CpG island hypermethylation of BRCA1 and loss of pRb as co-occurring events in basal/triple-negative breast cancer

Triple-negative breast cancer (TNBC) occurs in approximately 15% of all breast cancer patients, and the incidence of TNBC is greatly increased in BRCA1 mutation carriers. This study aimed to assess the impact of BRCA1 promoter methylation with respect to breast cancer subtypes in sporadic disease. Tissue microarrays (TMAs) were constructed representing tumors from 303 patients previously screened for BRCA1 germline mutations, of which a subset of 111 sporadic tumors had previously been analyzed with respect to BRCA1 methylation. Additionally, a set of eight tumors from BRCA1 mutation carriers were included on the TMAs. Expression analysis was performed on TMAs by immunohistochemistry (IHC) for BRCA1, pRb, p16, p53, PTEN, ER, PR, HER2, CK5/6, CK8, CK18, EGFR, MUC1, and Ki-67. Data on BRCA1 aberrations and IHC expression was examined with respect to breast cancer-specific survival. The results demonstrate that CpG island hypermethylation of BRCA1 significantly associates with the basal/triple-negative subtype. Low expression of pRb, and high/intense p16, were associated with BRCA1 promoter hypermethylation, and the same effects were seen in BRCA1 mutated tumors. The expression patterns of BRCA1, pRb, p16 and PTEN were highly correlated, and define a subgroup of TNBCs characterized by BRCA1 aberrations, high Ki-67 (≥ 40%) and favorable disease outcome. In conclusion, our findings demonstrate that epigenetic inactivation of the BRCA1 gene associates with RB/p16 dysfunction in promoting TNBCs. The clinical implications relate to the potential use of targeted treatment based on PARP inhibitors in sporadic TNBCs, wherein CpG island hypermethylation of BRCA1 represents a potential marker of therapeutic response

Immunohistochemistry profiles of breast ductal carcinoma: factor analysis of digital image analysis data

<p>Abstract</p> <p>Background</p> <p>Molecular studies of breast cancer revealed biological heterogeneity of the disease and opened new perspectives for personalized therapy. While multiple gene expression-based systems have been developed, current clinical practice is largely based upon conventional clinical and pathologic criteria. This gap may be filled by development of combined multi-IHC indices to characterize biological and clinical behaviour of the tumours. Digital image analysis (DA) with multivariate statistics of the data opens new opportunities in this field.</p> <p>Methods</p> <p>Tissue microarrays of 109 patients with breast ductal carcinoma were stained for a set of 10 IHC markers (ER, PR, HER2, Ki67, AR, BCL2, HIF-1α, SATB1, p53, and p16). Aperio imaging platform with the Genie, Nuclear and Membrane algorithms were used for the DA. Factor analysis of the DA data was performed in the whole group and hormone receptor (HR) positive subgroup of the patients (n = 85).</p> <p>Results</p> <p>Major factor potentially reflecting aggressive disease behaviour (i-Grade) was extracted, characterized by opposite loadings of ER/PR/AR/BCL2 and Ki67/HIF-1α. The i-Grade factor scores revealed bimodal distribution and were strongly associated with higher Nottingham histological grade (G) and more aggressive intrinsic subtypes. In HR-positive tumours, the aggressiveness of the tumour was best defined by positive Ki67 and negative ER loadings. High Ki67/ER factor scores were strongly associated with the higher G and Luminal B types, but also were detected in a set of G1 and Luminal A cases, potentially indicating high risk patients in these categories. Inverse relation between HER2 and PR expression was found in the HR-positive tumours pointing at differential information conveyed by the ER and PR expression. SATB1 along with HIF-1α reflected the second major factor of variation in our patients; in the HR-positive group they were inversely associated with the HR and BCL2 expression and represented the major factor of variation. Finally, we confirmed high expression levels of p16 in Triple-negative tumours.</p> <p>Conclusion</p> <p>Factor analysis of multiple IHC biomarkers measured by automated DA is an efficient exploratory tool clarifying complex interdependencies in the breast ductal carcinoma IHC profiles and informative value of single IHC markers. Integrated IHC indices may provide additional risk stratifications for the currently used grading systems and prove to be useful in clinical outcome studies.</p> <p>Virtual Slides</p> <p>The virtual slide(s) for this article can be found here: <url>http://www.diagnosticpathology.diagnomx.eu/vs/1512077125668949</url></p

