scholarly journals Consensus Recommendations of the German Consortium for Hereditary Breast and Ovarian Cancer

Breast Care ◽  
2021 ◽  
pp. 1-9
Author(s):  
Kerstin Rhiem ◽  
Bernd Auber ◽  
Susanne Briest ◽  
Nicola Dikow ◽  
Nina Ditsch ◽  
...  
Keyword(s):  
Ovarian Cancer ◽  
Disease Risk ◽  
Interdisciplinary Team ◽  
Individual Risk ◽  
Patient Counseling ◽  
Consensus Process ◽  
Breast And Ovarian Cancer ◽  
Risk Genes ◽  
Therapeutic Measures ◽  
Individual Disease

<b><i>Background:</i></b> The German Consortium for Hereditary Breast and Ovarian Cancer (GC-HBOC) has established a multigene panel (TruRisk®) for the analysis of risk genes for familial breast and ovarian cancer. <b><i>Summary:</i></b> An interdisciplinary team of experts from the GC-HBOC has evaluated the available data on risk modification in the presence of pathogenic mutations in these genes based on a structured literature search and through a formal consensus process. <b><i>Key Messages:</i></b> The goal of this work is to better assess individual disease risk and, on this basis, to derive clinical recommendations for patient counseling and care at the centers of the GC-HBOC from the initial consultation prior to genetic testing to the use of individual risk-adapted preventive/therapeutic measures.

scholarly journals Criteria of the German Consortium for Hereditary Breast and Ovarian Cancer for the Classification of Germline Sequence Variants in Risk Genes for Hereditary Breast and Ovarian Cancer

2020 ◽  
Vol 80 (04) ◽  
pp. 410-429 ◽  
Author(s):  
Barbara Wappenschmidt ◽  
Jan Hauke ◽  
Ulrike Faust ◽  
Dieter Niederacher ◽  
Lisa Wiesmüller ◽  
...  
Keyword(s):  
Ovarian Cancer ◽  
Genetic Variants ◽  
Task Force ◽  
Individual Risk ◽  
Extensive Literature ◽  
Breast And Ovarian Cancer ◽  
Risk Genes ◽  
New Information ◽  
Central Database ◽  
Set Up

AbstractMore than ten years ago, the German Consortium for Hereditary Breast and Ovarian Cancer (GC-HBOC) set up a panel of experts (VUS Task Force) which was tasked with reviewing the classifications of genetic variants reported by individual centres of the GC-HBOC to the central database in Leipzig and reclassifying them, where necessary, based on the most recent data. When it evaluates variants, the VUS Task Force must arrive at a consensus. The resulting classifications are recorded in a central database where they serve as a basis for ensuring the consistent evaluation of previously known and newly identified variants in the different centres of the GC-HBOC. The standardised VUS evaluation by the VUS Task Force is a key element of the recall system which has also been set up by the GC-HBOC. The system will be used to pass on information to families monitored and managed by GC-HBOC centres in the event that previously classified variants are reclassified based on new information. The evaluation algorithm of the VUS Task Force was compiled using internationally established assessment methods (IARC, ACMG, ENIGMA) and is presented here together with the underlying evaluation criteria used to arrive at the classification decision using a flow chart. In addition, the characteristics and special features of specific individual risk genes associated with breast and/or ovarian cancer are discussed in separate subsections. The URLs of relevant databases have also been included together with extensive literature references to provide additional information and cover the scope and dynamism of the current state of knowledge on the evaluation of genetic variants. In future, if criteria are updated based on new information, the update will be published on the website of the GC-HBOC (https://www.konsortium-familiaerer-brustkrebs.de/).

scholarly journals TIGAR-V2: Efficient TWAS Tool with Nonparametric Bayesian eQTL Weights of 49 Tissue Types from GTEx V8

