Sean V. Tavtigian

Sean V. Tavtigian, PhD

Languages spoken: English, French

Academic Information

Departments Primary - Oncological Sciences

Academic Office Information

Sean.Tavtigian@hci.utah.edu

Lab

Research Interests

  • Cancer Susceptibility Genes
  • Evaluation of Variants of Uncertain Significance
  • Breast Cancer
  • Ovarian Cancer
  • Colorectal Cancer Genetics

Sean V. Tavtigian, PhD, is a professor in the Department of Oncological Sciences at the University of Utah and a co-leader of the Huntsman Cancer Institute's Cancer Control and Population Sciences Program.

In 1984, he earned a Bachelor's degree (Honors) from Pomona College (Claremont, CA) where he was a joint-major in Biology and Chemistry.

After spending one year in medical school at UC San Francisco, he took a leave of absence and moved to graduate school.

He then earned a PhD from the California Institute of Technology (Caltech, Pasadena, CA) in Molecular Biology and Biochemistry. His PhD thesis was on the transcriptional regulatory capacity of c-Myc.

After graduation, Dr Tavtigian took a temporary postdoc position at Myriad Genetics (Salt Lake City, UT) while he was waiting for a fellowship that would have funded an academic postdoc at Harvard to activate. However, before that fellowship actually activated, Dr Tavtigian was offered a Senior Scientist position at Myriad. In the end, a planned 6-month postdoc in Cancer Genetics became a 9-year stay. During his time at Myriad, Dr Tavtigian contributed to the identification and/or complete cloning of the key cancer susceptibility genes BRCA1, BRCA2, and PTEN.

In 2002, Dr Tavtigian moved from Myriad to the International Agency for Research on Cancer (IARC, Lyon, France), which is the cancer research arm of the World Health Organization. There, he contributed to development of methods for clinical classification of Variants of Uncertain Significance (VUS) in cancer susceptibility genes and development of guidelines for classification of VUS in cancer susceptibility genes.

In 2009, Dr Tavtigian moved from IARC to the University of Utah Department of Oncological Sciences. Here, continuing work started towards the end of his time at IARC, he has calibrated computational methods for evaluating VUS in cancer susceptibility genes, most notably BRCA1, BRCA2, MLH1, and MSH2, that are applicable to clinical VUS classification. Using these methods, he has also elucidated the role of rare missense substitutions in moderate-risk cancer susceptibility genes such as ATM and CHEK2. He has also extended quantitative Bayesian methods of VUS classification to cover all high-risk susceptibility genes for simple Mendelian diseases.

Research Statement

Sean V. Tavtigian, PhD, is a professor in the Department of Oncological Sciences at the University of Utah and a Huntsman Cancer Institute investigator. He is a co-leader of the Cancer Control and Population Sciences Program and Director of the Huntsman Center for Cancer Genetics. Research in Tavtigian's lab concentrates on two areas of genetic susceptibility to cancer. The first is identification and characterization of intermediate-risk and high-risk cancer susceptibility genes. The second is analysis of unclassified variants that are observed during the clinical testing of established high-risk cancer susceptibility genes.

Historically, most of the known high-risk cancer susceptibility genes were found either by linkage analysis/ positional cloning or by mutation screening of established high-risk susceptibility genes' biochemical pathway "nearest-neighbors". While the linkage analysis/ positional cloning approach is nearly obsolete, next-generation sequencing enables a number of new strategies for gene identification. One of these is whole-exome mutation screening in pedigrees as a method to identify relatively high-risk susceptibility genes. Another is biochemical pathway-based mutation screening in a case-control format as a method to identify intermediate-risk susceptibility genes. We are pursuing breast cancer, colorectal cancer, and head & neck cancer genetics projects in these areas.

