Jun Zheng1, Xueqing Li1, Chunyan Zhang2, Yiqiang Zhang1. 1. Department of Biochemistry, Changzhi Medical College, Changzhi, Shanxi, China. 2. Department of Gynaecology and Obstetrics, Heping Hospital Affiliated to Changzhi Medical College, Changzhi, Shanxi, China.
Abstract
AIM: Ovarian cancer is a common malignant tumor of the gynecological oncology worldwide, with a high incidence and mortality rate and poor prognosis. Searching for new diagnostic molecular biomarkers for ovarian cancer is extremely significant. METHODS: Here, we analyzed the expression rates of eIF4E and cyclin D1 proteins in 123 cases of cancer tissue samples and 38 cases of paracancerous tissue samples and studied the connection between the expression rates of eIF4E and cyclin D1 proteins by immunohistochemistry and statistically correlated with clinicopathological features in ovarian cancer. RESULTS: The results showed that the expression rates of eIF4E and cyclin D1 proteins in ovarian cancer tissues were significantly higher than those in noncancerous epithelial ovarian tissues (P = 0.001 and P = 0.032, respectively). Additionally, the results revealed that a higher expression rate of eIF4E (P = 0.008) was found in the advanced stage (stage III/IV), and also patients with cervical lymph node metastasis displayed higher expression of eIF4E (P < 0.001) and cyclin D1 (P = 0.033) than those without lymph node metastasis. Spearman's rank correlation test showed that there was a significant positive correlation between the eIF4E and cyclin D1 proteins in ovarian cancer. The Kaplan-Meier method showed that patients with lower expression of eIF4E had marginally better survival than those with high expression of eIF4E (P = 0.012). Multivariate Cox regression analysis further identified that positive expression of eIF4E was an independent prognostic factor. CONCLUSION: In ovarian cancer, eIF4E might be a valuable biomarker to predict poor prognoses and a potential therapeutic target to develop valid treatment strategies.
AIM: Ovarian cancer is a common malignant tumor of the gynecological oncology worldwide, with a high incidence and mortality rate and poor prognosis. Searching for new diagnostic molecular biomarkers for ovarian cancer is extremely significant. METHODS: Here, we analyzed the expression rates of eIF4E and cyclin D1 proteins in 123 cases of cancer tissue samples and 38 cases of paracancerous tissue samples and studied the connection between the expression rates of eIF4E and cyclin D1 proteins by immunohistochemistry and statistically correlated with clinicopathological features in ovarian cancer. RESULTS: The results showed that the expression rates of eIF4E and cyclin D1 proteins in ovarian cancer tissues were significantly higher than those in noncancerous epithelial ovarian tissues (P = 0.001 and P = 0.032, respectively). Additionally, the results revealed that a higher expression rate of eIF4E (P = 0.008) was found in the advanced stage (stage III/IV), and also patients with cervical lymph node metastasis displayed higher expression of eIF4E (P < 0.001) and cyclin D1 (P = 0.033) than those without lymph node metastasis. Spearman's rank correlation test showed that there was a significant positive correlation between the eIF4E and cyclin D1 proteins in ovarian cancer. The Kaplan-Meier method showed that patients with lower expression of eIF4E had marginally better survival than those with high expression of eIF4E (P = 0.012). Multivariate Cox regression analysis further identified that positive expression of eIF4E was an independent prognostic factor. CONCLUSION: In ovarian cancer, eIF4E might be a valuable biomarker to predict poor prognoses and a potential therapeutic target to develop valid treatment strategies.
Authors: Terence P Farias; Fernando L Dias; Roberto A Lima; Jacob Kligerman; Geraldo M de Sá; Mauro M Barbosa; Fernando B Gonçalves Journal: Arch Otolaryngol Head Neck Surg Date: 2003-07
Authors: Blake A Jacobson; Saritha C Thumma; Joseph Jay-Dixon; Manish R Patel; K Dubear Kroening; Marian G Kratzke; Ryan G Etchison; Bruce W Konicek; Jeremy R Graff; Robert A Kratzke Journal: PLoS One Date: 2013-11-18 Impact factor: 3.240