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A study of prevalence of polymorphic variants of genes of blood coagulation factors in onco-logical patients
- Authors: Zykova T.A.1, Vladimirova L.Y.1, Katelnitskaya O.V.1, Maslov A.A.1, Shevyakova E.A.1, Lysenko I.B.1, Abramova N.A.1, Storozhakova A.E.1, Popova I.L.1, Novoselova K.A.1, Tikhanovskaya N.M.1, Lyanova A.A.1, Ryadinskaya L.A.1, Tishina A.V.1, Tishchenko I.S.1, Kabanov S.N.1, Kalabanova E.A.1
-
Affiliations:
- Rostov Research Institute of Oncology
- Issue: Vol 28, No 1 (2020)
- Pages: 44-56
- Section: Original study
- URL: https://journals.eco-vector.com/pavlovj/article/view/16376
- DOI: https://doi.org/10.23888/PAVLOVJ202028144-56
- ID: 16376
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Abstract
Aim. To study the prevalence of carriage of polymorphic allele variants of genes of blood coagulation factors in oncological patients.
Materials and Methods. 213 Patients with morphologically confirmed oncological diseases were examined. Samples of genomic DNA of peripheral blood of the patients were examined. Using polymerase chain reaction (PCR), polymorphic sites of genes of hemostatic system were studied in real time: F2 (G20210А, rs1799963), F5 (G1691A, rs6025), F7 (G10976A, rs6046), F13 (G226A, rs5985), FGB G(-455)A (rs1800790), ITGA2-α2 (C807T, rs1126643), ITGB3-b (Т1565С, rs5918), PAI-1 4G(-675)5G, rs1799889).
Results. The prevalence of carriage of alternative allele of F2 (G20210А) polymorphic locus in the studied group was 1.6%, of F5 (G1691A) – 3.5%, of F7 (G10976A) – 13.4%, of F13 (G226A) – 28.2%, of FGB G(-455)A – 24.9%, of ITGA2-α2 (C807T) – 41.5%, of ITGB3-b (Т1565С) – 15.5%, of PAI-1 4G(-675)5G – 56.6%. A statistically significant increase in the frequency of ‘risk alleles’ of F5 G1691A (р=0.0169), F13 G226A (р=0.0007), FGB G(-455)A (р<0.0001) and ITGA2-α2 C807T (р=0.0201) polymorphic loci was found in oncological patients as compared to the general population. In the same loci, except ITGA2-α2 (C807T), statistically significant differences in the frequency of alternative alleles were found in different localizations of the oncological process. In 92.0% of patients, SNR combination was determined in different components of hemostatic system.
Conclusion. Taking into account a high frequency of identification of ‘risk alleles’ in all components of hemostatic system, it is reasonable to carry out additional research to determine the necessity of addition of antiaggregants to antithrombotic therapy in oncological patients.
Full Text
Venous thromboembolic complications (VTEC) usually manifested as deep vein thrombosis (DVT) or thromboembolism of pulmonary artery (TEPA), are multifactorial diseases based on both acquired and genetic risk factors. In modern understanding of the pathogenesis of VTEC, a significant role is assigned to hereditary disorders in the blood coagulation system [1]. VTEC occur with age-related frequency in one to three individuals per 1000 population annually. The rate of lethal outcomes is more than 5%, mostly owing to TEPA [2]. Both genders equally suffer from the first venous thrombosis, but the risk of recurrent thrombosis is higher in males than in females [2, 3].
At present of no doubt is the fact that in patients with oncological diseases VTEC are more common, and migrating venous thrombosis is a manifestation of the paraneoplastic syndrome [4]. Mechanisms of hemostasis participating in thrombogenesis, are also involved in progression of tumor, angiogenesis and metastatic spread [5]. According to different data, risk of VTEC in oncological patients is four [6] to seven and more [4] times higher than in non-oncological patients. To some estimates, 15-20% of patients with cancer suffer from DVT or TEPA [7]. In later publications 11% of cases of thrombosis are identified within a year [8], F. Horsted, et al. showed that the annual rate of VTEC makes from 0.5 to 20% depending on the kind of cancer and the background risk [9], and the study of M. Li, et al. evaluated the general incidence of VTEC in oncological patients as 2.3% [10]. Besides, cancer is an independent risk factor for recurrence of VTEC and bleedings in oncological patients [11, 12].
In most publications, the connection between carriage of single nucleotide polymorphism (SNP) of genes of blood coagulation system and cancer is studied in the aspect of their influence on the risk of initiation, development and progression of tumor process. Thus, in carriers of anticoagulant variant of F13 (G226A) allele of XIII blood coagulation factor, the risk of development of colorectal cancer was 15% lower than in non-carriers, and procoagulant mutations of 4G(-675)5G PAI-1 plasminogen activator inhibitor gene did not influence the risk of its initiation [13]. Associations of SNR in F5 and F10 genes with the risk for development of breast cancer (BC) were shown [14]. At the same time the data of the frequency of inherited forms of VTEC in oncological patients are very scarce. It was found that in case of a combination of mutation in F5 Leiden gene and cancer, the risk for thrombosis increases 12-fold as compared to individuals without cancer and mutation [15]. An important problem in oncology is thromboses of rare localizations. In the presence of thrombophilia the risk of thrombosis of mesenteric veins increases 100-fold, in case of mutation in F5 (G1691A) gene the risk of thrombosis of retina increases 6-fold, and in case of mutation in F2 (G20210A) gene – 8-fold [16].