Clinical mutation screening of high-risk cancer susceptibility genes such as BRCA1, BRCA2, MLH1, and MSH2 will often find clearly pathogenic mutations, providing very useful information for the clinical management of high-risk patients and their close relatives. However, about 10% of patients who undergo mutation screening are found to carry an unclassified sequence variant (UV) or variant of uncertain significance (VUS). Observations of UVs are problematic for clinical mutation screening services, for clinical cancer genetics, and for the patients. We have developed a bioinformatics method, called the "integrated evaluation", for analysis and eventual classification of UVs. Currently, the method is applicable to UVs in the breast cancer susceptibility genes BRCA1 and BRCA2 as well as the colorectal cancer genes MLH1 and MSH2. We are working to improve the method, to extend it to other susceptibility genes, and to expand databases that disseminate classification results to clinical cancer geneticists throughout the world. We are also investing in development of functional assays for evaluation of UVs in BRCA1, MLH1, MSH2, and eventually other cancer susceptibility genes.

Tavtigian earned a PhD at the California Institute of Technology, Pasadena.

Education History

Postdoctoral Training Myriad Genetics Inc.
 Postdoctoral Training
Doctoral Training California Institute of Technology
 PhD
Undergraduate Pomona College
 BA

Selected Publications

Journal Article

  1. Thompson BA, Bell R, Welm BE, Burn J, Tavtigian SV (). Incorporating calibrated functional assay data into the BRCA1 Ex-UV database. (Epub ahead of print)
  2. Paquette A, Tao K, Stark AW, Rosenthal J, Bell R, Thompson BA, Milas BE, Gertz J, Varley KE, Thomas A, Boucher K, Foulkes WD, Goldgar DE (). Resolving the Functional Significance of BRCA1 RING Domain Missense Substitutions. (Epub ahead of print)
  3. Tavtigian SV, Harrison SM, Boucher KM, Biesecker LG (2020). Fitting a naturally scaled point system to the ACMG/AMP variant classification guidelines. Hum Mutat, 41(10), 1734-1737. (Read full article)
  4. Thompson BA, Walters R, Parsons MT, Dumenil T, Drost M, Tiersma Y, Lindor NM, Tavtigian SV, de Wind N, Spurdle AB, InSiGHT Variant Interpretation Committee (2020). Contribution of mRNA Splicing to Mismatch Repair Gene Sequence Variant Interpretation. Front Genet, 11, 798. (Read full article)
  5. Li C, Liu T, Tavtigian SV, Boucher K, Kohlmann W, Cannon-Albright L, Grossman D (2019). Targeted germline sequencing of patients with three or more primary melanomas reveals high rate of pathogenic variants. Melanoma Res, 30(3), 247-251. (Read full article)
  6. Drost M, Tiersma Y, Glubb D, Kathe S, van Hees S, Callja F, Zonneveld JBM, Boucher KM, Ramlal RPE, Thompson BA, Rasmussen LJ, Greenblatt MS, Lee A, Spurdle AB, Tavtigian SV, de Wind N (2020). Two integrated and highly predictive functional analysis-based procedures for the classification of MSH6 variants in Lynch syndrome. Genet Med, 22(5), 847-856. (Read full article)
