Contribution of Massive Parallel Sequencing to Diagnosis of Hereditary Ovarian Cancer in the Czech Republic

Background: Ovarian cancer is a disease with high mortality. Approximately 1,000 women are diagnosed with ovarian cancer in the Czech Republic annually. Women harboring a mutation in cancer-predisposing genes face an increased risk of tumor development. Mutations in BRCA1, BRCA2, BRIP1, and Lynch syndrome genes (RAD51C, RAD51D, and STK11) are associated with a high risk of ovarian cancer, and mutations in ATM, CHEK2, NBN, PALB2, and BARD1 appear to increase the risk. Our aim was to examine the frequency of mutations in cancer-predisposing genes in the Czech Republic.

Materials and methods: We analyzed 1,057 individuals including ovarian cancer patients and 617 non-cancer controls using CZECANCA panel next-generation sequencing on the Illumina platform. Pathogenic mutations in high-risk genes, including CNVs, were detected in 30.6% of patients. The mutation frequency reached 25.0% and 18.2% in subgroups of unselected ovarian cancer patients and patients with a negative family cancer history, respectively. The most frequently mutated genes were BRCA1 and BRCA2. The overall frequency of mutations in non-BRCA genes was comparable to that in BRCA2. The mutation frequency in ovarian cancer patients aged >70 years was three times higher than that in patients diagnosed before the age of 30.

Conclusion: Ovarian cancer is a heterogeneous disease with a high proportion of hereditary cases. The lack of efficient screening for early diagnosis emphasizes the importance of identifying carriers of mutations in ovarian cancer-predisposing genes; this is because proper follow-up and prevention strategies can reduce overall ovarian cancer-related mortality. This work was supported by grants AZV 15-27695A, SVV2019/260367, PROGRES Q28/LF1. The authors declare they have no potential conflicts of interest concerning drugs, products, or services used in the study. The Editorial Board declares that the manuscript met the ICMJE recommendation for biomedical papers. Submitted: 7. 3. 2019 Accepted: 24. 4. 2019.