Classification of germline variants identified in cancer predisposition genetic testing – consensus of the CZECANCA consortium

Česká verze

Authors: M. Janatová ¹; Š. Chvojka ²; E. Macháčková ³; J. Soukupová ¹; P. Zemánková ^1,4; P. Nehasil ^1,4,5; T. Zavoral ⁶; L. Hrušková ⁷; K. M. Kozáková Janíková ^{8 9}; F. Lhota ²; S. Tavandzis ¹⁰; P. Kleiblová ^1,11; Z. Kleibl ¹; Czecanca Konzorcium
Authors place of work: Ústav lékařské bio chemie a laboratorní dia gnostiky, 1. LF UK a VFN v Praze ¹; Centrum lékařské genetiky a reprodukční medicíny, Gennet, Praha ²; Oddělení epidemiologie a genetiky nádorů, MOÚ Brno ³; Ústav patologické fyziologie, 1. LF UK a VFN v Praze ⁴; Klinika pediatrie a dědičných poruch metabolizmu 1. LF UK a VFN v Praze ⁵; Ústav lékařské genetiky, LF v Plzni UK a FN Plzeň ⁶; GHC Genetics, s. r. o., Praha ⁷; Ústav lékařské genetiky, LF UP a FN Olomouc ⁸; Genetická laboratoř PRONATAL, PRONATAL s. r. o., Praha ⁹; Oddělení lékařské genetiky, Laboratoře AGEL a. s., Nový Jičín ¹⁰; Ústav bio logie a lékařské genetiky, 1. LF UK a VFN v Praze ¹¹
Published in the journal: Klin Onkol 2023; 37(6): 431-439
Category: Přehled
doi: https://doi.org/10.48095/ccko2023431

Summary

Background: Hereditary cancer syndromes are an important subset of malignant cancers caused by pathogenic variants in one of many known cancer predisposition genes. Diagnosis of cancer predisposition is based on genetic testing using next-generation sequencing. This allows many genes to be analysed at once, increasing the number of variants identified. The correct classification of the variants found is essential for the clinical interpretation of genetic test results.

Purpose: The aim of this study is to summarise the rules for classifying identified variants within individual laboratories and to present the process for creating a common classification. In the Czech Republic, the sharing of identified genetic variants and the development of their consensus classification among national laboratory diagnostic communities is carried out within the Czech Cancer Panel for Clinical Application (CZECANCA) consortium of scientific and diagnostic oncogenetic laboratories. Consensus for variant classification follows a defined protocol. Sharing the results and consensus classification accelerates and refines the release of genetic test results, harmonises results between laboratories and thus contributes to improving the care of individuals at high risk of cancer and their relatives.

Keywords:

genetic testing – massively-parallel sequencing – hereditary neoplastic syndromes – clinical relevance – variant classification – national consensus

Zdroje

1. Kulkarni A, Carley H. Advances in the recognition and management of hereditary cancer. Br Med Bull 2016; 120 (1): 123–138. doi: 10.1093/bmb/ldw046.

2. Lhotova K, Stolarova L, Zemankova P et al. Multigene panel germline testing of 1333 Czech patients with ovarian cancer. Cancers (Basel) 2020; 12 (4): 956. doi: 10.3390/cancers12040956.

3. Turnbull C, Sud A, Houlston RS. Cancer genetics, precision prevention and a call to action. Nat Genet 2018; 50 (9): 1212–1218. doi: 10.1038/s41588-018-0202-0.

4. Bewicke-Copley F, Kumar EA, Palladino G et al. Applications and analysis of targeted genomic sequencing in cancer studies. Comput Struct Biotechnol J 2019; 17: 1348–1359. doi: 10.1016/j.csbj.2019.10.004.

5. Walsh T, Lee MK, Casadei S 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 (28): 12629–12633. doi: 10.1073/pnas.1007983107.

6. 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 (11): 1282–1291. doi: 10.1002/humu.20880.

7. Fokkema IFAC, van der Velde K, Slofstra MK et al. Dutch genome diagnostic laboratories accelerated and improved variant interpretation and increased accuracy by sharing data. Hum Mutat 2019; 40 (12): 2230–2238. doi: 10.1002/humu.23896.

8. Garrett A, Callaway A, Durkie M et al. Cancer Variant Interpretation Group UK (CanVIG-UK): an exemplar national subspecialty multidisciplinary network. J Med Genet 2020; 57 (12): 829–834. doi: 10.1136/jmedgenet-2019-106 759.

9. Wappenschmidt B, Hauke J, Faust U et al. Criteria of the German consortium for hereditary breast and ovarian cancer for the classification of germline sequence variants in risk genes for hereditary breast and ovarian cancer. Geburtshilfe Frauenheilkd 2020; 80 (4): 410–429. doi: 10.1055/a-1110-0909.