Aim – to evaluate prevalence of polymorphic allelic variants of genes of hemostatic system in oncological patients.
Materials and Methods
The study involved 213 patients inclu-ding 143 women at the age of 51.89±1.12 years and 70 men at the age of 57.97±1.59 years with a morphologically verified oncological disease. All the patients were undergoing treatment in Rostov Research Institute of Oncology in the period from November 2018 to February 2019.
The candidates for study were selected using random selection method before the start of multi-course chemotherapy. All the participants signed informed consent (the study was approved by Local ethic committee).
The period of observation included four months. Distribution of tumors by localization was the following: BC – 73 (34.3%), lung cancer (LC) – 18 (8.4%), tumors of female reproductive system (TFRS) 16 (7.5%), tumors of GIT (TGIT) – 69 (32.4%), lymphomas – 15 (7.0%), others (multifocal carcinoma, tumors of the central nervous system, head and neck, bones and soft tissues) – 22 (10.3%). For comparison with the general population dbSNP data base was used developed and supported by the National Center of Biotechnological Information (NCBI) of the USA (TOPMED program) [17].
The studied material was samples of genomic DNA obtained from peripheral blood of patients. DNA was extracted using Proba-Rapid-genetika reagent kit; allelic variants of genes were determined by the method of polymerase chain reaction (PCR) in real time using CardioGenetika Thrombophilia reagent kit; the reaction was registered using DT prime 5M1 detecting amplifier (DNK-technologia, Russia). Eight polymorphic loci of genes of blood coagulation factors were used: of II coagulation factor, F2, (G20210А, rs1799963), of V factor Leiden, F5 (G1691A, rs6025), of VII factor, F7 (G10976A, rs6046), of XIII factor, F13 (G226A, rs5985), of fibrinogen, FGB G(-455)A (rs1800790), of platelet receptor to collagen ITGA2-α2 integrin (C807T, rs1126643), platelet receptor of fibrinogen ITGB3-b (Т1565С, rs5918), of plasminogen activator inhibitor PAI-1 4G(-675)5G, rs1799889).
Statistical processing of the data was implemented using standard approaches of population-genetic studies, with use of Office Excel (Microsoft Corporation, USA) and STATISTICA 10.0 (Stat Soft Inc., USA) application programs The control sample was tested for correspondence with Hardy-Weinberg equilibrium by χ2 (α=0.05, df=1) method. Association between a disease and genotype was established using multiplicative and additive inheritance models. Hypothesis of the reliability of differences between the studied groups was verified using χ² Pearson test (for absolute frequencies ˃10), and Fisher test (for absolute frequencies <5). OR-odds ratio parameters were calculated with 95% confidence interval (95% CI).
Results and Discussion
In evaluation of correspondence of the genotype distribution with Hardy-Weinberg distribution in the studied samples it was found that the ratio of the genotype frequencies for all loci of all the studied genes corresponded to this equilibrium. Mutant alleles of the studied polymorphic sites of genes of the plasmic, vasculo-platelet and/or fibri-nolytic components of hemostatic system in different combinations were identified in the absolute majority of the studied patients (210 of 213, 98.6%). ‘Risk alleles’ were completely absent only in three patients (1.4%).
The frequency of carriage of polymorphic variant of F2 (of F7 (G10976A) – 13.4%, of F13 (G226A) – 28.2%, FGB G(-455)A – 24.9%, ITGA2-α2 (C807T) – 41.5%, of ITGB3-b (Т1565С) – 15.5%, of PAI-1 4G(-675)5G – 56.6%. Homozygous genotypes for ‘risk alleles’ in F2 и F5 were not found, in F7 gene they were found in 1.4% of patients, in F13 gene – in 7.5% of patients, in FGB gene – in 4.7%, in ITGA2 gene – in 14.1%, in ITGB3 gene – in 2.3%, in PAI-1 gene – in 32.4% (Table 1).
In comparison of the incidence of ‘risk alleles’ with the data presented in dbSNP (Table 2), there was found a statistically significant exceedance of the incidence of A allele in F5 gene (p=0.0169), of A allele in FGB gene (р<0.0001) and of T allele in ITGA2 gene (р=0.0201 in the studied group. For other ‘risk alleles’ no statistically significant difference in the incidence was found as compared to the world population [17].
