Skipping of BRCA2 exon 3 (∆E3) is a naturally occurring splicing event, complicating clinical classification of variants that may alter ∆E3 expression. This study used multiple evidence types to assess pathogenicity of 85 variants in/near BRCA2 exon 3. Bioinformatically predicted spliceogenic variants underwent mRNA splicing analysis using minigenes and/or patient samples. ∆E3 was measured using quantitative analysis. A mouse embryonic stem cell (mESC) based assay was used to determine the impact of 18 variants on mRNA splicing and protein function. For each variant, population frequency, bioinformatic predictions, clinical data, and existing mRNA splicing and functional results were collated. Variant class was assigned using a gene-specific adaptation of ACMG/AMP guidelines, following a recently proposed points-based system. mRNA and mESC analysis combined identified six variants with transcript and/or functional profiles interpreted as loss of function. Cryptic splice site use for acceptor site variants generated a transcript encoding a shorter protein that retains activity. Overall, 69/85 (81%) variants were classified using the points-based approach. Our analysis shows the value of applying gene-specific ACMG/AMP guidelines using a points-based approach and highlights the consideration of cryptic splice site usage to appropriately assign PVS1 code strength.

Ambry Genetics Aliso Viejo California USA

Breast Cancer Research Programme Cancer Research Malaysia Subang Jaya Selangor Malaysia

Center for Familial Breast and Ovarian Cancer Faculty of Medicine and University Hospital Cologne University of Cologne Cologne Germany

Center for Genomic Medicine Rigshospitalet Copenhagen University Hospital Copenhagen Denmark

Center for Integrated Oncology Faculty of Medicine and University Hospital Cologne University of Cologne Cologne Germany

Centre for Medical Genetics Ghent University Gent Belgium

Centro de Investigación en Red de Enfermedades Raras Madrid Spain

Clinical Cancer Research Center Aalborg University Hospital Aalborg Denmark

Department of Biochemistry and Molecular Biology and the Villum Center for Bioanalytical Sciences University of Southern Denmark Odense Denmark

Department of Cancer Epidemiology and Genetics Masaryk Memorial Cancer Institute Brno Czech Republic

Department of Clinical Genetics Aarhus University Hospital Aarhus N Denmark

Department of Clinical Genetics Maastricht University Medical Center Maastricht the Netherlands

Department of Clinical Genetics Odense University Hospital Odence C Denmark

Department of Clinical Genetics Rigshospitalet Copenhagen University Hospital Copenhagen Denmark

Department of Clinical Medicine Aalborg University Aalborg Denmark

Department of Dermatology Huntsman Cancer Institute University of Utah School of Medicine Salt Lake City Utah USA

Department of Genetics and Computational Biology QIMR Berghofer Medical Research Institute Brisbane Queensland Australia

Department of Human Genetics Leiden University Medical Center Leiden the Netherlands

Department of Molecular Medicine Aarhus University Hospital Aarhus Denmark

Department of OB GYN and Comprehensive Cancer Center Medical University of Vienna Vienna Austria

Department of Pathology and Biomedical Science University of Otago Christchurch New Zealand

Department of Surgery Faculty of Medicine University of Malaya Kuala Lumpur Malaysia

Department of Tumour Biology The Norwegian Radium Hospital Oslo University Hospital Oslo Norway

Division of Functional Onco genomics and Genetics Centro di Riferimento Oncologico di Aviano IRCCS Aviano Italy

Division of Oncology Department of Clinical Sciences Lund Lund University Lund Sweden

Fundación Pública Galega de Medicina Xenómica Santiago de Compostela Spain

Hereditary Cancer Clinic Nelune Comprehensive Cancer Care Centre Sydney New South Wales Australia

Hereditary Cancer Program Catalan Institute of Oncology ONCOBELL IDIBELL IDTP CIBERONC Hospitalet de Llobregat Spain

Human Development and Health Faculty of Medicine University of Southampton Southampton UK

Institute for Medical Informatics Statistics and Epidemiology University of Leipzig Leipzig Germany

Instituto de Investigación Sanitaria de Santiago de Compostela Complejo Hospitalario Universitario de Santiago SERGAS Santiago de Compostela Spain

Middlesex Health Shoreline Cancer Center Westbrook Connecticut USA

Molecular Diagnostics Aalborg University Hospital Aalborg Denmark

Molecular Oncology Laboratory CIBERONC Hospital Clinico San Carlos IdISSC Madrid Spain

