Identification of a Prognostic Signature Associated With DNA Repair Genes in Ovarian Cancer
| Autor: | Xiangwen Ma, Ying Zhang, Dongyan Cao, Peng Peng, Lei Li, Hengzi Sun, Xiao Huo, Jiaxin Yang, Mei Yu, Keng Shen, Huimei Zhou |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2019 |
| Předmět: |
0301 basic medicine
Oncology medicine.medical_specialty endocrine system diseases lcsh:QH426-470 DNA repair DNA damage response 03 medical and health sciences 0302 clinical medicine Internal medicine Gene expression Genetics medicine prognostic signature Gene Genetics (clinical) Original Research Univariate analysis Prognostic signature business.industry Cancer therapeutic target medicine.disease lcsh:Genetics 030104 developmental biology ovarian cancer genome integrity 030220 oncology & carcinogenesis Molecular Medicine Immunohistochemistry Ovarian cancer business |
| Zdroj: | Frontiers in Genetics, Vol 10 (2019) Frontiers in Genetics |
| ISSN: | 1664-8021 |
| DOI: | 10.3389/fgene.2019.00839/full |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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