GWAS of bone size yields twelve loci that also affect height, BMD, osteoarthritis or fractures

© 2019, The Author(s). Bone area is one measure of bone size that is easily derived from dual-energy X-ray absorptiometry (DXA) scans. In a GWA study of DXA bone area of the hip and lumbar spine (N ≥ 28,954), we find thirteen independent association signals at twelve loci that replicate in samples of European and East Asian descent (N = 13,608 – 21,277). Eight DXA area loci associate with osteoarthritis, including rs143384 in GDF5 and a missense variant in COL11A1 (rs3753841). The strongest DXA area association is with rs11614913[T] in the microRNA MIR196A2 gene that associates with lumbar spine area (P = 2.3 × 10−42, β = −0.090) and confers risk of hip fracture (P = 1.0 × 10−8, OR = 1.11). We demonstrate that the risk allele is less efficient in repressing miR-196a-5p target genes. We also show that the DXA area measure contributes to the risk of hip fracture independent of bone density

A genome-wide association study with 1,126,563 individuals identifies new risk loci for Alzheimer's disease

Late-onset Alzheimer’s disease is a prevalent age-related polygenic disease that accounts for 50–70% of dementia cases. Currently, only a fraction of the genetic variants underlying Alzheimer’s disease have been identified. Here we show that increased sample sizes allowed identification of seven previously unidentified genetic loci contributing to Alzheimer’s disease. This study highlights microglia, immune cells and protein catabolism as relevant to late-onset Alzheimer’s disease, while identifying and prioritizing previously unidentified genes of potential interest. We anticipate that these results can be included in larger meta-analyses of Alzheimer’s disease to identify further genetic variants that contribute to Alzheimer’s pathology

High frequency of pathogenic non-founder germline mutations in BRCA1 and BRCA2 in families with breast and ovarian cancer in a founder population

Funding Information: This work was supported by State Research Program “Biomedicine for the public health (BIOMEDICINE)” project 5 “Personalised cancer diagnostics and treatment effectiveness evaluation”. Publisher Copyright: © 2018 The Author(s).Background: Pathogenic BRCA1 founder mutations (c.4035delA, c.5266dupC) contribute to 3.77% of all consecutive primary breast cancers and 9.9% of all consecutive primary ovarian cancers. Identifying germline pathogenic gene variants in patients with primary breast and ovarian cancer could significantly impact the medical management of patients. The aim of the study was to evaluate the rate of pathogenic mutations in the 26 breast and ovarian cancer susceptibility genes in patients who meet the criteria for BRCA1/2 testing and to compare the accuracy of different selection criteria for second-line testing in a founder population. Methods: Fifteen female probands and 1 male proband that met National Comprehensive Cancer Network (NCCN) criteria for BRCA1/2 testing were included in the study and underwent 26-gene panel testing. Fourteen probands had breast cancer, one proband had ovarian cancer, and one proband had both breast and ovarian cancer. In a 26-gene panel, the following breast and/or ovarian cancer susceptibility genes were included: ATM, BARD1, BLM, BRCA1, BRCA2, BRIP1, CDH1, CHEK2, EPCAM, FAM175A, MEN1, MLH1, MRE11A, MSH2, MSH6, MUTYH, NBN, PALB2, PMS2, PTEN, RAD50, RAD51C, RAD51D, STK11, TP53, and XRCC2. All patients previously tested negative for BRCA1 founder mutations. Results: In 44% (7 out of 16) of tested probands, pathogenic mutations were identified. Six probands carried pathogenic mutations in BRCA1, and one proband carried pathogenic mutations in BRCA2. In patients, a variant of uncertain significance was found in BRCA2, RAD50, MRE11A and CDH1. The Manchester scoring system showed a high accuracy (87.5%), high sensitivity (85.7%) and high specificity (88.9%) for the prediction of pathogenic non-founder BRCA1/2 mutations. Conclusion: A relatively high incidence of pathogenic non-founder BRCA1/2 mutations was observed in a founder population. The Manchester scoring system predicted the probability of non-founder pathogenic mutations with high accuracy.publishersversionPeer reviewe

