Aktualisierte Kriterien des Deutschen Konsortiums Familiärer Brust- und Eierstockkrebs zur Klassifizierung von Keimbahn-Sequenzvarianten in Risikogenen für familiären Brust- und Eierstockkrebs

Zusammenfassung

Das Deutsche Konsortium für Familiären Brust- und Eierstockkrebs (GC-HBOC) etablierte vor über 10 Jahren eine Expertengruppe (VUS Task Force), um die von Einzelzentren des GC-HBOC an die zentrale Datenbank in Leipzig gemeldeten Genvarianten hinsichtlich ihrer Klassifizierung zu überprüfen und ggf. nach aktueller Datenlage neu einzustufen. Die innerhalb der VUS Task Force konsentierten Variantenbewertungen und resultierenden Klassifizierungen werden in einer zentralen Datenbank (Heredicare) hinterlegt. Sie sind als Grundlage zu berücksichtigen, um eine einheitliche Bewertung bereits bekannter wie auch neu identifizierter Varianten innerhalb des GC-HBOC zu gewährleisten. Die standardisierte VUS-Bewertung durch die VUS Task Force ist ein zentrales Element des vom GC-HBOC ebenfalls etablierten Recall-Systems. Dieses dient der Weitergabe der Informationen an die genetischen Berater der in den Zentren betreuten Familien im Falle einer aufgrund neuer Erkenntnisse aktualisierten Bewertung bereits klassifizierter Varianten. Die mit international etablierten Bewertungsverfahren (IARC, ACMG, ENIGMA) harmonisierten Bewertungsalgorithmen der VUS Task Force werden in diesem Artikel anhand der zugrunde liegenden Entscheidungskriterien präsentiert, die mittels eines priorisierenden Fließschemas zum Klassifizierungsergebnis führen. Weiterhin werden genspezifische Regelungen und Besonderheiten, die für einzelne mit Brust- und/oder Eierstockkrebs assoziierte Risikogene zu berücksichtigen sind, in einzelnen Unterkapiteln dargelegt. Um dem Umfang und der Dynamik des aktuellen Wissens zur Variantenbewertung gerecht zu werden, sind neben umfangreichen Literaturverweisen insbesondere auch die URLs von relevanten Datenbanken angegeben. In Zukunft sollen die an neue Erkenntnisse angepassten Kriterien auf der Webseite des GC-HBOC (https://www.konsortium-familiaerer-brustkrebs.de/) veröffentlicht werden und als Grundlage für die automatisierte Bewertung von Varianten dienen. Dies ist Bestandteil des durch die Deutsche Krebshilfe geförderten Forschungsvorhabens HerediVar. Des Weiteren werden die so vom Expertengremium bewerten Varianten zukünftig in der ClinVar-Datenbank hinterlegt, um sie international zugänglich zu machen.

Abstract

More 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 at 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 (HerediCare) 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 the information to the geneticcounselors of the families monitored and managed by GC-HBOCcentres in the event of an updated re-evaluation of previously classified variants based on new information. The evaluation algorithm of the VUS Task Force was adapted to internationally established assessment methods (IARC, ACMG, ENIGMA) and is presented here together with the underlying decision-criteria used to arrive at the classification result according to a prioritizing 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 dynamics of the current knowledge on the evaluation of genetic variants. In the future, the criteria adapted to new findings are to be published on the GC-HBOC website (https://www.konsortium-familiaerer-brustkrebs.de/) and serve as a basis for the automated evaluation of variants. This is part of the HerediVar research project funded by the German Cancer Aid. Furthermore, the variants evaluated by the expert panel are to be stored in the ClinVar database in the future in order to make them internationally accessible.

Schlüsselwörter

familiärer Brust-/Eierstockkrebs - Klassifikation genetischer Varianten - Risikogene

Key words

hereditary breast/ovarian cancer - classification of genetic variants - risk genes

Publication History

Article published online:
01 June 2021

• Literatur

• 1 Plon SE, Eccles DM, Easton D. et al. Sequence variant classification and reporting: recommendations for improving the interpretation of cancer susceptibility genetic test results. Human mutation 2008; 29: 1282-1291 DOI: 10.1002/humu.20880.
• 2 Moghadasi S, Meeks HD, Vreeswijk MP. et al. The BRCA1c. 5096G>A p.Arg1699Gln (R1699Q) intermediate risk variant: breast and ovarian cancer risk estimation and recommendations for clinical management from the ENIGMA consortium. Journal of medical genetics 2017; DOI: 10.1136/jmedgenet-2017-104560.
• 3 Shimelis H, Mesman RLS, Von Nicolai C. et al. BRCA2 Hypomorphic Missense Variants Confer Moderate Risks of Breast Cancer. Cancer research 2017; 77: 2789-2799 DOI: 10.1158/0008-5472.can-16-2568.
• 4 Walker LC, Whiley PJ, Houdayer C. et al. Evaluation of a 5-tier scheme proposed for classification of sequence variants using bioinformatic and splicing assay data: inter-reviewer variability and promotion of minimum reporting guidelines. Human mutation 2013; 34: 1424-1431 DOI: 10.1002/humu.22388.
• 5 Whiley PJ, de la Hoya M, Thomassen M. et al. Comparison of mRNA splicing assay protocols across multiple laboratories: recommendations for best practice in standardized clinical testing. Clinical chemistry 2014; 60: 341-352 DOI: 10.1373/clinchem.2013.210658.
• 6 Fackenthal JD, Yoshimatsu T, Zhang B. et al. Naturally occurring BRCA2 alternative mRNA splicing events in clinically relevant samples. Journal of medical genetics 2016; 53: 548-558 DOI: 10.1136/jmedgenet-2015-103570.
