ArticleOncology letters2018
Two protein-coding genes act as a novel clinical signature to predict prognosis in patients with ovarian serous cystadenocarcinoma.
Article in Oncology letters, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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10 citing papers in PubMed, 10 citations in OpenAlex.
- Telomerase-Associated Genes as Prognostic Markers in High-Grade Serous Ovarian Cancer.Medical science monitor : international medical journal of experimental and clinical research · 2026Article
- The MexTAg collaborative cross: host genetics affects asbestos related disease latency, but has little influence once tumours develop.Frontiers in toxicology · 2024Article
- MANF Promotes Unexplained Recurrent Miscarriages by Interacting with NPM1 and Downregulating Trophoblast Cell Migration and Invasion.International journal of biological sciences · 2024Article
- Identification of an Individualized Prognostic Biomarker for Serous Ovarian Cancer: A Qualitative Model.Diagnostics (Basel, Switzerland) · 2022Article
- Identification of a glycolysis-related gene signature for survival prediction of ovarian cancer patients.Cancer medicine · 2021Article
- Development and verification of an immune-related gene pairs prognostic signature in ovarian cancer.Journal of cellular and molecular medicine · 2021Article
- Identification of prognostic biomarkers for major subtypes of non-small-cell lung cancer using genomic and clinical data.Journal of cancer research and clinical oncology · 2020Article
- Article
- Identification of a 3-mRNA signature as a novel potential prognostic biomarker in patients with ovarian serous cystadenocarcinoma in G2 and G3.Oncology letters · 2019Article
- A five-DNA methylation signature act as a novel prognostic biomarker in patients with ovarian serous cystadenocarcinoma.Clinical epigenetics · 2018Article
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Authors and funding
7 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Ovarian cancer is the seventh most common type of cancer and the eighth most common cause of cancer-associated mortality among women. A number of studies have hypothesized that the expression status of certain genes may be used to predict prognosis in ovarian cancer. In the present study, the RNA expression data from next-generation sequencing and the clinical information of 413 patients from The Cancer Genome Atlas dataset was downloaded to identify the association between gene-expression level and the survival time of the patients with ovarian serous cystadenocarcinoma. A five-gene model was predicted to be significantly associated with patient survival in ovarian serous cystadenocarcinoma by using random survival forests variable hunting algorithm and Cox analysis. A total of two genes, mesencephalic astrocyte-derived neurotrophic factor and dedicator of cytokinesis 11, of the predicted five genes demonstrated positive expression in the ovarian serous cystadenocarcinoma cancer tissues by polymerase chain reaction analysis. Kaplan-Meier and Receiver Operating Characteristic analysis confirmed that the model of the two genes exhibited high sensitivity and specificity to predict the prognostic survival of patients. In conclusion, the expression of the two genes in the two-gene model was associated with the prognostic outcomes of patients with ovarian serous cystadenocarcinoma; the model demonstrated potential as a novel prognostic indicator, which may have important clinical significance.
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