Parkville Familial Cancer Centre Peter MacCallum Cancer Center Melbourne Victoria Australia

Sir Peter MacCallum Department of Oncology The University of Melbourne Melbourne Victoria Australia

Unit of Molecular Bases of Genetic Risk and Genetic Testing Department of Research Fondazione IRCCS Istituto Nazionale dei Tumori Milan Italy

See more in PubMed

Abou Tayoun, A. N. , Pesaran, T. , DiStefano, M. T. , Oza, A. , Rehm, H. L. , Biesecker, L. G. , & Harrison, S. M. (2018). Recommendations for interpreting the loss of function PVS1 ACMG/AMP variant criterion. Human Mutation, 39(11), 1517–1524. 10.1002/humu.23626 PubMed DOI PMC

Biswas, K. , Das, R. , Eggington, J. M. , Qiao, H. , North, S. L. , Stauffer, S. , Burkett, S. S. , Martin, B. K. , Southon, E. , Sizemore, S. C. , Pruss, D. , Bowles, K. R. , Roa, B. B. , Hunter, N. , Tessarollo, L. , Wenstrup, R. J. , Byrd, R. A. , & Sharan, S. K. (2012). 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, 21(18), 3993–4006. 10.1093/hmg/dds222 PubMed DOI PMC

Canson, D. , Glubb, D. , & Spurdle, A. B. (2020). Variant effect on splicing regulatory elements, branchpoint usage, and pseudoexonization: Strategies to enhance bioinformatic prediction using hereditary cancer genes as exemplars. Human Mutation, 41(10), 1705–1721. 10.1002/humu.24074 PubMed DOI

Caputo, S. , Telly, D. , Briaux, A. , Sesen, J. , Ceppi, M. , Bonnet, F. , Bourdon, V. , Coulet, F. , Castera, L. , Delnatte, C. , Hardouin, A. , Mazoyer, S. , Schultz, I. , Sevenet, N. , Uhrhammer, N. , Bonnet, C. , Tilkin‐Mariamé, A. F. , Houdayer, C. , Moncoutier, V. , … Rouleau, E. (2021). 5' Region large genomic rearrangements in the BRCA1 gene in French families: Identification of a tandem triplication and nine distinct deletions with five recurrent breakpoints. Cancers, 13(13):3171. 10.3390/cancers13133171 PubMed DOI PMC

Caputo, S. M. , Léone, M. , Damiola, F. , Ehlen, A. , Carreira, A. , Gaidrat, P. , Martins, A. , Brandão, R. D. , Peixoto, A. , Vega, A. , Houdayer, C. , Delnatte, C. , Bronner, M. , Muller, D. , Castera, L. , Guillaud‐Bataille, M. , Søkilde, I. , Uhrhammer, N. , Demontety, S. , … Rouleau, E. (2018). Full in‐frame exon 3 skipping of BRCA2 confers high risk of breast and/or ovarian cancer. Oncotarget, 9(25), 17334–17348. 10.18632/oncotarget.24671 PubMed DOI PMC

Cartegni, L. , Chew, S. L. , & Krainer, A. R. (2002). Listening to silence and understanding nonsense: Exonic mutations that affect splicing. Nature Reviews Genetics, 3(4), 285–298. 10.1038/nrg775 PubMed DOI

Colombo, M. , Lòpez‐Perolio, I. , Meeks, H. D. , Caleca, L. , Parsons, M. T. , Li, H. , De Vecchi, G. , Tudini, E. , Foglia, C. , Mondini, P. , Manoukian, S. , Behar, R. , Garcia, E. B. G. , Meindl, A. , Montagna, M. , Niederacher, D. , Schmidt, A. Y. , Varesco, L. , Wappenschmidt, B. , … Radice, P. (2018). The BRCA2 c.68‐7T > A variant is not pathogenic: A model for clinical calibration of spliceogenicity. Human Mutation, 39, 729–741. 10.1002/humu.23411 PubMed DOI PMC

Conner, B. R. , Hernandez, F. , Souders, B. , Landrith, T. , Boland, C. R. , & Karam, R. (2019). RNA analysis identifies pathogenic duplications in MSH2 in patients with lynch syndrome. Gastroenterology, 156(6), 1924–1925. 10.1053/j.gastro.2019.01.248 PubMed DOI PMC