Table 1
Distribution of Frequencies of Genotypes and Alleles of Genes of Blood Coagulation Factors in Oncological Patients depending on Gender
Gene | Genotype/ Allele | Men, n=70 | Women, n=143 | Total (main group), n=213 | |||
abs. | % | abs. | % | abs. | % | ||
F2 | 20210 GG | 67 | 95.7 | 139 | 97.2 | 206 | 96.7 |
20210 GA | 3 | 4.3 | 4 | 2.8 | 7 | 3.3 | |
20210 AA | 0 | 0.0 | 0 | 0.0 | 0 | 0.0 | |
G | 137 | 97.9 | 282 | 98.6 | 419 | 98.4 | |
A | 3 | 2.1 | 4 | 1.4 | 7 | 1.6 | |
F5 | 1691 GG | 64 | 91.4 | 134 | 93.7 | 198 | 93.0 |
1691 GA | 6 | 8.6 | 9 | 6.3 | 15 | 7.0 | |
1691 AA | 0 | 0.0 | 0 | 0.0 | 0 | 0.0 | |
G | 134 | 95.7 | 277 | 96.9 | 411 | 96.5 | |
A | 6 | 4.3 | 9 | 3.1 | 15 | 3.5 | |
F7 | 10976 GG | 50 | 71.4 | 109 | 76.2 | 159 | 74.6 |
10976 GA | 20 | 28.6 | 31 | 21.7 | 51 | 23.9 | |
10976 AA | 0 | 0.0 | 3 | 2.1 | 3 | 1.4 | |
G | 120 | 85.7 | 249 | 87.1 | 369 | 86.6 | |
A | 20 | 14.3 | 37 | 12.9 | 57 | 13.4 | |
F13 | GG | 33 | 47.1 | 76 | 53.1 | 109 | 51.2 |
GT | 32 | 45.7 | 56 | 39.2 | 88 | 41.3 | |
TT | 5 | 7.1 | 11 | 7.7 | 16 | 7.5 | |
G | 98 | 70.0 | 208 | 72.7 | 306 | 71.8 | |
T | 42 | 30.0 | 78 | 27.3 | 120 | 28.2 | |
FGB | (-455) GG | 34 | 48.6 | 83 | 58.0 | 117 | 54.9 |
(-455) GA | 33 | 47.1 | 53 | 37.1 | 86 | 40.4 | |
(-455) AA | 3 | 4.3 | 7 | 4.9 | 10 | 4.7 | |
G | 101 | 72.1 | 219 | 76.6 | 320 | 75.1 | |
A | 39 | 27.9 | 67 | 23.4 | 106 | 24.9 | |
ITGA2 | CC | 26 | 37.1 | 40 | 28.0 | 66 | 31.0 |
CT | 36 | 51.4 | 81 | 56.6 | 117 | 54.9 | |
TT | 8 | 11.4 | 22 | 15.4 | 30 | 14.1 | |
C | 88 | 62.9 | 161 | 56.3 | 249 | 58.5 | |
T | 52 | 37.1 | 125 | 43.7 | 177 | 41.5 | |
ITGB3 | 1565 TT | 48 | 68.6 | 104 | 72.7 | 152 | 71.4 |
1565 TC | 20 | 28.6 | 36 | 25.2 | 56 | 26.3 | |
1565 CC | 2 | 2.9 | 3 | 2.1 | 5 | 2.3 | |
T | 116 | 82.9 | 244 | 85.3 | 360 | 84.5 | |
C | 24 | 17.1 | 42 | 14.7 | 66 | 15.5 | |
PAI-1 | (-675) 5G5G | 14 | 20.0 | 27 | 18.9 | 41 | 19.2 |
(-675) 5G4G | 32 | 45.7 | 71 | 49.7 | 103 | 48.4 | |
(-675) 4G4G | 24 | 34.3 | 45 | 31.5 | 69 | 32.4 | |
5G | 60 | 42.9 | 125 | 43.7 | 185 | 43.4 | |
4G | 80 | 57.1 | 161 | 56.3 | 241 | 56.6 | |
Notes: mutant alleles are accentuated semi-bold, for all comparisons p>0.05
In study of the distribution of genotype and allele frequencies depending on the oncological diagnosis we established the following statistically significant regularities (Table 3): polymorphic variant of F5 (G1691A) was more commonly determined in patients with LC (8.3%) as compared to TGIT at p=0.03 (1.4%, χ2=4.85); F7 (G10976A) in heterozygous condition was more common in patients with LC as compared to lymphomas at p=0.03 (6.7%, χ2=4.63); F13 (G226A) in homozygous condition for a mutant allele was more common in patients with lymphomas (20.0%) as compared to BC at p=0.03 (2.7%, χ2=6.94; OR=0.11, 95% CI: 0.02-0.75); FGB G(-455)A in homozygous condition for the mutant allele was more frequent in TGIT (4.3%) as compared to LC (0.0%, p=0.03, χ2=4.49) and TFRO (0.0%, p=0.03, χ2=4.81).
Of the total number of patients of the main group one alternative allele was identified in 14 patients (6.6%), two – in 45 (21.1%), three – in 78 (36.6%), four – in 51 (23.9%), five – in 18 (8.5%), six – in 4 (1.9%). That is, in the absolute amount of patients – 196 (92.0%) combinations of several alternative alleles were found in different polymorphic sites of hemostatic system. The analysis of different variants of gene-gene combinations identified 126 genetic profiles in 213 oncological patients.
