Abstract
Approximately 95% of all testicular cancers are testicular germ cell tumors (GCTTs), represented by seminoma and nonseminoma germ cell testicular cancer. There is a hypothesis that the formation of GCTTs begins in early embryogenesis being a part of testicular dysgenesis syndrome (TDS). To determine the role of genetic factors in the development of GCTTs. We studied the frequency of alleles and genotypes KITLG (rs995030, rs1508595), SPRY4 (rs4624820, rs6897876) and BAK1 (rs210138) in 97 fertile men (control), and 73 patients with GCTTs (34 seminoma and 39 nonseminoma). GCTTs were statistically significantly associated with KITLG rs1508595 gene (p=0.0003 for allele G, p=0.0014 for genotype GG), and with rs995030 gene (p=0.0031 for genotype GG). When comparing patients with seminoma and control group, statistically significant differences were found for SPRY4 rs4624820 (p=0.0226 for the A and p=0.04 for the AA), for KITLG rs995030 (p=0.0375 for the G and p=0.0282 for GG), rs1508595 (p=0.0306 for G), for BAK1 rs210138 (p=0.0329 for the G and p=0.0219 for the GG). When comparing patients with nonseminoma and fertile men, statistically significant differences were found only for KITLG rs1508595 (p=0.0005 for the G and p=0.0021 for the GG). There was no statistically significant difference between the allele and genotype frequencies of the investigated genes from seminoma and nonseminoma GCTTs patients. However, these groups differed statistically significantly when genotype combinations of the three genes were investigated (p=0,029; OR 3,709 [1.147-11.99]). The combination of genotypes of the three genes was found to increase the risk of GCTTs by 6.5 times (p=0.0005; OR 6.526 [2.078-20.5], and the risk for seminoma was over 12-fold (p<0.0001; OR 12,68 [3,731-43,11]. A comprehensive study of genotypes associated with GCTTs in patients with manifested TDS can be used for risk stratification to identify and follow-up high-risk patients, develop approaches to family counseling and treatment, which is the basis for predictive medicine.
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