Enhancer-associated regulatory network and gene signature based on transcriptome and methylation data to predict the survival of patients with lung adenocarcinoma

Accumulating evidence has proved that aberrant methylation of enhancers plays regulatory roles in gene expression for various cancers including lung adenocarcinoma (LUAD). In this study, the transcriptome and methylation data of The Cancer Genome Atlas (TCGA)-LUAD cohort were comprehensively analyzed with a five-step Enhancer Linking by Methylation/Expression Relationships (ELMER) process. Step 1: 131,371 distal (2 kb upstream from the transcription start site) probes were obtained. Step 2: 10,665 distal hypomethylated probes were identified in an unsupervised mode with the get.diff.meth function. Step 3: 699 probe-gene pairs with negative correlations were screened using the get.pair function in an unsupervised mode. Step 4: After mapping with probes, 768 motifs were obtained and 24 of them were enriched. Step 5: 127 transcription factors (TFs) with differential expressions and negative correlations with methylation levels were screened, which were corresponding to 21 motifs. After the ELMER process, a prognostic “TFs-motifs-genes” regulatory network was constructed. The Least absolute shrinkage and selection operator (LASSO) and Stepwise regression analyses were further applied to identify variables in the TCGA-LUAD cohort and an eight-gene signature was constructed for calculating the risk score. The risk score was verified in two independent validation cohorts. The area under curve values of receiver operating characteristic curves predicting 1-, 3-, and 5-years survival ranged from 0.633 to 0.764. With the increase of the risk scores, both the survival statuses and clinical traits showed a worse tendency. There were significant differences in the degrees of immune cell infiltration, TMB values, and TIDE scores between the high-risk and low-risk groups. Finally, a better-performing prognostic nomogram was integrated with the risk score and other clinical traits. In short, this multi-omics analysis demonstrated the application of ELMER in analyzing enhancer-associated regulatory network in LUAD, which provided promising strategies for epigenetic therapy and prognostic biomarkers.