Table 2
Distribution of Frequencies of ‘Risk Alleles’ of Genes of Blood Coagulation Factors in Groups of Study as Compared to dbSNP Data Base of National Center of Biotechnological Information (NCBI) TOPMED
SNP | Frequency in Oncological Patients (data obtained by us) | TOPMED Frequency [17] | p |
F2 G20210А | A=0.016 (7/426) | A=0.00995 (1250/125568) | 0.1793 |
F5 G1691A | A=0.035 (15/426) | A=0.01926 (2418/125568) | 0.0169 |
F7 G10976A | A=0.134 (57/426) | A=0.11534 (14483/125568) | 0.2338 |
F13 G226A | A=0.282 (120/426) | A=0.21382 (26849/125568) | 0.0007 |
FGB G(-455)A | A=0.249 (106/426) | A=0.15431 (19376/125568) | <0.0001 |
ITGA2 C807T | T=0.415 (177/426) | T=0.36129 (45367/125568) | 0.0201 |
ITGB3-b Т1565С | C=0.155 (66/426) | C=0.12551 (15760/125568) | 0.0674 |
PAI-1 4G(-675)5G | C=0.566 (241/426) | – | – |
Table 3
Distribution of Frequencies of Genotypes and Alleles of Genes of Hemostatic System in Oncological Patients Depending on Diagnosis
Gene | Genotype/ Allele | BC, n=73 | LC, n=18 | TFRS, n=16 | TGIT, n=69 | Lymphomas, n=15 | Others, n=22 | ||||||
abs. | % | abs. | % | abs. | % | abs. | % | abs. | % | abs. | % | ||
F2 | 20210 GG | 70 | 95.9 | 18 | 100.0 | 16 | 100.0 | 67 | 97.1 | 14 | 93.3 | 21 | 95.5 |
20210 GA | 3 | 4.1 | 0 | 0.0 | 0 | 0.0 | 2 | 2.9 | 1 | 6.7 | 1 | 4.5 | |
20210 AA | 0 | 0.0 | 0 | 0.0 | 0 | 0.0 | 0 | 0.0 | 0 | 0.0 | 0 | 0.0 | |
G | 143 | 97.9 | 36 | 100.0 | 32 | 100.0 | 136 | 98.6 | 29 | 96.7 | 43 | 97.7 | |
A | 3 | 2.1 | 0 | 0.0 | 0 | 0.0 | 2 | 1.4 | 1 | 3.3 | 1 | 2.3 | |
F5 | 1691 GG | 67 | 91.8 | 15 | 83.31 | 15 | 93.8 | 67 | 97.11 | 14 | 93.3 | 20 | 90.9 |
1691 GA | 6 | 8.2 | 3 | 16.71 | 1 | 6.3 | 2 | 2.91 | 1 | 6.7 | 2 | 9.1 | |
1691 AA | 0 | 0.0 | 0 | 0.01 | 0 | 0.0 | 0 | 0.01 | 0 | 0.0 | 0 | 0.0 | |
G | 140 | 95.9 | 33 | 91.71 | 31 | 96.9 | 136 | 98.61 | 29 | 96.7 | 42 | 95.5 | |
A | 6 | 4.1 | 3 | 8.31 | 1 | 3.1 | 2 | 1.41 | 2 | 6.7 | 2 | 4.5 | |
F7 | 10976 GG | 55 | 75.3 | 11 | 61.12 | 12 | 75.0 | 51 | 73.9 | 14 | 93.32 | 16 | 72.7 |
10976 GA | 17 | 23.3 | 7 | 38.92 | 3 | 18.8 | 18 | 26.1 | 1 | 6.72 | 5 | 22.7 | |
10976 AA | 1 | 1.4 | 0 | 0.02 | 1 | 6.3 | 0 | 0.0 | 0 | 0.02 | 1 | 4.5 | |
G | 127 | 87.0 | 29 | 80.6 | 27 | 84.4 | 120 | 87.0 | 29 | 96.7 | 37 | 84.1 | |
A | 19 | 13.0 | 7 | 19.4 | 5 | 15.6 | 18 | 13.0 | 1 | 3.3 | 7 | 15.9 | |
F13 | GG | 43 | 58.93 | 9 | 50.0 | 9 | 56.3 | 31 | 44.9 | 7 | 46.73 | 10 | 45.5 |
GT | 28 | 38.43 | 7 | 38.9 | 5 | 31.3 | 32 | 46.4 | 5 | 33.33 | 11 | 50.,0 | |
TT | 2 | 2.73 | 2 | 11.1 | 2 | 12.5 | 6 | 8.7 | 3 | 20.03 | 1 | 4.5 | |
G | 114 | 78.1 | 25 | 69.4 | 23 | 71.9 | 94 | 68.1 | 19 | 63.3 | 31 | 70.5 | |
T | 32 | 21.9 | 11 | 30.6 | 9 | 28.1 | 44 | 31.9 | 11 | 36.7 | 13 | 29.5 | |
FGB | (-455) GG | 44 | 60.3 | 13 | 72.25.7 | 12 | 75.04.6 | 31 | 44.94.5 | 7 | 46.7 | 10 | 45.56.7 |
(-455) GA | 26 | 35.6 | 5 | 27.85.7 | 4 | 25.04.6 | 35 | 50.74.5 | 8 | 53.3 | 8 | 36.46.7 | |
(-455) AA | 3 | 4.1 | 0 | 0.05.7 | 0 | 0.04.6 | 3 | 4.34.5 | 0 | 0.0 | 4 | 18.26.7 | |
