Research Paper Volume 12, Issue 14 pp 14649—14676

Identifying CpG methylation signature as a promising biomarker for recurrence and immunotherapy in non–small-cell lung carcinoma

Ruihan Luo1, , Jing Song1, , Xiao Xiao2, , Zhengbo Xie3, , Zhiyuan Zhao3, , Wanfeng Zhang1, , Shiqi Miao1, , Yongyao Tang4, , Longke Ran1, ,

  • 1 Department of Bioinformatics, The Basic Medical School of Chongqing Medical University, Chongqing, China
  • 2 Department of Endocrine and Breast Surgery, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China
  • 3 Information Center Department, Chongqing Medical University, Chongqing, China
  • 4 Molecular and Tumor Research Center, Chongqing Medical University, Chongqing, China

Received: March 19, 2020       Accepted: June 4, 2020       Published: July 28, 2020
How to Cite

Copyright: © 2020 Luo et al. This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.


Epigenetic alterations are crucial to oncogenesis and regulation of gene expression in non–small-cell lung carcinoma (NSCLC). DNA methylation (DNAm) biomarkers may provide molecular-level prediction of relapse risk in cancer. Identification of optimal treatment is warranted for improving clinical management of NSCLC patients. Using machine learning algorithm we identified 4 recurrence predictive CpG methylation markers (cg00253681/ART4, cg00111503/KCNK9, cg02715629/FAM83A, cg03282991/C6orf10) and constructed a risk score model that potently predicted recurrence-free survival and prognosis for patients with NSCLC (P = 0.0002). Integrating genomic, transcriptomic, proteomic and clinical data, the DNAm-based risk score was observed to significantly associate with clinical stage, cell proliferation markers, somatic alterations, tumor mutation burden (TMB) as well as DNA damage response (DDR) genes, and potentially predict the efficacy of immunotherapy. In general, our identified DNAm signature shows a significant correlation to TMB and DDR pathways, and serves as an effective biomarker for predicting NSCLC recurrence and response to immunotherapy. These findings demonstrate the utility of 4-DNAm-marker panel in the prognosis, treatment decision-making and evaluation of therapeutic responses for NSCLC.


BH: Benjamini-Hochberg; DDR: DNA damage response; DEGs: differentially expressed genes; DNAm: DNA methylation; DMPs: differentially methylated positions; FDR: false discovery rate; GEO: Gene Expression Omnibus; GSEA: gene set enrichment analysis; GSVA: gene set variation analysis; ICBs: immune checkpoint blockades; LASSO: Least Absolute Shrinkage and Selection Operator; LUAD: lung adenocarcinoma; LUSC: lung squamous cell carcinoma; NSCLC: non–small-cell lung carcinoma; OS: overall survival; RFS: recurrence-free survival; RNA-seq: RNA sequencing; RPPA: reverse phase protein array; ROC: receiver operating characteristic; SMGs: significantly mutated genes; TCGA: The Cancer Genome Atlas; TMB: tumor mutation burden; TME: tumor microenvironment; WES: whole-exome sequencing.