Identification of molecular subtypes in lung adenocarcinoma based on DNA methylation and gene expression profiling-a bioinformatic analysis

Shuying Wang; Xiaoxing Liang; Ruomi Guo; Jiao Gong; Xiaolong Zhong; Yulin Liu; Deqing Wang; Yanmei Hao; Bo Hu

doi:10.21037/atm-22-3340

Identification of molecular subtypes in lung adenocarcinoma based on DNA methylation and gene expression profiling-a bioinformatic analysis

Ann Transl Med. 2022 Aug;10(16):882. doi: 10.21037/atm-22-3340.

Authors

Shuying Wang^#^{1

2}, Xiaoxing Liang^#³, Ruomi Guo^#⁴, Jiao Gong⁵, Xiaolong Zhong⁶, Yulin Liu⁶, Deqing Wang^{1

2}, Yanmei Hao³, Bo Hu⁵

Affiliations

¹ Department of Clinical Laboratory Diagnostics, PLA medical college, Beijing, China.
² Department of Blood Transfusion Medicine, The First Medical Center, Chinese PLA General Hospital, Beijing, China.
³ School of Laboratory Medicine, Bengbu Medical College, Bengbu, China.
⁴ Department of Radiology, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, China.
⁵ Department of Laboratory Medicine, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, China.
⁶ Department of Blood Transfusion Medicine, Affiliated Hospital of Southwest Medical University, Luzhou, China.

^# Contributed equally.

Abstract

Background: Molecular typing based on deoxyribonucleic acid (DNA) methylation and gene expression can extend understandings of the molecular mechanisms involved in lung adenocarcinoma (LUAD) and enhance current diagnostic, treatment, and prognosis prediction approaches.

Methods: Gene expression and DNA methylation data sets of LUAD were obtained from The Cancer Genome Atlas (TCGA), and the differential gene and methylation expression levels were analyzed.

Results: We successfully divided the LUAD samples into 2 clinically relevant subtypes with significantly different survival times and tumor stages according to the transcriptome and methylation data. We found significant differences in the survival status, age, gender, tumor stage, node stage, and clinical stage between the 2 subtypes. The hub genes identified in the subnetworks, including NCAPG, CCNB1, DLGAP5, HLA-DQA1, HLA-DPA1, HLA-DPB1, SFTP, SCGBA1A, and SFTPD, were correlated with the cell cycle and immune system. The Gene Ontology annotation of the hub genes showed that the biological processes included organelle fission mitotic nuclear division, and sister chromatid segregation. The cellular components included chromosomal region, spindle, and kinetochore. The molecular functions included tubulin-binding, microtubule-binding, and DNA replication origin binding. The Kyoto Encyclopedia of Genes and Genomes signaling pathways related to the hub genes mainly included the cell cycle, human T-cell leukemia virus (type 1) infection, inflammatory bowel disease, and the intestinal immune network for immunoglobulin A production. The clinical stage difference was also confirmed in the validation group using the GSE32863 data set.

Conclusions: Our findings extend understandings of the pathogenesis of LUAD and can be used to improve current diagnosis, treatment, and prognosis prediction strategies.

Keywords: Gene Expression Omnibus (GEO); Lung adenocarcinoma (LUAD); The Cancer Genome Atlas (TCGA); cancer subtypes; methylation.