Expression levels of genes involved in cell adhesion and motility correlate with poor clinicopathological features of epithelial ovarian cancer

J BUON. 2020 Jul-Aug;25(4):1911-1917.

Abstract

Purpose: Changes in the expression levels of genes involved in cancer cell adhesion and motility have been reported to have an important role in tumor progression. In this study, we aimed to investigate the clinical significance of ITGAV and CALD1 gene expression in epithelial ovarian cancer (EOC), the most lethal gynecological malignancy.

Methods: Reverse transcription quantitative polymerase chain reaction was used to evaluate ITGAV and CALD1 expression levels in 47 EOC and 19 benign formalin-fixed paraffin-embedded samples. We used Spearman's test to determine the association between ITGAV and CALD1 expression and Wilcoxon test to compare expression levels between malignant and benign ovarian tumor specimens as well as to determine their association with clinicopathological characteristics of EOC. Survival analysis was done by the Kaplan-Meier method and the log-rank test. P ≤ 0.05 was considered statistically significant.

Results: CALD1 and ITGAV showed significantly lower expression in EOC than in benign ovarian samples (p<0.001). Furthermore, CALD1 was significantly lower expressed in high-grade tumors (p=0.037) while there was a trend for a lower expression of ITGAV in tumors with high histological grade (p=0.043), in tumors with ascites (p=0.055), and in tumors of patients who relapsed (p=0.083). We also found a significant positive association between ITGAV and CALD1 expression (ρ=0.640, p<0.001) in EOC samples. Kaplan-Meier analysis showed no significant impact of ITGAV and CALD1 expression levels on overall survival of EOC patients (p=0.149 and p=0.430, respectively).

Conclusion: Our findings indicate that CALD1 and ITGAV gene expression levels correlate with poor clinicopathological features of the EOC.

MeSH terms

  • Cell Adhesion / genetics*
  • Cell Movement / genetics*
  • Female
  • Humans
  • Middle Aged
  • Ovarian Neoplasms / genetics*
  • Survival Analysis