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Optimization of prediction methods for risk assessment of pathogenic germline variants in the Japanese population

Senda, Noriko 京都大学 DOI:10.14989/doctor.k24089

2022.05.23

概要

Predicting pathogenic germline variants (PGVs) in breast cancer patients is important for selecting optimal therapeutics and implementing risk reduction strategies. However, PGV risk factors and the performance of prediction methods in the Japanese population remain unclear. We investigated clinicopathological risk factors using the Tyrer-Cuzick (TC) breast cancer risk evaluation tool to predict BRCA PGVs in unselected Japanese breast cancer patients (n = 1,995). Eleven breast cancer susceptibility genes were analyzed using target-capture sequencing in a previous study; the PGV prevalence in BRCA1, BRCA2, and PALB2 was 0.75%, 3.1%, and 0.45%, respectively. Significant associations were found between the presence of BRCA PGVs and early disease onset, number of familial cancer cases (up to third-degree relatives), triple-negative breast cancer patients under the age of 60, and ovarian cancer history (all P < .0001). In total, 816 patients (40.9%) satisfied the National Comprehensive Cancer Network (NCCN) guidelines for recommending multigene testing. The sensitivity and specificity of the NCCN criteria for discriminating PGV carriers from noncarriers were 71.3% and 60.7%, respectively. The TC model showed good discrimination for predicting BRCA PGVs (area under the curve, 0.75; 95% confidence interval, 0.69-0.81). Furthermore, use of the TC model with an optimized cutoff of TC score ≥0.16% in addition to the NCCN guidelines improved the predictive efficiency for high-risk groups (sensitivity, 77.2%; specificity, 54.8%; about 11 genes). Given the influence of ethnic differences on prediction, we consider that further studies are warranted to elucidate the role of environmental and genetic factors for realizing precise prediction.

KEYWORDS
BRCA, breast cancer, risk factor, pathogenic germline variant, Tyrer-Cuzick mode

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参考文献

1. Hori M, Matsuda T, Shibata A, Katanoda K, Sobue T, Nishimoto H. Cancer incidence and incidence rates in Japan in 2009: a study of 32 population-based cancer registries for the Monitoring of Cancer Incidence in Japan (MCIJ) project. Jpn J Clin Oncol. 2015;45(9):884-891.

2. Foulkes WD. Inherited susceptibility to common cancers. N Engl J Med. 2008;359:2143-2153.

3. Whittemore AS. Risk of breast cancer in carriers of BRCA gene mu- tations. N Engl J Med. 1997;337:788-789.

4. Easton DF, Pharoah PD, Antoniou AC, et al. Gene-panel se- quencing and the prediction of breast-cancer risk. N Engl J Med. 2015;372:2243-2257.

5. Miki Y, Swensen J, Shattuck-Eidens D, et al. A strong candidate for the breast and ovarian cancer susceptibility gene BRCA1. Science. 1994;266:66-71.

6. Momozawa Y, Iwasaki Y, Parsons MT, et al. Germline pathogenic variants of 11 breast cancer genes in 7,051 Japanese patients and 11,241 controls. Nat Commun. 2018;9:4083.

7. Sun J, Meng H, Yao L, et al. Germline Mutations in cancer suscep- tibility genes in a large series of unselected breast cancer patients. Clin Cancer Res. 2017;23:6113-6119.

8. Nakamura S, Takahashi M, Tozaki M, et al. Prevalence and differ- entiation of hereditary breast and ovarian cancers in Japan. Breast Cancer. 2015;22:462-468.

9. Finch AP, Lubinski J, Møller P, et al. Impact of oophorectomy on cancer incidence and mortality in women with a BRCA1 or BRCA2 mutation. J Clin Oncol. 2014;32:1547-1553.

10. Li X, You R, Wang X, et al. Effectiveness of prophylactic surgeries in BRCA1 or BRCA2 mutation carriers: A meta-analysis and systematic review. Clin Cancer Res. 2016;22:3971-3981.

11. Tung NM, Boughey JC, Pierce LJ, et al. Management of hereditary breast cancer: American Society of Clinical Oncology, American Society for Radiation Oncology, and Society of Surgical Oncology Guideline. J Clin Oncol. 2020;38:2080-2106.

12. Valencia OM, Samuel SE, Viscusi RK, Riall TS, Neumayer LA, Aziz H. The role of genetic testing in patients with breast cancer: a review. JAMA Surg. 2017;152:589-594.

13. Owens DK, Davidson KW, Krist AH, et al. Risk assessment, ge- netic counseling, and genetic testing for BRCA-related cancer: US Preventive services task force recommendation statement. JAMA. 2019;322:652-665.

14. Armstrong N, Ryder S, Forbes C, Ross J, Quek RG. A systematic review of the international prevalence of BRCA mutation in breast cancer. Clin Epidemiol. 2019;11:543-561.

15. Lichtenstein P, Holm NV, Verkasalo PK, et al. Environmental and heritable factors in the causation of cancer–analyses of cohorts of twins from Sweden, Denmark, and Finland. N Engl J Med. 2000;343:78-85.

16. Dorling L, Carvalho S, Allen J, et al. Breast cancer risk genes - as- sociation analysis in more than 113,000 women. N Engl J Med. 2021;384(5):428–439.

