Rare genetic variants: making the connection with breast cancer susceptibility

Tú Nguyen-Dumont; Jenna Stewart; Ingrid Winship; Melissa C. Southey; Tú Nguyen-Dumont; Jenna Stewart; Ingrid Winship; Melissa C. Southey

doi:10.3934/genet.2015.4.281

AIMS Genetics

2015, Volume 2, Issue 4: 281-292. doi: 10.3934/genet.2015.4.281

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Rare genetic variants: making the connection with breast cancer susceptibility

1.
Genetic Epidemiology Laboratory, Department of Pathology, The University of Melbourne, Victoria, 3010, Australia and The Royal Melbourne Hospital, Parkville, Victoria, 3050, Australia
2.
Department of Medicine, The University of Melbourne, Victoria, 3010, Australia and The Royal Melbourne Hospital, Parkville, Victoria, 3050, Australia

Received: 08 October 2015 Accepted: 14 December 2015 Published: 21 December 2015

The practice of clinical genetics in the context of breast cancer predisposition has reached another critical point in its evolution. For the past two decades, genetic testing offered to women attending clinics has been limited to BRCA1 and BRCA2 unless other syndromic indicators have been evident (e.g. PTEN and TP53 for Cowden and Li-Fraumeni syndrome, respectively). Women (and their families) who are concerned about their personal and/or family history of breast and ovarian cancer have enthusiastically engaged with clinical genetics services, anticipating a genetic cause for their cancer predisposition will be identified and to receive clinical guidance for their risk management and treatment options. Genetic testing laboratories have demonstrated similar enthusiasm for transitioning from single gene to gene panel testing that now provide opportunities for the large number of women found not to carry mutations in BRCA1 and BRCA2, enabling them to undergo additional genetic testing. However, these panel tests have limited clinical utility until more is understood about the cancer risks (if any) associated with the genetic variation observed in the genes included on these panels. New data is urgently needed to improve the interpretation of the genetic variation data that is already reported from these panels and to inform the selection of genes included in gene panel tests in the future. To address this issue, large internationally coordinated research studies are required to provide the evidence-base from which clinical genetics for breast cancer susceptibility can be practiced in the era of gene panel testing and oncogenetic practice.
Two significant steps associated with this process include i) validating the genes on these panels (and those likely to be added in the future) as bona fide breast cancer predisposition genes and ii) interpreting the variation, on a variant-by-variant basis in terms of their likely “pathogenicity” ― a process commonly referred to as “variant classification” that will enable this new genetic information to be used at an individual level in clinical genetics services. Neither of these fundamental steps have been achieved for the majority of genes included on the panels.
We are thus at a critical point for translational research in breast cancer clinical genetics ― how can rare genetic variants be interpreted such that they can be used in clinical genetics services and oncogenetic practice to identify and to inform the management of families that carry these variants?
- Rare variants,
- breast cancer,
- clinical genetics,
- clinical translation,
- in silico prediction
Citation: Tú Nguyen-Dumont, Jenna Stewart, Ingrid Winship, Melissa C. Southey. Rare genetic variants: making the connection with breast cancer susceptibility[J]. AIMS Genetics, 2015, 2(4): 281-292. doi: 10.3934/genet.2015.4.281

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Abstract

The practice of clinical genetics in the context of breast cancer predisposition has reached another critical point in its evolution. For the past two decades, genetic testing offered to women attending clinics has been limited to BRCA1 and BRCA2 unless other syndromic indicators have been evident (e.g. PTEN and TP53 for Cowden and Li-Fraumeni syndrome, respectively). Women (and their families) who are concerned about their personal and/or family history of breast and ovarian cancer have enthusiastically engaged with clinical genetics services, anticipating a genetic cause for their cancer predisposition will be identified and to receive clinical guidance for their risk management and treatment options. Genetic testing laboratories have demonstrated similar enthusiasm for transitioning from single gene to gene panel testing that now provide opportunities for the large number of women found not to carry mutations in BRCA1 and BRCA2, enabling them to undergo additional genetic testing. However, these panel tests have limited clinical utility until more is understood about the cancer risks (if any) associated with the genetic variation observed in the genes included on these panels. New data is urgently needed to improve the interpretation of the genetic variation data that is already reported from these panels and to inform the selection of genes included in gene panel tests in the future. To address this issue, large internationally coordinated research studies are required to provide the evidence-base from which clinical genetics for breast cancer susceptibility can be practiced in the era of gene panel testing and oncogenetic practice.
Two significant steps associated with this process include i) validating the genes on these panels (and those likely to be added in the future) as bona fide breast cancer predisposition genes and ii) interpreting the variation, on a variant-by-variant basis in terms of their likely “pathogenicity” ― a process commonly referred to as “variant classification” that will enable this new genetic information to be used at an individual level in clinical genetics services. Neither of these fundamental steps have been achieved for the majority of genes included on the panels.
We are thus at a critical point for translational research in breast cancer clinical genetics ― how can rare genetic variants be interpreted such that they can be used in clinical genetics services and oncogenetic practice to identify and to inform the management of families that carry these variants?

