Rationale: Ovarian cancer is the leading death cause in gynecological malignancies. More than 70% of the patients are diagnosed with progressing disease extending to outside the true pelvis. The 5-year survival of ovarian cancer patients remains low (about 47%) due to frequent relapses and drug resistance. Identification of markers for early diagnosis and relapse prediction could improve the outcomes of the disease.Aim: To assess relative copy number of cancer-associated genetic loci c-Myc, CDK12, CDKN1B, PRPF19, ERBB2, DDB1, GAB2, COL6A3 in the tumor cells of ovarian cancer, in order to identify potential prognostic oncomarkers in ovarian cancer patients.Materials and methods: The study included 50 women aged 27 to 70 years with ovarian cancer T1-3cN0-1M0-1, Gr. 2 (stages I—IV), who received their elective treatment in the National Medical Research Centre for Oncology in 2015 to 2019. The study was based on samples of genomic DNA from paraffinized blocks of tumor and “healthy” tissues. Relative copy numbers of 8 genetic loci (c-Myc, CDK12, CDKN1B, PRPF19, ERBB2, DDB1, GAB2, COL6A3) was assessed by RT-qPCR technique. Relative copy quantitation of a genetic locus was calculated as 2-ΔCt. The dose of the locus studied was considered equal to diploid set (2n) if RCQtumor/healthy was about 1. If RCQtumor/healthy was > 1.5 or < 0.5, then the locus dose was considered increased (≥ 3n) or decreased (≤ 1n), respectively.Results: For all genetic loci, an increase of relative copy quantitation in the ovarian tumor cells was observed compared to that in “healthy” tissues. There was a significant (р<0.05) aberrant copy quantitation of 4 genes: c-Myc (р = 0.001), DDB1 (р = 0.002), PRPF19 (р = 0.0001), and CDKN1B (р = 0.001). We identified differential thresholds for these genes that made it possible to predict an unfavorable disease course in the patients (р < 0.05). The strongest association with the risk of adverse outcomes was found for increased copy number of PRPF19 (odds ratio (OR) 7.3; р = 0.0001) and c-Myc (OR 6.8; р = 0.001).Conclusion: In this study, we determined the prognostic value of 4 oncogenic drivers, namely, DDB1, PRPF19, CDKN1B, and с-Myc, whose increased copy number was associated with an adverse disease prognosis in ovarian cancer patients.