167 research outputs found
Guidelines for follow-up of women at high risk for inherited breast cancer: Consensus statement from the Biomed 2 Demonstration Programme on Inherited Breast Cancer
Protocols for activity aiming at early diagnosis and treatment of inherited breast or breast-ovarian cancer have been reported. Available reports on outcome of such programmes are considered here. It is concluded that the ongoing activities should continue with minor modifications. Direct evidence of a survival benefit from breast and ovarian screening is not yet available. On the basis of expert opinion and preliminary results from intervention programmes indicating good detection rates for early breast cancers and 5-year survival concordant with early diagnosis, we propose that women at high risk for inherited breast cancer be offered genetic counselling, education in ‘breast awareness’ and annual mammography and clinical expert examination from around 30 years of age. Mammography every second year may be sufficient from 60 years on. BRCA1 mutation carriers may benefit from more frequent examinations and cancer risk may be reduced by oophorectomy before 40–50 years of age. We strongly advocate that all activities should be organized as multicentre studies subjected to continuous evaluation to measure the effects of the interventions on long-term mortality, to match management options more precisely to individual risks and to prepare the ground for studies on chemoprevention
Strain and strain rate parametric imaging. A new method for post processing to 3-/4-dimensional images from three standard apical planes. Preliminary data on feasibility, artefact and regional dyssynergy visualisation
BACKGROUND: We describe a method for 3-/4D reconstruction of tissue Doppler data from three standard apical planes, post processing to derived data of strain rate / strain and parametric colour imaging of the data. The data can be displayed as M-mode arrays from all six walls, Bull's eye projection and a 3D surface figure that can be scrolled and rotated. Numerical data and waveforms can be re-extracted. METHODS: Feasibility was tested by Strain Rate Imaging in 6 normal subjects and 6 patients with acute myocardial infarction. Reverberation artefacts and dyssynergy was identified by colour images. End systolic strain, peak systolic and mid systolic strain rate were measured. RESULTS: Infarcts were visualised in all patients by colour imaging of mid systolic strain rate, end systolic strain and post systolic shortening by strain rate. Reverberation artefacts were visible in 3 of 6 normals, and 2 of 6 patients, and were identified both on bull's eye and M-mode display, but influenced quantitative measurement. Peak systolic strain rate was in controls minimum -1.11, maximum -0.89 and in patients minimum -1.66, maximum 0.02 (p = 0.04). Mid systolic strain rate and end systolic strain did not separate the groups significantly. CONCLUSION: 3-/4D reconstruction and colour display is feasible, allowing quick visual identification of infarcts and artefacts, as well as extension of area of post systolic shortening. Strain rate is better suited to colour parametric display than strain
Genome-wide linkage analysis of 1,233 prostate cancer pedigrees from the International Consortium for prostate cancer Genetics using novel sumLINK and sumLOD analyses
BACKGROUND Prostate cancer (PC) is generally believed to have a strong inherited component, but the search for susceptibility genes has been hindered by the effects of genetic heterogeneity. The recently developed sumLINK and sumLOD statistics are powerful tools for linkage analysis in the presence of heterogeneity. METHODS We performed a secondary analysis of 1,233 PC pedigrees from the International Consortium for Prostate Cancer Genetics (ICPCG) using two novel statistics, the sumLINK and sumLOD. For both statistics, dominant and recessive genetic models were considered. False discovery rate (FDR) analysis was conducted to assess the effects of multiple testing. RESULTS Our analysis identified significant linkage evidence at chromosome 22q12, confirming previous findings by the initial conventional analyses of the same ICPCG data. Twelve other regions were identified with genome-wide suggestive evidence for linkage. Seven regions (1q23, 5q11, 5q35, 6p21, 8q12, 11q13, 20p11–q11) are near loci previously identified in the initial ICPCG pooled data analysis or the subset of aggressive PC pedigrees. Three other regions (1p12, 8p23, 19q13) confirm loci reported by others, and two (2p24, 6q27) are novel susceptibility loci. FDR testing indicates that over 70% of these results are likely true positive findings. Statistical recombinant mapping narrowed regions to an average of 9 cM. CONCLUSIONS Our results represent genomic regions with the greatest consistency of positive linkage evidence across a very large collection of high-risk PC pedigrees using new statistical tests that deal powerfully with heterogeneity. These regions are excellent candidates for further study to identify PC predisposition genes. Prostate 70: 735–744, 2010. © 2010 Wiley-Liss, Inc.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/71371/1/21106_ftp.pd