References

[1]	Easton DF, Pharoah PD, Antoniou AC, et al. (2015) Gene-panel sequencing and the prediction of breast-cancer risk. N Engl J Med 372: 2243-2257. doi: 10.1056/NEJMsr1501341
[2]	Desmond A, Kurian AW, Gabree M, et al. (2015) Clinical Actionability of Multigene Panel Testing for Hereditary Breast and Ovarian Cancer Risk Assessment. JAMA Oncol 1: 943-951. doi: 10.1001/jamaoncol.2015.2690
[3]	Campuzano O, Sarquella-Brugada G, Mademont-Soler I, et al. (2014) Identification of Genetic Alterations, as Causative Genetic Defects in Long QT Syndrome, Using Next Generation Sequencing Technology. PLoS One 9: e114894. doi: 10.1371/journal.pone.0114894
[4]	Kapoor NS, Curcio LD, Blakemore CA, et al. (2015) Multigene Panel Testing Detects Equal Rates of Pathogenic BRCA1/2 Mutations and has a Higher Diagnostic Yield Compared to Limited BRCA1/2 Analysis Alone in Patients at Risk for Hereditary Breast Cancer. Ann Surg Oncol 22: 3282-3288. doi: 10.1245/s10434-015-4754-2
[5]	Antoniou A, Pharoah PDP, Narod S, et al. (2003) Average risks of breast and ovarian cancer associated with BRCA1 or BRCA2 mutations detected in case Series unselected for family history: a combined analysis of 22 studies. Am J Hum Genet 72: 1117-1130. doi: 10.1086/375033
[6]	Lovelock PK, Spurdle AB, Mok MT, et al. (2007) Identification of BRCA1 missense substitutions that confer partial functional activity: potential moderate risk variants? Breast Cancer Res 9: R82. doi: 10.1186/bcr1826
[7]	Spurdle AB, Whiley PJ, Thompson B, et al. (2012) BRCA1 R1699Q variant displaying ambiguous functional abrogation confers intermediate breast and ovarian cancer risk. J Med Genet 49: 525-532. doi: 10.1136/jmedgenet-2012-101037
[8]	Michailidou K, Hall P, Gonzalez-Neira A, et al. (2013) Large-scale genotyping identifies 41 new loci associated with breast cancer risk. Nat Genet 45: 353-361, 361e351-352. doi: 10.1038/ng.2563
[9]	Meeks HD, Song H, Michailidou K, et al. (2016) BRCA2 Polymorphic Stop Codon K3326X and the Risk of Breast, Prostate, and Ovarian Cancers. J Natl Cancer Inst 108.
[10]	Antoniou AC, Casadei S, Heikkinen T, et al. (2014) Breast-cancer risk in families with mutations in PALB2. N Engl J Med 371: 497-506. doi: 10.1056/NEJMoa1400382
[11]	Southey MC, Teo ZL, Dowty JG, et al. (2010) A PALB2 mutation associated with high risk of breast cancer. Breast Cancer Res 12: R109. doi: 10.1186/bcr2796
[12]	Southey MC, Teo ZL, Winship I (2013) PALB2 and breast cancer: ready for clinical translation! Appl Clin Genet 6: 43-52.
[13]	Teo ZL, Park DJ, Provenzano E, et al. (2013) Prevalence of PALB2 mutations in Australasian multiple-case breast cancer families. Breast Cancer Res 15: R17. doi: 10.1186/bcr3392
[14]	Teo ZL, Sawyer SD, James PA, et al. (2013) The incidence of PALB2 c.3113G>A in women with a strong family history of breast and ovarian cancer attending familial cancer centres in Australia. Fam Cancer 12: 587-595.
[15]	Wong MW, Nordfors C, Mossman D, et al. (2011) BRIP1, PALB2, and RAD51C mutation analysis reveals their relative importance as genetic susceptibility factors for breast cancer. Breast Cancer Res Treat 127: 853-859. doi: 10.1007/s10549-011-1443-0
[16]	Dansonka-Mieszkowska A, Kluska A, Moes J, et al. (2010) A novel germline PALB2 deletion in Polish breast and ovarian cancer patients. BMC Med Genet 11: 20.
