Analysis of methylation‐driven genes for predicting the prognosis of patients with head and neck squamous cell carcinoma

Pan, Yihua; Song, Yidan; Cheng, Lan; Xu, Hongdan; Liu, Jun

doi:10.1002/jcb.29252

Cited by 25 publications

(21 citation statements)

References 52 publications

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“…Zhu in 2019 found out that the combined analysis of the methylation status of 5 genes (CENPV, SYTL2, OCLN, CASD1, and TUB) helped in the construction of a risk prediction model of the prognosis of OSCC [38] Pan et al in 2019 reported that subsequent combined survival analysis on six genes (INA, LINC01354, TSPYL4, MAGEB2, EPHX3, and ZNF134) could be used as independent prognostic markers and potentially used as drug targets [39].…”

Section: Discussionmentioning

confidence: 99%

Pre-Operative Evaluation of DNA Methylation Profile in Oral Squamous Cell Carcinoma Can Predict Tumor Aggressive Potential

Gissi

Fabbri

Gabusi

et al. 2020

IJMS

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Background: Prognosis of oral squamous cell carcinoma (OSCC) is difficult to exactly assess on pre-operative biopsies. Since OSCC DNA methylation profile has proved to be a useful pre-operative diagnostic tool, the aim of the present study was to evaluate the prognostic impact of DNA methylation profile to discriminate OSCC with high and low aggressive potential. Methods: 36 OSCC cases underwent neoplastic cells collection by gentle brushing of the lesion, before performing a pre-operative biopsy. The CpG islands methylation status of 13 gene (ZAP70, ITGA4, KIF1A, PARP15, EPHX3, NTM, LRRTM1, FLI1, MiR193, LINC00599, MiR296, TERT, GP1BB) was studied by bisulfite Next Generation Sequencing (NGS). A Cox proportional hazards model via likelihood-based component-wise boosting was used to evaluate the prognostic power of the CpG sites. Results: The boosting estimation identified five CpGs with prognostic significance: EPHX3-24, EPHX3-26, ITGA4-3, ITGA4-4, and MiR193-3. The combination of significant CpGs provided promising results for adverse events prediction (Brier score = 0.080, C-index = 0.802 and AUC = 0.850). ITGA4 had a strong prognostic power in patients with early OSCC. Conclusions: These data confirm that the study of methylation profile provides new insights into the molecular mechanisms of OSCC and can allow a better OSCC prognostic stratification even before surgery.

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Section: Discussionmentioning

confidence: 99%

Pre-Operative Evaluation of DNA Methylation Profile in Oral Squamous Cell Carcinoma Can Predict Tumor Aggressive Potential

Gissi

Fabbri

Gabusi

et al. 2020

IJMS

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“…However, classical factors of head and neck tumors were not taken into account in the study. Moreover, reports [ 30 ] showed that different methylation status by the MethylMix R package based on the β mixture model constructed using six genes (INA, LINC01354, TSPYL4, MAGEB2, EPHX3, and ZNF134) could predict OS in HNSCC patients. However, the area under the curve (AUC) for the model was only 0.723.…”

Section: Discussionmentioning

confidence: 99%

Novel Prognostic Model Based on Immune Signature for Head and Neck Squamous Cell Carcinoma

Wang

Hua

et al. 2020

BioMed Research International

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Background. Deciphering the immune characteristics within tumors and identifying the immune signals related to the prognostic factor are helpful for the treatment and management of tumor patients. However, systematic analysis of immune signatures in head and neck squamous cell carcinoma (HNSCC) remains largely unstudied. Methods. A total of 718 immune-related genes were extracted from RNA sequencing data from 519 HNSCC patients in the TCGA database, and survival analysis with integrated bioinformatics analyses was performed to build the final predictive prognosis model. Results. The 178 survival-associated genes ( P < 0.05 ) participated in important immune functions, including immune cell activation and migration. Multivariate regression analysis using 93 genes ( P < 0.01 ), together with survival-associated clinicopathological parameters, identified 35 independent prognostic factors. The most significant 8 independent factors were CD3E, CD40LG, TNFRSF4, CD3G, CD5, ITGA2B, ABCB1, and TNFRSF13b. The final prognostic model achieved outstanding predictive efficiency with the highest AUC of 0.963. Conclusion. Our prognostic model based on the immune signature could effectively predict the prognosis of HNSCC patients, providing novel predictive biomarkers and potential therapeutic targets for HNSCC patients.

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“…MethylMix is a program designed to identify methylation events related to gene expression. 12 We explored the association between DNA methylation and gene expression. Pearson coefficient between methylation level (β value) and gene expression level was calculated to find significantly negatively related genes using the MethylMix package in R. Pearson coefficient < −0.3 with P < .05 was set as the criterion for methylation-related DEGs identification.…”

Section: Methodsmentioning

confidence: 99%

Multiomic Analysis of Methylation and Transcriptome Reveals a Novel Signature in Esophageal Cancer

Jin¹,

Miao²

2020

Dose-Response

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Background: Epigenetic alterations have been shown to lead to human carcinogenesis. The aim of this study was to perform an integrative analysis to develop an epigenetic signature to predict overall survival (OS) of esophageal cancer. Methods: DNA methylation and messenger RNA expression data of esophageal cancer samples were downloaded from The Cancer Genome Atlas database and were incorporated and analyzed using an R package MethylMix. Functional enrichment analysis of the methylation-related differentially expressed genes (DEGs) was performed. Epigenetic signature and nomogram associated with the OS of esophageal cancer were established by the multivariate Cox model. Results: A total of 71 methylation-related DEGs were identified. Kyoto Encyclopedia of Genes and Genomes pathway analysis revealed that these genes were involved in the biological process related to the initiation and progression of esophageal cancer. Two-gene (FAM24B and FAM200A) risk signature for OS was developed by multivariate Cox analysis, of which had high accuracy. The signature is independent of clinicopathological variables and indicated better predictive power than other clinicopathological variables. Moreover, we developed a novel prognostic nomogram based on risk score and 3 clinicopathological factors. Conclusions: Our study indicated possible methylation-related DEGs and established an epigenetic signature, which may provide novel insights for understanding the pathogenesis of esophageal cancer.

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Analysis of methylation‐driven genes for predicting the prognosis of patients with head and neck squamous cell carcinoma

Cited by 25 publications

References 52 publications

Pre-Operative Evaluation of DNA Methylation Profile in Oral Squamous Cell Carcinoma Can Predict Tumor Aggressive Potential

Pre-Operative Evaluation of DNA Methylation Profile in Oral Squamous Cell Carcinoma Can Predict Tumor Aggressive Potential

Novel Prognostic Model Based on Immune Signature for Head and Neck Squamous Cell Carcinoma

Multiomic Analysis of Methylation and Transcriptome Reveals a Novel Signature in Esophageal Cancer

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