ArticleInternational journal of molecular medicine2020
A risk score system based on DNA methylation levels and a nomogram survival model for lung squamous cell carcinoma.
Article in International journal of molecular medicine, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
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14 citing papers in PubMed, 36 citations in OpenAlex.
- A nomogram based on A-to-I RNA editing predicting overall survival of patients with lung squamous carcinoma.BMC cancer · 2022Trial
- Comprehensive analysis of palmitoylation-related proteins for prognostic risk evaluation and tumor immune microenvironment assessment in glioma.Frontiers in immunology · 2025Article
- Comparison of left- and right-sided colorectal cancer to explore prognostic signatures related to pyroptosis.Heliyon · 2024Article
- Potential diagnostic biomarkers: 6 cuproptosis- and ferroptosis-related genes linking immune infiltration in acute myocardial infarction.Genes and immunity · 2023Article
- Comprehensive analysis of ceRNA network composed of circRNA, miRNA, and mRNA in septic acute kidney injury patients based on RNA-seq.Frontiers in genetics · 2023Article
- Ginsenoside Rg3 attenuates pulmonary fibrosis by inhibiting endothelial to mesenchymal transition.Animal cells and systems · 2023Article
- Article
- A Novel Prognosis Signature Based on Ferroptosis-Related Gene DNA Methylation Data for Lung Squamous Cell Carcinoma.Journal of oncology · 2022Article
- Identification of the Potential Molecular Mechanism ofComputational and mathematical methods in medicine · 2022Article
- Identification and validation of a novel redox-related lncRNA prognostic signature in lung adenocarcinoma.Bioengineered · 2021Article
- The regulation mechanisms and the Lamarckian inheritance property of DNA methylation in animals.Mammalian genome : official journal of the International Mammalian Genome Society · 2021Review
- Specific Lung Squamous Cell Carcinoma Prognosis-Subtype Distinctions Based on DNA Methylation Patterns.Medical science monitor : international medical journal of experimental and clinical research · 2021Article
- A Robust Panel Based on Mitochondrial Localized Proteins for Prognostic Prediction of Lung Adenocarcinoma.Oxidative medicine and cellular longevity · 2021Article
- An Immune Gene-Related Five-lncRNA Signature for to Predict Glioma Prognosis.Frontiers in genetics · 2020Article
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Authors and funding
9 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Lung squamous cell carcinoma (LSCC) is one of the primary types of non‑small cell lung carcinoma, and patients with recurrent LSCC usually have a poor prognosis. The present study was conducted to build a risk score (RS) system for LSCC. Methylation data on LSCC (training set) and on head and neck squamous cell carcinoma (validation set 2) were obtained from The Cancer Genome Atlas database, and GSE39279 (validation set 1) was retrieved from the Gene Expression Omnibus database. Differentially methylated protein‑coding genes (DMGs)/long non‑coding RNAs (DM‑lncRNAs) between recurrence‑associated samples and nonrecurrence samples were screened out using the limma package, and their correlation analysis was conducted using the cor.test() function. Following identification of the optimal combinations of DMGs or DM‑lncRNAs using the penalized package in R, RS systems were built, and the system with optimal performance was selected. Using the rms package, a nomogram survival model was then constructed. For the differentially expressed genes (DEGs) between the high‑ and low‑risk groups, pathway enrichment analysis was performed by Gene Set Enrichment Analysis. There were 335 DMGs and DM‑lncRNAs in total. Following screening out of the top 10 genes (aldehyde dehydrogenase 7 family member A1, chromosome 8 open reading frame 48, cytokine‑like 1, heat shock protein 90 alpha family class A member 1, isovaleryl‑CoA dehydrogenase, phosphodiesterase 3A, PNMA family member 2, SAM domain, SH3 domain and nuclear localization signals 1, thyroid hormone receptor interactor 13 and zinc finger protein 878) and 6 top lncRNAs, RS systems were constructed. According to Kaplan‑Meier analysis, the DNA methylation level‑based RS system exhibited the best performance. In combination with independent clinical prognostic factors, a nomogram survival model was built and successfully predicted patient survival. Furthermore, 820 DEGs between the high‑ and low‑risk groups were identified, and 3 pathways were identified to be enriched in this gene set. The 10‑DMG methylation level‑based RS system and the nomogram survival model may be applied for predicting the outcomes of patients with LSCC.
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