• 7 Colombo M, Blok MJ, Whiley P. et al. Comprehensive annotation of splice junctions supports pervasive alternative splicing at the BRCA1 locus: a report from the ENIGMA consortium. Human molecular genetics 2014; 23: 3666-3680 DOI: 10.1093/hmg/ddu075.
• 8 de la Hoya M, Soukarieh O, Lopez-Perolio I. et al. Combined genetic and splicing analysis of BRCA1c.[594-2A>C; 641A>G] highlights the relevance of naturally occurring in-frame transcripts for developing disease gene variant classification algorithms. Human molecular genetics 2016; 25: 2256-2268 DOI: 10.1093/hmg/ddw094.
• 9 Li L, Biswas K, Habib LA. et al. Functional redundancy of exon 12 of BRCA2 revealed by a comprehensive analysis of the c.6853A>G (p.I2285V) variant. Human mutation 2009; 30: 1543-1550 DOI: 10.1002/humu.21101.
• 10 Goldgar DE, Easton DF, Deffenbaugh AM. et al. Integrated evaluation of DNA sequence variants of unknown clinical significance: application to BRCA1 and BRCA2. American journal of human genetics 2004; 75: 535-544 DOI: 10.1086/424388.
• 11 Hauke J, Harter P, Ernst C. et al. Sensitivity and specificity of loss of heterozygosity analysis for the classification of rare germline variants in BRCA1/2: results of the observational AGO-TR1 study (NCT02222883). Journal of medical genetics 2020; DOI: 10.1136/jmedgenet-2020-107353.
• 12 Houdayer C, Caux-Moncoutier V, Krieger S. et al. Guidelines for splicing analysis in molecular diagnosis derived from a set of 327 combined in silico/in vitro studies on BRCA1 and BRCA2 variants. Human mutation 2012; 33: 1228-1238 DOI: 10.1002/humu.22101.
• 13 Hartmann L, Theiss S, Niederacher D. et al. Diagnostics of pathogenic splicing mutations: does bioinformatics cover all bases?. Front Biosci 2008; 13: 3252-3272 DOI: 10.2741/2924.
• 14 Plon SE, Eccles DM, Easton D. et al. Sequence variant classification and reporting: recommendations for improving the interpretation of cancer susceptibility genetic test results. Hum Mutat 2008; 29: 1282-1291 DOI: 10.1002/humu.20880.
• 15 Findlay GM, Boyle EA, Hause RJ. et al. Saturation editing of genomic regions by multiplex homology-directed repair. Nature 2014; 513: 120-123 DOI: 10.1038/nature13695.
• 16 Starita LM, Young DL, Islam M. et al. Massively Parallel Functional Analysis of BRCA1 RING Domain Variants. Genetics 2015; 200: 413-422 DOI: 10.1534/genetics.115.175802.
• 17 Fortuno C, Lee K, Olivier M. et al. Specifications of the ACMG/AMP variant interpretation guidelines for germline TP53 variants. Human mutation 2020; DOI: 10.1002/humu.24152.
• 18 Lee K, Krempely K, Roberts ME. et al. Specifications of the ACMG/AMP variant curation guidelines for the analysis of germline CDH1 sequence variants. Human mutation 2018; 39: 1553-1568 DOI: 10.1002/humu.23650.
• 19 Harrison SM, Biesecker LG, Rehm HL. Overview of Specifications to the ACMG/AMP Variant Interpretation Guidelines. Curr Protoc Hum Genet 2019; 103: e93 DOI: 10.1002/cphg.93.
• 20 Lopez-Perolio I, Leman R, Behar R. et al. Alternative splicing and ACMG-AMP-2015-based classification of PALB2 genetic variants: an ENIGMA report. Journal of medical genetics 2019; 56: 453-460 DOI: 10.1136/jmedgenet-2018-105834.
• 21 Rivera-Muñoz EA, Milko LV, Harrison SM. et al. ClinGen Variant Curation Expert Panel experiences and standardized processes for disease and gene-level specification of the ACMG/AMP guidelines for sequence variant interpretation. Human mutation 2018; 39: 1614-1622 DOI: 10.1002/humu.23645.
• 22 Meeks HD, Song H, Michailidou K. et al. BRCA2 Polymorphic Stop Codon K3326X and the Risk of Breast, Prostate, and Ovarian Cancers. Journal of the National Cancer Institute 2016; 108 DOI: 10.1093/jnci/djv315.
• 23 Hayes F, Cayanan C, Barilla D. et al. Functional assay for BRCA1: mutagenesis of the COOH-terminal region reveals critical residues for transcription activation. Cancer research 2000; 60: 2411-2418
• 24 Kuznetsov SG, Liu P, Sharan SK. Mouse embryonic stem cell-based functional assay to evaluate mutations in BRCA2. Nature medicine 2008; 14: 875-881 DOI: 10.1038/nm.1719.
• 25 Monteiro AN, Bouwman P, Kousholt AN. et al. Variants of uncertain clinical significance in hereditary breast and ovarian cancer genes: best practices in functional analysis for clinical annotation. Journal of medical genetics 2020; 57: 509-518 DOI: 10.1136/jmedgenet-2019-106368.
• 26 Findlay GM, Daza RM, Martin B. et al. Accurate classification of BRCA1 variants with saturation genome editing. Nature 2018; 562: 217-222 DOI: 10.1038/s41586-018-0461-z.
• 27 Bouwman P, van der Gulden H, van der Heijden I. et al. A high-throughput functional complementation assay for classification of BRCA1 missense variants. Cancer Discov 2013; 3: 1142-1155 DOI: 10.1158/2159-8290.CD-13-0094.
• 28 Woods NT, Baskin R, Golubeva V. et al. Functional assays provide a robust tool for the clinical annotation of genetic variants of uncertain significance. NPJ Genom Med 2016; 1: 16001 DOI: 10.1038/npjgenmed.2016.1.