G | 114 | 78.1 | 31 | 86.17 | 28 | 87.56 | 97 | 70.3 | 22 | 73.3 | 28 | 63.66.7 | |
A | 32 | 21.9 | 5 | 13,97 | 4 | 12.56 | 41 | 29.7 | 8 | 26.7 | 16 | 36.46.7 | |
ITGA2 | CC | 23 | 31.5 | 6 | 33.3 | 4 | 25.0 | 25 | 36.2 | 3 | 20.0 | 5 | 22.7 |
CT | 39 | 53.4 | 9 | 50.0 | 9 | 56.3 | 36 | 52.2 | 11 | 73.3 | 13 | 59.1 | |
TT | 11 | 15.1 | 3 | 16.7 | 3 | 18.8 | 8 | 11.6 | 1 | 6.7 | 4 | 18.2 | |
C | 85 | 58.2 | 21 | 58.3 | 17 | 53.1 | 86 | 62.3 | 17 | 56.7 | 23 | 52.3 | |
T | 61 | 41.8 | 15 | 41.7 | 15 | 46.9 | 52 | 37.7 | 13 | 43.3 | 21 | 47.7 | |
ITGB3 | 1565 TT | 48 | 65.8 | 14 | 77.8 | 13 | 81.3 | 48 | 69.6 | 12 | 80.0 | 17 | 77.3 |
1565 TC | 24 | 32.9 | 4 | 22.2 | 2 | 12.5 | 18 | 26.1 | 3 | 20.0 | 5 | 22.7 | |
1565 CC | 1 | 1.4 | 0 | 0.0 | 1 | 6.3 | 3 | 4.3 | 0 | 0.0 | 0 | 0.0 | |
T | 120 | 82.2 | 32 | 88.9 | 28 | 87.5 | 114 | 82.6 | 27 | 90.0 | 39 | 88.6 | |
C | 26 | 17.8 | 4 | 11.1 | 4 | 12.5 | 24 | 17.4 | 3 | 10.0 | 5 | 11.4 | |
PAI-1 | (-675)5G5G | 14 | 19.2 | 4 | 22.2 | 3 | 18.8 | 11 | 15.9 | 3 | 20.0 | 6 | 27.3 |
(-675)5G4G | 37 | 50.7 | 9 | 50.0 | 6 | 37.5 | 40 | 58.0 | 4 | 26.7 | 7 | 31.8 | |
(-675)4G4G | 22 | 30.1 | 5 | 27.8 | 7 | 43.8 | 18 | 26.1 | 8 | 53.3 | 9 | 40.9 | |
5G | 65 | 44.5 | 17 | 47.2 | 12 | 37.5 | 62 | 44.9 | 10 | 33.3 | 19 | 43.2 | |
4G | 81 | 55.5 | 19 | 52.8 | 20 | 62.5 | 76 | 55.1 | 20 | 66.7 | 25 | 56.8 | |
Notes: statistically significant differences at p<0.05 between groups: 1 – LC and TGIT (p=0.03, χ2=4.85); 2 – LC and lymphomas (p=0.03, χ2=4.63); 3 – BC and lymphomas (p=0.03, χ2=6.94); 4 – TFRS and TGIT (p=0.03, χ2=4.81); 5 – LC and TGIT (p=0.03, χ2=4.49); 6 – TFRS and others (p=0.02, χ2=5.44; for A allele OR=0.25, 95% CI: 0.07-0.84); 7 – LC and others (p=0.02, χ2=5.17; for A allele OR=0.28, 95% CI: 0.09-0.87)
Table 4
Most Frequent Genetic Profiles of Hemostatic System in Oncological Patients
Genes/Polymorphism | F2: 20210 G>A | F5: 1691 G>A | F7: 10976 G>A | F13: G>T | FGB: -455 G>A | ITGA2: 807 C>T | ITGB3: 1565 T>C | PAI-1: -675 5G>4G | Number of Patients with the Given Profile |
Genetic Profile | GG | GG | GG | GT | GG | CT | TT | 4G4G | 8 |
GG | GG | GG | GT | GG | CT | TT | 5G4G | 6 | |
GG | GG | GG | GT | GA | CC | TT | 4G4G | 5 | |
GG | GG | GG | GG | GG | CT | TT | 4G4G | 5 | |
GG | GG | GG | GG | GG | TT | TT | 4G4G | 5 | |
GG | GG | GG | GG | GG | CT | TC | 5G4G | 5 | |
GG | GG | GG | GG | GA | CT | TT | 4G4G | 4 | |
GG | GG | GG | GT | GA | CT | TT | 5G4G | 4 | |
GG | GG | GG | GG | GG | CT | TT | 5G4G | 4 | |
GG | GG | GG | GG | GG | CT | TT | 5G5G | 4 |
Note: mutant alleles are accentuated semi-bold
Most of them (81) were unique and occurred only once, 15 profiles repeated in two patients, 16 in three ones. Ten genetic profiles occurring more often than others are presented in Table 4. However, even among frequently occurring genetic profiles no predomination of any one was found characteristic of a specific nosological form.