The role of the prostate cancer gene 3 urine test in addition to serum prostate-specific antigen level in prostate cancer screening among breast cancer, early-onset gene mutation carriers
Objective: To evaluate the additive value of the prostate cancer gene 3 (PCA3) urine test to serum prostate-specific antigen (PSA) in prostate cancer (PC) screening among breast cancer, early-onset gene (BRCA) mutation carriers. This study was performed among the Dutch participants of IMPACT, a large international study on the effectiveness of PSA screening among BRCA mutation carriers. Materials and methods: Urinary PCA3 was measured in 191 BRCA1 mutation carriers, 75 BRCA2 mutation carriers, and 308 noncarriers. The physicians and participants were blinded for the results. Serum PSA level≥3.0. ng/ml was used to indicate prostate biopsies. PCA3 was evaluated (1) as an independent indicator for prostate biopsies and (2) as an indicator for prostate biopsies among men with an elevated
Chromosomes 4 and 8 implicated in a genome wide SNP linkage scan of 762 prostate cancer families collected by the ICPCG
BACKGROUND In spite of intensive efforts, understanding of the genetic aspects of familial prostate cancer (PC) remains largely incomplete. In a previous microsatellite‐based linkage scan of 1,233 PC families, we identified suggestive evidence for linkage (i.e., LOD ≥ 1.86) at 5q12, 15q11, 17q21, 22q12, and two loci on 8p, with additional regions implicated in subsets of families defined by age at diagnosis, disease aggressiveness, or number of affected members. METHODS In an attempt to replicate these findings and increase linkage resolution, we used the Illumina 6000 SNP linkage panel to perform a genome‐wide linkage scan of an independent set of 762 multiplex PC families, collected by 11 International Consortium for Prostate Cancer Genetics (ICPCG) groups. RESULTS Of the regions identified previously, modest evidence of replication was observed only on the short arm of chromosome 8, where HLOD scores of 1.63 and 3.60 were observed in the complete set of families and families with young average age at diagnosis, respectively. The most significant linkage signals found in the complete set of families were observed across a broad, 37 cM interval on 4q13–25, with LOD scores ranging from 2.02 to 2.62, increasing to 4.50 in families with older average age at diagnosis. In families with multiple cases presenting with more aggressive disease, LOD scores over 3.0 were observed at 8q24 in the vicinity of previously identified common PC risk variants, as well as MYC , an important gene in PC biology. CONCLUSIONS These results will be useful in prioritizing future susceptibility gene discovery efforts in this common cancer. Prostate 72:410–426, 2012. © 2011 Wiley Periodicals, Inc.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/90245/1/21443_ftp.pd
Germline variation at 8q24 and prostate cancer risk in men of European ancestry
An Author Correction to this article was published on 17 January 2019.Chromosome 8q24 is a susceptibility locus for multiple cancers, including prostate cancer. Here we combine genetic data across the 8q24 susceptibility region from 71,535 prostate cancer cases and 52,935 controls of European ancestry to define the overall contribution of germline variation at 8q24 to prostate cancer risk. We identify 12 independent risk signals for prostate cancer (p < 4.28 × 10 −15 ), including three risk variants that have yet to be reported. From a polygenic risk score (PRS) model, derived to assess the cumulative effect of risk variants at 8q24, men in the top 1% of the PRS have a 4-fold (95%CI = 3.62–4.40) greater risk compared to the population average. These 12 variants account for ~25% of what can be currently explained of the familial risk of prostate cancer by known genetic risk factors. These findings highlight the overwhelming contribution of germline variation at 8q24 on prostate cancer risk which has implications for population risk stratification. © 2018, The Author(s).Chromosome 8q24 is a susceptibility locus for multiple cancers, including prostate cancer. Here we combine genetic data across the 8q24 susceptibility region from 71,535 prostate cancer cases and 52,935 controls of European ancestry to define the overall contribution of germline variation at 8q24 to prostate cancer risk. We identify 12 independent risk signals for prostate cancer (p < 4.28 × 10 −15 ), including three risk variants that have yet to be reported. From a polygenic risk score (PRS) model, derived to assess the cumulative effect of risk variants at 8q24, men in the top 1% of the PRS have a 4-fold (95%CI = 3.62–4.40) greater risk compared to the population average. These 12 variants account for ~25% of what can be currently explained of the familial risk of prostate cancer by known genetic risk factors. These findings highlight the overwhelming contribution of germline variation at 8q24 on prostate cancer risk which has implications for population risk stratification. © 2018, The Author(s).Peer reviewe
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