[17]	Foulkes WD, Ghadirian P, Akbari MR, et al. (2007) Identification of a novel truncating PALB2 mutation and analysis of its contribution to early-onset breast cancer in French-Canadian women. Breast Cancer Res 9: R83. doi: 10.1186/bcr1828
[18]	Erkko H, Xia B, Nikkila J, et al. (2007) A recurrent mutation in PALB2 in Finnish cancer families. Nature 446: 316-319. doi: 10.1038/nature05609
[19]	Tischkowitz M, Capanu M, Sabbaghian N, et al. (2012) Rare germline mutations in PALB2 and breast cancer risk: a population-based study. Hum Mutat 33: 674-680. doi: 10.1002/humu.22022
[20]	Plon SE, Eccles DM, Easton D, et al. (2008) Sequence variant classification and reporting: recommendations for improving the interpretation of cancer susceptibility genetic test results. Hum Mutat 29: 1282-1291. doi: 10.1002/humu.20880
[21]	Scott CL, Jenkins MA, Southey MC, et al. (2003) Average age-specific cumulative risk of breast cancer according to type and site of germline mutations in BRCA1 and BRCA2 estimated from multiple-case breast cancer families attending Australian family cancer clinics. Hum Genet 112: 542-551.
[22]	Tavtigian SV, Oefner PJ, Babikyan D, et al. (2009) Rare, evolutionarily unlikely missense substitutions in ATM confer increased risk of breast cancer. Am J Hum Genet 85: 427-446. doi: 10.1016/j.ajhg.2009.08.018
[23]	Le Calvez-Kelm F, Lesueur F, Damiola F, et al. (2011) Rare, evolutionarily unlikely missense substitutions in CHEK2 contribute to breast cancer susceptibility: results from a breast cancer family registry case-control mutation-screening study. Breast cancer research : BCR 13: R6. doi: 10.1186/bcr2810
[24]	Thusberg J, Vihinen M (2009) Pathogenic or not? And if so, then how? Studying the effects of missense mutations using bioinformatics methods. Hum Mutat 30: 703-714.
[25]	Zuckerkandl E (1965) [Remarks on the evolution of polynucleotides compared to that of polypeptides]. Bull Soc Chim Biol (Paris) 47: 1729-1730.
[26]	Jukes TH, King JL (1971) Deleterious mutations and neutral substitutions. Nature 231: 114-115. doi: 10.1038/231114a0
[27]	Jordan DM, Ramensky VE, Sunyaev SR (2010) Human allelic variation: perspective from protein function, structure, and evolution. Curr Opin Struct Biol 20: 342-350. doi: 10.1016/j.sbi.2010.03.006
[28]	Ng PC, Henikoff S (2001) Predicting deleterious amino acid substitutions. Genome Res 11: 863-874. doi: 10.1101/gr.176601
[29]	Ferrer-Costa C, Gelpi JL, Zamakola L, et al. (2005) PMUT: a web-based tool for the annotation of pathological mutations on proteins. Bioinformatics 21: 3176-3178. doi: 10.1093/bioinformatics/bti486
[30]	Chun S, Fay JC (2009) Identification of deleterious mutations within three human genomes. Genome Res 19: 1553-1561. doi: 10.1101/gr.092619.109
[31]	Adzhubei IA, Schmidt S, Peshkin L, et al. (2010) A method and server for predicting damaging missense mutations. Nat Methods 7: 248-249. doi: 10.1038/nmeth0410-248
[32]	Tavtigian SV, Deffenbaugh AM, Yin L, et al. (2006) Comprehensive statistical study of 452 BRCA1 missense substitutions with classification of eight recurrent substitutions as neutral. J Med Genet 43: 295-305.
[33]	Bromberg Y, Rost B (2007) SNAP: predict effect of non-synonymous polymorphisms on function. Nucleic Acids Res 35: 3823-3835. doi: 10.1093/nar/gkm238