• 29 Lee MS, Green R, Marsillac SM. et al. Comprehensive analysis of missense variations in the BRCT domain of BRCA1 by structural and functional assays. Cancer research 2010; 70: 4880-4890 DOI: 10.1158/0008-5472.Can-09-4563.
• 30 Petitalot A, Dardillac E, Jacquet E. et al. Combining Homologous Recombination and Phosphopeptide-binding Data to Predict the Impact of BRCA1 BRCT Variants on Cancer Risk. Mol Cancer Res 2019; 17: 54-69 DOI: 10.1158/1541-7786.Mcr-17-0357.
• 31 Guidugli L, Shimelis H, Masica DL. et al. Assessment of the Clinical Relevance of BRCA2 Missense Variants by Functional and Computational Approaches. American journal of human genetics 2018; 102: 233-248 DOI: 10.1016/j.ajhg.2017.12.013.
• 32 Mesman RLS, Calléja F, Hendriks G. et al. The functional impact of variants of uncertain significance in BRCA2. Genetics in medicine : official journal of the American College of Medical Genetics 2019; 21: 293-302 DOI: 10.1038/s41436-018-0052-2.
• 33 Biswas K, Das R, Alter BP. et al. A comprehensive functional characterization of BRCA2 variants associated with Fanconi anemia using mouse ES cell-based assay. Blood 2011; 118: 2430-2442 DOI: 10.1182/blood-2010-12-324541.
• 34 Biswas K, Das R, Eggington JM. et al. Functional evaluation of BRCA2 variants mapping to the PALB2-binding and C-terminal DNA-binding domains using a mouse ES cell-based assay. Human molecular genetics 2012; 21: 3993-4006 DOI: 10.1093/hmg/dds222.
• 35 Biswas K, Lipton GB, Stauffer S. et al. A computational model for classification of BRCA2 variants using mouse embryonic stem cell-based functional assays. NPJ Genom Med 2020; 5: 52 DOI: 10.1038/s41525-020-00158-5.
• 36 Sirisena N, Biswas K, Sullivan T. et al. Functional evaluation of five BRCA2 unclassified variants identified in a Sri Lankan cohort with inherited cancer syndromes using a mouse embryonic stem cell-based assay. Breast Cancer Res 2020; 22: 43 DOI: 10.1186/s13058-020-01272-z.
• 37 Sullivan T, Thirthagiri E, Chong CE. et al. Epidemiological and ES cell-based functional evaluation of BRCA2 variants identified in families with breast cancer. Human mutation 2021; 42: 200-212 DOI: 10.1002/humu.24154.
• 38 Richardson ME, Hu C, Lee KY. et al. Strong functional data for pathogenicity or neutrality classify BRCA2 DNA-binding-domain variants of uncertain significance. American journal of human genetics 2021; DOI: 10.1016/j.ajhg.2021.02.005.
• 39 Hart SN, Hoskin T, Shimelis H. et al. Comprehensive annotation of BRCA1 and BRCA2 missense variants by functionally validated sequence-based computational prediction models. Genetics in medicine : official journal of the American College of Medical Genetics 2019; 21: 71-80 DOI: 10.1038/s41436-018-0018-4.
• 40 Goldgar DE, Healey S, Dowty JG. et al. Rare variants in the ATM gene and risk of breast cancer. Breast Cancer Res 2011; 13: R73 DOI: 10.1186/bcr2919.
• 41 Maxwell KN, Hart SN, Vijai J. et al. Evaluation of ACMG-Guideline-Based Variant Classification of Cancer Susceptibility and Non-Cancer-Associated Genes in Families Affected by Breast Cancer. American journal of human genetics 2016; 98: 801-817 DOI: 10.1016/j.ajhg.2016.02.024.
• 42 Richards S, Aziz N, Bale S. et al. Standards and guidelines for the interpretation of sequence variants: a joint consensus recommendation of the American College of Medical Genetics and Genomics and the Association for Molecular Pathology. Genetics in medicine : official journal of the American College of Medical Genetics 2015; 17: 405-424 DOI: 10.1038/gim.2015.30.
• 43 Teraoka SN, Malone KE, Doody DR. et al. Increased frequency of ATM mutations in breast carcinoma patients with early onset disease and positive family history. Cancer 2001; 92: 479-487
• 44 Fernet M, Moullan N, Lauge A. et al. Cellular responses to ionising radiation of AT heterozygotes: differences between missense and truncating mutation carriers. Br J Cancer 2004; 90: 866-873 DOI: 10.1038/sj.bjc.6601549.
• 45 Dork T, Bendix-Waltes R, Wegner RD. et al. Slow progression of ataxia-telangiectasia with double missense and in frame splice mutations. Am J Med Genet A 2004; 126A: 272-277 DOI: 10.1002/ajmg.a.20601.
• 46 Lavin MF, Scott S, Gueven N. et al. Functional consequences of sequence alterations in the ATM gene. DNA Repair (Amst) 2004; 3: 1197-1205 DOI: 10.1016/j.dnarep.2004.03.011.
• 47 Renwick A, Thompson D, Seal S. et al. ATM mutations that cause ataxia-telangiectasia are breast cancer susceptibility alleles. Nature genetics 2006; 38: 873-875 DOI: 10.1038/ng1837.
• 48 Tavtigian SV, Oefner PJ, Babikyan D. et al. Rare, evolutionarily unlikely missense substitutions in ATM confer increased risk of breast cancer. American journal of human genetics 2009; 85: 427-446 DOI: 10.1016/j.ajhg.2009.08.018.