Diez, O. , Gutierrez‐Enriquez, S. , Ramon y Cajal, T. , Alonso, C. , Balmana, J. , & Llort, G. (2007). Caution should be used when interpreting alterations affecting the exon 3 of the BRCA2 gene in breast/ovarian cancer families. Journal of Clinical Oncology, 25(31), 5035–5036. 10.1200/JCO.2007.13.4346 PubMed DOI

Dines, J. N. , Shirts, B. H. , Slavin, T. P. , Walsh, T. , King, M. C. , Fowler, D. M. , & Pritchard, C. C. (2020). Systematic misclassification of missense variants in BRCA1 and BRCA2 “coldspots”. Genetics in Medicine, 22(5), 825–830. 10.1038/s41436-019-0740-6 PubMed DOI PMC

Dorling, L. , Carvalho, S. , Allen, J. , González‐Neira, A. , Luccarini, C. , Wahlström, C. , Pooley, K. A. , Parsons, M. T. , Fortuno, C. , Wang, Q. , Bolla, M. K. , Dennis, J. , Keeman, R. , Alonso, M. R. , Álvarez, N. , Herraez, B. , Fernandez, V. , Núñez‐Torres, R. , Osorio, A. , … Rookus, M. A. (2021). Breast cancer risk genes – Association analysis in more than 113,000 women. New England Journal of Medicine, 384(5), 428–439. 10.1056/NEJMoa1913948 PubMed DOI PMC

Easton, D. F. , Deffenbaugh, A. M. , Pruss, D. , Frye, C. , Wenstrup, R. J. , Allen‐Brady, K. , Tavtigian, S. V. , Monteiro, A. N. , Iversen, E. S. , Couch, F. J. , & Goldgar, D. E. (2007). A systematic genetic assessment of 1,433 sequence variants of unknown clinical significance in the BRCA1 and BRCA2 breast cancer‐predisposition genes. American Journal of Human Genetics, 81(5), 873–883. 10.1086/521032 PubMed DOI PMC

Fackenthal, J. D. , Yoshimatsu, T. , Zhang, B. , de Garibay, G. R. , Colombo, M. , De Vecchi, G. , Ayoub, S. C. , Lal, K. , Olopade, O. I. , Vega, A. , Santamariña, M. , Blanco, A. , Wappenschmidt, B. , Becker, A. , Houdayer, C. , Walker, L. C. , López‐Perolio, I. , Thomassen, M. , Parsons, M. , … de la Hoya, M. (2016). Naturally occurring BRCA2 alternative mRNA splicing events in clinically relevant samples. Journal of Medical Genetics, 53(8), 548–558. 10.1136/jmedgenet-2015-103570 PubMed DOI

Farber‐Katz, S. , Hsuan, V. , Wu, S. , Landrith, T. , Vuong, H. , Xu, D. , Li, B. , Hoo, J. , Lam, S. , Nashed, S. , Toppmeyer, D. , Gray, P. , Haynes, G. , Lu, H. M. , Elliott, A. , Tippin Davis, B. , & Karam, R. (2018). Quantitative analysis of BRCA1 and BRCA2 germline splicing variants using a novel RNA‐massively parallel sequencing assay. Frontiers in Oncology, 8, 286. 10.3389/fonc.2018.00286 PubMed DOI PMC

Fraile‐Bethencourt, E. , Valenzuela‐Palomo, A. , Diez‐Gomez, B. , Goina, E. , Acedo, A. , Buratti, E. , & Velasco, E. A. (2019). Mis‐splicing in breast cancer: Identification of pathogenic BRCA2 variants by systematic minigene assays. Journal of Pathology, 248(4), 409–420. 10.1002/path.5268 PubMed DOI

de Garibay, G. R. , Acedo, A. , García‐Casado, Z. , Gutiérrez‐Enríquez, S. , Tosar, A. , Romero, A. , Garre, P. , Llort, G. , Thomassen, M. , Díez, O. , Pérez‐Segura, P. , Díaz‐Rubio, E. , Velasco, E. A. , Caldés, T. , & de la Hoya, M. (2014). Capillary electrophoresis analysis of conventional splicing assays: IARC analytical and clinical classification of 31 BRCA2 genetic variants. Human Mutation, 35(1), 53–57. 10.1002/humu.22456 PubMed DOI

