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Open Access 01-12-2018 | Research article

Pancreatic cancer as a sentinel for hereditary cancer predisposition

Authors: Erin L. Young, Bryony A. Thompson, Deborah W. Neklason, Matthew A. Firpo, Theresa Werner, Russell Bell, Justin Berger, Alison Fraser, Amanda Gammon, Cathryn Koptiuch, Wendy K. Kohlmann, Leigh Neumayer, David E. Goldgar, Sean J. Mulvihill, Lisa A. Cannon-Albright, Sean V. Tavtigian

Published in: BMC Cancer | Issue 1/2018

Abstract

Background

Genes associated with hereditary breast and ovarian cancer (HBOC) and colorectal cancer (CRC) predisposition have been shown to play a role in pancreatic cancer susceptibility. Growing evidence suggests that pancreatic cancer may be useful as a sentinel cancer to identify families that could benefit from HBOC or CRC surveillance, but to date pancreatic cancer is only considered an indication for genetic testing in the context of additional family history.

Methods

Preliminary data generated at the Huntsman Cancer Hospital (HCH) included variants identified on a custom 34-gene panel or 59-gene panel including both known HBOC and CRC genes for respective sets of 66 and 147 pancreatic cancer cases, unselected for family history. Given the strength of preliminary data and corresponding literature, 61 sequential pancreatic cancer cases underwent a custom 14-gene clinical panel. Sequencing data from HCH pancreatic cancer cases, pancreatic cancer cases of the Cancer Genome Atlas (TCGA), and an unselected pancreatic cancer screen from the Mayo Clinic were combined in a meta-analysis to estimate the proportion of carriers with pathogenic and high probability of pathogenic variants of uncertain significance (HiP-VUS).

Results

Approximately 8.6% of unselected pancreatic cancer cases at the HCH carried a variant with potential HBOC or CRC screening recommendations. A meta-analysis of unselected pancreatic cancer cases revealed that approximately 11.5% carry a pathogenic variant or HiP-VUS.

Conclusion

With the inclusion of both HBOC and CRC susceptibility genes in a panel test, unselected pancreatic cancer cases act as a useful sentinel cancer to identify asymptomatic at-risk relatives who could benefit from relevant HBOC and CRC surveillance measures.

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Walsh T, Lee MK, Casadei S, Thornton AM, Stray SM, Pennil C, et al. Detection of inherited mutations for breast and ovarian cancer using genomic capture and massively parallel sequencing. Proc. Natl. Acad. Sci. U. S. A. 2010 ;107:12629–12633. Available from: http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=2906584&tool=pmcentrez&rendertype=abstract. [cited 2010 Dec 8]

Easton DF, Pharoah PDP, Antonious AC, Tischkowitz M, Tavtigian SV, Nathanson KL, et al. Gene-panel sequencing and the prediction of breast-Cancer risk. N Engl J Med. 2015;372:2243–57.CrossRefPubMedPubMedCentral

Hall MJ, Forman AD, Pilarski R, Wiesner G, Giri VN. Gene panel testing for inherited cancer risk. J Natl Compr Cancer Netw. 2014;12:1339–46. Available from: http://www.ncbi.nlm.nih.gov/pubmed/25190699 CrossRef

Salo-Mullen EE, O’Reilly EM, Kelsen DP, Ashraf AM, Lowery MA, Yu KH, et al. Identification of germline genetic mutations in patients with pancreatic cancer. Cancer. 2015;121:4382–8. Available from: http://doi.wiley.com/10.1002/cncr.29664 CrossRefPubMedPubMedCentral

Harinck F, Poley JW, Kluijt I, Fockens P, Bruno MJ, Dutch Research Group of Pancreatic Cancer Surveillance in High-Risk Individuals. Is early diagnosis of pancreatic cancer fiction? Surveillance of individuals at high risk for pancreatic cancer. Dig. Dis. 2010;28:670–8. Available from: http://www.ncbi.nlm.nih.gov/pubmed/21088419 CrossRefPubMed

Chari ST, Kelly K, Hollingsworth MA, Thayer SP, Ahlquist DA, Andersen DK, et al. Early detection of sporadic pancreatic cancer: summative review. Pancreas. 2015;44:693–712. Available from: http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=4467589&tool=pmcentrez&rendertype=abstract CrossRefPubMedPubMedCentral

Daly MB, Pilarski R, Axilbund JE, Berry M, Buys SS, Crawford B, et al. Genetic/familial high-risk assessment: breast and ovarian, version 2.2015. J Natl Compr Cancer Netw. 2016;14:153–62. Available from: http://www.ncbi.nlm.nih.gov/pubmed/26850485 CrossRef

Whitcomb DC, Shelton CA, Brand RE. Genetics and genetic testing in pancreatic cancer. Gastroenterology. 2015;149:1–13. Available from: http://linkinghub.elsevier.com/retrieve/pii/S0016508515010896 CrossRef

Leachman SA, Carucci J, Kohlmann W, Banks KC, Asgari MM, Bergman W, et al. Selection criteria for genetic assessment of patients with familial melanoma. J Am Acad Dermatol. 2009;61:1–14.CrossRef

10.

