ArticleMolecular medicine reports2019
An 8‑gene signature predicts the prognosis of cervical cancer following radiotherapy.
Article in Molecular medicine reports, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 1 of them a synthesis that pooled it.
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Who cites it
9 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Prediction Models for Prognosis of Cervical Cancer: Systematic Review and Critical Appraisal.Frontiers in public health · 2021Pooled it
- Effectiveness of Nonfunctionalized Graphene Oxide Nanolayers as Nanomedicine against Colon, Cervical, and Breast Cancer Cells.International journal of molecular sciences · 2023Article
- Radiotherapy resistance: identifying universal biomarkers for various human cancers.Journal of cancer research and clinical oncology · 2022Review
- Identifying a cervical cancer survival signature based on mRNA expression and genome-wide copy number variations.Experimental biology and medicine (Maywood, N.J.) · 2022Article
- Identification of candidate miRNA biomarkers correlated with the prognosis of cell carcinoma and endocervical adenocarcinoma via integrated bioinformatics analysis.American journal of translational research · 2022Article
- An 8-gene DNA methylation signature predicts the recurrence risk of cervical cancer.The Journal of international medical research · 2021Article
- Identification of a tumor microenvironment-related gene signature to improve the prediction of cervical cancer prognosis.Cancer cell international · 2021Article
- Higher T cell immunoglobulin mucin-3 (Tim-3) expression in cervical cancer is associated with a satisfactory prognosis.Translational cancer research · 2020Article
- Integrated Profiles Analysis Identified a Coding-Non-Coding Signature for Predicting Lymph Node Metastasis and Prognosis in Cervical Cancer.Frontiers in cell and developmental biology · 2020Article
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Authors and funding
10 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Gene expression and DNA methylation levels affect the outcomes of patients with cancer. The present study aimed to establish a multigene risk model for predicting the outcomes of patients with cervical cancer (CerC) treated with or without radiotherapy. RNA sequencing training data with matched DNA methylation profiles were downloaded from The Cancer Genome Atlas database. Patients were divided into radiotherapy and non‑radiotherapy groups according to the treatment strategy. Differently expressed and methylated genes between the two groups were identified, and 8 prognostic genes were identified using Cox regression analysis. The optimized risk model based on the 8‑gene signature was defined using the Cox's proportional hazards model. Kaplan‑Meier survival analysis indicated that patients with higher risk scores exhibited poorer survival compared with patients with lower risk scores (log‑rank test, P=3.22x10‑7). Validation using the GSE44001 gene set demonstrated that patients in the high‑risk group exhibited a shorter survival time comprared with the low‑risk group (log‑rank test, P=3.01x10‑3). The area under the receiver operating characteristic curve values for the training and validation sets were 0.951 and 0.929, respectively. Cox regression analyses indicated that recurrence and risk status were risk factors for poor outcomes in patients with CerC treated with or without radiotherapy. The present study defined that the 8‑gene signature was an independent risk factor for the prognosis of patients with CerC. The 8‑gene prognostic model had predictive power for CerC prognosis.
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