Научная статья на тему 'Association of 22 Potential Pathogenic Variants of New Candidate Genes and the Risk of Ovarian Cancer'

Association of 22 Potential Pathogenic Variants of New Candidate Genes and the Risk of Ovarian Cancer Текст научной статьи по специальности «Биотехнологии в медицине»

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Ключевые слова
ovarian cancer / candidate genes / exome sequencing / potential pathogenic variants / risk of disease / Fluidigm BioMark™ HD.

Аннотация научной статьи по биотехнологиям в медицине, автор научной работы — E.T. Mingazheva, D.S. Prokofyeva, Ya.V. Valova, E.A. Andreeva, A.Kh. Nurgalieva

The high risk of ovarian cancer is primarily associated with mutations in BRCA1 and BRCA2 genes. However, mutations in these explain only a small proportion of cases. Mutations in other genes are also involved in the disease. As a result of previous exome sequencing of DNA samples from breast cancer Germany patients with clinical signs of a hereditary form of the disease without major mutations in the BRCA1, BRCA2, CHEK2 and NBN genes, potentially pathogenic genetic variants in new breast and ovarian cancer candidate genes were selected. Selected as a result of bioinformatics analysis genes are involved in vital cell signaling pathways such as repair, apoptosis, cell cycle regulation, cell proliferation, migration, differentiation, as well as immune response and inflammation. Recently, biological microarray technologies have been widely used to study the general genetic variability throughout the human genome in order to determine genetic associations with the disease and search for genes involved in the pathogenesis of multifactorial pathologies. The use of such approaches can be very useful for identifying risk markers for the development and severity of diseases. Our case-control study is aimed at researching potentially pathogenic variants selected as a result of exome sequencing of DNA samples from Caucasian patients using microarray technology Fluidigm to assess their contribution to ovarian cancer pathogenesis in Bashkortostan. Most of the researched alleles were found with different frequencies among cases and controls; however, our data indicate that the researched potentially pathogenic variants do not contribute to ovarian cancer pathogenesis in Bashkortostan populations.

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Текст научной работы на тему «Association of 22 Potential Pathogenic Variants of New Candidate Genes and the Risk of Ovarian Cancer»

ASSOCIATION OF 22 POTENTIAL PATHOGENIC VARIANTS OF NEW CANDIDATE GENES AND THE RISK OF OVARIAN CANCER

E.T. Mingazheva1, D.S. Prokofyeva1*, Ya.V. Valova1'3, E.A. Andreeva1, A.Kh. Nurgalieva1, R.R. Valiev1, N.V. Ekomasova1'2, R.R. Faishanova5, A.R. Romanova4, E.K. Khusnutdinova1'2

1 Federal State Educational Institution of Higher Education «Ufa University of Science and Technology», 32 Zaki Validi St., Ufa, 450076, Russia;

2 Institute of Biochemistry and Genetics, Ufa Federal Research Center of the Russian Academy of Sciences, 71 prospect Oktyabrya, Ufa, 450054, Russia;

3 Federal Institution of Science «Ufa Research Institute of Occupational Health and Human Ecology», 94 Stepan Kuvykin St., Ufa, 450106, Russia;

4 Federal State Budgetary Educational Institution of Higher Education «Bashkir State Medical University» of the Ministry of Health of the Russian Federation, 3 Lenin St., Ufa, 450008, Russia;

5 Ministry of Health of the Republic of Bashkortostan State Autonomous Institution of Health «Republican Clinical Oncological Dispensary», 73/1 prospect Oktyabrya, Ufa, 450054, Russia.

* Corresponding author: [email protected]