• 49 Keimling M, Volcic M, Csernok A. et al. Functional characterization connects individual patient mutations in ataxia telangiectasia mutated (ATM) with dysfunction of specific DNA double-strand break-repair signaling pathways. FASEB J 2011; 25: 3849-3860 DOI: 10.1096/fj.11-185546.
• 50 Rothblum-Oviatt C, Wright J, Lefton-Greif MA. et al. Ataxia telangiectasia: a review. Orphanet J Rare Dis 2016; 11: 159 DOI: 10.1186/s13023-016-0543-7.
• 51 Fernandes N, Sun Y, Chen S. et al. DNA damage-induced association of ATM with its target proteins requires a protein interaction domain in the N terminus of ATM. J Biol Chem 2005; 280: 15158-15164 DOI: 10.1074/jbc.M412065200.
• 52 Young DB, Jonnalagadda J, Gatei M. et al. Identification of domains of ataxia-telangiectasia mutated required for nuclear localization and chromatin association. J Biol Chem 2005; 280: 27587-27594 DOI: 10.1074/jbc.M411689200.
• 53 Gilad S, Chessa L, Khosravi R. et al. Genotype-phenotype relationships in ataxia-telangiectasia and variants. American journal of human genetics 1998; 62: 551-561 DOI: 10.1086/301755.
• 54 Mitui M, Nahas SA, Du LT. et al. Functional and computational assessment of missense variants in the ataxia-telangiectasia mutated (ATM) gene: mutations with increased cancer risk. Human mutation 2009; 30: 12-21 DOI: 10.1002/humu.20805.
• 55 Tavtigian SV, Oefner PJ, Babikyan D. et al. Rare, evolutionarily unlikely missense substitutions in ATM confer increased risk of breast cancer. American journal of human genetics 2009; 85: 427-446 DOI: 10.1016/j.ajhg.2009.08.018.
• 56 Barone G, Groom A, Reiman A. et al. Modeling ATM mutant proteins from missense changes confirms retained kinase activity. Human mutation 2009; 30: 1222-1230 DOI: 10.1002/humu.21034.
• 57 Southey MC, Goldgar DE, Winqvist R. et al. PALB2, CHEK2 and ATM rare variants and cancer risk: data from COGS. Journal of medical genetics 2016; 53: 800-811 DOI: 10.1136/jmedgenet-2016-103839.
• 58 Khanna KK, Keating KE, Kozlov S. et al. ATM associates with and phosphorylates p53: mapping the region of interaction. Nature genetics 1998; 20: 398-400 DOI: 10.1038/3882.
• 59 Gatei M, Scott SP, Filippovitch I. et al. Role for ATM in DNA damage-induced phosphorylation of BRCA1. Cancer research 2000; 60: 3299-3304
• 60 Fiévet A, Bellanger D, Rieunier G. et al. Functional classification of ATM variants in ataxia-telangiectasia patients. Human mutation 2019; 40: 1713-1730 DOI: 10.1002/humu.23778.
• 61 Girard E, Eon-Marchais S, Olaso R. et al. Familial breast cancer and DNA repair genes: Insights into known and novel susceptibility genes from the GENESIS study, and implications for multigene panel testing. International journal of cancer 2018; DOI: 10.1002/ijc.31921.
• 62 Catucci I, Radice P, Milne RL. et al. The PALB2p.Leu939Trp mutation is not associated with breast cancer risk. Breast Cancer Res 2016; 18: 111 DOI: 10.1186/s13058-016-0762-9.
• 63 Antoniou AC, Casadei S, Heikkinen T. et al. Breast-cancer risk in families with mutations in PALB2. N Engl J Med 2014; 371: 497-506 DOI: 10.1056/NEJMoa1400382.
• 64 Antoniou AC, Foulkes WD, Tischkowitz M. Breast-cancer risk in families with mutations in PALB2. N Engl J Med 2014; 371: 1651-1652 DOI: 10.1056/NEJMc1410673.
• 65 Antoniou AC, Foulkes WD, Tischkowitz M. Breast cancer risk in women with PALB2 mutations in different populations. Lancet Oncol 2015; 16: e375-e376 DOI: 10.1016/s1470-2045(15)00002-9.
• 66 Southey MC, Teo ZL, Dowty JG. et al. A PALB2 mutation associated with high risk of breast cancer. Breast Cancer Res 2010; 12: R109 DOI: 10.1186/bcr2796.
• 67 Tischkowitz M, Capanu M, Sabbaghian N. et al. Rare germline mutations in PALB2 and breast cancer risk: a population-based study. Human mutation 2012; 33: 674-680 DOI: 10.1002/humu.22022.
• 68 Tischkowitz M, Sabbaghian N, Hamel N. et al. Contribution of the PALB2c.2323C>T [p.Q775X] founder mutation in well-defined breast and/or ovarian cancer families and unselected ovarian cancer cases of French Canadian descent. BMC Med Genet 2013; 14: 5 DOI: 10.1186/1471-2350-14-5.
• 69 Obermeier K, Sachsenweger J, Friedl TW. et al. Heterozygous PALB2c.1592delT mutation channels DNA double-strand break repair into error-prone pathways in breast cancer patients. Oncogene 2016; 35: 3796-3806 DOI: 10.1038/onc.2015.448.
• 70 Hayakawa T, Zhang F, Hayakawa N. et al. MRG15 binds directly to PALB2 and stimulates homology-directed repair of chromosomal breaks. J Cell Sci 2010; 123: 1124-1130 DOI: 10.1242/jcs.060178.
• 71 Sy SM, Huen MS, Chen J. MRG15 is a novel PALB2-interacting factor involved in homologous recombination. J Biol Chem 2009; 284: 21127-21131 DOI: 10.1074/jbc.C109.023937.
