Abstract
Introduction: Ovarian cancer is a highly malignant cancer with a poor prognosis. At present, there is no accurate strategy for predicting the prognosis of ovarian cancer. A prognosis prediction signature associated with DNA repair genes in ovarian cancer was explored in this study.Methods: Gene expression profiles of ovarian cancer were downloaded from the GEO, UCSC, and TCGA databases. Cluster analysis, univariate analysis, and stepwise regression were used to identify DNA repair genes as potential targets and a prognostic signature for ovarian cancer survival prediction. The top genes were evaluated by immunohistochemical staining of ovarian cancer tissues, and external data were used to assess the signature.Results: A total of 28 DNA repair genes were identified as being significantly associated with overall survival (OS) among patients with ovarian cancer. The results showed that high expression of XPC and RECQL and low expression of DMC1 were associated with poor prognosis in ovarian cancer patients. The prognostic signature combining 14 DNA repair genes was able to separate ovarian cancer samples associated with different OS times and showed robust performance for predicting survival (Training set: p < 0.0001, AUC = 0.759; Testing set: p < 0.0001, AUC = 0.76).Conclusion: Our study identified 28 DNA repair genes related to the prognosis of ovarian cancer. Using some of these potential biomarkers, we constructed a prognostic signature to effectively stratify ovarian cancer patients with different OS rates, which may also serve as a potential therapeutic target in ovarian cancer.
Highlights
Ovarian cancer is a highly malignant cancer with a poor prognosis
9) Ovarian cancer molecular subtypes were constructed by unsupervised clustering based on prognostic DNA repair genes, and multivariate Cox proportional hazards models were applied to observe their impacts on prognosis
We used a high-throughput method to search for genetic differences in terms of DNA repair genes associated with ovarian cancer prognosis and conducted a comprehensive analysis to obtain more reliable targets of DNA repair genes and a prognostic signature for ovarian cancer survival prediction
Summary
There is no accurate strategy for predicting the prognosis of ovarian cancer. A prognosis prediction signature associated with DNA repair genes in ovarian cancer was explored in this study. The average lifetime risk of developing ovarian cancer is 1.3%, and the 5-year survival rate ranges from 29% to 93% depending on the spread of the cancer at diagnosis (Torre et al, 2018). The mortality rate of ovarian cancer has declined only slightly over the past 3 decades, despite advances in treatment strategies and techniques, largely because nearly 60% of cases are diagnosed at an advanced stage due to a lack of obvious symptoms. Considering the critical role that tumor molecular biology plays in the initiation and progression of tumors, researchers and clinicians have to date focused on effective targeted prognostic and treatment strategies for ovarian cancer (Klinck et al, 2008)
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