Abstract. The high risk of ovarian cancer is primarily associated with mutations in BRCA1 and BRCA2 genes. However, mutations in these explain only a small proportion of cases. Mutations in other genes are also involved in the disease. As a result of previous exome sequencing of DNA samples from breast cancer Germany patients with clinical signs of a hereditary form of the disease without major mutations in the BRCA1, BRCA2, CHEK2 and NBN genes, potentially pathogenic genetic variants in new breast and ovarian cancer candidate genes were selected. Selected as a result of bioinformatics analysis genes are involved in vital cell signaling pathways such as repair, apoptosis, cell cycle regulation, cell proliferation, migration, differentiation, as well as immune response and inflammation. Recently, biological microarray technologies have been widely used to study the general genetic variability throughout the human genome in order to determine genetic associations with the disease and search for genes involved in the pathogenesis of multifactorial pathologies. The use of such approaches can be very useful for identifying risk markers for the development and severity of diseases. Our case-control study is aimed at researching potentially pathogenic variants selected as a result of exome sequencing of DNA samples from Caucasian patients using microarray technology Fluidigm to assess their contribution to ovarian cancer pathogenesis in Bashkortostan. Most of the researched alleles were found with different frequencies among cases and controls; however, our data indicate that the researched potentially pathogenic variants do not contribute to ovarian cancer pathogenesis in Bashkortostan populations.

Keywords: ovarian cancer, candidate genes, exome sequencing, potential pathogenic variants, risk of disease, Fluidigm BioMark™ HD.

List of Abbreviations

OC - ovarian cancer

OCAC - cancer association consortium

WES whole - exome sequencing

DNA - deoxyribonucleic acid

HWE -Hardy-Weinberg equilibrium

PCR - polymerase chain reaction

LSP - locus-specific primer

STA - specific target amplification

Introduction

Ovarian cancer (OC) is one of the most common gynecological malignancy that has the highest mortality rate. Worldwide, approximately 313,000 women are diagnosed with

ovarian cancer each year, and 207, 000 dies. In 2020, in Russia has estimated 13,192 new cases of ovarian cancer, and more than half of the cases were fatal (Kaprin et al., 2021). The high mortality rate is primarily due to the detection of ovarian cancer in the late stages of development (III-IV). In the first year after diagnosis, every third patient dies. There has been a tendency over the last years towards the rejuvenation of this cancer type, so the disease is more often diagnosed in a group of women under the age of 30 (Cress et al., 2015; Torre et al., 2018).

Ovarian cancer is a complex, multifactorial, heterogeneous disease that includes a number of different histological type. The high risk of

this pathology is primarily associated with mutations in the tumor suppressor genes BRCA1 and BRCA2 (Antoniou et al., 2003; Bateneva et al., 2013; Bermisheva et al., 2018; Lyubchenko, 2009; Shubin & Karpukhin, 2011). Other genes with moderate and low penetrance are also involved in OC development, which are part in maintaining the integrity of the genome, the processes of cell proliferation and migration, and repair (NBN, RAD50, MRE11, CHEK2, BLM, PALB2, ATM, BRIP1, BARD1, MDC1, STK11, TP53, CDK12 and others) (Bateneva et al., 2013; Bermisheva et al., 2018; Bogdanova et al., 2019; Gordiev et al., 2018; Koczkowska, et al., 2018; Prokofieva, 2013).

Despite the fact that to date some progress has been achieved in the study of genetic predisposition to ovarian cancer, there are still many unclear aspects. International Ovarian Cancer Association Consortium (OCAC) has been established for a comprehensive study of the OC. These researchers have identified new genetic risk factors and targets for treatment of patients diagnosed with ovarian cancer (Johnatty et al., 2015; Knijnenburg et al., 2018).

Recently, biological microarray technologies have been widely used to study the general genetic variability throughout the human genome in order to determine genetic associations with the disease and search for genes involved in the pathogenesis of multifactorial pathologies, which allow simultaneous testing of thousands of samples in a short time. The use of such approaches can be very useful for identifying risk markers for the development and severity of diseases, as well as for creating a person's "genetic passport" (Chan et al., 2017).

We have screened and analyzed the association of 22 potential pathogenic variants of new OC candidate genes. The options under consideration were selected as a result of bioinfor-matic analysis of data from exome sequencing of DNA samples from patients with hereditary breast cancer and OC, carried out earlier by colleagues from Germany (School of Medicine, Hannover).

Materials and Methods

Study populations

The material for this research was DNA samples from women diagnosed with ovarian cancer (n = 212) and women without cancer at the time of blood sampling (n = 212) at the age of 17-87 years from the Republic of Bashkortostan. All OC patients and healthy women originated from the Volga-Ural region but belonged to different ethnic groups, including Russians (47.9%), Tatars (30.6%), Bashkirs (12.3%), Ukrainians (2.9%), and patients of other (3.9%) or mixed ancestry (2.3%). In terms of ethnic composition, the control group corresponded to the group of patients.

