Abstract
Ovarian cancer is a highly lethal cancer in females. Therefore, it is necessary to explore effective biomarkers for the diagnosis and prognosis of the disease. Stratifin (SFN) is a cell cycle checkpoint protein that has been reported to be involved in oncogenesis. Our studies detected the expression of SFN in ovarian cancer by Oncomine, Human Protein Atlas database and ULCAN database. Meanwhile, we found its coexpression gene by cBioPortal online tool and validated their expression in different ovarian cancer cells by western blot and reverse transcription quantitative PCR. Then, we also investigated their prognostic values via the Kaplan–Meier plotter database in different subtypes of ovarian cancer patients. The results demonstrated that SFN was found to be increased in ten various ovarian cancer datasets, compared with healthy tissues. Additionally, up-regulation of SFN expression is associated with age and cancer grades. The higher expression of SFN in all patients with ovarian cancers is significantly correlated with worse postprogression survival. In addition, high SFN expression is associated with significantly worse overall survival in patients who received chemotherapy contains gemcitabine, taxol, taxol+platin, paclitaxel and avastin. In human ovarian carcinoma SKOV3 and A2780 cells, the expression of SFN and its coexpression gene MICB were also increased at protein and mRNA levels compared with the normal ovarian epithelial cells. Based on above results, overexpression of SFN was correlated with the prognosis in ovarian cancer. The present study might be useful for better understanding the clinical significance of SFN mRNA.
Highlights
Ovarian cancer, a highly aggressive and lethal cancer, is in seventh place amongst all cancers in women worldwide in terms of occurrence [1]
Using UALCAN database, we analyzed the expression profiles of SFN in normal and ovarian serous cystadenocarcinoma samples based on clinicopathologic parameters, such as cancer stage, age, race, and tumor grade
SFN was found to be increased in ten various ovarian cancer datasets, compared with healthy tissues (P value < 0.01 and fold change > 1.5) including ovarian mucinous adenocarcinoma [12,13], ovarian clear cell adenocarcinoma [12], ovarian carcinoma [14], ovarian serous adenocarcinoma [12,13,15,16], ovarian serous cystadenocarcinoma, and ovarian endometrioid adenocarcinoma [12]
Summary
A highly aggressive and lethal cancer, is in seventh place amongst all cancers in women worldwide in terms of occurrence [1]. Some statistical data displayed that up to 225,000 women were diagnosed with ovarian cancer and approximately 150,000 people die of this disease every year [2,3]. The development of the early diagnosis and treatment in ovarian cancer has been accomplished in recent decades, this disease is still a severe global burden and attracts more attention from the public. Diagnosis of biomarkers and more accurate prognosis can optimize the efficiency of current ovarian cancer therapy and provide potential molecular markers for targetted treatment. It is necessary that screening and identification of high efficiency molecular biomarkers regarding on ovarian cancer. SFN has been reported to be a novel biomarker in various cancers. Combined with OCIAD2, immunocytochemical staining for SFN could enhance diagnostic sensitivity for lung cancers [8]. It is determined that the License 4.0 (CC BY)
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