10. Tudini E, Andrews J, Lawrence DM et al. Shariant platform: enabling evidence sharing across Australian clinical genetic-testing laboratories to support variant interpretation. Am J Hum Genet 2022; 109 (11): 1960–1973. doi: 10.1016/j.ajhg.2022.10.006.

11. Acmg Board Of Directors. Laboratory and clinical genomic data sharing is crucial to improving genetic health care: a position statement of the American College of Medical Genetics and Genomics. Genet Med 2017; 19 (7): 721–722. doi: 10.1038/gim.2016.196.

12. Soukupová J, Zemánková P, Kleiblová P et al. CZECANCA: CZEch CAncer paNel for Clinical Application – design and optimization of the targeted sequencing panel for the identification of cancer susceptibility in high-risk individuals from the Czech Republic. Klin Onkol 2016; 29 (Suppl 1): S46–54. doi: 10.14735/amko2016s46.

13. Soukupova J, Zemankova P, Lhotova K et al. Validation of CZECANCA (CZEch CAncer paNel for Clinical Application) for targeted NGS-based analysis of hereditary cancer syndromes. PLoS One 2018; 13 (4): e0195761. doi: 10.1371/journal.pone.0195761.

14. Hovhannisyan M, Kleiblova P, Nehasil P et al. Polygenic risk score (PRS) and its potential for breast cancer risk stratification. Klin Onkol 2023; 36 (3): 198–205. doi: 10.48095/ccko2023198.

15. Stolarova L, Kleiblova P, Janatova M et al. CHEK2 germline variants in cancer predisposition: stalemate rather than checkmate. Cells 2020; 9 (12): 2675. doi: 10.3390/cells9122675.

16. Stolarova L, Kleiblova P, Zemankova P et al. ENIGMA CHEK2gether project: a comprehensive study identifies functionally impaired CHEK2 germline missense variants associated with increased breast cancer risk. Clin Cancer Res 2023; 29 (16): 3037–3050. doi: 10.1158/1078-0432.CCR-23-0212.

17. Kleiblova P, Stolarova L, Krizova K et al. Identification of deleterious germline CHEK2 mutations and their association with breast and ovarian cancer. Int J Cancer 2019; 145 (7): 1782–1797. doi: 10.1002/ijc.32385.

18. 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. Genet Med 2015; 17 (5): 405–424. doi: 10.1038/gim.2015.30.

19. Spurdle AB, Greville-Heygate S, Antoniou AC et al. Towards controlled terminology for reporting germline cancer susceptibility variants: an ENIGMA report. J Med Genet 2019; 56 (6): 347–357. doi: 10.1136/jmedgenet- 2018-105872.

20. Wörmann B, Bokemayer C, Burmeister T et al. Dihydropyrimidine dehydrogenase testing prior to treatment with 5-fluorouracil, capecitabine, and tegafur: a consensus paper. Oncol Res Treat 2020; 43 (11): 628–636. doi: 10.1159/000510258.

21. Fortuno C, Lee K, Olivier M et al. Specifications of the ACMG/AMP variant interpretation guidelines for germline TP53 variants. Hum Mutat 2021; 42 (3): 223–236. doi: 10.1002/humu.24152.

22. Feliubadalo L, Moles-fernandez A, Santamarina-Pena M et al. A collaborative effort to define classification criteria for ATM variants in hereditary cancer patients. Clin Chem 2021; 67 (3): 518–533. doi: 10.1093/clinchem/hvaa250.

23. Moghadasi S, Meeks HD, Vreeswijk MP et al. The BRCA1 c. 5096G>A p.Arg1699Gln (R1699Q) intermediate risk variant: breast and ovarian cancer risk estimation and recommendations for clinical management from the ENIGMA consortium. J Med Genet 2018; 55 (1): 15–20. doi: 10.1136/jmedgenet-2017-104560.

24. King MC. “The race” to clone BRCA1. Science 2014; 343 (6178): 1462–1465. doi: 10.1126/science.1251900.

25. Curia MC, Catalano T, Aceto GM. MUTYH: not just polyposis. World J Clin Oncol 2020; 11 (7): 428–449. doi: 10.5306/wjco.v11.i7.428.

26. Federici G, Soddu S. Variants of uncertain significance in the era of high-throughput genome sequencing: a lesson from breast and ovary cancers. J Exp Clin Cancer Res 2020; 39 (1): 46. doi: 10.1186/s13046-020-01554-6.

27. 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. J Med Genet 2020; 57 (8): 509–518. doi: 10.1136/jmedgenet-2019-106368.