Peripheral venous blood was taken by employees of the State Autonomous Institution of Health Republican Clinical Oncology Center of the Health Ministry of the Bashkortostan Republic (Ufa) and the Oncology Department of the City Clinical Hospital No. 1 (Sterlitamak). All participants of this research signed voluntary informed consent for molecular genetic studies. The work was approved by the Bioethical Committee of the Institute of Biochemistry and Genetics, Ufa Federal Research Center of the Russian Academy of Sciences.

In this study were included DNA samples from patients with epithelial OC. Of these, 76,4% of women had poorly differentiated serous tumors, 2% had highly differentiated serous tumors, 5% had mucinous tumors, 1,5% had clear cell tumors, and 1% had endometrioid tumors. Tumors were predominantly of a high grade (G1-G2) - 31.2%. A low-grade tumor (G3-G4) was detected in 15.2% cases, and grading of cancer cells was not histologically determined in 52.9% patients. Bilateral OC was present in 57% women with OC. Stage I of disease was established in 16.8% of patients; II -in 33.2%; III - in 43.4% and stage IV - in 6.6% of cases. Family history of OC and/or breast cancer was found in 9.5% of patients.

Ethical approval

All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional re-

E.T. Mingazheva, D.S. Prokofyeva, Ya. V. Valova et al.

search bioethical committee of the Institute of Biochemistry and Genetics, Ufa Federal Research Center of the Russian Academy of Sciences and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards. Each participant gave written informed consent.

Methods

Genomic DNA was isolated from peripheral blood samples from ovarian cancer patients and controls by routine phenol-chloroform extraction. The DNA concentration was measured using NanoDrop 2000c UV-Vis Spectrophotometer (Thermo Fisher Scientific Inc., Waltham, MA, USA).

As a result of previous whole exome sequencing (WES), 24 potentially pathogenic genetic variants were selected, which became the object of study in this project. Genetic variants were selected by them role in protein function: truncating variants (essential splice-site, frameshift, stop gained and one genetic variant that results in the substitution of the first amino acid). We genotyped using standard protocol of Fluidigm 192.24 SNPtype Genotyping Technology (Fluidigm, South San Francisco, CA, USA) (Olwagen et al., 2019). Investigated genetic variants of ovarian cancer candidate genes presented in the study are shown in Table 1.

The genotypes of the polymorphisms listed above were determined by polymerase chain reaction (PCR). First, for the polymerase chain reaction analysis, the amount of DNA was quantified to 50 ng and the DNA fragment was amplified using two preamplification primers (locus-specific primer (LSP) and specific target amplification (STA) primer to amplify the target region containing the genetic variants. Multiplex PCR was performed on an Applied Biosystems 2720 Thermal Cycler (Applied Biosystems, Foster City, CA, USA), with the following conditions: hold at 95 °C for 15 min, 14 cycles at 95 °C for 15 s, and 60 °C for 4 min. The ready STA-product was diluted 100-fold in suspension DNA buffer.

A second amplification was performed on the Fluidigm 96.96 Dynamic Array. Assay mixes was prepared by mixing 3 pL of each al-

lele-specific primer (ASP), 8 pL of each locus-specific primer (LSP), and 29 pL DNA hydration buffer. 0.8 pl of each assay mix was combined with 2.0 pL of 2 x Assay Loading Reagent and 1.2 pL of nuclease-free water. To prepare a pre-mix for samples, 2.25 pl Biotium 2X Fast Probe Master Mix, 0.225 pl 20X SNP Type Sample Loading Reagent, 0.075 pl 60X SNP Type Reagent, 0.027 pl ROX, 0.048 pl nucle-ase-free water were mixed. Sample mixture with a volume of 4.5 pL was prepared by combining 2.6 pL of the pre-mix with 1.9 pL of 1: 100 diluted STA amplifier. The mixture with samples was vortexed for 20 seconds and then centrifuged for 30 seconds. The BioMark HD dynamic array was first primed with control line fluid, and then loaded with the samples and assay mixtures via the appropriate inlets using an IFC (integrated fluidic circuit) controller. Samples were applied to the chip according to the manufacturer's instructions. The array chip was placed in the BioMark HD Instrument. PCR was carried out using the following cycling conditions: 95 °C for 5 min, followed by four touchdown cycles (95 °C for 15 s, from 64 °C to 61 °C for 45 s, 72 °C for 15 s) and 34 additional cycles (95 °C for 15 s, 60 °C for 45 s, 72 °C for 15 s). Each PCR reaction used distilled water instead of DNA as negative control. For variants rs201755391 and rs763189487 in genes PARP14 and TSR1, respectively, low fluorescence signals were obtained and subsequently their studies were excluded. Results were plotted on a two-dimensional scatter plot of the major versus the minor allele using the BioMark SNP Genotyping Analysis software version 2.1.1. Genotyping calls were assessed based on the allele discrimination plots and manually reviewed by looking at the single amplification plots. Genotyping calls were exported as a CSV file and processed for secondary analysis.

