DNA methylation signatures associated with prognosis of gastric cancer

BMC Cancer

Akihiro Nishi¹  Tong Zhou²  Kai-Feng Pan²  Yang Zhang²  Zhe-Xuan Li²  Wei-Cheng You²  Jin Dai³  Wen-Qing Li⁴ 

[1] Department of Epidemiology, UCLA Fielding School of Public Health, 90095, Los Angeles, CA, USA;Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Cancer Epidemiology, Peking University Cancer Hospital & Institute, 52 Fucheng Rd, Haidian District, 100142, Beijing, People’s Republic of China;Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Cancer Epidemiology, Peking University Cancer Hospital & Institute, 52 Fucheng Rd, Haidian District, 100142, Beijing, People’s Republic of China;Department of Epidemiology, UCLA Fielding School of Public Health, 90095, Los Angeles, CA, USA;Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Cancer Epidemiology, Peking University Cancer Hospital & Institute, 52 Fucheng Rd, Haidian District, 100142, Beijing, People’s Republic of China;Joint International Research Center of Translational and Clinical Research, 100142, Beijing, China;

关键词: Bioinformatics;    Biomarkers;    Epigenetics;    Gastric cancer;    Heterogeneity;    Methylation;    Precision medicine;    Prognosis;    Survival;    The Cancer Genome Atlas;   

DOI  :  10.1186/s12885-021-08389-0

来源: Springer

【 摘 要 】

BackgroundFew studies have examined prognostic outcomes-associated molecular signatures other than overall survival (OS) for gastric cancer (GC). We aimed to identify DNA methylation biomarkers associated with multiple prognostic outcomes of GC in an epigenome-wide association study.MethodsBased on the Cancer Genome Atlas (TCGA), DNA methylation loci associated with OS (n = 381), disease-specific survival (DSS, n = 372), and progression-free interval (PFI, n = 383) were discovered in training set subjects (false discovery rates < 0.05) randomly selected for each prognostic outcome and were then validated in remaining subjects (P-values < 0.05). Key CpGs simultaneously validated for OS, DSS, and PFI were further assessed for disease-free interval (DFI, n = 247). Gene set enrichment analyses were conducted to explore the Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathways simultaneously enriched for multiple GC prognostic outcomes. Methylation correlated blocks (MCBs) were identified for co-methylation patterns associated with GC prognosis. Based on key CpGs, risk score models were established to predict four prognostic outcomes. Spearman correlation analyses were performed between key CpG sites and their host gene mRNA expression.ResultsWe newly identified DNA methylation of seven CpGs significantly associated with OS, DSS, and PFI of GC, including cg10399824 (GRK5), cg05275153 (RGS12), cg24406668 (MMP9), cg14719951(DSC3), and cg25117092 (MED12L), and two in intergenic regions (cg11348188 and cg11671115). Except cg10399824 and cg24406668, five of them were also significantly associated with DFI of GC. Neuroactive ligand-receptor interaction pathway was suggested to play a key role in the effect of DNA methylation on GC prognosis. Consistent with individual CpG-level association, three MCBs involving cg11671115, cg14719951, and cg24406668 were significantly associated with multiple prognostic outcomes of GC. Integrating key CpG loci, two risk score models performed well in predicting GC prognosis. Gene body DNA methylation of cg14719951, cg10399824, and cg25117092 was associated with their host gene expression, whereas no significant associations between their host gene expression and four clinical prognostic outcomes of GC were observed.ConclusionsWe newly identified seven CpGs associated with OS, DSS, and PFI of GC, with five of them also associated with DFI, which might inform patient stratification in clinical practices.

【 授权许可】

CC BY