• 72 Zhang F, Ma J, Wu J. et al. PALB2 links BRCA1 and BRCA2 in the DNA-damage response. Curr Biol 2009; 19: 524-529 DOI: 10.1016/j.cub.2009.02.018.
• 73 Foo TK, Tischkowitz M, Simhadri S. et al. Compromised BRCA1-PALB2 interaction is associated with breast cancer risk. Oncogene 2017; 36: 4161-4170 DOI: 10.1038/onc.2017.46.
• 74 Buisson R, Dion-Cote AM, Coulombe Y. et al. Cooperation of breast cancer proteins PALB2 and piccolo BRCA2 in stimulating homologous recombination. Nat Struct Mol Biol 2010; 17: 1247-1254 DOI: 10.1038/nsmb.1915.
• 75 Dray E, Etchin J, Wiese C. et al. Enhancement of RAD51 recombinase activity by the tumor suppressor PALB2. Nat Struct Mol Biol 2010; 17: 1255-1259 DOI: 10.1038/nsmb.1916.
• 76 Bleuyard JY, Buisson R, Masson JY. et al. ChAM, a novel motif that mediates PALB2 intrinsic chromatin binding and facilitates DNA repair. EMBO Rep 2012; 13: 135-141 DOI: 10.1038/embor.2011.243.
• 77 Park JY, Singh TR, Nassar N. et al. Breast cancer-associated missense mutants of the PALB2 WD40 domain, which directly binds RAD51C, RAD51 and BRCA2, disrupt DNA repair. Oncogene 2014; 33: 4803-4812 DOI: 10.1038/onc.2013.421.
• 78 Oliver AW, Swift S, Lord CJ. et al. Structural basis for recruitment of BRCA2 by PALB2. EMBO Rep 2009; 10: 990-996 DOI: 10.1038/embor.2009.126.
• 79 Zhang F, Fan Q, Ren K. et al. PALB2 functionally connects the breast cancer susceptibility proteins BRCA1 and BRCA2. Mol Cancer Res 2009; 7: 1110-1118 DOI: 10.1158/1541-7786.mcr-09-0123.
• 80 Caleca L, Catucci I, Figlioli G. et al. Two Missense Variants Detected in Breast Cancer Probands Preventing BRCA2-PALB2 Protein Interaction. Frontiers in oncology 2018; 8: 480 DOI: 10.3389/fonc.2018.00480.
• 81 Hellebrand H, Sutter C, Honisch E. et al. Germline mutations in the PALB2 gene are population specific and occur with low frequencies in familial breast cancer. Human mutation 2011; 32: E2176-E2188 DOI: 10.1002/humu.21478.
• 82 Wiltshire T, Ducy M, Foo TK. et al. Functional characterization of 84 PALB2 variants of uncertain significance. Genetics in medicine : official journal of the American College of Medical Genetics 2020; 22: 622-632 DOI: 10.1038/s41436-019-0682-z.
• 83 Boonen R, Rodrigue A, Stoepker C. et al. Functional analysis of genetic variants in the high-risk breast cancer susceptibility gene PALB2. Nat Commun 2019; 10: 5296 DOI: 10.1038/s41467-019-13194-2.
• 84 Sodha N, Williams R, Mangion J. et al. Screening hCHK2 for mutations. Science (New York, NY) 2000; 289: 359
• 85 Cybulski C, Gorski B, Huzarski T. et al. CHEK2 is a multiorgan cancer susceptibility gene. American journal of human genetics 2004; 75: 1131-1135 DOI: 10.1086/426403.
• 86 Cai Z, Chehab NH, Pavletich NP. Structure and activation mechanism of the CHK2 DNA damage checkpoint kinase. Mol Cell 2009; 35: 818-829 DOI: 10.1016/j.molcel.2009.09.007.
• 87 Roeb W, Higgins J, King MC. Response to DNA damage of CHEK2 missense mutations in familial breast cancer. Human molecular genetics 2012; 21: 2738-2744 DOI: 10.1093/hmg/dds101.
• 88 Ow GS, Ivshina AV, Fuentes G. et al. Identification of two poorly prognosed ovarian carcinoma subtypes associated with CHEK2 germ-line mutation and non-CHEK2 somatic mutation gene signatures. Cell cycle (Georgetown, Tex) 2014; 13: 2262-2280 DOI: 10.4161/cc.29271.
• 89 Dong X, Wang L, Taniguchi K. et al. Mutations in CHEK2 associated with prostate cancer risk. American journal of human genetics 2003; 72: 270-280 DOI: 10.1086/346094.
• 90 Matsuoka S, Rotman G, Ogawa A. et al. Ataxia telangiectasia-mutated phosphorylates Chk2 in vivo and in vitro. Proc Natl Acad Sci U S A 2000; 97: 10389-10394 DOI: 10.1073/pnas.190030497.
• 91 Ahn J, Prives C. Checkpoint kinase 2 (Chk2) monomers or dimersphosphorylate Cdc25C after DNA damage regardless of threonine 68 phosphorylation. J Biol Chem 2002; 277: 48418-48426 DOI: 10.1074/jbc.M208321200.
• 92 Ahn J, Urist M, Prives C. The Chk2 protein kinase. DNA Repair (Amst) 2004; 3: 1039-1047 DOI: 10.1016/j.dnarep.2004.03.033.
• 93 Delimitsou A, Fostira F, Kalfakakou D. et al. Functional characterization of CHEK2 variants in a Saccharomyces cerevisiae system. Human mutation 2019; 40: 631-648 DOI: 10.1002/humu.23728.
• 94 Kleiblova P, Stolarova L, Krizova K. et al. Identification of deleterious germline CHEK2 mutations and their association with breast and ovarian cancer. International journal of cancer 2019; 145: 1782-1797 DOI: 10.1002/ijc.32385.