Chi-square was used to test association and Hardy-Weinberg equilibrium (HWE) for each variant. Variants that did not pass the HWE criteria have been discarded from further analysis. All statistical assessments were two-sided and considered to be significant when p-value was < 0.05.

The potential pathogenic variants of ovarian cancer candidate genes presented in the research

№ Gene Variant Type of variant dbSNP Chr ( GRCh37) Ref Allele Alt Allele

1 USP39 g.85876139G > C, c.*208G > C violation of the acceptor site rs112653307 Chr.2:85876139 G C

2 EGF g.110932393dupC, c.3406dupC, p.Gln1136fs Frameshift rs11569144 Chr.4:110932393 CCCC CCCCC

3 SMAR-CAL1 S.217342939G > T, c.2542G > T, p.Glu848Ter Nonsense rs 119473033 Chr.2:217342939 G T

4 BCLAF1 S.136599127G > A, c.892C > T, p.Arg298Ter Nonsense rs138333275 Chr.6:136599127 G A

5 ANKRD36 g.97779488delC,c.12delC, p.Lys5fs Frameshift rs 141447363 Chr.2:97779488 C delC

6 PHKB g.47495300G > A, c.39G > A, p.Trp13Ter Nonsense rs141733590 Chr.16:47495300 G A

7 TP53I3 g.24302375G > C, c.755C > G, p.Ser252Ter Nonsense rs145078765 Chr.2:24302375 G C

8 PZP g.9321534G > A, c.2038C > T, p.Arg680Ter Nonsense rs 145240281 Chr.12:9321534 G A

9 APLF g.68805146delA, c.1528delA, p.Arg510fs Frameshift rs 149897324 Chr.2:68805146 AAAA AAA

10 EXO5 g.40981245 40981246insG, c.1029 1030insG, p.Arg344fs Frameshift rs150018949 Chr.1:40981245 D insG (I)

11 BABAM2 g.28532947A > C, c.1088+11589A > C violation of the acceptor site rs150302537 Chr.2:28532947 A C

12 HERC6 g.89318021T > A, c.906T > A, p.Tyr302Ter Nonsense rs 192005184 Chr.4:89318021 T A

13 DCLRE1A S.115610226C > T, c.638G > A, p.Trp213Ter Nonsense rs200026311 Chr.10:115610226 C T

14 SLX1B g.29469248G > C, c.711-1G > C violation of the acceptor site / occurrence new acceptor site rs200435542 Chr.16:29469248 G C

№ Gene Variant Type of variant dbSNP Chr ( GRCh37) Ref Allele Alt Allele

15 PARP14 g.122404166G > A violation of the donor site rs201755391 Chr.3:122404166 G A

16 APOBEC1 g.7805414C > T, c.62G > A, p.Trp21Ter Nonsense rs34275479 Chr.12:7805414 C T

17 H4C2 g.26027457dupA, c.24dupA, p.Lys9Ter Nonsense rs535221714 Chr.6:26027457 A dupA

18 H4C12 g.27799162 27799163insA, c.143 144insT, p.Gly49fs Frameshift rs544620282 Chr.6:27799162 D insA (I)

19 AUNIP g.26161770 26161779del, c.780 789delTTCACTGATT, p.Glu260fs Frameshift rs564635111 Chr.1:26161770 TTTCACTGATT delTTTCACTGATT