  7. Brnich SE, Abou Tayoun AN, Couch FJ, Cutting GR, Greenblatt MS, Heinen CD, Kanavy DM, Luo X, McNulty SM, Starita LM, Tavtigian SV, Wright MW, Harrison SM, Biesecker LG, Berg JS, Clinical Genome Resource Sequence Variant Interpretation Working Group (2019). Recommendations for application of the functional evidence PS3/BS3 criterion using the ACMG/AMP sequence variant interpretation framework. Genome Med, 12(1), 3. (Read full article)
  8. Parsons MT, Tudini E, Li H, Hahnen E, Wappenschmidt B, Feliubadal L, Aalfs CM, Agata S, Aittomki K, Alducci E, Alonso-Cerezo MC, Arnold N, Auber B, Austin R, Azzollini J, Balmaa J, Barbieri E, Bartram CR, Blanco A, Blmcke B, Bonache S, Bonanni B, Borg, Bortesi B, Brunet J, Bruzzone C, Bucksch K, Cagnoli G, Calds T, Caliebe A, Caligo MA, Calvello M, Capone GL, Caputo SM, Carnevali I, Carrasco E, Caux-Moncoutier V, Cavalli P, Cini G, Clarke EM, Concolino P, Cops EJ, Cortesi L, Couch FJ, Darder E, de la Hoya M, Dean M, Debatin I, Del Valle J, Delnatte C, Derive N, Diez O, Ditsch N, Domchek SM, Dutrannoy V, Eccles DM, Ehrencrona H, Enders U, Evans DG, Farra C, Faust U, Felbor U, Feroce I, Fine M, Foulkes WD, Galvao HCR, Gambino G, Gehrig A, Gensini F, Gerdes AM, Germani A, Giesecke J, Gismondi V, Gmez C, Gmez Garcia EB, Gonzlez S, Grau E, Grill S, Gross E, Guerrieri-Gonzaga A, Guillaud-Bataille M, Gutirrez-Enrquez S, Haaf T, Hackmann K, Hansen TVO, Harris M, Hauke J, Heinrich T, Hellebrand H, Herold KN, Honisch E, Horvath J, Houdayer C, Hbbel V, Iglesias S, Izquierdo A, James PA, Janssen LAM, Jeschke U, Kaulfu S, Keupp K, Kiechle M, Klbl A, Krieger S, Kruse TA, Kvist A, Lalloo F, Larsen M, Lattimore VL, Lautrup C, Ledig S, Leinert E, Lewis AL, Lim J, Loeffler M, Lpez-Fernndez A, Lucci-Cordisco E, Maass N, Manoukian S, Marabelli M, Matricardi L, Meindl A, Michelli RD, Moghadasi S, Moles-Fernndez A, Montagna M, Montalban G, Monteiro AN, Montes E, Mori L, Moserle L, Mller CR, Mundhenke C, Naldi N, Nathanson KL, Navarro M, Nevanlinna H, Nichols CB, Niederacher D, Nielsen HR, Ong KR, Pachter N, Palmero EI, Papi L, Pedersen IS, Peissel B, Perez-Segura P, Pfeifer K, Pineda M, Pohl-Rescigno E, Poplawski NK, Porfirio B, Quante AS, Ramser J, Reis RM, Revillion F, Rhiem K, Riboli B, Ritter J, Rivera D, Rofes P, Rump A, Salinas M, Snchez de Abajo AM, Schmidt G, Schoenwiese U, Seggewi J, Solanes A, Steinemann D, Stiller M, Stoppa-Lyonnet D, Sullivan KJ, Susman R, Sutter C, Tavtigian SV, Teo SH, Teul A, Thomassen M, Tibiletti MG, Tischkowitz M, Tognazzo S, Toland AE, Tornero E, Trngren T, Torres-Esquius S, Toss A, Trainer AH, Tucker KM, van Asperen CJ, van Mackelenbergh MT, Varesco L, Vargas-Parra G, Varon R, Vega A, Velasco, Vesper AS, Viel A, Vreeswijk MPG, Wagner SA, Waha A, Walker LC, Walters RJ, Wang-Gohrke S, Weber BHF, Weichert W, Wieland K, Wiesmller L, Witzel I, Wckel A, Woodward ER, Zachariae S, Zampiga V, Zeder-G C, KConFab Investigators, Lzaro C, De Nicolo A, Radice P, Engel C, Schmutzler RK, Goldgar DE, Spurdle AB (2019). Large scale multifactorial likelihood quantitative analysis of BRCA1 and BRCA2 variants: An ENIGMA resource to support clinical variant classification. Hum Mutat, 40(9), 1557-1578. (Read full article)