Kastrinos F, Mukherjee B, Tayob N, Wang F, Sparr J, Raymond VM, et al. Risk of pancreatic cancer in families with lynch syndrome. JAMA. 2009;302:1790–5. Available from: http://www.ncbi.nlm.nih.gov/pubmed/29151953 CrossRefPubMedPubMedCentral

11.

Bujanda L, Herreros-Villanueva M. Pancreatic Cancer in lynch syndrome patients. J Cancer. 2017;8:3667–74. Available from: http://www.ncbi.nlm.nih.gov/pubmed/29151953 CrossRefPubMedPubMedCentral

12.

Mandelker D, Zhang L, Kemel Y, Stadler ZK, Joseph V, Zehir A, et al. Mutation Detection in Patients With Advanced Cancer by Universal Sequencing of Cancer-Related Genes in Tumor and Normal DNA vs Guideline-Based Germline Testing. JAMA. 2017;318:825. Available from: http://jama.jamanetwork.com/article.aspx?doi=10.1001/jama.2017.11137CrossRefPubMedPubMedCentral

13.

Shindo K, Yu J, Suenaga M, Fesharakizadeh S, Cho C, Macgregor-Das A, et al. Deleterious germline mutations in patients with apparently sporadic pancreatic adenocarcinoma. J Clin Oncol. 2017;JCO2017723502 Available from: http://www.ncbi.nlm.nih.gov/pubmed/28767289

14.

Catts ZA-K, Baig MK, Milewski B, Keywan C, Guarino M, Petrelli N. Statewide Retrospective Review of Familial Pancreatic Cancer in Delaware, and Frequency of Genetic Mutations in Pancreatic Cancer Kindreds. Ann. Surg. Oncol. 2016;99. Available from: http://link.springer.com/10.1245/s10434-015-5026-x

15.

Kim DH, Crawford B, Ziegler J, Beattie MS. Prevalence and characteristics of pancreatic cancer in families with BRCA1 and BRCA2 mutations. Fam. Cancer. 2009;8:153–8. Available from: http://www.ncbi.nlm.nih.gov/pubmed/18855126 CrossRefPubMed

16.

Grant RC, Selander I, Connor AA, Selvarajah S, Borgida A, Briollais L, et al. Prevalence of germline mutations in Cancer predisposition genes in patients with pancreatic Cancer. Gastroenterology. 2015;148:556–64. [cited 2015 Jan 22]; Available from: http://www.ncbi.nlm.nih.gov/pubmed/25479140 CrossRefPubMed

17.

Holter S, Borgida A, Dodd A, Grant R, Semotiuk K, Hedley D, et al. Germline BRCA mutations in a large clinic-based cohort of patients with pancreatic adenocarcinoma. J Clin Oncol. 2015;33:3124–9.CrossRefPubMed

18.

Hahn SA, Greenhalf B, Ellis I, Sina-Frey M, Rieder H, Korte B, et al. BRCA2 germline mutations in familial pancreatic carcinoma. J Natl Cancer Inst. 2003;95:214–21. Available from: http://www.ncbi.nlm.nih.gov/pubmed/12569143 CrossRefPubMed

19.

Easton DF, Matthews FE, Ford D, Swerdlow AJ, Peto J. Cancer mortality in relatives of women with ovarian cancer: the OPCS study. Office of Population Censuses and Surveys. Int J Cancer. 1996;65:284–94. Available from: http://www.ncbi.nlm.nih.gov/pubmed/8575846 CrossRefPubMed

20.

Lal G, Liu G, Schmocker B, Kaurah P, Ozcelik H, Narod SA, et al. Inherited predisposition to pancreatic adenocarcinoma: role of family history and germ-line p16, BRCA1, and BRCA2 mutations. Cancer Res. 2000;60:409–16. Available from: http://www.ncbi.nlm.nih.gov/pubmed/10667595 PubMed

21.

