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Träfflista för sökning "WFRF:(Kvist Anders) ;pers:(Hahnen Eric)"

Sökning: WFRF:(Kvist Anders) > Hahnen Eric

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1.
  • Catucci, Irene, et al. (författare)
  • Individuals with FANCM biallelic mutations do not develop Fanconi anemia, but show risk for breast cancer, chemotherapy toxicity and may display chromosome fragility
  • 2018
  • Ingår i: Genetics in Medicine. - : Elsevier BV. - 1098-3600. ; 20:4, s. 452-457
  • Tidskriftsartikel (refereegranskat)abstract
    • PurposeMonoallelic germ-line mutations in the BRCA1/FANCS, BRCA2/FANCD1 and PALB2/FANCN genes confer high risk of breast cancer. Biallelic mutations in these genes cause Fanconi anemia (FA), characterized by malformations, bone marrow failure, chromosome fragility, and cancer predisposition (BRCA2/FANCD1 and PALB2/FANCN), or an FA-like disease presenting a phenotype similar to FA but without bone marrow failure (BRCA1/FANCS). FANCM monoallelic mutations have been reported as moderate risk factors for breast cancer, but there are no reports of any clinical phenotype observed in carriers of biallelic mutations.MethodsBreast cancer probands were subjected to mutation analysis by sequencing gene panels or testing DNA damage response genes.ResultsFive cases homozygous for FANCM loss-of-function mutations were identified. They show a heterogeneous phenotype including cancer predisposition, toxicity to chemotherapy, early menopause, and possibly chromosome fragility. Phenotype severity might correlate with mutation position in the gene.ConclusionOur data indicate that biallelic FANCM mutations do not cause classical FA, providing proof that FANCM is not a canonical FA gene. Moreover, our observations support previous findings suggesting that FANCM is a breast cancer-predisposing gene. Mutation testing of FANCM might be considered for individuals with the above-described clinical features.Genetics in Medicine advance online publication, 24 August 2017; doi:10.1038/gim.2017.123.
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2.
  • Parsons, Michael T, et al. (författare)
  • Large scale multifactorial likelihood quantitative analysis of BRCA1 and BRCA2 variants : An ENIGMA resource to support clinical variant classification
  • 2019
  • Ingår i: Human Mutation. - : Hindawi Limited. - 1059-7794 .- 1098-1004. ; , s. 1557-1578
  • Tidskriftsartikel (refereegranskat)abstract
    • The multifactorial likelihood analysis method has demonstrated utility for quantitative assessment of variant pathogenicity for multiple cancer syndrome genes. Independent data types currently incorporated in the model for assessing BRCA1 and BRCA2 variants include clinically calibrated prior probability of pathogenicity based on variant location and bioinformatic prediction of variant effect, co-segregation, family cancer history profile, co-occurrence with a pathogenic variant in the same gene, breast tumor pathology, and case-control information. Research and clinical data for multifactorial likelihood analysis were collated for 1395 BRCA1/2 predominantly intronic and missense variants, enabling classification based on posterior probability of pathogenicity for 734 variants: 447 variants were classified as (likely) benign, and 94 as (likely) pathogenic; 248 classifications were new or considerably altered relative to ClinVar submissions. Classifications were compared to information not yet included in the likelihood model, and evidence strengths aligned to those recommended for ACMG/AMP classification codes. Altered mRNA splicing or function relative to known non-pathogenic variant controls were moderately to strongly predictive of variant pathogenicity. Variant absence in population datasets provided supporting evidence for variant pathogenicity. These findings have direct relevance for BRCA1 and BRCA2 variant evaluation, and justify the need for gene-specific calibration of evidence types used for variant classification. This article is protected by copyright. All rights reserved.
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4.
  • Yang, Xin, et al. (författare)
  • Cancer risks associated with germline PALB2 pathogenic variants : An international study of 524 families
  • 2020
  • Ingår i: Journal of Clinical Oncology. - 0732-183X. ; 38:7, s. 674-685
  • Tidskriftsartikel (refereegranskat)abstract
    • PURPOSE To estimate age-specific relative and absolute cancer risks of breast cancer and to estimate risks of ovarian, pancreatic, male breast, prostate, and colorectal cancers associated with germline PALB2 pathogenic variants (PVs) because these risks have not been extensively characterized. METHODS We analyzed data from 524 families with PALB2 PVs from 21 countries. Complex segregation analysis was used to estimate relative risks (RRs; relative to country-specific population incidences) and absolute risks of cancers. The models allowed for residual familial aggregation of breast and ovarian cancer and were adjusted for the family-specific ascertainment schemes. RESULTS We found associations between PALB2 PVs and risk of female breast cancer (RR, 7.18; 95% CI, 5.82 to 8.85; P = 6.5 × 10-76), ovarian cancer (RR, 2.91; 95% CI, 1.40 to 6.04; P = 4.1 × 10-3), pancreatic cancer (RR, 2.37; 95% CI, 1.24 to 4.50; P = 8.7 × 10-3), and male breast cancer (RR, 7.34; 95% CI, 1.28 to 42.18; P = 2.6 3 1022). There was no evidence for increased risks of prostate or colorectal cancer. The breast cancer RRs declined with age (P for trend = 2.0 × 10-3). After adjusting for family ascertainment, breast cancer risk estimates on the basis of multiple case families were similar to the estimates from families ascertained through population-based studies (P for difference = .41). On the basis of the combined data, the estimated risks to age 80 years were 53% (95% CI, 44% to 63%) for female breast cancer, 5% (95% CI, 2% to 10%) for ovarian cancer, 2%-3% (95% CI females, 1% to 4%; 95% CI males, 2% to 5%) for pancreatic cancer, and 1% (95% CI, 0.2% to 5%) for male breast cancer. CONCLUSION These results confirm PALB2 as a major breast cancer susceptibility gene and establish substantial associations between germline PALB2 PVs and ovarian, pancreatic, and male breast cancers. These findings will facilitate incorporation of PALB2 into risk prediction models and optimize the clinical cancer risk management of PALB2 PV carriers.
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