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Specific Lung Squamous Cell Carcinoma Prognosis-Subtype Distinctions Based on DNA Methylation Patterns

Authors
  • Huang, Guichuan1
  • Zhang, Jing2
  • Gong, Ling1
  • Liu, Daishun1
  • Wang, Xin3
  • Chen, Yi3
  • Guo, Shuliang3
  • 1 Department of Pulmonary and Critical Care Medicine, The First People’s hospital of Zunyi (The Third Affiliated Hospital of Zunyi Medical University), Zunyi, Guizhou, P.R. China
  • 2 Department of Pulmonary and Critical Care Medicine, Affiliated Hospital of Zunyi Medical University, Zunyi, Guizhou, P.R. China
  • 3 Department of Pulmonary and Critical Care Medicine, The First Affiliated Hospital of Chongqing Medical University, Chongqing, P.R. China
Type
Published Article
Journal
Medical Science Monitor
Publisher
"International Scientific Information, Inc."
Publication Date
Mar 04, 2021
Volume
27
Identifiers
DOI: 10.12659/MSM.929524
PMID: 33661858
PMCID: PMC7942209
Source
PubMed Central
Keywords
License
Green

Abstract

Background Lung squamous cell carcinoma (LUSC) is one of the major types of non-small-cell lung cancer. Epigenetic alterations, such as DNA methylation, have been recognized to be closely associated with the tumorigenesis and progression. Material/Methods In this study, we investigated the prognosis subgroups and assessed their correlation with clinical characteristics in LUSC using a methylation array acquired from The Cancer Genome Atlas (TCGA) database. Results A total of 196 DNA methylation sites exhibited a significant association with patient prognosis, and patients were further stratified into 7 prognosis subgroups based upon the consensus clustering. The patients in every subgroup were different in terms of prognosis and TNM stage. In addition, we found these 196 significant methylation sites corresponded to 258 genes. The function enrichment analysis revealed that these 258 genes enriched in biological pathways were closely related to cancers, such as DNA methylation and demethylation, cell cycle DNA replication, regulation of signal transduction by p53 class mediator, and genetic imprinting. Subsequently, we determined the levels of methylation sites in 7 subgroups, and found 24 intra-subgroup-specific methylation sites. Meanwhile, we selected 3 subgroups-specific methylation sites to construct the prognosis model for LUSC patients using multivariate Cox proportional risk regression model analysis. This model can effectively predict the prognosis of LUSC patients. Conclusions Our study identified a new classification of LUSC into 7 prognosis subgroups on the basis of DNA methylation data in TCGA, which demonstrated that molecular subtypes are independent factor for prognosis in LUSC. This may provide a more detailed explanation for LUSC heterogeneity. Additionally, this classification will contribute to discovery of new biomarkers of LUSC and provide more accurate subdivision of LUSC. Furthermore, these specific DNA methylation sites and corresponding genes can serve as biomarkers for early diagnosis, accurate therapy, and prognosis prediction.

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