Differential Expression Pattern of Epithelial Mesenchymal Transition Gens: AXL, GAS6, Claudin-1, and Cofilin-1, in Different Stages of Epithelial Ovarian Cancer

Autor: Reza Shirkoohi, Elham Hassani, Sima Mansoori Derakhshan, Amirnader Emami Razavi, Mojtaba Saffari, Mahmood Shekari Khaniani
Jazyk: angličtina
Rok vydání: 2019
Předmět:
Zdroj: Iranian Journal of Public Health, Vol 48, Iss 9 (2019)
Scopus-Elsevier
Iranian Journal of Public Health
Europe PubMed Central
ISSN: 2251-6093
2251-6085
Popis: Background: Epithelial ovarian cancer (EOC), is the fatal form of gynecological cancer. Almost 70% of ovarian cancer patients are detected at an advanced stage (III-IV) with metastases. Epithelial‑mesenchymal transition (EMT) is a critical process associated with metastasis. This study investigated the expression levels of AXL, GAS6, Claudin-1, and Cofilin-1, as genes involved in EMT in relation to clinicopathologic features in ovarian cancer patients. Methods: In this descriptive study, 78 ovarian epithelial cancer patients were enrolled. Samples were provided by the Iran National Tumor Bank, founded by the Cancer Institute of Tehran University of Medical Sciences in 2017. The expression levels of AXL, GAS6, Claudin-1, and Cofilin-1 genes were investigated in a fresh, frozen tumor sample and normal adjacent tissue by real-time PCR (RT-PCR). Results: Findings showed a significant relationship between the overexpression of AXL and TNM staging (P=0.03). The expression level of GAS6 decreased in more advanced stages (P=0.01). There is a negative relationship between Cofilin-1 expression level and TNM staging (P=0.002). Claudin-1 expression level was higher in low stages compared with that in high stages (P=0.01). There was no relationship between gene expression levels of target genes with size and grade of the tumor. Conclusion: Given the importance of these genes in EMT, alteration in their expression pattern can contribute to the progression of the disease and distant metastasis of cancer cells. Additionally, knowing the alteration pattern of these genes expression can help to better understanding and prediction of the prognosis of EOC.
Databáze: OpenAIRE