[34]	Goldgar DE, Easton DF, Deffenbaugh AM, et al. (2004) Integrated evaluation of DNA sequence variants of unknown clinical significance: application to BRCA1 and BRCA2. Am J Hum Genet 75: 535-544. doi: 10.1086/424388
[35]	Easton DF, Deffenbaugh AM, Pruss D, et al. (2007) A systematic genetic assessment of 1,433 sequence variants of unknown clinical significance in the BRCA1 and BRCA2 breast cancer-predisposition genes. Am J Hum Genet 81: 873-883. doi: 10.1086/521032
[36]	Goldgar DE, Easton DF, Byrnes GB, et al. (2008) Genetic evidence and integration of various data sources for classifying uncertain variants into a single model. Hum Mutat 29: 1265-1272. doi: 10.1002/humu.20897
[37]	Spurdle AB, Lakhani SR, Healey S, et al. (2008) Clinical classification of BRCA1 and BRCA2 DNA sequence variants: the value of cytokeratin profiles and evolutionary analysis--a report from the kConFab Investigators. J Clin Oncol 26: 1657-1663. doi: 10.1200/JCO.2007.13.2779
[38]	Spurdle AB, Healey S, Devereau A, et al. (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. Hum Mutat 33: 2-7. doi: 10.1002/humu.21628
[39]	Vallee MP, Francy TC, Judkins MK, et al. (2012) Classification of missense substitutions in the BRCA genes: a database dedicated to Ex-UVs. Hum Mutat 33: 22-28. doi: 10.1002/humu.21629
[40]	Couch FJ, Rasmussen LJ, Hofstra R, et al. (2008) Assessment of functional effects of unclassified genetic variants. Hum Mutat 29: 1314-1326. doi: 10.1002/humu.20899
[41]	Wu K, Hinson SR, Ohashi A, et al. (2005) Functional evaluation and cancer risk assessment of BRCA2 unclassified variants. Cancer Res 65: 417-426.
[42]	Mitui M, Nahas SA, Du LT, et al. (2009) Functional and computational assessment of missense variants in the ataxia-telangiectasia mutated (ATM) gene: mutations with increased cancer risk. Hum Mutat 30: 12-21. doi: 10.1002/humu.20805
[43]	Roeb W, Higgins J, King MC (2012) Response to DNA damage of CHEK2 missense mutations in familial breast cancer. Hum Mol Genet 21: 2738-2744. doi: 10.1093/hmg/dds101
[44]	Kato S, Han SY, Liu W, et al. (2003) 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 100: 8424-8429. doi: 10.1073/pnas.1431692100
[45]	Iversen ES, Jr., Couch FJ, Goldgar DE, et al. (2011) A computational method to classify variants of uncertain significance using functional assay data with application to BRCA1. Cancer Epidemiol Biomarkers Prev 20: 1078-1088. doi: 10.1158/1055-9965.EPI-10-1214
[46]	Guidugli L, Pankratz VS, Singh N, et al. (2013) A classification model for BRCA2 DNA binding domain missense variants based on homology-directed repair activity. Cancer Res 73: 265-275.
[47]	Rahman N (2014) Mainstreaming genetic testing of cancer predisposition genes. Clin Med 14: 436-439. doi: 10.7861/clinmedicine.14-4-436
[48]	http://apps.ccge.medschl.cam.ac.uk/consortia/bcac/index.html.
[49]	French JD, Ghoussaini M, Edwards SL, et al. (2013) Functional variants at the 11q13 risk locus for breast cancer regulate cyclin D1 expression through long-range enhancers. Am J Hum Genet 92: 489-503. doi: 10.1016/j.ajhg.2013.01.002
[50]	Goldgar DE, Healey S, Dowty JG, et al. (2011) Rare variants in the ATM gene and risk of breast cancer. Breast Cancer Res 13: R73. doi: 10.1186/bcr2919
[51]	Gorringe KL, Choong DY, Visvader JE, et al. (2008) BARD1 variants are not associated with breast cancer risk in Australian familial breast cancer. Breast Cancer Res Treat 111: 505-509. doi: 10.1007/s10549-007-9799-x