Gayther, S. A. , Mangion, J. , Russell, P. , Seal, S. , Barfoot, R. , Ponder, B. A. , Stratton, M. R. , & Easton, D. (1997). Variation of risks of breast and ovarian cancer associated with different germline mutations of the BRCA2 gene. Nature Genetics, 15(1), 103–105. 10.1038/ng0197-103 PubMed DOI

Goldgar, D. E. , Easton, D. F. , Byrnes, G. B. , Spurdle, A. B. , Iversen, E. S. ,  Greenblatt, M. S. , & IARC Unclassified Genetic Variants Working Group . (2008). Genetic evidence and integration of various data sources for classifying uncertain variants into a single model. Human Mutation, 29(11), 1265–1272. 10.1002/humu.20897 PubMed DOI PMC

Goldgar, D. E. , Easton, D. F. , Deffenbaugh, A. M. , Monteiro, A. N. , Tavtigian, S. V. , Couch, F. J. , & Breast Cancer Information Core Steering, C. (2004). Integrated evaluation of DNA sequence variants of unknown clinical significance: Application to BRCA1 and BRCA2. American Journal of Human Genetics, 75(4), 535–544. 10.1086/424388 PubMed DOI PMC

Guidugli, L. , Shimelis, H. , Masica, D. L. , Pankratz, V. S. , Lipton, G. B. , Singh, N. , Hu, C. , Monteiro, A. , Lindor, N. M. , Goldgar, D. E. , Karchin, R. , Iversen, E. S. , & Couch, F. J. (2018). Assessment of the clinical relevance of BRCA2 missense variants by functional and computational approaches. American Journal of Human Genetics, 102, 233–248. 10.1016/j.ajhg.2017.12.013 PubMed DOI PMC

Hartford, S. A. , Chittela, R. , Ding, X. , Vyas, A. , Martin, B. , Burkett, S. , Haines, D. C. , Southon, E. , Tessarollo, L. , & Sharan, S. K. (2016). Interaction with PALB2 is essential for maintenance of genomic integrity by BRCA2. PLoS Genetics, 12(8):e1006236. 10.1371/journal.pgen.1006236 PubMed DOI PMC

de la Hoya, M. , Soukarieh, O. , López‐Perolio, I. , Vega, A. , Walker, L. C. , van Ierland, Y. , Baralle, D. , Santamariña, M. , Lattimore, V. , Wijnen, J. , Whiley, P. , Blanco, A. , Raponi, M. , Hauke, J. , Wappenschmidt, B. , Becker, A. , Hansen, T. V. , Behar, R. , Investigators, K. , … Spurdle, A. B. (2016). Combined genetic and splicing analysis of BRCA1 c.[594‐2A>C; 641A>G] highlights the relevance of naturally occurring in‐frame transcripts for developing disease gene variant classification algorithms. Human Molecular Genetics, 25(11), 2256–2268. 10.1093/hmg/ddw094 PubMed DOI PMC

http://agvgd.hci.utah.edu/

http://fengbj-laboratory.org/BayesDel/BayesDel.html

https://spliceailookup.broadinstitute.org

http://varnomen.hgvs.org/

Ikegami, M. , Kohsaka, S. , Ueno, T. , Momozawa, Y. , Inoue, S. , Tamura, K. , Shimomura, A. , Hosoya, N. , Kobayashi, H. , Tanaka, S. , & Mano, H. (2020). High‐throughput functional evaluation of BRCA2 variants of unknown significance. Nature Communications, 11(1), 2573. 10.1038/s41467-020-16141-8 PubMed DOI PMC

Jaganathan, K. , Kyriazopoulou Panagiotopoulou, S. , McRae, J. F. , Darbandi, S. F. , Knowles, D. , Li, Y. I. , Kosmicki, J. A. , Arbelaez, J. , Cui, W. , Schwartz, G. B. , Chow, E. D. , Kanterakis, E. , Gao, H. , Kia, A. , Batzoglou, S. , Sanders, S. J. , & Farh, K. K. (2019). Predicting splicing from primary sequence with deep learning. Cell, 176(3), 535–548. 10.1016/j.cell.2018.12.015 PubMed DOI

Landrith, T. , Li, B. , Cass, A. A. , Conner, B. R. , LaDuca, H. , McKenna, D. B. , Maxwell, K. N. , Domchek, S. , Morman, N. A. , Heinlen, C. , Wham, D. , Koptiuch, C. , Vagher, J. , Rivera, R. , Bunnell, A. , Patel, G. , Geurts, J. L. , Depas, M. M. , Gaonkar, S. , … Karam, R. (2020). Splicing profile by capture RNA‐seq identifies pathogenic germline variants in tumor suppressor genes. npj Precision Oncology, 4, 4. 10.1038/s41698-020-0109-y PubMed DOI PMC