Humphris JL, Johns AL, Simpson SH, Cowley MJ, Pajic M, Chang DK, et al. Clinical and pathologic features of familial pancreatic cancer. Cancer. 2014;120:1–7. [cited 2014 Oct 25]; Available from: http://www.ncbi.nlm.nih.gov/pubmed/25313458 CrossRef

22.

Lucas AL, Frado LE, Hwang C, Kumar S, Khanna LG, Levinson EJ, et al. BRCA1 and BRCA2 germline mutations are frequently demonstrated in both high-risk pancreatic cancer screening and pancreatic cancer cohorts. Cancer. 2014;120:1–8. [cited 2014 May 7]; Available from: http://www.ncbi.nlm.nih.gov/pubmed/24737347 CrossRef

23.

Skolnick M. The Utah genealogical database: a resource for genetic epidemiology. Banbury Rep. 1980;4:285–97.

24.

Tomczak K, Czerwińska P, Wiznerowicz M. The Cancer genome atlas (TCGA): an immeasurable source of knowledge. Wspolczesna Onkol. 2015;1A:A68–77.CrossRef

25.

DePristo MA, Banks E, Poplin R, Garimella KV, Maguire JR, Hartl C, et al. A framework for variation discovery and genotyping using next-generation DNA sequencing data. Nat. Genet. 2011;43:491–8. Available from: http://dx.doi.org/10.1038/ng.806CrossRefPubMedPubMedCentral

26.

Wildeman M, van Ophuizen E, den Dunnen JT, Taschner PEM. Improving sequence variant descriptions in mutation databases and literature using the Mutalyzer sequence variation nomenclature checker. Hum Mutat. 2008;29:6–13. Available from: http://www.ncbi.nlm.nih.gov/pubmed/16835861 CrossRefPubMed

27.

Wang K, Li M, Hakonarson H. ANNOVAR: functional annotation of genetic variants from high-throughput sequencing data. Nucleic Acids Res. 2010;38:e164. Available from: http://www.ncbi.nlm.nih.gov/pubmed/20601685 CrossRefPubMedPubMedCentral

28.

Lek M, Karczewski KJ, Minikel EV, Samocha KE, Banks E, Fennell T, et al. Analysis of protein-coding genetic variation in 60,706 humans. Nature. 2016;536:285–91. Available from: http://www.nature.com/doifinder/10.1038/nature19057 CrossRefPubMedPubMedCentral

29.

Yeo G, Burge CB. Maximum entropy modeling of short sequence motifs with applications to RNA splicing signals. J Comput Biol. 2004;11:377–94. [cited 2013 Feb 13]; Available from: http://www.ncbi.nlm.nih.gov/pubmed/15285897 CrossRefPubMed

30.

Tavtigian SV, Deffenbaugh a M, Yin L, Judkins T, Scholl T, Samollow PB, et al. Comprehensive statistical study of 452 BRCA1 missense substitutions with classification of eight recurrent substitutions as neutral. J Med Genet. 2006;43:295–305. [cited 2013 Nov 7]; Available from: http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=2563222&tool=pmcentrez&rendertype=abstract CrossRefPubMed

31.

Adzhubei I, Jordan DM, Sunyaev SR. Predicting Functional Effect of Human Missense Mutations Using PolyPhen-2. Curr. Protoc. Hum. Genet. 2013;Chapter 7:–Unit7.20. [cited 2013 Feb 5]; Available from: http://www.ncbi.nlm.nih.gov/pubmed/23315928

32.

Kircher M, Witten DM, Jain P, O’Roak BJ, Cooper GM, Shendure J. A general framework for estimating the relative pathogenicity of human genetic variants. Nat. Genet. 2014;46:310–5. [cited 2014 Mar 3]; Available from: http://www.nature.com/doifinder/10.1038/ng.2892 CrossRefPubMedPubMedCentral

33.

Young EL, Feng BJ, Stark AW, Damiola F, Durand G, Forey N, et al. Multigene testing of moderate-risk genes: be mindful of the missense. J Med Genet. 2016;53:366–76. Available from: http://jmg.bmj.com/lookup/doi/10.1136/jmedgenet-2015-103398%5Cn http://www.ncbi.nlm.nih.gov/pubmed/26787654CrossRefPubMedPubMedCentral

34.

E a S, Sidow A. Physicochemical constraint violation by missense substitutions mediates impairment of protein function and disease severity. Genome Res. 2005;15:978–86. [cited 2013 Feb 5] Available from: http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=1172042&tool=pmcentrez&rendertype=abstract CrossRef

35.