• 95 Kato S, Han SY, Liu W. et al. Understanding the function-structure and function-mutation relationships of p53 tumor suppressor protein by high-resolution missense mutation analysis. Proc Natl Acad Sci U S A 2003; 100: 8424-8429 DOI: 10.1073/pnas.1431692100.
• 96 Mathe E, Olivier M, Kato S. et al. Predicting the transactivation activity of p53 missense mutants using a four-body potential score derived from Delaunay tessellations. Human mutation 2006; 27: 163-172 DOI: 10.1002/humu.20284.
• 97 Soussi T, Kato S, Levy PP. et al. Reassessment of the TP53 mutation database in human disease by data mining with a library of TP53 missense mutations. Human mutation 2005; 25: 6-17 DOI: 10.1002/humu.20114.
• 98 Leroy B, Fournier JL, Ishioka C. et al. The TP53 website: an integrative resource centre for the TP53 mutation database and TP53 mutant analysis. Nucleic Acids Res 2013; 41: D962-D969 DOI: 10.1093/nar/gks1033.
• 99 Monti P, Ciribilli Y, Jordan J. et al. Transcriptional functionality of germ line p53 mutants influences cancer phenotype. Clin Cancer Res 2007; 13: 3789-3795 DOI: 10.1158/1078-0432.ccr-06-2545.
• 100 Monti P, Perfumo C, Bisio A. et al. Dominant-negative features of mutant TP53 in germline carriers have limited impact on cancer outcomes. Mol Cancer Res 2011; 9: 271-279 DOI: 10.1158/1541-7786.mcr-10-0496.
• 101 Giacomelli AO, Yang X, Lintner RE. et al. Mutational processes shape the landscape of TP53 mutations in human cancer. Nature genetics 2018; 50: 1381-1387 DOI: 10.1038/s41588-018-0204-y.
• 102 Kotler E, Shani O, Goldfeld G. et al. A Systematic p53 Mutation Library Links Differential Functional Impact to Cancer Mutation Pattern and Evolutionary Conservation. Mol Cell 2018; 71: 178-190 DOI: 10.1016/j.molcel.2018.06.012.
• 103 Saha T, Kar RK, Sa G. Structural and sequential context of p53: A review of experimental and theoretical evidence. Prog Biophys Mol Biol 2015; 117: 250-263 DOI: 10.1016/j.pbiomolbio.2014.12.002.
• 104 Buchhop S, Gibson MK, Wang XW. et al. Interaction of p53 with the human Rad51 protein. Nucleic Acids Res 1997; 25: 3868-3874
• 105 Liang SH, Clarke MF. The nuclear import of p53 is determined by the presence of a basic domain and its relative position to the nuclear localization signal. Oncogene 1999; 18: 2163-2166 DOI: 10.1038/sj.onc.1202350.
• 106 Shaulsky G, Goldfinger N, Ben-Ze'ev A. et al. Nuclear accumulation of p53 protein is mediated by several nuclear localization signals and plays a role in tumorigenesis. Mol Cell Biol 1990; 10: 6565-6577
• 107 Linke SP, Sengupta S, Khabie N. et al. p53 interacts with hRAD51 and hRAD54, and directly modulates homologous recombination. Cancer research 2003; 63: 2596-2605
• 108 Wiese C, Hinz JM, Tebbs RS. et al. Disparate requirements for the Walker A and B ATPase motifs of human RAD51D in homologous recombination. Nucleic Acids Res 2006; 34: 2833-2843 DOI: 10.1093/nar/gkl366.
• 109 Rivera B, Di Iorio M, Frankum J. et al. Functionally Null RAD51D Missense Mutation Associates Strongly with Ovarian Carcinoma. Cancer research 2017; 77: 4517-4529 DOI: 10.1158/0008-5472.Can-17-0190.
• 110 Pittman DL, Weinberg LR, Schimenti JC. Identification, characterization, and genetic mapping of Rad51d, a new mouse and human RAD51/RecA-related gene. Genomics 1998; 49: 103-111 DOI: 10.1006/geno.1998.5226.
• 111 Cartwright R, Dunn AM, Simpson PJ. et al. Isolation of novel human and mouse genes of the recA/RAD51 recombination-repair gene family. Nucleic Acids Res 1998; 26: 1653-1659
• 112 Kim YM, Choi BS. Structural and functional characterization of the N-terminal domain of human Rad51D. The international journal of biochemistry & cell biology 2011; 43: 416-422 DOI: 10.1016/j.biocel.2010.11.014.
• 113 Gruver AM, Miller KA, Rajesh C. et al. The ATPase motif in RAD51D is required for resistance to DNA interstrand crosslinking agents and interaction with RAD51C. Mutagenesis 2005; 20: 433-440 DOI: 10.1093/mutage/gei059.
• 114 Gutierrez-Enriquez S, Bonache S, de Garibay GR. et al. About 1% of the breast and ovarian Spanish families testing negative for BRCA1 and BRCA2 are carriers of RAD51D pathogenic variants. International journal of cancer 2014; 134: 2088-2097 DOI: 10.1002/ijc.28540.
• 115 Janatova M, Soukupova J, Stribrna J. et al. Mutation Analysis of the RAD51C and RAD51D Genes in High-Risk Ovarian Cancer Patients and Families from the Czech Republic. PloS one 2015; 10: e0127711 DOI: 10.1371/journal.pone.0127711.
• 116 Thompson ER, Rowley SM, Sawyer S. et al. Analysis of RAD51D in ovarian cancer patients and families with a history of ovarian or breast cancer. PloS one 2013; 8: e54772 DOI: 10.1371/journal.pone.0054772.
• 117 Miller KA, Sawicka D, Barsky D. et al. Domain mapping of the Rad51 paralog protein complexes. Nucleic Acids Res 2004; 32: 169-178 DOI: 10.1093/nar/gkg925.