20 MYCT1 g.153019103 153019106delTAGA, c.66 69delTAGA, p.Asp22fs frameshift rs3841162 Chr.6:153019103 AGATAGA delTAGA

21 NANOG g.7947687 7947688delTG, c.914 915delTG,p.Ter306LysextTer Nonsense rs762642172 Chr.12:7947687 GTGTG delTG

22 TSR1 g.2238179G > A, c.568C > T, p.Gln190Ter Nonsense rs763189487 Chr.17:2238179 G A

23 ATP23 g.58335486T > A, c.2T > A, p.Met1Lys Missense rs768622289 Chr.12:58335486 T A

24 FANCL g.58386930 58386933dupAATT, c.1111 1114dupAATT, p.Thr372fs Frameshift rs759217526 Chr.2:58386930 TAATT dupAATT

Results

As a result of previous exome sequencing of DNA samples from breast cancer patients with clinical signs of a hereditary form of the disease, in whom major mutations in the BRCA1, BRCA2, CHEK2 and NBN genes were not detected, potentially pathogenic genetic variants in new breast and ovarian cancer candidate genes were selected. All variants are truncating. The genes included in the study are involved in vital cell signaling pathways such as repair, apoptosis, cell cycle regulation, cell proliferation, migration, differentiation, as well as immune response and inflammation.

The role predisposing to OC was studied for 22 alleles. Three alleles SMARCAL1 p.Glu848Ter, DCLRE1A p.Trp213Ter and ATP23 p.MetlLys were not detected. These al-leles are also extremely rare in population databases. Especially the ATP23 p.MetlLys allele, which was found with a frequency of 0.0004% to 0.002% in the ALFA and gnomAD-Exomes projects. Missense variant ATP23 p.MetlLys leads to the replacement of the start codon with lysine, which identifies it as pathogenic and is confirmed by predictive algorithms. Such a low frequency of occurrence of a rare allele also testifies in favor of the high pathogenicity of the considered genetic variant. Minor allele of variants USP39 c.*208G>C (0.72%), BCLAF1 p.Arg298Ter (1.21%), TP53I3 p.Ser252Ter (1.67%), PHKB p.Trp13Ter (1.90%) and HERC6 p.Tyr302Ter (1.44%) with different low frequencies were found among controls only. These alleles occurred at a much higher frequency than the 1000 Genome Project, ALFA and gnomAD-Exomes populations (Table 2). For 14 potentially pathogenic variants, rare alleles were identified both among patients and control and we could association research (Table 3).

Minor allele of variants APLF p.Arg510fs (1.65% vs 0.72%), EXO5 p.Arg344fs (1.66% vs 0.72%) and H4C12 p.Gly49fs (0.98% vs 0.79%) were more common in cases than controls, respectively. Potentially pathogenic genetic variants MYCT1 p.Asp22fs (4.95%) and NANOG p.Ter306LysextTer (3.10%) were detected at a markedly higher frequency in case

and control, respectively. The highest frequency of the minor allele was found for ANKRD36 p.Lys5fs (12.44% in patients with OC and 9.38% in controls). The allele frequencies of the studied genetic variants assessed are reported in Table 3.

Discussion

As mentioned earlier, the selected truncating variants were found by exome sequencing and most of them have not been described in the literature. However, several alleles have been described in relation to various diseases.

The EXO5 c.1029_1030insG (p.Arg344fs) variant, which leads to a frameshift and synthesis of the defective protein, was also identified by full exome sequencing in Spanish patients with testicular cancer with a family history. Using algorithms that predict the effect of this genetic variant on the structure and function of the protein, the authors of the study concluded that it is highly pathogenic (Phred = 28.3). Subsequently, this variant was searched for in an expanded sample of patients and healthy individuals, which revealed an association of the p.Arg344fs polymorphic locus with a moderate risk of developing testicular cancer (Paumard-Hernandez et al., 2018). In our study, the frequency of the minor allele in the group of patients was more than two times higher (3.32%) than in the control group (1.44%) for this reason, we do not exclude the possibility of an association with OC with an increase in the statistical power of the study.