[52]	Seal S, Thompson D, Renwick A, et al. (2006) Truncating mutations in the Fanconi anemia J gene BRIP1 are low-penetrance breast cancer susceptibility alleles. Nat Genet 38: 1239-1241. doi: 10.1038/ng1902
[53]	Schrader KA, Masciari S, Boyd N, et al. (2011) Germline mutations in CDH1 are infrequent in women with early-onset or familial lobular breast cancers. J Med Genet 48: 64-68. doi: 10.1136/jmg.2010.079814
[54]	Bogdanova N, Schurmann P, Waltes R, et al. (2008) NBS1 variant I171V and breast cancer risk. Breast Cancer Res Treat 112: 75-79. doi: 10.1007/s10549-007-9820-4
[55]	Tommiska J, Seal S, Renwick A, et al. (2006) Evaluation of RAD50 in familial breast cancer predisposition. Int J Cancer 118: 2911-2916. doi: 10.1002/ijc.21738
[56]	Rennert G, Lejbkowicz F, Cohen I, et al. (2012) MutYH mutation carriers have increased breast cancer risk. Cancer 118: 1989-1993. doi: 10.1002/cncr.26506
[57]	Sharif S, Moran A, Huson SM, et al. (2007) Women with neurofibromatosis 1 are at a moderately increased risk of developing breast cancer and should be considered for early screening. J Med Genet 44: 481-484. doi: 10.1136/jmg.2007.049346
[58]	Pradella LM, Evangelisti C, Ligorio C, et al. (2014) A novel deleterious PTEN mutation in a patient with early-onset bilateral breast cancer. BMC Cancer 14: 70. doi: 10.1186/1471-2407-14-70
[59]	Figer A, Kaplan A, Frydman M, et al. (2002) Germline mutations in the PTEN gene in Israeli patients with Bannayan-Riley-Ruvalcaba syndrome and women with familial breast cancer. Clin Genet 62: 298-302. doi: 10.1034/j.1399-0004.2002.620407.x
[60]	Meindl A, Hellebrand H, Wiek C, et al. (2010) Germline mutations in breast and ovarian cancer pedigrees establish RAD51C as a human cancer susceptibility gene. Nat Genet 42: 410-414. doi: 10.1038/ng.569
[61]	Loveday C, Turnbull C, Ruark E, et al. (2012) Germline RAD51C mutations confer susceptibility to ovarian cancer. Nat Genet 44: 475-476; author reply 476. doi: 10.1038/ng.2224
[62]	Boardman LA, Couch FJ, Burgart LJ, et al. (2000) Genetic heterogeneity in Peutz-Jeghers syndrome. Hum Mutat 16: 23-30.
[63]	Evans DG, Birch JM, Thorneycroft M, et al. (2002) Low rate of TP53 germline mutations in breast cancer/sarcoma families not fulfilling classical criteria for Li-Fraumeni syndrome. J Med Genet 39: 941-944. doi: 10.1136/jmg.39.12.941
[64]	Mouchawar J, Korch C, Byers T, et al. (2010) Population-based estimate of the contribution of TP53 mutations to subgroups of early-onset breast cancer: Australian Breast Cancer Family Study. Cancer Res 70: 4795-4800. doi: 10.1158/0008-5472.CAN-09-0851
[65]	Park DJ, Lesueur F, Nguyen-Dumont T, et al. (2012) Rare mutations in XRCC2 increase the risk of breast cancer. Am J Hum Genet 90: 734-739. doi: 10.1016/j.ajhg.2012.02.027
[66]	Park DJ, Tao K, Le Calvez-Kelm F, et al. (2014) Rare mutations in RINT1 predispose carriers to breast and Lynch syndrome-spectrum cancers. Cancer Discov 4: 804-815. doi: 10.1158/2159-8290.CD-14-0212
[67]	Kiiski JI, Pelttari LM, Khan S, et al. (2014) Exome sequencing identifies FANCM as a susceptibility gene for triple-negative breast cancer. Proc Natl Acad Sci U S A 111: 15172-15177. doi: 10.1073/pnas.1407909111

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