2.4. Statistical Analysis

Statistical analysis of the results that were obtained by genetic and protein analyses was done in the software package SPSS v.19.0.1 (SPSS, Chicago, IL, USA), with a selected significance level of p ≤ 0.05. All of the variables obtained by genetic and protein analyzes were correlated with variables of collected pathohistological and demographic (sex, age) parameters. Before selecting appropriate statistical tests, the distribution of normality of the included variables was obtained with the Kolmogorov–Smirnov test. When testing the significance of the difference between the two groups, the t-test for independent samples was used (or Mann–Whitney U test as its nonparametric replacement), when testing the significance of the difference between more than two groups, one-way analysis of variance (ANOVA) was used (or Kruskal–Wallis test as nonparametric replacement). To test the correlation in the distributions of two or more variables, the χ² test and the corresponding correlation coefficients (Φ coefficient in the case of 2 × 2 tables or Cramer’s V coefficient in the case of asymmetric tables) were used. The Pearson r correlation coefficient was used to test the correlation between two continuous variables or one continuous and one naturally dichotomous variable.