Li, H. , LaDuca, H. , Pesaran, T. , Chao, E. C. , Dolinsky, J. S. , Parsons, M. , Spurdle, A. B. , Polley, E. C. , Shimelis, H. , Hart, S. N. , Hu, C. , Couch, F. J. , & Goldgar, D. E. (2020). Classification of variants of uncertain significance in BRCA1 and BRCA2 using personal and family history of cancer from individuals in a large hereditary cancer multigene panel testing cohort. Genetics in Medicine, 22(4), 701–708. 10.1038/s41436-019-0729-1 PubMed DOI PMC

Mesman, R. , Calléja, F. , Hendriks, G. , Morolli, B. , Misovic, B. , Devilee, P. , van Asperen, C. J. , Vrieling, H. , & Vreeswijk, M. (2019). The functional impact of variants of uncertain significance in BRCA2. Genetics in Medicine, 21(2), 293–302. 10.1038/s41436-018-0052-2 PubMed DOI PMC

Mesman, R. L. S. , Calleja, F. , de la Hoya, M. , Devilee, P. , van Asperen, C. J. , Vrieling, H. , & Vreeswijk, M. P. G. (2020). Alternative mRNA splicing can attenuate the pathogenicity of presumed loss‐of‐function variants in BRCA2. Genetics in Medicine, 22(8), 1355–1365. 10.1038/s41436-020-0814-5 PubMed DOI PMC

Mohammadi, L. , Vreeswijk, M. P. , Oldenburg, R. , van den Ouweland, A. , Oosterwijk, J. C. , van der Hout, A. H. , Hoogerbrugge, N. , Ligtenberg, M. , Ausems, M. G. , van der Luijt, R. B. , Dommering, C. J. , Gille, J. J. , Verhoef, S. , Hogervorst, F. B. , van Os, T. A. , Gómez García, E. , Blok, M. J. , Wijnen, J. T. , Helmer, Q. , … van Houwelingen, H. C. (2009). A simple method for co‐segregation analysis to evaluate the pathogenicity of unclassified variants; BRCA1 and BRCA2 as an example. BMC Cancer, 9, 211. 10.1186/1471-2407-9-211 PubMed DOI PMC

Montalban, G. , Fraile‐Bethencourt, E. , López‐Perolio, I. , Pérez‐Segura, P. , Infante, M. , Durán, M. , Alonso‐Cerezo, M. C. , López‐Fernández, A. , Diez, O. , de la Hoya, M. , Velasco, E. A. , & Gutiérrez‐Enríquez, S. (2018). Characterization of spliceogenic variants located in regions linked to high levels of alternative splicing: BRCA2 c.7976+5G > T as a case study. Human Mutation, 39(9), 1155–1160. 10.1002/humu.23583 PubMed DOI

Nacson, J. , Di Marcantonio, D. , Wang, Y. , Bernhardy, A. J. , Clausen, E. , Hua, X. , Cai, K. Q. , Martinez, E. , Feng, W. , Callén, E. , Wu, W. , Gupta, G. P. , Testa, J. R. , Nussenzweig, A. , Sykes, S. M. , & Johnson, N. (2020). BRCA1 mutational complementation induces synthetic viability. Molecular Cell, 78(5), 951–959. 10.1016/j.molcel.2020.04.006 PubMed DOI PMC

Nix, P. , Mundt, E. , Coffee, B. , Goossen, E. , Warf, B. M. , Brown, K. , Bowles, K. , & Roa, B. (2021). Interpretation of BRCA2 splicing variants: A case series of challenging variant interpretations and the importance of functional RNA analysis. Familial Cancer, 21, 7–19. 10.1007/s10689-020-00224-y PubMed DOI PMC

Nordling, M. , Karlsson, P. , Wahlstrom, J. , Engwall, Y. , Wallgren, A. , & Martinsson, T. (1998). A large deletion disrupts the exon 3 transcription activation domain of the BRCA2 gene in a breast/ovarian cancer family. Cancer Research, 58(7), 1372–1375. PubMed