The variant USP39 (c.*208G>C) leads to disruption of mRNA splicing acceptor site in the 3'-untranslated region of the gene (Fujiwara et al., 2014). This variant was associated with triple-negative breast cancer in Russians, as well as with breast cancer in a combined analysis of three populations (Russians, Germans, and Belarusians) (Kuligina et al., 2020). Interestingly, carriers of this variant were found only in the control group (0.72%) in our research.

The PZP p.Arg680Ter variant, which leads to the loss of protein function, was previously identified by whole exome sequencing in female patients with clinical signs of hereditary breast cancer from Brazil (Thompson et al.,

Frequency investigated alleles of ovarian cancer candidate genes in this case-control study and few projects of allele frequency in different populations

№ Gen Variant Cases Controls 1000 Genomes ALFA gnomAD - Exomes

1 USP39 c.*208G>C 0 0.72 0.1 0.78 0.5

2 EGF c.3406dupC, p.Gln1136fs 0.71 2.13 8.7 0.50 3.97

3 SMARCAL1 c.2542G>T, p.Glu848Ter 0 0 - 0.02 0.008

4 BCLAF1 c.892C>T, p.Arg298Ter 0 1.21 0.10 0.073 0.2

5 ANKRD36 c.12delC, p.Lys5fs 12.44 9.38 2.42 5.91 7.40

6 PHKB c.39G>A, p.Trp13Ter 0 1.90 0.14 0.11 0.22

7 TP53I3 c.755C>G, p.Ser252Ter 0 1.67 - 0.13 0.19

8 PZP c.2038C>T, p.Arg680Ter 0.24 0.47 0.14 0.44 0.43

9 APLF c.1528delA, p.Arg510fs 1.65 0.72 0.46 2.08 1.1

10 EXO5 c.1029 1030insG, p.Arg344fs 1.66 0.72 0.84 1.71 1.3

11 BABAM2 c.1088+11589A>C 0.94 1.19 0.04 0.25 0.41

12 HERC6 c.906T>A, p.Tyr302Ter 0 1.44 0.16 0.45 0.6

13 DCLRE1A c.638G>A,p.Trp213Ter 0 0 - 0.004 0.02

14 SLX1B c.711-1G>C 0.71 0.95 0.02 - 0.1

15 APOBEC1 c.62G>A, p.Trp21Ter 0.24 0.48 0.22 0.9 0.6

16 H4C2 c.24dupA, p.Lys9Ter 0.47 0.24 0.06 0.02 0.14

17 H4C12 c.143 144insT, p.Gly49fs 0.98 0.79 0.06 0 0.2

18 AUNIP c.780 789delTTCACTGAT, p.Glu260fs 0.50 1.77 0.22 0.4 0.41

19 MYCT1 c.66 69delTAGA, p.Asp22fs 4.95 3.15 8.43 3.45 5.48

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20 NANOG c.914 915delTG, p.Ter306LysextTer 3.10 4.76 1.74 1.2 1.1

21 ATP23 c.2T>A, p.Met1Lys 0 0 0 0.002 0.0004

22 FANCL c.1111 1114dupAATT, p.Thr372fs 0.47 0.48 - 0.43 0.3

Analysis of Case-Control Association Study for 22 po Frequency investigated potential pathogenic variants

of ovarian cancer candidate genes in patients and controls

№ Gen Variant Alleles(A1)*/A2 Frequency A1 (cases) Frequency A1 (control) X2 P

1 EGF c.3406dupC dupC/C 0.71 2.13 2.14 0.14

2 ANKRD36 c.12delC delC/C 12.44 9.38 1.71 0.19

3 PZP c.2038C>T T/C 0.24 0.47 0.00002 1

4 APLF c.1528delA delA/A 1.65 0.72 0.85 0.36

5 EXO5 c.1029 1030insG D/I 1.66 0.72 0.88 0.35

6 BABAM2 c.1088+11589A>C C/A 0.94 1.19 0.0002 0.99

7 SLX1B c.711-1G>C C/G 0.71 0.95 0.00004 0.99

8 APOBEC1 c.62G>A T/C 0.24 0.48 0.0003 0.99

9 H4C2 c.24dupA dupA/A 0.47 0.24 0.00007 0.99

10 H4C12 c.143 144insT I/D 0.98 0.79 0.01 0.92

11 AUNIP c.780 789delTTCACTGATT D/I 0.50 1.77 1.87 0.17

12 MYCT1 c.66 69delTAGA D/I 4.95 3.15 1.30 0.25

13 NANOG c.914 915delTG D/I 3.10 4.76 1.14 0.29

14 FANCL c.1111 1114dupAATT Dup AATT/AATT 0.47 0.48 0.24 0.63

* Allelel (Ai)-minor allele

E.T. Mingazheva, D.S. Prokofyeva, Ya. V. Valova et al.