• 118 Loveday C, Turnbull C, Ramsay E. et al. Germline mutations in RAD51D confer susceptibility to ovarian cancer. Nature genetics 2011; 43: 879-882 DOI: 10.1038/ng.893.
• 119 Song H, Dicks E, Ramus SJ. et al. Contribution of Germline Mutations in the RAD51B, RAD51C, and RAD51D Genes to Ovarian Cancer in the Population. Journal of clinical oncology : official journal of the American Society of Clinical Oncology 2015; 33: 2901-2907 DOI: 10.1200/jco.2015.61.2408.
• 120 Meindl A, Hellebrand H, Wiek C. et al. Germline mutations in breast and ovarian cancer pedigrees establish RAD51C as a human cancer susceptibility gene. Nature genetics 2010; 42: 410-414 DOI: 10.1038/ng.569.
• 121 Osorio A, Endt D, Fernandez F. et al. Predominance of pathogenic missense variants in the RAD51C gene occurring in breast and ovarian cancer families. Human molecular genetics 2012; 21: 2889-2898 DOI: 10.1093/hmg/dds115.
• 122 Somyajit K, Mishra A, Jameei A. et al. Enhanced non-homologous end joining contributes toward synthetic lethality of pathological RAD51C mutants with poly (ADP-ribose) polymerase. Carcinogenesis 2015; 36: 13-24 DOI: 10.1093/carcin/bgu211.
• 123 Vaz F, Hanenberg H, Schuster B. et al. Mutation of the RAD51C gene in a Fanconi anemia-like disorder. Nature genetics 2010; 42: 406-409 DOI: 10.1038/ng.570.
• 124 Clague J, Wilhoite G, Adamson A. et al. RAD51C germline mutations in breast and ovarian cancer cases from high-risk families. PloS one 2011; 6: e25632 DOI: 10.1371/journal.pone.0025632.
• 125 French CA, Tambini CE, Thacker J. Identification of functional domains in the RAD51L2 (RAD51C) protein and its requirement for gene conversion. J Biol Chem 2003; 278: 45445-45450 DOI: 10.1074/jbc.M308621200.
• 126 Jonson L, Ahlborn LB, Steffensen AY. et al. Identification of six pathogenic RAD51C mutations via mutational screening of 1228 Danish individuals with increased risk of hereditary breast and/or ovarian cancer. Breast cancer research and treatment 2016; 155: 215-222 DOI: 10.1007/s10549-015-3674-y.
• 127 Schnurbein G, Hauke J, Wappenschmidt B. et al. RAD51C deletion screening identifies a recurrent gross deletion in breast cancer and ovarian cancer families. Breast Cancer Res 2013; 15: R120 DOI: 10.1186/bcr3589.
• 128 Moyer CL, Ivanovich J, Gillespie JL. et al. Rare BRIP1 Missense Alleles Confer Risk for Ovarian and Breast Cancer. Cancer research 2020; 80: 857-867 DOI: 10.1158/0008-5472.Can-19-1991.
• 129 Ali AM, Singh TR, Meetei AR. FANCM-FAAP24 and FANCJ: FA proteins that metabolize DNA. Mutation research 2009; 668: 20-26 DOI: 10.1016/j.mrfmmm.2009.04.002.
• 130 Yu X, Chini CC, He M. et al. The BRCT domain is a phospho-protein binding domain. Science (New York, NY) 2003; 302: 639-642 DOI: 10.1126/science.1088753.
• 131 Peng M, Litman R, Xie J. et al. The FANCJ/MutLalpha interaction is required for correction of the cross-link response in FA-J cells. The EMBO journal 2007; 26: 3238-3249 DOI: 10.1038/sj.emboj.7601754.
• 132 Weber-Lassalle N, Hauke J, Ramser J. et al. BRIP1 loss-of-function mutations confer high risk for familial ovarian cancer, but not familial breast cancer. Breast Cancer Res 2018; 20: 7 DOI: 10.1186/s13058-018-0935-9.
• 133 Castera L, Harter V, Muller E. et al. Landscape of pathogenic variations in a panel of 34 genes and cancer risk estimation from 5131 HBOC families. Genetics in medicine : official journal of the American College of Medical Genetics 2018; DOI: 10.1038/s41436-018-0005-9.
• 134 Couch FJ, Shimelis H, Hu C. et al. Associations Between Cancer Predisposition Testing Panel Genes and Breast Cancer. JAMA oncology 2017; 3: 1190-1196 DOI: 10.1001/jamaoncol.2017.0424.
• 135 Li J, Meeks H, Feng BJ. et al. Targeted massively parallel sequencing of a panel of putative breast cancer susceptibility genes in a large cohort of multiple-case breast and ovarian cancer families. Journal of medical genetics 2016; 53: 34-42 DOI: 10.1136/jmedgenet-2015-103452.
• 136 Norquist BM, Harrell MI, Brady MF. et al. Inherited Mutations in Women With Ovarian Carcinoma. JAMA oncology 2016; 2: 482-490 DOI: 10.1001/jamaoncol.2015.5495.
• 137 Ramus SJ, Song H, Dicks E. et al. Germline Mutations in the BRIP1, BARD1, PALB2, and NBN Genes in Women With Ovarian Cancer. Journal of the National Cancer Institute 2015; 107 DOI: 10.1093/jnci/djv214.
• 138 Lilyquist J, LaDuca H, Polley E. et al. Frequency of mutations in a large series of clinically ascertained ovarian cancer cases tested on multi-gene panels compared to reference controls. Gynecologic oncology 2017; 147: 375-380 DOI: 10.1016/j.ygyno.2017.08.030.