Oliver, A. W. , Swift, S. , Lord, C. J. , Ashworth, A. , & Pearl, L. H. (2009). Structural basis for recruitment of BRCA2 by PALB2. EMBO Reports, 10(9), 990–996. 10.1038/embor.2009.126 PubMed DOI PMC

Parsons, M. T. , Tudini, E. , Li, H. , Hahnen, E. , Wappenschmidt, B. , Feliubadaló, L. , Aalfs, C. M. , Agata, S. , Aittomäki, K. , Alducci, E. , Alonso‐Cerezo, M. C. , Arnold, N. , Auber, B. , Austin, R. , Azzollini, J. , Balmaña, J. , Barbieri, E. , Bartram, C. R. , Blanco, A. , … Pohl‐Rescigno, E. (2019). Large scale multifactorial likelihood quantitative analysis of BRCA1 and BRCA2 variants: An ENIGMA resource to support clinical variant classification. Human Mutation, 40(9), 1557–1578. 10.1002/humu.23818 PubMed DOI PMC

Peixoto, A. , Santos, C. , Rocha, P. , Pinheiro, M. , Príncipe, S. , Pereira, D. , Rodrigues, H. , Castro, F. , Abreu, J. , Gusmão, L. , Amorim, A. , & Teixeira, M. R. (2009). The c.156_157insAlu BRCA2 rearrangement accounts for more than one‐fourth of deleterious BRCA mutations in northern/central Portugal. Breast Cancer Research and Treatment, 114(1), 31–38. 10.1007/s10549-008-9978-4 PubMed DOI

Richards, S. , Aziz, N. , Bale, S. , Bick, D. , Das, S. , Gastier‐Foster, J. , Grody, W. W. , Hegde, M. , Lyon, E. , Spector, E. , Voelkerding, K. , Rehm, H. L. , & ACMG Laboratory Quality Assurance, C. (2015). 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, 17(5), 405–424. 10.1038/gim.2015.30 PubMed DOI PMC

Sanz, D. J. , Acedo, A. , Infante, M. , Durán, M. , Pérez‐Cabornero, L. , Esteban‐Cardeñosa, E. , Lastra, E. , Pagani, F. , Miner, C. , & Velasco, E. A. (2010). A high proportion of DNA variants of BRCA1 and BRCA2 is associated with aberrant splicing in breast/ovarian cancer patients. Clinical Cancer Research, 16(6), 1957–1967. 10.1158/1078-0432.CCR-09-2564 PubMed DOI

Shamsani, J. , Kazakoff, S. H. , Armean, I. M. , McLaren, W. , Parsons, M. T. , Thompson, B. A. , O'Mara, T. A. , Hunt, S. E. , Waddell, N. , & Spurdle, A. B. (2019). A plugin for the ensembl variant effect predictor that uses MaxEntScan to predict variant spliceogenicity. Bioinformatics, 35(13), 2315–2317. 10.1093/bioinformatics/bty960 PubMed DOI PMC

Spurdle, A. B. , Couch, F. J. , Parsons, M. T. , McGuffog, L. , Barrowdale, D. , Bolla, M. K. , Wang, Q. , Healey, S. , Schmutzler, R. , Wappenschmidt, B. , Rhiem, K. , Hahnen, E. , Engel, C. , Meindl, A. , Ditsch, N. , Arnold, N. , Plendl, H. , Niederacher, D. , Sutter, C. , … Henderson, B. E. (2014). Refined histopathological predictors of BRCA1 and BRCA2 mutation status: a large‐scale analysis of breast cancer characteristics from the BCAC, CIMBA, and ENIGMA consortia. Breast Cancer Research, 16(6):3419. 10.1186/s13058-014-0474-y PubMed DOI PMC

Spurdle, A. B. , Healey, S. , Devereau, A. , Hogervorst, F. B. , Monteiro, A. N. , Nathanson, K. L. , Radice, P. , Stoppa‐Lyonnet, D. , Tavtigian, S. , Wappenschmidt, B. , Couch, F. J. , & Goldgar, D. E. , ENIGMA . (2012). ENIGMA—Evidence‐based network for the interpretation of germline mutant alleles: an international initiative to evaluate risk and clinical significance associated with sequence variation in BRCA1 and BRCA2 genes. Human Mutation, 33(1), 2–7. 10.1002/humu.21628 PubMed DOI PMC