Germline Variation Controls the Architecture of Somatic Alterations in Tumors

Studies have suggested that somatic events in tumors can depend on an individual's constitutional genotype. We used squamous cell carcinomas (SCC) of the skin, which arise in high multiplicity in organ transplant recipients, as a model to compare the pattern of somatic alterations within and across individuals. Specifically, we performed array comparative genomic hybridization on 104 tumors from 25 unrelated individuals who each had three or more independently arisen SCCs and compared the profiles occurring within patients to profiles of tumors across a larger set of 135 patients. In general, chromosomal aberrations in SCCs were more similar within than across individuals (two-sided exact-test p-value ), consistent with the notion that the genetic background was affecting the pattern of somatic changes. To further test this possibility, we performed allele-specific imbalance studies using microsatellite markers mapping to 14 frequently aberrant regions of multiple independent tumors from 65 patients. We identified nine loci which show evidence of preferential allelic imbalance. One of these loci, 8q24, corresponded to a region in which multiple single nucleotide polymorphisms have been associated with increased cancer risk in genome-wide association studies (GWAS). We tested three implicated variants and identified one, rs13281615, with evidence of allele-specific imbalance (p-value = 0.012). The finding of an independently identified cancer susceptibility allele with allele-specific imbalance in a genomic region affected by recurrent DNA copy number changes suggest that it may also harbor risk alleles for SCC. Together these data provide strong evidence that the genetic background is a key driver of somatic events in cancer, opening an opportunity to expand this approach to identify cancer risk alleles

Use of DNA–Damaging Agents and RNA Pooling to Assess Expression Profiles Associated with BRCA1 and BRCA2 Mutation Status in Familial Breast Cancer Patients

A large number of rare sequence variants of unknown clinical significance have been identified in the breast cancer susceptibility genes, BRCA1 and BRCA2. Laboratory-based methods that can distinguish between carriers of pathogenic mutations and non-carriers are likely to have utility for the classification of these sequence variants. To identify predictors of pathogenic mutation status in familial breast cancer patients, we explored the use of gene expression arrays to assess the effect of two DNA–damaging agents (irradiation and mitomycin C) on cellular response in relation to BRCA1 and BRCA2 mutation status. A range of regimes was used to treat 27 lymphoblastoid cell-lines (LCLs) derived from affected women in high-risk breast cancer families (nine BRCA1, nine BRCA2, and nine non-BRCA1/2 or BRCAX individuals) and nine LCLs from healthy individuals. Using an RNA–pooling strategy, we found that treating LCLs with 1.2 µM mitomycin C and measuring the gene expression profiles 1 hour post-treatment had the greatest potential to discriminate BRCA1, BRCA2, and BRCAX mutation status. A classifier was built using the expression profile of nine QRT–PCR validated genes that were associated with BRCA1, BRCA2, and BRCAX status in RNA pools. These nine genes could distinguish BRCA1 from BRCA2 carriers with 83% accuracy in individual samples, but three-way analysis for BRCA1, BRCA2, and BRCAX had a maximum of 59% prediction accuracy. Our results suggest that, compared to BRCA1 and BRCA2 mutation carriers, non-BRCA1/2 (BRCAX) individuals are genetically heterogeneous. This study also demonstrates the effectiveness of RNA pools to compare the expression profiles of cell-lines from BRCA1, BRCA2, and BRCAX cases after treatment with irradiation and mitomycin C as a method to prioritize treatment regimes for detailed downstream expression analysis