2021 ◽  
Author(s):  
Randy L. Parrish ◽  
Greg C. Gibson ◽  
Michael P. Epstein ◽  
Jingjing Yang
Keyword(s):  
Gene Expression ◽  
Ovarian Cancer ◽  
Parallel Computation ◽  
Dirichlet Process ◽  
Prediction Models ◽  
Complex Diseases ◽  
Breast And Ovarian Cancer ◽  
Nonparametric Bayesian ◽  
Risk Genes ◽  
Regulated Gene Expression

Standard Transcriptome-Wide Association Study (TWAS) methods first train gene expression prediction models using reference transcriptomic data, and then test the association between the predicted genetically regulated gene expression and phenotype of interest. Most existing TWAS tools require cumbersome preparation of genotype input files and extra coding to enable parallel computation. To improve the efficiency of TWAS tools, we develop TIGAR-V2, which directly reads VCF files, enables parallel computation, and reduces up to 90% computation cost compared to the original version. TIGAR-V2 can train gene expression imputation models using either nonparametric Bayesian Dirichlet Process Regression (DPR) or Elastic-Net (as used by PrediXcan), perform TWAS using either individual-level or summary-level GWAS data, and implements both burden and variance-component test statistics for inference. We trained gene expression prediction models by DPR for 49 tissues using GTEx V8 by TIGAR-V2 and illustrated the usefulness of these nonparametric Bayesian DPR eQTL weights through TWAS of breast and ovarian cancer utilizing public GWAS summary statistics. We identified 88 and 37 risk genes respectively for breast and ovarian cancer, most of which are either known or near previously identified GWAS (~95%) or TWAS (~40%) risk genes of the corresponding phenotype and three novel independent TWAS risk genes with known functions in carcinogenesis. These findings suggest that TWAS can provide biological insight into the transcriptional regulation of complex diseases. TIGAR-V2 tool, trained Bayesian cis-eQTL weights, and LD information from GTEX V8 are publicly available, providing a useful resource for mapping risk genes of complex diseases.

Searching for new genes responsible for unexplained hereditary breast and ovarian cancer patients.

2013 ◽  
Vol 31 (15_suppl) ◽  
pp. e12516-e12516
Author(s):  
Alex Teule ◽  
Francisco Quiles ◽  
Rafael Valdes-Mas ◽  
Miguel Angel Pujana ◽  
Monica Salinas ◽  
...  
Keyword(s):  
Ovarian Cancer ◽  
Exome Sequencing ◽  
Cancer Patients ◽  
Rare Variants ◽  
Individual Risk ◽  
Control Group ◽  
Breast And Ovarian Cancer ◽  
Brca1 And Brca2 ◽  
New Genes ◽  
Whole Exome

e12516 Background: About 10-20% of breast and ovarian cancer patients show family history of the disease. Germline mutations in the BRCA1 and BRCA2 genes are usually found in 20-25% of these cases, while the remaining ones are commonly known as BRCAX. Next generation sequencing (NGS) studies have the promise to expedite the identification of the genetic basis underlying BRCAX cases. Aim: To identify gene mutations associated with BRCAX cases by means of whole exome sequencing. Methods: Five selected BRCAX families with more than three affected individuals across at least three generations, and with an apparent dominant pattern of inheritance of the disease were selected in this study. All type of potential alterations of BRCA1/2and linkage to the corresponding loci were excluded in these families. For sequencing, libraries representing the whole exome of multiple affected individuals were obtained using the SureSelect Human All Exon 50 Mb Kit (Agilent) together with the Paired-End Sample Preparation Kit (Illumina) following manufacturers' protocols. Bioinformatics analysis to identify candidate variants present in each family was performed as previously described (PubMed ID: 21549337). Selected rare variants have been analyzed in a set of 288 controls and are currently being evaluated in 500 additional BRCAX cases. Results: By using the described workflow we have identified 16 candidate genes. They were selected based on the presence of rare missense variants that were not found in our control group, predicted as pathogenic using several algorithms (SIFT, PoplyPhen2, Condel and Mutation Taster). Currently, we are re-sequencing these genes in a set of BRCAX samples and complementarily performing loss-of-heterozigosity studies in tumor samples. Conclusions: Exome sequencing of 20 patients from 5 independent Spanish BRCAX families identified a list of putative new BRCAX genes that are currently in the process of validation. Identification of the genetic causes underlying breast and ovarian cancer in BRCAX families is paramount to perform genetic counseling and individual risk assessment in these patients.

