Abstract

Abstract
Purpose: The purpose of this paper is to construct and validate the immune-related prognostic signature in lung squamous cell carcinoma through integrated bioinformatics analysis. Methods: We constructed an optimized prognostic risk model consisting of five PIR-lncRNAs (AC107884.1, LCMT1-AS1, AL163051.1, AC005730.3 and LINC02635). We then performed survival analysis and independent prognostic analysis on the prognostic risk model to assess and validate the prognostic value of the model. Further, we performed differential analysis of immune cell infiltration between high- and low-risk patients in the model. Results: In this article, we obtained 546 differentially expressed genes and 21 immune-related genes, identified 654 immune-related lncRNAs (IR-lncRNAs) by co-expression network analysis, and identified 18 prognostic IR-lncRNAs (PIR-lncRNAs) by univariate Cox analysis. Through the analysis of immune escape and immunotherapy, we verified that the effect of immunotherapy in high-risk group patients may be lower. Conclusion: Our findings elucidate the intrinsic molecular biological link between the pathogenic genes of lung squamous cell carcinoma (LUSC) and immune cells, which has important exploration and reference significance for the precise and potential immunotherapy of LUSC patients, especially for high-risk patients.

Key words: immune-related genes; lncRNAs; lung squamous cell carcinoma; prognostic risk model; immune cell infiltration; immunotherapy.