In view of the variety of gene-gene combinations it seemed interesting to us to analyze distribution of frequencies of the identified variants in components of hemostatic system (Table 5). Alternative alleles only in genes of plasmic component of hemostasis were found in eight patients (3.8%), including four genes (1.9%) possessing procoagulant ((F2 (G20210А), F5 (G1691A), FGB G(-455)A)), three genes (1.4%) possessing anticoagulant potential ((F7 (G10976A), F13 (G226A)) and one gene (0.5%) possessing opposite action (pro- and anticoagulant).
Alternative alleles in genes of only vasculo-platelet component ((ITGA2-α2 (C807T) and ITGB3-b (Т1565С)) were found in seven patients (3.3%), only of fibrinolytic component ((PAI-1 4G(-675)5G)) – in five patients (2.3%). That is, alternative alleles were rarely encountered only in one component of hemostatic system. In 108 patients (50.7% of the total number of patients) alternative alleles were identified in different combinations in genes simultaneously involved in all components of hemostatic system (plasmic, platelet, fibrinolytic), and in 82 patients (38.5%) in genes involved in two components (Table 5).
Despite antithrombotic prophylaxis conducted according to recommendations of RUSSCO, 18 patients (8.5%) in the course of antineoplastic treatment, developed complications in the form of DVT – 13 (6.1%), TEPA – 2 (0.9%), acute cerebrovascular events – 2 (0.9%), myocardial infarction – 1 (0.47%). The genetic profile of the patients with thrombotic complications was also very diverse: not a single repeated profile was found. In F2 (G20210А) polymorphic locus only reference alleles were found, in F5 (G1691A) locus alternative allele was identified in three patients (16.7% of patients with VTEC), F7 (G10976A) – in six (33.3%), F13 (G226A – in nine (50.0%), FGB G(-455)A – in 8 (44.4%), ITGA2-α2 (C807T) – in 14 (77.8%), ITGB3-b (Т1565С) – in 2 (11.11%), PAI-1 4G(-675)5 – in 14 patients (77.8%).
Table 5
Distribution of SNR Detection Frequency in Components of Hemostatic System in Oncological Patients
№ п/п | Variants of SNR Combinations Determined in Components of Hemostatic System | n=213 | |
abs | % | ||
1 | No SNP | 3 | 1.4 |
2 | SNP in genes of plasmic component (procoagulant) | 4 | 1.9 |
3 | SNP in genes of plasmic component (anticoagulant) | 3 | 1.4 |
4 | SNP in genes of plasmic component (pro- and anticoagulant) | 1 | 0.5 |
5 | SNP in genes of plasmic (pro- and anticoagulant) and platelet components | 9 | 4.2 |
6 | SNP in genes of plasmic (pro- and anticoagulant) and fibrinolytic components | 17 | 8.0 |
7 | SNP in genes of plasmic (pro- and anticoagulant), platelet and fibrinolytic components | 41 | 19.2 |
8 | SNP in genes of plasmic (procoagulant), and platelet components | 3 | 1.4 |
9 | SNR in genes of plasmic (procoagulant) and fibrinolytic components | 4 | 1.9 |
10 | SNP in genes of plasmic (procoagulant), platelet and fibrinolytic components | 29 | 13.6 |
11 | SNP in genes of plasmic (anticoagulant) and platelet components | 10 | 4.7 |
12 | SNR in genes of plasmic (anticoagulant) and fibrinolytic components | 12 | 5.6 |
13 | SNP in genes of plasmic (anticoagulant), platelet and fibrinolytic components | 38 | 17.8 |
14 | SNP in genes of platelet component | 7 | 3.3 |
15 | SNP in genes of fibrinolytic component | 5 | 2.3 |
16 | SNP in genes of platelet and fibrinolytic components | 27 | 12.7 |
The analysis of frequency of ‘risk alleles’ in genes of hemostatic system in oncological patients with and without thrombotic complications developed in the course of antineoplastic treatment, no statistically significant differences were found (Table 6).
