To identify immune related lncRNAs associated with the prognosis of esophageal squamous cell carcinoma (ESCC) by bioinformatics analysis and construct a prognostic risk model.

The transcriptome data and clinical data of patients with esophageal squamous cell carcinoma were downloaded from the TCGA database. Immune genes and transcriptome data were intersected to obtain immune-related genes. The correlation analysis was used to get immune-related lncRNA (correlation coefficient >0.4, P<0.01). The immune lncRNA related to prognosis was obtained through single factor COX analysis. Based on the expression of these lncRNAs in the sample, a COX prognostic risk scoring model was constructed and the risk value was calculated. According to the risk value, the patients were divided into high and low risk groups. The receiver operator characteristic (ROC) curve was used to compare the area under the ROC curve (AUC) to evaluate the effectiveness of the model.

Totally, 95 samples of ESCC were downloaded from the TCGA database. Intersection of immune genes and transcript data yielded 331 immune-related genes. Through single-factor COX analysis, we obtained 6 immune lncRNAs (LINC02159, AC092484.1, AC099850.3, AC125807.2, AC105277.1 and AC037459.3) significantly related to prognosis, and constructed a prognosis risk model based on these 6 lncRNAs. According to the risk model, the patients were divided into high and low risk groups based on their risk value. Through survival analysis to compare the 5-year survival rate, it was found that the survival rate in the high risk group was significantly lower than that in the low risk group (P<0.01). The ROC curve results showe dthat the AUC was 0.844.

Immune prognosis-related lncRNA can predict the prognosis of patients with ESCC, and provide clues for the research and treatment of immune-related lncRNA in ESCC.

Bioinformatics analysis; Esophageal squamous cell carcinoma