Functional identification and prediction of lncRNAs in esophageal cancer

• Published in: Computers in biology and medicine 2023-10, Vol.165, p.107205-107205, Article 107205
• Main Authors: Han, Lu, Wang, Zhikuan, Li, Congyong, Fan, Mengjiao, Wang, Yanrong, Sun, Gang, Dai, Guanghai
• Format: Article
• Language: English
• Subjects: Apoptosis; Biomarkers; Cancer; Cancer therapies; Cell cycle; Cell growth; Deep learning; DNA methylation; Esophageal cancer; Esophagus; Genes; Immune cell; Immunotherapy; Liver cancer; LncRNA; Lymphatic system; Malignancy; Medical prognosis; Metastasis; Microenvironments; Non-coding RNA; Prognosis; Proteins; Signal transduction
• ISSN: 0010-4825; 1879-0534
• DOI: 10.1016/j.compbiomed.2023.107205

Esophageal cancer is a highly lethal malignancy with poor prognosis, and the identification of molecular biomarkers is crucial for improving diagnosis and treatment. Long non-coding RNAs (lncRNAs) have been shown to play important roles in the development and progression of esophageal cancer. However, due to the time cost of biological experiments, only a small number of lncRNAs related to esophageal cancer have been discovered. Currently, computational methods have emerged as powerful tools for identifying and characterizing lncRNAs, as well as predicting their potential functions. Therefore, this article proposes a transformer-based method for identifying esophageal cancer-related lncRNAs. Experimental results show that the AUC and AUPR of this method are superior to other comparison methods, with an AUC of 0.87 and an AUPR of 0.83, and the identified lncRNA targets are closely associated with esophageal cancer. We focus on the role of esophageal cancer-related lncRNAs in the immune microenvironment, and fully explore the functions of the target genes regulated by lncRNAs. Enrichment analysis shows that the predicted target genes are related to multiple pathways involved in the occurrence, development, and prognosis of esophageal cancer. This not only demonstrates the effectiveness of the method but also indicates the accuracy of the prediction results. •Proposed a transformer based method for predicting lncRNA related to esophageal cancer.•The novel method performed best among other methods.•lncRNAs play a significant role in the immune microenvironment of esophageal cancer.•LncRNAs play an important regulatory role in various immune cells.