  9. Voskanian A, Katsonis P, Lichtarge O, Pejaver V, Radivojac P, Mooney SD, Capriotti E, Bromberg Y, Wang Y, Miller M, Martelli PL, Savojardo C, Babbi G, Casadio R, Cao Y, Sun Y, Shen Y, Garg A, Pal D, Yu Y, Huff CD, Tavtigian SV, Young E, Neuhausen SL, Ziv E, Pal LR, Andreoletti G, Brenner SE, Kann MG (2019). Assessing the performance of in silico methods for predicting the pathogenicity of variants in the gene CHEK2, among Hispanic females with breast cancer. Hum Mutat, 40(9), 1612-1622. (Read full article)
  10. Drost M, Tiersma Y, Thompson BA, Frederiksen JH, Keijzers G, Glubb D, Kathe S, Osinga J, Westers H, Pappas L, Boucher KM, Molenkamp S, Zonneveld JB, van Asperen CJ, Goldgar DE, Wallace SS, Sijmons RH, Spurdle AB, Rasmussen LJ, Greenblatt MS, de Wind N, Tavtigian SV (2018). A functional assay-based procedure to classify mismatch repair gene variants in Lynch syndrome. Genet Med, 21(7), 1486-1496. (Read full article)
  11. Fortuno C, Cipponi A, Ballinger ML, Tavtigian SV, Olivier M, Ruparel V, Haupt Y, Haupt S, Study ISK, Tucker K, Spurdle AB, Thomas DM, James PA (2019). A quantitative model to predict pathogenicity of missense variants in the TP53 gene. Hum Mutat, 40(6), 788-800. (Read full article)
  12. Tavtigian SV, Greenblatt MS, Harrison SM, Nussbaum RL, Prabhu SA, Boucher KM, Biesecker LG, ClinGen Sequence Variant Interpretation Working Group ClinGen SVI (2018). Modeling the ACMG/AMP variant classification guidelines as a Bayesian classification framework. Genet Med, 20(9), 1054-1060. (Read full article)
  13. Young EL, Thompson BA, Neklason DW, Firpo MA, Werner T, Bell R, Berger J, Fraser A, Gammon A, Koptiuch C, Kohlmann WK, Neumayer L, Goldgar DE, Mulvihill SJ, Cannon-Albright LA, Tavtigian SV (2018). Pancreatic cancer as a sentinel for hereditary cancer predisposition. BMC Cancer, 18(1), 697. (Read full article)
  14. Valle MP, Di Sera TL, Nix DA, Paquette AM, Parsons MT, Bell R, Hoffman A, Hogervorst FB, Goldgar DE, Spurdle AB, Tavtigian SV (2016). Adding In Silico Assessment of Potential Splice Aberration to the Integrated Evaluation of BRCA Gene Unclassified Variants. Hum Mutat, 37(7), 627-39. (Read full article)
  15. Young EL, Feng BJ, Stark AW, Damiola F, Durand G, Forey N, Francy TC, Gammon A, Kohlmann WK, Kaphingst KA, McKay-Chopin S, Nguyen-Dumont T, Oliver J, Paquette AM, Pertesi M, Robinot N, Rosenthal JS, Vallee M, Voegele C, Hopper JL, Southey MC, Andrulis IL, John EM, Hashibe M, Gertz J, Breast Cancer Family Registry, Le Calvez-Kelm F, Lesueur F, Goldgar DE, Tavtigian SV (2016). Multigene testing of moderate-risk genes: be mindful of the missense. J Med Genet, 53(6), 366-76. (Read full article)
  16. Samadder NJ, Neklason DW, Boucher KM, Byrne KR, Kanth P, Samowitz W, Jones D, Tavtigian SV, Done MW, Berry T, Jasperson K, Pappas L, Smith L, Sample D, Davis R, Topham MK, Lynch P, Strait E, McKinnon W, Burt RW, Kuwada SK (2016). Effect of Sulindac and Erlotinib vs Placebo on Duodenal Neoplasia in Familial Adenomatous Polyposis: A Randomized Clinical Trial. JAMA, 315(12), 1266-75. (Read full article)
