Metadata supporting Association of germline variation with the survival of women with BRCA1/2 pathogenic variants and breast cancer

This metadata record describes the data generated and analysed in the study "Association of germline variation with the survival of women with BRCA1/2 pathogenic variants and breast cancer". The study investigates genetic survival associations in pathogenic variant carriers from Consortium of Investigators of Modifiers of BRCA1/2 (CIMBA), genotyped on the OncoArray. Data availability and sourcesA subset of the genotype data that support the findings of this study is publicly available via dbGaP https://identifiers.org/dbgap:phs001321.v1.p1 CIMBA 1000 Genomes-imputed genotype data is protected in accordance with the informed consent received from the study participants and therefore cannot be made publicly available. Requests for data can be made to the CIMBA Data Access Coordination Committee. DACC approval is required to access data from the BCFR-ON, EMBRACE, GC-HBOC, HEBCS, HEBON, IHCC, IPOBCS, MCGILL, and OUH studies Phenotype data is stored in a relational database and an output would be a text file. Imputed genotype data can be requested in the QCTOOL dosage format (https://www.well.ox.ac.uk/~gav/qctool_v2/documentation/genotype_file_formats.html), which has been used in these analyses The contact for data access requests is Lesley McGuffog ([email protected]), Data Manager, Department of Public Health and Primary Care, University of Cambridge Newly discovered survival SNPs were characterized in silico utilizing data from the 1000 genomes and Encode projects as integrated in databases LDlink, RegulomeDB and GeneCards. Candidate genes’ mRNA expression and patient survival was tested in the METABRIC data in European Genome-phenome Archive: EGAD00010000434 (1,302 breast cancer patients). BCAC survival summary results are available from the University of Cambridge BCAC site All summary results will be made available on the CIMBA website upon publication of the related article: http://cimba.ccge.medschl.cam.ac.uk The data that support each table and figure in the related article are summarised in the excel file in this data record. BackgroundThis study investigates the survival of women carrying germline pathogenic BRCA1 or BRCA2 variants. These are the two most important genes linked to breast cancer susceptibility. The great variation in survival rates between tumors with similar characteristics and stage suggests a heritable component, e.g. genetic differences in metastatic potential sensitivity to adjuvant therapy or host factors, like tumor microenvironment interaction, immune surveillance, and efficiency in drug metabolism. Both candidate gene and genome-wide approaches have been employed to find genetic determinants patient prognosis and treatment outcome prediction. Participants women of European ancestry diagnosed with invasive breast cancer before the age of 70 years, enrolled in studies participating in CIMBA. CIMBA studies included in analysis if sufficient follow-up data are available, at least 15 study subjects at risk during the time when five events occurred. Patients were followed from the diagnosis of the first primary breast cancer until death of any causeand censored after 15 years or when lost from follow-up Supplementary table 1 of the related article lists all CIMBA studies, characteristics, sample and cohort sizes. Overall sample sizes: 21 studies for carrier of BRCA1 variants (n = 3,008) 15 studies for carriers of BRCA2 variants (n = 2,009)

Additional file 3 of PredictCBC-2.0: a contralateral breast cancer risk prediction model developed and validated in ~ 200,000 patients

Additional file 1: Table S3. Patient and primary breast cancer characteristics per study

Additional file 2 of PredictCBC-2.0: a contralateral breast cancer risk prediction model developed and validated in ~ 200,000 patients

Additional file 2: Table S1. Description of the studies included in the analyses

Additional file 2 of PredictCBC-2.0: a contralateral breast cancer risk prediction model developed and validated in ~ 200,000 patients

Additional file 2: Table S1. Description of the studies included in the analyses

Additional file 2 of PredictCBC-2.0: a contralateral breast cancer risk prediction model developed and validated in ~ 200,000 patients

Additional file 2: Table S1. Description of the studies included in the analyses

Metadata supporting Association of germline variation with the survival of women with BRCA1/2 pathogenic variants and breast cancer

This metadata record describes the data generated and analysed in the study "Association of germline variation with the survival of women with BRCA1/2 pathogenic variants and breast cancer". The study investigates genetic survival associations in pathogenic variant carriers from Consortium of Investigators of Modifiers of BRCA1/2 (CIMBA), genotyped on the OncoArray. Data availability and sourcesA subset of the genotype data that support the findings of this study is publicly available via dbGaP https://identifiers.org/dbgap:phs001321.v1.p1 CIMBA 1000 Genomes-imputed genotype data is protected in accordance with the informed consent received from the study participants and therefore cannot be made publicly available. Requests for data can be made to the CIMBA Data Access Coordination Committee. DACC approval is required to access data from the BCFR-ON, EMBRACE, GC-HBOC, HEBCS, HEBON, IHCC, IPOBCS, MCGILL, and OUH studies Phenotype data is stored in a relational database and an output would be a text file. Imputed genotype data can be requested in the QCTOOL dosage format (https://www.well.ox.ac.uk/~gav/qctool_v2/documentation/genotype_file_formats.html), which has been used in these analyses The contact for data access requests is Lesley McGuffog ([email protected]), Data Manager, Department of Public Health and Primary Care, University of Cambridge Newly discovered survival SNPs were characterized in silico utilizing data from the 1000 genomes and Encode projects as integrated in databases LDlink, RegulomeDB and GeneCards. Candidate genes’ mRNA expression and patient survival was tested in the METABRIC data in European Genome-phenome Archive: EGAD00010000434 (1,302 breast cancer patients). BCAC survival summary results are available from the University of Cambridge BCAC site All summary results will be made available on the CIMBA website upon publication of the related article: http://cimba.ccge.medschl.cam.ac.uk The data that support each table and figure in the related article are summarised in the excel file in this data record. BackgroundThis study investigates the survival of women carrying germline pathogenic BRCA1 or BRCA2 variants. These are the two most important genes linked to breast cancer susceptibility. The great variation in survival rates between tumors with similar characteristics and stage suggests a heritable component, e.g. genetic differences in metastatic potential sensitivity to adjuvant therapy or host factors, like tumor microenvironment interaction, immune surveillance, and efficiency in drug metabolism. Both candidate gene and genome-wide approaches have been employed to find genetic determinants patient prognosis and treatment outcome prediction. Participants women of European ancestry diagnosed with invasive breast cancer before the age of 70 years, enrolled in studies participating in CIMBA. CIMBA studies included in analysis if sufficient follow-up data are available, at least 15 study subjects at risk during the time when five events occurred. Patients were followed from the diagnosis of the first primary breast cancer until death of any causeand censored after 15 years or when lost from follow-up Supplementary table 1 of the related article lists all CIMBA studies, characteristics, sample and cohort sizes. Overall sample sizes: 21 studies for carrier of BRCA1 variants (n = 3,008) 15 studies for carriers of BRCA2 variants (n = 2,009)

PredictCBC-2.0: a contralateral breast cancer risk prediction model developed and validated in ~ 200,000 patients

Abstract 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

Additional file 3 of PredictCBC-2.0: a contralateral breast cancer risk prediction model developed and validated in ~ 200,000 patients

Additional file 1: Table S3. Patient and primary breast cancer characteristics per study

Additional file 2 of Breast cancer risks associated with missense variants in breast cancer susceptibility genes

Additional file 2

Additional file 1 of Colorectal cancer incidences in Lynch syndrome: a comparison of results from the prospective lynch syndrome database and the international mismatch repair consortium

Additional file 1