Table 6
Frequency of Minor Alleles in Genes of Hemostatic System in Oncological Patients with and without Thrombotic Complications
SNP | Frequency in Patients with Thrombotic Complications | Frequency in Patients without Thrombotic Complications | p |
F2 G20210А | A=0.0 (0/36) | A=0.017 (7/390) | 0.4176 |
F5 G1691A | A=0.083 (3/36) | A=0.031 (12/390) | 0.1245 |
F7 G10976A | A=0.167 (6/36) | A=0.131 (51/390) | 0.3465 |
F13 G226A | A=0.306 (11/36) | A=0.279 (109/390) | 0.4356 |
FGB G(-455)A | A=0.250 (9/36) | A=0.249 (97/390) | 0.5621 |
ITGA2 C807T | T=0.444 (16/36) | T=0.413 (161/390) | 0.4210 |
ITGB3-b Т1565С | C=0.056 (2/36) | C=0.164 (64/390) | 0.0591 |
PAI-1 4G(-675)5G | C=0.472 (17/36) | C=0.574 (224/390) | 0.1569 |
Proceeding to discussion of the obtained results, it is first of all necessary to note that attempts to stratify the risk of appearance of VTEC in patients with cancer were undertaken in several studies. J.W. Blom, et al. showed in their work that patients with hematological malignant neoplasms with correction to age were under the highest risk of venous thrombosis, followed by patients with cancer of lungs and of GIT [15]. According to F. Horsted, et al., the highest risk for VTEC was associated with tumors of the brain and pancreatic cancer [9], and to the estimates of M. Li, et al. – with tumors of bones, soft tissues (10.6%) and with LC (8.1%) [10]. According to the data of our clinics, the highest risk for thrombotic complications was associated with malignant tumors of the GIT and with cervical cancer [18]. No gender differences were found by us in distribution of the frequency of genotype and alleles of blood coagulation factors in oncological patients which differs from the studies conducted in Barnaul where it was found that the frequency of carriage of mutant A allele in F2 (G20210А) polymorphic locus was statistically significantly higher in girls, and of 4G allele in PAI-1 4G(-675)5 locus – in boys [19].
In our study a statistically significant increase in frequency of ‘risk alleles’ in the group of oncological patients was found in polymorphic sites F5 G1691A (А=0.035, р=0.0169), F13 G226A (А=0.282, р=0.0007), FGB G(-455)A (А=0.249, р<0.0001) and ITGA2-α2 C807T (Т=0.415, р=0.0201). As compared to the world population. The presence of hereditary thrombophilia in a patient does not suggest basal chronic hyper-coagulation, but determines the exaggerated response of the hemostatic system to traditional provoking influences in the form of excessively high or prolonged regeneration of active thrombin which may lead to faster initiation and spread of thrombotic process [20]. Such provoking actions in oncological patients include both surgical support, chemo- and radiological treatment, and the disease itself. We did not find any statistically significant differences in the incidence of ‘risk alleles’ in genes of hemostatic system in patients with thrombotic complications developed in the course of antineoplastic therapy, and in those without them. It can be suggested that the rate of development of VTEC is to a larger extent determined by the character of the neoplastic process and by the conducted chemotherapy, and not by genetic factors. At the same time, in our study, in comparison of frequencies of genotypes and alleles between the groups only isolated SNR were analyzed. Taking into account the facts of recording of combinations of several ‘risk alleles’ in different polymorphic sites of genes of hemostatic system in 92.0% of patients, the variety of gene-gene combinations in the studied sample, and also the data of potentiation of the thrombogenic effect in case of carriage of several procoagulant mutations [21], we consider it necessary to study the influence of combined SNR on development of thrombotic complications in oncological patients in the large sample.
A high frequency of ‘risk alleles’ not only in plasmic, but also in vasculo-platelet component of hemostatic system shows the necessity to add antiaggregants to prophylactic anticoagulant therapy in the period of treatment of the main disease (chemoradiotherapy, postoperative period), if there are no contraindications to their administration. However, this point also requires additional investigations.
Conclusion
The results of study demonstrated statistically significant exceedance of the frequency of ‘risk alleles’ of polymorphic loci F5 G1691A (А=0.035, р=0.0169), F13 G226A (А=0.282, р=0.0007), FGB G(-455)A (А=0.249, р<0.0001) and ITGA2-α2 C807T (Т=0.415, р=0.0201) in the group of oncological patients as compared to the world population. In the same polymorphic loci except ITGA2-α2 (C807T), statistically significant differences in the frequency of alternative alleles in different localizations of an oncological process were found. In 92.0% of patients a combination of SNR in different components of hemostatic system was determined that requiresunderlying studying reasonability of use of antiaggregant therapy along with anticoagulant therapy.
About the authors
Tatiana A. Zykova
Rostov Research Institute of Oncology
Author for correspondence.