scholarly journals MEDICAL AND GENETIC COUNSELING OF HEREDITARY BREAST AND OVARIAN CANCER

2018 ◽  
Vol 25 (2) ◽  
pp. 7-18 ◽  
Author(s):  
S. A. Laptiev ◽  
M. A. Korzhenevskaia ◽  
A. P. Sokolenko ◽  
A. G. Iyevleva ◽  
E. N. Imyanitov
Keyword(s):  
Ovarian Cancer ◽  
Genetic Counseling ◽  
Cancer Care ◽  
Healthy Individuals ◽  
Breast And Ovarian Cancer ◽  
Therapeutic Measures

Hereditary breast and ovarian cancer is one of the most common genetic pathology. Medical and genetic counseling of patients with hereditary breast and ovarian cancer and their families plays the important role in cancer care, as it helps to develop the set of diagnostic, preventive and therapeutic measures aimed at monitoring healthy individuals and to create personalized approaches to the treatment of patients.

NGS-based multi-gene panel analysis in BRCA1/2-negative breast and ovarian cancer families.

2017 ◽  
Vol 35 (15_suppl) ◽  
pp. 1526-1526
Author(s):  
Esther Pohl ◽  
Jan Hauke ◽  
Judit Horvath ◽  
Bernd Dworniczak ◽  
Andrea Gehrig ◽  
...  
Keyword(s):  
Ovarian Cancer ◽  
Copy Number Variations ◽  
Breast And Ovarian Cancer ◽  
Risk Genes ◽  
Routine Diagnostics ◽  
High Prevalence ◽  
Sequencing Platforms ◽  
Gene Panels ◽  
Next Generation Sequencing Ngs ◽  
Ngs Data

1526 Background: 24% of familial breast cancer (BC) and/or ovarian cancer (OC) cases analyzed within the framework of the German Consortium for Hereditary Breast and Ovarian Cancer (GC-HBOC) are due to pathogenic mutations in the BRCA1 or BRCA2 genes. The population-specific mutation prevalence of non- BRCA1/2 genes associated with familial BC and/or OC is largely unknown and was determined in a large German cohort. Methods: Here, we present next-generation sequencing (NGS) data established from TruRisk (GC-HBOC-designed) or TruSight cancer gene panels. A cohort of 6,507 BRCA1/2-negative index cases fulfilling the inclusion criteria of the GC-HBOC for germline testing was analyzed. Illumina sequencing platforms were used and data analysis was carried out at each individual center using different analysis pipelines. Analysis of copy number variations (CNV) was not included in the present data evaluation. Results: By focusing on 8 confirmed BC/OC risk genes ( ATM, CDH1, CHEK2, NBN, PALB2, RAD51C, RAD51D, TP53), the 6,507 cancer patients revealed 165 different deleterious variants in 378 unrelated mutation carriers (5.8%). We found a high prevalence of CHEK2 (n = 150, 2.3%), ATM (n = 89, 1.4% ), and PALB2 (n = 72, 1.1%) mutations while RAD51C (n = 21, 0.3%), TP53 (n = 16, 0.2%), NBN (n = 15, 0.2%), CDH1 (n = 10, 0.2%), and RAD51D (n = 5, 0.1%) were less frequently mutated. Conclusions: The high frequency of pathologic mutations in the genes ATM, CDH1, CHEK2, NBN, PALB2, RAD51C, RAD51D, and TP53, together accounting for almost 6% of familial BC/OC risk, highlights the importance of these genes to be included in BC/OC routine diagnostics. The relevance of these mutations in a clinical setting for early detection of breast and ovarian cancer needs to be established.

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