Abstract

Thymic stromal lymphopoietin (TSLP) is an IL-7-like cytokine that has been reported to be associated with several malignant tumors. The present study aimed to evaluate its role in epithelial ovarian carcinoma (EOC). The mRNA levels of TSLP in human EOC samples and EOC cell lines were determined. Then, the expression of TSLP was examined in 144 clinical tissue microarray samples and correlated with clinicopathological factors. Finally, the correlation between TSLP overexpression and prognosis of EOC patients was analyzed. Our data show that mRNA levels of TSLP were significantly higher in EOC tissues and cell lines. Chi-square tests revealed that TSLP overexpression in EOC was significantly associated with age, histological type, Federation of Gynecology and Obstetrics (FIGO) stage, histological differentiation, pelvic involvement, and lymphatic metastasis. Kaplan–Meier survival analysis revealed that poor prognosis was significantly correlated with older age, advanced FIGO stage, poor histological differentiation, pelvic involvement, lymphatic involvement, or TSLP overexpression (P<0.05). Additionally, multivariate Cox regression analysis confirmed pelvic involvement and TSLP overexpression as independent prognostic factors for both overall and disease-free survival. Taken altogether, TSLP overexpression reflects a more malignant phenotype and TSLP may be a novel biomarker for EOC.

Highlights

  • Ovarian carcinoma is common amongst women and is one of the most lethal carcinomas of the genital system

  • Evaluation of Thymic stromal lymphopoietin (TSLP) mRNA levels in Epithelial ovarian cancers (EOC) tissue samples and EOC cell lines Compared with adjacent normal tissues, TSLP mRNA levels determined by real-time PCR were significantly higher in human ovarian cancer tissues (n=27), (P

  • Significantly elevated mRNA levels of TSLP were detected in widely recognized EOC cell lines SKOV3 and HO8910, in comparison with ovarian epithelial cell line IOSE386 (Figure 1B)

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Summary

Introduction

Ovarian carcinoma is common amongst women and is one of the most lethal carcinomas of the genital system. 22,440 new cases of ovarian cancer are reported each year in the U.S.A., and this disease was expected to cause over 14,070 deaths in 2018 [1]. Approximately 52,100 new cases of ovarian cancer and 22,500 associated deaths are reported each year in China [2]. Since more than two-thirds of ovarian cancer cases are diagnosed at advanced stages (stage III–IV), a high mortality rate for this disease is observed [3]. Since only a few early-stage ovarian carcinomas can be diagnosed, it is difficult to predict the disease progression using standard clinical or pathological prognostic factors, such as grade, stage, or expressions of CA125/MUC16. To the development of novel molecular biomarkers to improve the diagnosis and prognosis prediction for ovarian carcinoma is urgently required

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