Tavtigian SV, Byrnes GB, Goldgar DE, Thomas A. Classification of rare missense substitutions, using risk surfaces, with genetic- and molecular-epidemiology applications. Hum Mutat. 2008;29:1342–54. Available from: http://www.ncbi.nlm.nih.gov/pubmed/18951461 CrossRefPubMedPubMedCentral

36.

Vallée MP, Di STL, Nix DA, Paquette AM, Parsons MT, Bell R, et al. Adding In Silico Assessment of Potential Splice Aberration to the Integrated Evaluation of BRCA Gene Unclassified Variants. Hum. Mutat. 2016; Available from: http://www.ncbi.nlm.nih.gov/pubmed/26913838

37.

Hu C, Hart SN, Bamlet WR, Moore RM, Nandakumar K, Eckloff BW, et al. Prevalence of Pathogenic Mutations in Cancer Predisposition Genes among Pancreatic Cancer Patients. Cancer Epidemiol Biomark Prev. 2016;25:207–11. Available from: http://cebp.aacrjournals.org/cgi/doi/10.1158/1055-9965.EPI-15-0455 CrossRef

38.

Freeman MF, Tukey JW. Transformations related to the angular and the square root. Ann Math Stat. 1950;21:607–11.CrossRef

39.

Lek M, Karczewski K, Minikel E, Samocha K, Banks E, Fennell T, et al. Analysis of protein-coding genetic variation in 60,706 humans. bioRxiv. 2015:1–26. Available from: http://biorxiv.org/content/early/2015/10/30/030338.abstract

40.

Rosner B. Fundamentals of biostatistics. 2nd ed. Boston: Duxbury Press; 1986.

41.

Wickham H. ggplot2: elegant graphics for data analysis. Springer-Verlag New York; 2009.CrossRef

42.

Roeb W, Higgins J, King M. Response to DNA Damage of CHEK2 Missense Mutations in Familial Breast Cancer. Hum. Mol. Genet. 2012;21:2738–44. [cited 2012 Apr 9] Available from: http://www.ncbi.nlm.nih.gov/pubmed/22419737 CrossRefPubMedPubMedCentral

43.

Daly MB, Pilarski R, Berry M, Buys SS, Farmer M, Friedman S, et al. NCCN guidelines insights: genetic/familial high-risk assessment: breast and ovarian, version 2.2017. J Natl Compr Cancer Netw. 2017;15:9–20. Available from: http://www.jnccn.org/content/15/1/9.long CrossRef

44.

Couch FJ, Shimelis H, Hu C, Hart SN, Polley EC, Na J, et al. Associations Between Cancer Predisposition Testing Panel Genes and Breast Cancer. JAMA Oncologia. 2017;3:1190–6. Available from: http://oncology.jamanetwork.com/article.aspx?doi=10.1001/jamaoncol.2017.0424 CrossRef

45.

Provenzale D, Jasperson K, Ahnen DJ, Aslanian H, Bray T, Cannon JA, et al. Colorectal Cancer screening, version 1.2015. J Natl Compr Cancer Netw. 2015;13:959–68. quiz 968. Available from: http://www.jnccn.org/content/13/8/959.full.pdf CrossRef

46.

Villani A, Tabori U, Schiffman J, Shlien A, Beyene J, Druker H, et al. Biochemical and imaging surveillance in germline TP53 mutation carriers with Li-Fraumeni syndrome: a prospective observational study. Lancet. Oncol. 2011;12:559–67. Available from: http://www.ncbi.nlm.nih.gov/pubmed/21601526 CrossRefPubMed

47.

van der Post RS, Vogelaar IP, Carneiro F, Guilford P, Huntsman D, Hoogerbrugge N, et al. Hereditary diffuse gastric cancer: updated clinical guidelines with an emphasis on germline CDH1 mutation carriers. J Med Genet. 2015;52:361–74. Available from: http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=4453626&tool=pmcentrez&rendertype=abstract CrossRefPubMedPubMedCentral

48.

Evaluation of Genomic Applications in Practice and Prevention (EGAPP) Working Group. Recommendations from the EGAPP Working Group: genetic testing strategies in newly diagnosed individuals with colorectal cancer aimed at reducing morbidity and mortality from Lynch syndrome in relatives. Genet. Med. 2009;11:35–41. Available from: http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=2743612&tool=pmcentrez&rendertype=abstract CrossRef

49.

