Investigating the Long Non-Coding RNA Expression Profiles in the development of esophageal cancer: Insights from genomic Analysis

Esophageal carcinoma (ESCA) is one of the most common types of cancer. ESCA accounted for the sixth leading cause of cancer-related deaths globally. Most patients are diagnosed at late stages of ESCA, with distance metastasis or chemoresistance, which leads to a poor prognosis. Previous studies demonstrated lncRNA presentation and roles in ESCA cells and patients' tissue. It has been proposed that lncRNAs can be considered a new prognostic and diagnostic biomarker in ESCA. In this study, we comprehensively explored the interaction of lncRNAs with miRNAs and mRNAs of the TCGA database and proposed a novel promising biomarker with good diagnostic and prognostic values.

The public data of RNA-seq, miR-seq, and related clinical data were downloaded from the TCGA database. Differential expression analysis was conducted by “limma” in R. GO, and KEGG signaling pathways were used for enrichments. STRING database was used for PPI analysis. CE-network was constructed by the STAR database in R. Kaplan-Meier survival analysis (log-rank test), and ROC curve analysis was used to indicate the diagnostic and prognostic values of the biomarkers.

Differentially expressed data illustrated that 45.8% of the total mRNAs in the data related to ESCA patients showed increased expression and 54.2% decreased expression. The GO and KEGG pathway analysis showed that the differentially expressed mRNAs were enriched in critical biological processes. Important protein-protein interaction hubs were identified. The ceRNA network data demonstrated critical lncRNAs essential in ESCA development, including TMEM16B-AS1, AC093010.3, SNHG3, and PVT1. The data revealed that the lncRNA WDFY3-AS2, AC108449.2, DLEU2, AC007128.1, and AP003356.1 are potential diagnostic and prognostic biomarkers in ESCA patients.

Altogether, this study demonstrates lncRNA, miRNA, and mRNA interaction and mentions regulatory networks which can be considered as a therapeutic option in ESCA. In addition, we proposed potential diagnostic and prognostic biomarkers for ESCA patients.