Email: tatiana2904@yandex.ru
ORCID iD: 0000-0001-5345-4872
SPIN-code: 7054-0803
Scopus Author ID: 57200075494
ResearcherId: U-3559-2019
MD, PhD, Head of the Laboratory of Virology
Russian Federation, Rostov- on-DonLyubov Yu. Vladimirova
Rostov Research Institute of Oncology
Email: rnioi@list.ru
ORCID iD: 0000-0003-4236-6476
SPIN-code: 4857-6202
ResearcherId: U-8132-2019
MD, PhD, Professor, Head of the Department of Anticancer Drug Therapy №1
Russian Federation, Rostov-on-DonOksana V. Katelnitskaya
Rostov Research Institute of Oncology
Email: Katelnitskayaov@rnioi.ru
MD, PhD, Cardiovascular Surgeon of the Department of Abdominal Oncology № 2
Russian Federation, Rostov-on-DonAndrey A. Maslov
Rostov Research Institute of Oncology
Email: Maslovaa@rnioi.ru
ORCID iD: 0000-0003-4902-5789
SPIN-code: 5963-5915
ResearcherId: W-5180-2019
MD, PhD, Professor, Honored Doctor of the Russian Federation, Chief Physician, Head of the Department of Abdominal Oncology №3
Russian Federation, Rostov-on-DonElena A. Shevyakova
Rostov Research Institute of Oncology
Email: Shevyakovaea@rnioi.ru
ORCID iD: 0000-0002-4232-6733
SPIN-code: 9595-7616
ResearcherId: U-3551-2019
Biologist of Laboratory Virology
Russian Federation, Rostov-on-DonIrina B. Lysenko
Rostov Research Institute of Oncology
Email: Lysenkoib@rnioi.ru
ORCID iD: 0000-0003-4457-3815
SPIN-code: 9510-3504
MD, PhD, Head of the Department of Oncohematology
Russian Federation, Rostov-on-DonNatalia A. Abramova
Rostov Research Institute of Oncology
Email: Abramovana@rnioi.ru
ORCID iD: 0000-0001-7793-9794
SPIN-code: 1784-8819
ResearcherId: U-6181-2019
MD, PhD, Oncologist of Department of Anticancer Drug Therapy №1
Russian Federation, Rostov-on-DonAnna E. Storozhakova
Rostov Research Institute of Oncology
Email: Storozhakovaae@rnioi.ru
MD, PhD, Head of the Department of Anticancer Drug Therapy №2
Russian Federation, Rostov-on-DonIrina L. Popova
Rostov Research Institute of Oncology
Email: Popovail@rnioi.ru
ORCID iD: 0000-0003-4865-8832
SPIN-code: 4542-1937
ResearcherId: U-6397-2019
MD, PhD, Oncologist of the Department of Anticancer Drug Therapy №1
Russian Federation, Rostov-on-DonKristina A. Novoselova
Rostov Research Institute of Oncology
Email: Novoselovaka@rnioi.ru
ORCID iD: 0000-0002-7059-9026
SPIN-code: 3492-1620
ResearcherId: V-1130-2017
MD, PhD, Oncologist of the Department of Anticancer Drug Therapy №1
Russian Federation, Rostov-on-DonNatalya M. Tikhanovskaya
Rostov Research Institute of Oncology
Email: Tikhanovskayanm@rnioi.ru
ORCID iD: 0000-0001-5139-2639
SPIN-code: 9000-4877
ResearcherId: U-8128-2019
Oncologist of the Department of Anticancer Drug Therapy №1
Russian Federation, Rostov-on-DonAza A. Lyanova
Rostov Research Institute of Oncology
Email: Lyanovaaa@rnioi.ru
Oncologist of the Department of Anticancer Drug Therapy №1
Russian Federation, Rostov-on-DonLyudmila A. Ryadinskaya
Rostov Research Institute of Oncology
Email: Ryadinskayala@rnioi.ru
ORCID iD: 0000-0002-5964-2513
SPIN-code: 6146-2396
ResearcherId: U-6199-2019
MD, PhD, Oncologist of the Department of Anticancer Drug Therapy №1
Russian Federation, Rostov-on-DonAnna V. Tishina
Rostov Research Institute of Oncology
Email: Tishinaav@rnioi.ru
ORCID iD: 0000-0002-7990-8710
SPIN-code: 7686-3707
ResearcherId: H-2460-2018
Oncologist of the Department of Anticancer Drug Therapy №2
Russian Federation, Rostov-on-DonIrina S. Tishchenko
Rostov Research Institute of Oncology
Email: Tishchenkois@rnioi.ru
ORCID iD: 0000-0002-4990-0881
SPIN-code: 7705-2954
ResearcherId: W-5183-2019
Surgeon of the Department of Thoracic Surgery
Russian Federation, Rostov-on-DonSergey N. Kabanov
Rostov Research Institute of Oncology
Email: Kabanovsn@rnioi.ru
MD, PhD, Oncologist of the Department of Anticancer Drug Therapy №2
Russian Federation, Rostov-on-DonElena A. Kalabanova
Rostov Research Institute of Oncology
Email: Kalabanovaea@rnioi.ru
ORCID iD: 0000-0003-0158-3757
SPIN-code: 9090-3007
ResearcherId: V-2943-2019
MD, PhD, Oncologist of the Department of Anticancer Drug Therapy №2
Russian Federation, Rostov-on-DonReferences
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