2012; Torrezan et al., 2018). However, a rep-licative study by Kuligina et al. among breast cancer patients of Russian, Belarusian and German ethnicity did not reveal a significant association of this variant with the disease (Kuligina et al., 2020). In our research, this variant occurred at a low frequency among cases and controls, more common in health women (0.24% vs 0.47%, respectively). The frequency of this allele among controls corresponded to the prevalence of the genetic variant in population databases the 1000 Genome Project, ALFA and gnomAD-Exomes (0.14-0.44%). So, we do not to draw unambiguous conclusions about its role in the development of OC.

We research of the role of new ovarian cancer candidate genes. Many of alleles occur at a low frequency in populations and were not identified in this work. We do not exclude the possibility of finding associations with the ovarian cancer risk for these alleles with an increase in the number of samples (> 1 000).

Thus, our data indicate that the researched potentially pathogenic genetic variants do not

contribute to the ovarian cancer pathogenesis in Bashkortostan populations.

Conflicts of interest: the authors declare no conflict of interest.

Acknowledgements

Targeted Next-Generation sequencing was funded by Ministry of Science and Higher Education of Russian Federation (№ 075-032021-193/5), grant of the republic of Bashkortostan (№ 210/1), grants of the President of the Russian Federation (MK-3208.2022.1.4), the scholarship of the President of the Russian Federation Order of the Ministry of Science and Higher Education of the Russian Federation No. 38 dated January 20, 2022, RFBR grants No. 20-34-90003. We thank all patients who took part in this research work and all scientists, clinicians, oncologists and technicians who enabled this work to be carried out. Also, we so thank our colleagues Natalia V Bog-danova and Thilo Dork from Hannover Medical School for long standing and productive collaboration.

References

ANTONIOU A., PHAROAH P.D., NAROD S., RISCH H.A., EYFJORD J.E., HOPPER J.L., ... & EASTON D. (2003): Average risks of breast and ovarian cancer associated with BRCA1 or BRCA2 mutations detected in case series unselected for family history: a combined analysis of 22 studies. The American Journal of Human Genetics 72(5), 1117-1130.

BATENEVA E.I. et al. (2013): Substantiation ofthe composition ofthe diagnostic panel for genetic screening of patients with breast cancer and / or ovarian cancer: the spectrum of frequent mutations in the BRCA1 and BRCA2 genes in the Russian population. Medical genetics 12, 26-31.

BERMISHEVA M.A., BOGDANOVA N.V. & GILYAZOVA I.R. (2018): Ethnic features of the formation of genetic predisposition to the development of breast cancer. Genetics 54(2), 233-242.

BOGDANOVA N.V., SCHURMANN P., VALOVA Y., DUBROWINSKAJA N., TURMANOV N., YUGAY T., ... & DORK T. (2019): A splice site variant of CDK12 and breast cancer in three Eurasian populations. Frontiers in Oncology 9, 493.

CHAN C.H.T., MUNUSAMY P., LOKE S.Y., KOH G.L., WONG E.S.Y., LAW H.Y., ... & LEE A.S.G. (2017): Identification of Novel Breast Cancer Risk Loci Novel Breast Cancer Risk Loci Identified by Targeted NGS. Cancer research 77(19), 5428-5437.

CRESS R.D., CHEN Y.S., MORRIS C.R., PETERSEN M., & LEISEROWITZ G.S. (2015): Characteristics of long-term survivors of epithelial ovarian cancer. Obstetrics and gynecology 126(3), 491-497.