Hartman DJ, Brand RE, Hu H, Bahary N, Dudley B, Chiosea SI, et al. Lynch syndrome-associated colorectal carcinoma: Frequent involvement of the left colon and rectum and late-onset presentation supports a universal screening approach. Hum. Pathol. 2013;44:2518–28. Available from: http://dx.doi.org/10.1016/j.humpath.2013.06.012CrossRefPubMed

50.

Heald B, Plesec T, Liu X, Pai R, Patil D, Moline J, et al. Implementation of universal microsatellite instability and immunohistochemistry screening for diagnosing lynch syndrome in a large academic medical center. J Clin Oncol. 2013;31:1336–40.CrossRefPubMedPubMedCentral

51.

Kidambi TD, Blanco A, Myers M, Conrad P, Loranger K, Terdiman JP. Selective versus universal screening for lynch syndrome: a six-year clinical experience. Dig. Dis. Sci. 2014;60:2463–9. Available from: http://dx.doi.org/10.1007/s10620-014-3234-zCrossRefPubMed

52.

Musulén E, Sanz C, Muñoz-Mármol AM, Ariza A. Mismatch repair protein immunohistochemistry: A useful population screening strategy for Lynch syndrome. Hum. Pathol. 2014;45:1388–96. Available from: http://dx.doi.org/10.1016/j.humpath.2014.02.012CrossRefPubMed

53.

Hampel H, Frankel WL, Martin E, Arnold M, Khanduja K, Kuebler P, et al. Feasibility of screening for lynch syndrome among patients with colorectal cancer. J Clin Oncol. 2008;26:5783–8. Available from: http://www.ncbi.nlm.nih.gov/pubmed/20045164 CrossRefPubMedPubMedCentral

54.

Chang SC, Lin PC, Yang SH, Wang HS, Liang WY, Lin JK. Taiwan hospital-based detection of lynch syndrome distinguishes 2 types of microsatellite instabilities in colorectal cancers. Surgery. 2010;147:720–8. Available from: http://dx.doi.org/10.1016/j.surg.2009.10.069CrossRefPubMed

55.

Hampel H, Frankel WL, Martin E, Arnold M, Khanduja K, Kuebler P, et al. Screening for the lynch syndrome (hereditary nonpolyposis colorectal cancer). N. Engl. J Med. 2005;352:1851–60. Available from: http://www.ncbi.nlm.nih.gov/pubmed/19038878 CrossRefPubMed

56.

Erten MZ, Fernandez LP, Ng HK, McKinnon WC, Heald B, Koliba CJ, et al. Universal versus targeted screening for lynch syndrome: comparing ascertainment and costs based on clinical experience. Dig Dis Sci. 2016; Available from: http://www.ncbi.nlm.nih.gov/pubmed/27384051

57.

Gould-Suarez M, El-Serag HB, Musher B, Franco LM, Chen GJ. Cost-effectiveness and diagnostic effectiveness analyses of multiple algorithms for the diagnosis of lynch syndrome. Dig Dis Sci. 2014;59:2913–26.CrossRefPubMed

58.

Pritchard CC, Mateo J, Walsh MF, De Sarkar N, Abida W, Beltran H, et al. Inherited DNA-Repair Gene Mutations in Men with Metastatic Prostate Cancer. N Engl J Med. 2016:NEJMoa1603144. Available from: http://www.nejm.org/doi/10.1056/NEJMoa1603144

59.

https://clinicaltrials.gov/. Available from: https://clinicaltrials.gov/. Accessed 1 June 2018.

60.

Czink E, Kloor M, Goeppert B, Fröhling S, Uhrig S, Weber TF, et al. Successful immune checkpoint blockade in a patient with advanced stage microsatellite-unstable biliary tract cancer. Mol. Case Stud. 2017;3:a001974. Available from: http://molecularcasestudies.cshlp.org/lookup/doi/10.1101/mcs.a001974 CrossRef

Title: Pancreatic cancer as a sentinel for hereditary cancer predisposition
Authors: Erin L. Young
Bryony A. Thompson
Deborah W. Neklason
Matthew A. Firpo
Theresa Werner
Russell Bell
Justin Berger
Alison Fraser
Amanda Gammon
Cathryn Koptiuch
Wendy K. Kohlmann
Leigh Neumayer
David E. Goldgar
Sean J. Mulvihill
Lisa A. Cannon-Albright
Sean V. Tavtigian
Publication date: 01-12-2018
Publisher: BioMed Central
Published in: BMC Cancer / Issue 1/2018
Electronic ISSN: 1471-2407
DOI: https://doi.org/10.1186/s12885-018-4573-5

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