ArticleCancer medicine2021
An aberrant DNA methylation signature for predicting the prognosis of head and neck squamous cell carcinoma.
Article in Cancer medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed, 9 citations in OpenAlex.
- Review
- T cell exhaustion methylation signature drives differential immune responses in glioblastoma.Discover oncology · 2024Article
- DNA-methylome-derived epigenetic fingerprint as an immunophenotype indicator of durable clinical immunotherapeutic benefits in head and neck squamous cell carcinoma.Cellular oncology (Dordrecht, Netherlands) · 2024Article
- Promoter DNA methylation patterns in oral, laryngeal and oropharyngeal anatomical regions are associated with tumor differentiation, nodal involvement and survival.Oncology letters · 2024Article
- Influence of pathogens on host genome and epigenome in development of head and neck cancer.Cancer reports (Hoboken, N.J.) · 2023Review
- An aberrant DNA methylation signature for predicting the prognosis of head and neck squamous cell carcinoma.Cancer medicine · 2021Article
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Authors and funding
10 authors at 3 institutions in 1 country.
Funding
Abstract
Head and neck squamous cell carcinoma (HNSCC) is a common malignancy worldwide with a poor prognosis. DNA methylation is an epigenetic modification that plays a critical role in the etiology and pathogenesis of HNSCC. The current study aimed to develop a predictive methylation signature based on bioinformatics analysis to improve the prognosis and optimize therapeutic outcome in HNSCC. Clinical information and methylation sequencing data of patients with HNSCC were downloaded from The Cancer Genome Atlas database. The R package was used to identify differentially methylated genes (DMGs) between HNSCC and adjacent normal tissues. We identified 22 DMGs associated with 246 differentially methylated sites. Patients with HNSCC were classified into training and test groups. Cox regression analysis was used to build a risk score formula based on the five methylation sites (cg26428455, cg13754259, cg17421709, cg19229344, and cg11668749) in the training group. The Kaplan-Meier survival curves showed that the overall survival (OS) rates were significantly different between the high- and low-risk groups sorted by the signature in the training group (median: 1.38 vs. 1.57 years, log-rank test, p < 0.001). The predictive power was then validated in the test group (median: 1.34 vs. 1.75 years, log-rank test, p < 0.001). The area under the receiver operating characteristic curve (area under the curve) based on the signature for predicting the 5-year survival rates, was 0.7 in the training and 0.73 in test groups, respectively. The results of multivariate Cox regression analysis showed that the riskscore (RS) signature based on the five methylation sites was an independent prognostic tool for OS prediction in patients. In addition, a predictive nomogram model that incorporated the RS signature and patient clinical information was developed. The innovative methylation signature-based model developed in our study represents a robust prognostic tool for guiding clinical therapy and predicting the OS in patients with HNSCC.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.