  17. Easton DF, Pharoah PD, Antoniou AC, Tischkowitz M, Tavtigian SV, Nathanson KL, Devilee P, Meindl A, Couch FJ, Southey M, Goldgar DE, Evans DG, Chenevix-Trench G, Rahman N, Robson M, Domchek SM, Foulkes WD (2015). Gene-panel sequencing and the prediction of breast-cancer risk. N Engl J Med, 372(23), 2243-57. (Read full article)
  18. Park DJ, Tao K, Le Calvez-Kelm F, Nguyen-Dumont T, Robinot N, Hammet F, Odefrey F, Tsimiklis H, Teo ZL, Thingholm LB, Young EL, Voegele C, Lonie A, Pope BJ, Roane TC, Bell R, Hu H, Shankaracharya, Huff CD, Ellis J, Li J, Makunin IV, John EM, Andrulis IL, Terry MB, Daly M, Buys SS, Snyder C, Lynch HT, Devilee P, Giles GG, Hopper JL, Feng BJ, Lesueur F, Tavtigian SV, Southey MC, Goldgar DE (2014). Rare mutations in RINT1 predispose carriers to breast and Lynch syndrome-spectrum cancers. Cancer Discov, 4(7), 804-15. (Read full article)
  19. Damiola F, Pertesi M, Oliver J, Le Calvez-Kelm F, Voegele C, Young EL, Robinot N, Forey N, Durand G, Vallee MP, Tao K, Roane TC, Williams GJ, Hopper JL, Southey MC, Andrulis IL, John EM, Goldgar DE, Lesueur F, Tavtigian SV (2014). Rare key functional domain missense substitutions in MRE11A, RAD50, and NBN contribute to breast cancer susceptibility: results from a Breast Cancer Family Registry case-control mutation-screening study. Breast Cancer Res, 16(3), R58.
  20. Thompson BA, Greenblatt MS, Vallee MP, Herkert JC, Tessereau C, Young EL, Adzhubey IA, Li B, Bell R, Feng B, Mooney SD, Radivojac P, Sunyaev SR, Frebourg T, Hofstra RM, Sijmons RH, Boucher K, Thomas A, Goldgar DE, Spurdle AB, Tavtigian SV (2013). Calibration of multiple in silico tools for predicting pathogenicity of mismatch repair gene missense substitutions. Hum Mutat, 34(1), 255-65. (Read full article)
  21. Park DJ, Lesueur F, Nguyen-Dumont T, Pertesi M, Odefrey F, Hammet F, Neuhausen SL, John EM, Andrulis IL, Terry MB, Daly M, Buys S, Le Calvez-Kelm F, Lonie A, Pope BJ, Tsimiklis H, Voegele C, Hilbers FM, Hoogerbrugge N, Barroso A, Osorio A, Giles GG, Devilee P, Benitez J, Hopper JL, Tavtigian SV, Goldgar DE, Southey MC (2012). Rare mutations in XRCC2 increase the risk of breast cancer. Am J Hum Genet, 90(4), 734-9. (Read full article)
  22. Vallee MP, Francy TC, Judkins MK, Babikyan D, Lesueur F, Gammon A, Goldgar DE, Couch FJ, Tavtigian SV (2012). Classification of missense substitutions in the BRCA genes: A database dedicated to Ex-UVs. Hum Mutat, 33(1), 22-8. (Read full article)
  23. Le Calvez-Kelm F, Lesueur F, Damiola F, Vallee M, Voegele C, Babikyan D, Durand G, Forey N, McKay-Chopin S, Robinot N, Nguyen-Dumont T, Thomas A, Byrnes GB, Breast Cancer Family Registry T, Hopper JL, Southey MC, Andrulis IL, John EM, Tavtigian SV (2011). Rare, evolutionarily unlikely missense substitutions in CHEK2 contribute to breast cancer susceptibility: results from a breast cancer family registry (CFR) case-control mutation screening study. Breast Cancer Res, 13(1), R6. (Read full article)
