were not significantly different for HE4 (0.88 and 0.84, respectively; P = 0.20) or mesothelin (0.74 and 0.72, respectively; P = 0.38)., Conclusion: Yeast-secreted Bbs can be used reliably in cost-effective yet highly sensitive bead-based assays for use in large validation studies.