Sy, S. M. , Huen, M. S. , & Chen, J. (2009). PALB2 is an integral component of the BRCA complex required for homologous recombination repair. Proceedings of the National Academy of Sciences of the United States of America, 106(17), 7155–7160. 10.1073/pnas.0811159106 PubMed DOI PMC

Tavtigian, S. V. , Byrnes, G. B. , Goldgar, D. E. , & Thomas, A. (2008). Classification of rare missense substitutions, using risk surfaces, with genetic‐ and molecular‐epidemiology applications. Human Mutation, 29(11), 1342–1354. 10.1002/humu.20896 PubMed DOI PMC

Tavtigian, S. V. , Greenblatt, M. S. , Harrison, S. M. , Nussbaum, R. L. , Prabhu, S. A. , Boucher, K. M. ,  Biesecker, L. G. , & ClinGen Sequence Variant Interpretation Working Group (ClinGen SVI) . (2018). Modeling the ACMG/AMP variant classification guidelines as a Bayesian classification framework. Genetics in Medicine, 20(9), 1054–1060. 10.1038/gim.2017.210 PubMed DOI PMC

Tavtigian, S. V. , Harrison, S. M. , Boucher, K. M. , & Biesecker, L. G. (2020). Fitting a naturally scaled point system to the ACMG/AMP variant classification guidelines. Human Mutation, 41, 1734–1737. 10.1002/humu.24088 PubMed DOI PMC

Thomassen, M. , Blanco, A. , Montagna, M. , Hansen, T. V. , Pedersen, I. S. , Gutiérrez‐Enríquez, S. , Menéndez, M. , Fachal, L. , Santamariña, M. , Steffensen, A. Y. , Jønson, L. , Agata, S. , Whiley, P. , Tognazzo, S. , Tornero, E. , Jensen, U. B. , Balmaña, J. , Kruse, T. A. , Goldgar, D. E. , … Vega, A. (2012). Characterization of BRCA1 and BRCA2 splicing variants: A collaborative report by ENIGMA consortium members. Breast Cancer Research and Treatment, 132(3), 1009–1023. 10.1007/s10549-011-1674-0 PubMed DOI

Thompson, D. , Easton, D. F. , & Goldgar, D. E. (2003). A full‐likelihood method for the evaluation of causality of sequence variants from family data. American Journal of Human Genetics, 73(3), 652–655. 10.1086/378100 PubMed DOI PMC

Tubeuf, H. , Caputo, S. M. , Sullivan, T. , Rondeaux, J. , Krieger, S. , Caux‐Moncoutier, V. , Hauchard, J. , Castelain, G. , Fiévet, A. , Meulemans, L. , Révillion, F. , Léoné, M. , Boutry‐Kryza, N. , Delnatte, C. , Guillaud‐Bataille, M. , Cleveland, L. , Reid, S. , Southon, E. , Soukarieh, O. , … Martins, A. (2020). Calibration of pathogenicity due to variant‐induced leaky splicing defects by using BRCA2 exon 3 as a model system. Cancer Research, 80(17), 3593–3605. 10.1158/0008-5472.CAN-20-0895 PubMed DOI PMC

Valenzuela‐Palomo, A. , Bueno‐Martínez, E. , Sanoguera‐Miralles, L. , Lorca, V. , Fraile‐Bethencourt, E. , Esteban‐Sánchez, A. , Gómez‐Barrero, S. , Carvalho, S. , Allen, J. , García‐Álvarez, A. , Pérez‐Segura, P. , Dorling, L. , Easton, D. F. , Devilee, P. , Vreeswijk, M. P. , de la Hoya, M. , & Velasco, E. A. (2022). Splicing predictions, minigene analyses, and ACMG‐AMP clinical classification of 42 germline PALB2 splice‐site variants. Journal of Pathology, 256(3), 321–334. 10.1002/path.5839 PubMed DOI PMC

Xia, B. , Sheng, Q. , Nakanishi, K. , Ohashi, A. , Wu, J. , Christ, N. , Liu, X. , Jasin, M. , Couch, F. J. , & Livingston, D. M. (2006). Control of BRCA2 cellular and clinical functions by a nuclear partner, PALB2. Molecular Cell, 22(6), 719–729. 10.1016/j.molcel.2006.05.022 PubMed DOI

Yeo, G. , & Burge, C. B. (2004). Maximum entropy modeling of short sequence motifs with applications to RNA splicing signals. Journal of Computational Biology, 11(2–3), 377–394. 10.1089/1066527041410418 PubMed DOI