  24. Tavtigian SV, Oefner PJ, Babikyan D, Hartmann A, Healey S, Le Calvez-Kelm F, Lesueur F, Byrnes GB, Chuang SC, Forey N, Feuchtinger C, Gioia L, Hall J, Hashibe M, Herte B, McKay-Chopin S, Thomas A, Vallee MP, Voegele C, Webb PM, Whiteman DC, Sangrajrang S, Hopper JL, Southey MC, Andrulis IL, John EM, Chenevix-Trench G (2009). Rare, evolutionarily unlikely missense substitutions in ATM confer increased risk of breast cancer. Am J Hum Genet, 85(4), 427-46. (Read full article)
  25. Plon SE, Eccles DM, Easton D, Foulkes WD, Genuardi M, Greenblatt MS, Hogervorst FB, Hoogerbrugge N, Spurdle AB, Tavtigian SV (2008). Sequence variant classification and reporting: recommendations for improving the interpretation of cancer susceptibility genetic test results. Hum Mutat, 29(11), 1282-91. (Read full article)
  26. Mathe E, Olivier M, Kato S, Ishioka C, Hainaut P, Tavtigian SV (2006). Computational approaches for predicting the biological effect of p53 missense mutations: a comparison of three sequence analysis based methods. Nucleic Acids Res, 34(5), 1317-25.
  27. Tavtigian SV, Samollow PB, de Silva D, Thomas A (2006). An analysis of unclassified missense substitutions in human BRCA1. Fam Cancer, 5(1), 77-88.
  28. Abkevich V, Zharkikh A, Deffenbaugh AM, Frank D, Chen Y, Shattuck D, Skolnick MH, Gutin A, Tavtigian SV (2004). Analysis of missense variation in human BRCA1 in the context of interspecific sequence variation. J Med Genet, 41(7), 492-507. (Read full article)
  29. Steck PA, Pershouse MA, Jasser SA, Yung WK, Lin H, Ligon AH, Langford LA, Baumgard ML, Hattier T, Davis T, Frye C, Hu R, Swedlund B, Teng DH, Tavtigian SV (1997). Identification of a candidate tumour suppressor gene, MMAC1, at chromosome 10q23.3 that is mutated in multiple advanced cancers. Nat Genet, 15(4), 356-62. (Read full article)
  30. Tavtigian SV, Simard J, Rommens J, Couch F, Shattuck-Eidens D, Neuhausen S, Merajver S, Thorlacius S, Offit K, Stoppa-Lyonnet D, Belanger C, Bell R, Berry S, Bogden R, Chen Q, Davis T, Dumont M, Frye C, Hattier T, Jammulapati S, Janecki T, Jiang P, Kehrer R, Leblanc JF, Mitchell JT, McArthur-Morrison J, Nguyen K, Peng Y, Samson C, Schroeder M, Snyder SC, Steele L, Stringfellow M, Stroup C, Swedlund B, Swense J, Teng D, Thomas A, Tran T, Tranchant M, Weaver-Feldhaus J, Wong AK, Shizuya H, Eyfjord JE, Cannon-Albright L, Tranchant M, Labrie F, Skolnick MH, Weber B, Kamb A, Goldgar DE (1996). The complete BRCA2 gene and mutations in chromosome 13q-linked kindreds. Nat Genet, 12(3), 333-7. (Read full article)
  31. Miki Y, Swensen J, Shattuck-Eidens D, Futreal PA, Harshman K, Tavtigian S, Liu Q, Cochran C, Bennett LM, Ding W, et al (1994). A strong candidate for the breast and ovarian cancer susceptibility gene BRCA1. Science, 266(5182), 66-71. (Read full article)

Letter

  1. Thompson BA, Snow AK, Koptiuch C, Kohlmann WK, Mooney R, Johnson S, Huff CD, Yu Y, Teerlink CC, Feng BJ, Neklason DW, Cannon-Albright LA, Tavtigian SV (2019). A novel ribosomal protein S20 variant in a family with unexplained colorectal cancer and polyposis. [Letter to the editor]. Clin Genet, 97(6), 943-944. (Read full article)

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