FUJIWARA T., KATSUDA T., HAGIWARA K., KOSAKA N., YOSHIOKA Y., TAKAHASHI R.U., ... & OCHIYA T. (2014): Clinical relevance and therapeutic significance of microRNA-133a expression profiles and functions in malignant osteosarcoma-initiating cells. Stem cells 32(4), 959-973.

GORDIEV M. G., SAKAEVA D.D., PETKAU V.V., ENIKEEV R.F., BROVKINA O.I., SHIGAPOVA L.Kh., ... & SHUMSKAYA I.S. (2018): Targeted sequencing of a new generation of genes for the detection of rare mutations in hereditary breast cancer. Malignant tumors 8(1), 107-109.

JOHNATTY S.E., TYRER J.P., KAR S., BEESLEY J., LU Y., GAO B., ... & CHENEVIX-TRENCH G. (2015): Genome-wide analysis identifies novel loci associated with ovarian cancer outcomes: findings from the Ovarian Cancer Association Consortium. Clinical Cancer Research 21(23), 5264-5276.

KAPRIN A.D., STARINSKY V.V. & SHAHZADOVA AO. (2021): Malignant neoplasms in Russia in 2020 (morbidity and mortality). Moscow Scientific Research Institute named after P.A. Herzen: Branch of the FSBI "National Medical Research Center of Radiology" Ministry of Health of Russia, 252 pp.

KNIJNENBURG T.A., WANG L., ZIMMERMANN M.T., CHAMBWE N., GAO G.F., CHERNIACK A.D., ... & THIESSEN N. (2018): Genomic and molecular landscape of DNA damage repair deficiency across the cancer genome atlas. Cell reports 23(1), 239-254.

KOCZKOWSKA M., KRAWCZYNSKA N., STUKAN M., KUZNIACKA A., BROZEK I., SNIADECKI M., ... & RATAJSKA M. (2018): Spectrum and prevalence of pathogenic variants in ovarian cancer susceptibility genes in a group of 333 patients. Cancers 10(11), 442-449.

KULIGINA E S., SOKOLENKO A.P., BIZIN I.V., ROMANKO A.A., ZAGORODNEV K.A., ANISI-MOVA M.O., ... & IMYANITOV E.N. (2020): Exome sequencing study of Russian breast cancer patients suggests a predisposing role for USP39. Breast cancer research and treatment 179(3), 731-742.

LYUBCHENKO L.N. (2009): Hereditary breast and/or ovarian cancer: DNA diagnosis, individual prognosis, treatment and prevention. Doctoral dissertation, Moscow, 295 pp.

OLWAGEN CP., ADRIAN P.V., & MADHI S.A. (2019): Performance of the Biomark HD real-time qPCR System (Fluidigm) for the detection of nasopharyngeal bacterial pathogens and Streptococcus pneumoniae typing. Scientific reports 9(1), 1-11.

PAUMARD-HERNÂNDEZ B., CALVETE O., INGLADA PÉREZ L., TEJERO H., AL-SHAHROUR F., PITA G., ... & BENÎTEZ J. (2018): Whole exome sequencing identifies PLEC, EXO5 and DNAH7 as novel susceptibility genes in testicular cancer. International journal of cancer 143(8), 1954-1962.

PROKOFIEVA D.S. (2013): Study of genetic risk factors for ovarian cancer. Dissertation, Ufa, 186 pp.

SHUBIN V.P. & KARPUKHIN A.V. (2011): Molecular genetics of hereditary predisposition to ovarian cancer. Medical genetics 10, 39-47.

THOMPSON E.R., DOYLE M.A., RYLAND G.L., ROWLEY S.M., CHOONG D.Y., TOTHILL R.W., ... & CAMPBELL I.G. (2012): PLoS Genet 8(9), 894.

TORRE L A., TRABERT B., DESANTIS C.E., MILLER K.D., SAMIMI G., RUNOWICZ CD., ... & SIEGEL R.L. (2018): Ovarian cancer statistics. CA: a cancer journal for clinicians 68(4), 284-296.

TORREZAN G.T., DE ALMEIDA F.G.D.S.R., FIGUEIREDO MC., BARROS B.D.D.F., DE PAULA C.A., VALIERIS R., ... & CARRARO D.M. (2018): Complex landscape of germline variants in Brazilian patients with hereditary and early onset breast cancer. Frontiers in genetics 9, 161.

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