17. Hu C, Hart SN, Gnanaolivu R, et al. A population-based study of genes previously implicated in breast cancer. N Engl J Med. 2021;384(5):440-451.

18. Apostolou P, Fostira F. Hereditary breast cancer: the era of new susceptibility genes. Biomed Res Int. 2013;2013:1-11.

19. Meindl A, Ditsch N, Kast K, Rhiem K, Schmutzler RK. Hereditary breast and ovarian cancer: new genes, new treatments, new con- cepts. Dtsch Arztebl Int. 2011;108(19):323-330.

20. Tyrer J, Duffy SW, Cuzick J. A breast cancer prediction model incorporating familial and personal risk factors. Stat Med. 2004;23:1111-1130.

21. Inagaki-Kawata Y, Yoshida K, Kawaguchi-Sakita N, et al. Genetic and clinical landscape of breast cancers with germline BRCA1/2 variants. Commun Biol. 2020;3(1):578.

22. Daly MB, Pilarski R, Yurgelun MB, et al. NCCN guidelines insights: Genetic/familial high-risk assessment: breast, ovarian, and pancre- atic, version 1.2020. J Natl Compr Canc Netw. 2020;18:380-391.

23. Lee A, Mavaddat N, Wilcox AN, et al. BOADICEA: a comprehensive breast cancer risk prediction model incorporating genetic and non- genetic risk factors. Genet Med. 2019;21(8):1708-1718.

24. Mazzola E, Blackford A, Parmigiani G, Biswas S. Recent enhance- ments to the genetic risk prediction model BRCAPRO. Cancer Inform. 2015;14(Suppl 2):147-157.

25. Lindor NM, Johnson KJ, Harvey H, et al. Predicting BRCA1 and BRCA2 gene mutation carriers: comparison of PENN II model to previous study. Fam Cancer. 2010;9(4):495-502.

26. Yadav S, Hu C, Hart SN, et al. Evaluation of germline genetic testing criteria in a hospital-based series of women with breast cancer. J Clin Oncol. 2020;38:1409-1418.

27. Shimoi T, Nagai SE, Yoshinami T, et al. The Japanese Breast Cancer Society Clinical Practice Guidelines for systemic treatment of breast cancer. Breast Cancer. 2020;27(3):322-331.

28. Japanese Organization of Hereditary Breast and Ovarian (JOHBOC). Guidebook for diagnosis and treatment of hereditary breast and ovarian cancer syndrome. 2017. http://johboc.jp/guide book2017/

29. Beck AC, Yuan H, Liao J, et al. Rate of BRCA mutation in pa- tients tested under NCCN genetic testing criteria. Am J Surg. 2020;219:145-149.

30. WHO. Cancer Key Facts. Geneva: WHO; 2018. https://www.who. int/news-room/fact-sheets/detail/cancer

31. Tung N, Battelli C, Allen B, et al. Frequency of mutations in indi- viduals with breast cancer referred for BRCA1 and BRCA2 testing using next-generation sequencing with a 25-gene panel. Cancer. 2015;121:25-33.

32. Tung N, Lin NU, Kidd J, et al. Frequency of germline mutations in 25 cancer susceptibility genes in a sequential series of patients with breast cancer. J Clin Oncol. 2016;34:1460-1468.

33. Lang GT, Shi JX, Hu X, et al. The spectrum of BRCA mutations and characteristics of BRCA-associated breast cancers in China: Screening of 2,991 patients and 1,043 controls by next-generation sequencing. Int J Cancer. 2017;141:129-142.

34. Bhaskaran SP, Chandratre K, Gupta H, et al. Germline variation in BRCA1/2 is highly ethnic-specific: Evidence from over 30,000 Chinese hereditary breast and ovarian cancer patients. Int J Cancer. 2019;145(4):962-973.

35. Rebbeck TR, Mitra N, Wan F, et al. Association of type and location of BRCA1 and BRCA2 mutations with risk of breast and ovarian can- cer. JAMA. 2015;313:1347-1361.

36. Li Q, Seo JH, Stranger B, et al. Integrative eQTL-based anal- yses reveal the biology of breast cancer risk loci. Cell. 2013;152(3):633-634.

37. Renehan AG, Tyson M, Egger M, Heller RF, Zwahlen M. Body- mass index and incidence of cancer: a systematic review an meta-analysis of prospective observational studies. Lancet. 2008;371:569-578.

38. Arora N, King TA, Jacks LM, et al. Impact of breast density on the presenting features of malignancy. Ann Surg Oncol. 2010;17(Suppl 3):211-218.

39. Burton A, Maskarinec G, Perez-Gomez B, et al. Mammographic den- sity and ageing: A collaborative pooled analysis of cross-sectional data from 22 countries worldwide. PLOS Med. 2017;14(6):e1002335.

40. Boyd NF, Martin LJ, Yaffe MJ, Minkin S. Mammographic density and breast cancer risk: current understanding and future prospects. Breast Cancer Res. 2011;13:223.

41. Kaneyasu T, Mori S, Yamauchi H, et al. Prevalence of disease- causing genes in Japanese patients with BRCA1/2-wildtype he- reditary breast and ovarian cancer syndrome. NPJ Breast Cancer. 2020;6:25.

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