Identification of KIF23 as a prognostic signature for ovarian cancer based on large scale samples and clinical validation

Abstract

Background: Ovarian cancer is one of the common malignant tumors in gynecology. Although the treatment strategy for ovarian cancer has been greatly improved in recent years, due to the metastasis, recurrence and drug resistance, the 5-year overall survival rate of patients is still less than 47%. However, at present, there is no specific markers for clinical application. The purpose of this study is to verify the expression and clinical significance of KIF23 in ovarian cancer and identify potential targets for the clinical treatment of ovarian cancer. Methods: The expression of KIF23 in ovarian cancer tissues and its relationship between survival prognosis and clinical pathological parameters were analyzed in Oncomine, GEO, and TCGA databases. KIF23 expression was analyzed by Kaplan-Meier plotter database and its relationship with chemo-resistance was studied. The molecular mechanism involved in KIF23 was analyzed from the perspective of gene mutation, copy number variation and other genomics. Finally, immunohistochemistry experiment was used to verify the expression of KIF2, and its relationship between the clinical pathological parameters and prognosis of ovarian cancer patients was analyzed by single factor and multivariate Cox regression models. Results: Bioinformatic and experimental results have demonstrated that KIF23 is highly expressed in ovarian cancer, and its high expression is positively correlated with poor prognosis. Overexpression of KIF23 can cause chemotherapy resistance in ovarian cancer and affect the overall survival of patients. Genomics analysis showed that KIF23 expression was associated with mutations such as FLG2 and TTN, and it was significantly enriched in tumor signaling pathways such as DNA replication and cell cycle. Conclusions: KIF23 can not only be used as a biomarker of poor prognosis in patients with various stages of ovarian cancer, but also be used as a molecular targeted drug and an independent prognostic biomarker for the treatment of ovarian cancer patients.

Identification of potential markers for differentiating epithelial ovarian cancer from ovarian low malignant potential tumors through integrated bioinformatics analysis

“…Meanwhile, they also found that both miR-503-5p and miR-424-5p could directly targeted KIF23 to inhibit OC development in vitro [ 69 ]. Additionally, Hu Y et al has reported that KIF23 could not only be used as a prognostic indicator for EOC, but also had a positive correlation with immune checkpoint protein, suggesting that it can be performed as a potential target for cancer immunotherapy, which is consistent with the results of our study [ 70 ].…”

Mutation and Copy Number Alterations Analysis of KIF23 in Glioma

“…It seems that elevated of KIF23 expression is a common event in various human cancers. KIF23 was reported to be overexpressed in pancreatic ductal adenocarcinoma ( Gao et al, 2020 ), malignant pleural mesothelioma ( Kato et al, 2016a ), lung cancer ( Kato et al, 2016b ; Ye et al, 2017 ), breast cancer ( Zou et al, 2014 ), hepatocellular carcinoma (HCC) ( Sun et al, 2015 ; Cheng et al, 2020 ), gastric cancer ( Li X. L. et al, 2019 ; Liang et al, 2020 ), and ovarian cancer ( Li T. et al, 2019 ; Hu et al, 2020 ). Interestingly, most studies also showed that patients with higher KIF23 expression had worse prognosis survival compared to these with lower KIF23 expression ( Kato et al, 2016b ; Ye et al, 2017 ; Li T. et al, 2019 ; Li X. L. et al, 2019 ).…”

Systematic analysis of the relationship between ovarian cancer prognosis and alternative splicing

“…Independent prognostic factors are often used as a part of prognostic monitoring and usually divided into clinical features and molecular biology.Common clinical features such as age, performance status, grade, Figo stage, and histology were considered independent prognostic factors for OC [ 49 , 50 ]. On the other hand, researchers found that low level of AK7, high expression of KIF23, P-gp protein, and SIX-gene signature(TGFBI, SFRP1, COL16A1, THY1, PPIB, BGN) could all be considered independent prognostic factors for OC [ 51 – 54 ]. In this study, we analyzed some clinical traits and found that age can be used as an independent prognostic factor for OC.However, grade and stage were not significant as independent prognostic factors of OC in our study,this may be due to differences in research data and experimental methods.At the same time, we added the score of risk calculated by the prognostic model for evaluation, and risk score was also an independent prognostic factor.…”