• 139 Hansford S, Kaurah P, Li-Chang H. et al. Hereditary Diffuse Gastric Cancer Syndrome: CDH1 Mutations and Beyond. JAMA Oncol 2015; 1: 23-32 DOI: 10.1001/jamaoncol.2014.168.
• 140 Melo S, Figueiredo J, Fernandes MS. et al. Predicting the Functional Impact of CDH1 Missense Mutations in Hereditary Diffuse Gastric Cancer. Int J Mol Sci 2017; 18 DOI: 10.3390/ijms18122687.
• 141 Oliveira C, Pinheiro H, Figueiredo J. et al. Familial gastric cancer: genetic susceptibility, pathology, and implications for management. Lancet Oncol 2015; 16: e60-e70 DOI: 10.1016/S1470-2045(14)71016-2.
• 142 Corso G, Intra M, Trentin C. et al. CDH1 germline mutations and hereditary lobular breast cancer. Fam Cancer 2016; 15: 215-219 DOI: 10.1007/s10689-016-9869-5.
• 143 Krempely K, Karam R. A novel de novo CDH1 germline variant aids in the classification of carboxy-terminal E-cadherin alterations predicted to escape nonsense-mediated mRNA decay. Cold Spring Harb Mol Case Stud 2018; 4 DOI: 10.1101/mcs.a003012.
• 144 Kluijt I, Siemerink EJ, Ausems MG. et al. CDH1-related hereditary diffuse gastric cancer syndrome: clinical variations and implications for counseling. International journal of cancer 2012; 131: 367-376 DOI: 10.1002/ijc.26398.
• 145 Alenezi WM, Fierheller CT, Recio N. et al. Literature Review of BARD1 as a Cancer Predisposing Gene with a Focus on Breast and Ovarian Cancers. Genes (Basel) 2020; 11 DOI: 10.3390/genes11080856.
• 146 Wu LC, Wang ZW, Tsan JT. et al. Identification of a RING protein that can interact in vivo with the BRCA1 gene product. Nature genetics 1996; 14: 430-440 DOI: 10.1038/ng1296-430.
• 147 Adamovich AI, Banerjee T, Wingo M. et al. Functional analysis of BARD1 missense variants in homology-directed repair and damage sensitivity. PLoS Genet 2019; 15: e1008049 DOI: 10.1371/journal.pgen.1008049.
• 148 Billing D, Horiguchi M, Wu-Baer F. et al. The BRCT Domains of the BRCA1 and BARD1 Tumor Suppressors Differentially Regulate Homology-Directed Repair and Stalled Fork Protection. Mol Cell 2018; 72: 127-139 DOI: 10.1016/j.molcel.2018.08.016.
• 149 Weber-Lassalle N, Borde J, Weber-Lassalle K. et al. Germline loss-of-function variants in the BARD1 gene are associated with early-onset familial breast cancer but not ovarian cancer. Breast Cancer Res 2019; 21: 55 DOI: 10.1186/s13058-019-1137-9.
• 150 Dorling L, Carvalho S, Allen J. et al. Breast Cancer Risk Genes – Association Analysis in More than 113,000 Women. N Engl J Med 2021; DOI: 10.1056/NEJMoa1913948.
• 151 Hu C, Hart SN, Gnanaolivu R. et al. A Population-Based Study of Genes Previously Implicated in Breast Cancer. N Engl J Med 2021; DOI: 10.1056/NEJMoa2005936.
• 152 Lee C, Banerjee T, Gillespie J. et al. Functional Analysis of BARD1 Missense Variants in Homology-Directed Repair of DNA Double Strand Breaks. Human mutation 2015; 36: 1205-1214 DOI: 10.1002/humu.22902.
• 153 Toh MR, Chong ST, Chan SH. et al. Functional analysis of clinical BARD1 germline variants. Cold Spring Harb Mol Case Stud 2019; 5 DOI: 10.1101/mcs.a004093.
• 154 Thompson ER, Gorringe KL, Rowley SM. et al. Reevaluation of the BRCA2 truncating allele c.9976A > T (p.Lys3326Ter) in a familial breast cancer context. Sci Rep 2015; 5: 14800 DOI: 10.1038/srep14800.
• 155 Mavaddat N, Michailidou K, Dennis J. et al. Polygenic Risk Scores for Prediction of Breast Cancer and Breast Cancer Subtypes. Am J Hum Genet 2019; 104: 21-34 DOI: 10.1016/j.ajhg.2018.11.002.
• 156 Kuchenbaecker KB, McGuffog L, Barrowdale D. et al. Evaluation of Polygenic Risk Scores for Breast and Ovarian Cancer Risk Prediction in BRCA1 and BRCA2 Mutation Carriers. J Natl Cancer Inst 2017; 109 DOI: 10.1093/jnci/djw302.
• 157 Mavaddat N, Pharoah PD, Michailidou K. et al. Prediction of breast cancer risk based on profiling with common genetic variants. J Natl Cancer Inst 2015; 107 DOI: 10.1093/jnci/djv036.
• 158 Muranen TA, Blomqvist C, Dork T. et al. Patient survival and tumor characteristics associated with CHEK2:p.I157T – findings from the Breast Cancer Association Consortium. Breast Cancer Res 2016; 18: 98 DOI: 10.1186/s13058-016-0758-5.
• 159 Han FF, Guo CL, Liu LH. The effect of CHEK2 variant I157T on cancer susceptibility: evidence from a meta-analysis. DNA and cell biology 2013; 32: 329-335 DOI: 10.1089/dna.2013.1970.
• 160 Hauke J, Horvath J, Gross E. et al. Gene panel testing of 5589 BRCA1/2-negative index patients with breast cancer in a routine diagnostic setting: results of the German Consortium for Hereditary Breast and Ovarian Cancer. Cancer Med 2018; 7: 1349-1358 DOI: 10.1002/cam4.1376.