Construction and validation of an immunity-related prognostic signature for lung squamous cell carcinoma

Background The aim of the current study is to develop the immune-related prognostic signature in lung squamous cell carcinoma and verify the same via integrated bioinformatics analysis method. Methods For this study, an optimized prognostic risk model was developed by the authors. It has a total of five PIR-lncRNAs (such as AC107884.1, LCMT1-AS1, AL163051.1, AC005730.3 and LINC02635). Survival analysis was conducted in the study followed by independent prognostic analysis upon the prognostic risk model in order to evaluate and verify the model’s prognostic value. In addition to these, the authors also conducted differential analysis for immune cell infiltration between patients of high and low-risk groups in the model. Results In current research work, a total of 21 immune-related genes and 546 differentially-expressed genes were obtain by the authors. On the other hand, co-expression network analysis was conducted from which 654 immune-related lncRNAs (IR-lncRNAs) were identified. With the help of univariate Cox analysis, the study further found 18 prognostic IR-lncRNAs (PIR-lncRNAs). The impact of immunotherapy among the high-risk group patients was found to be lower through the immunotherapy and immune escape analyses. Conclusion The current study outcomes infer the presence of an intrinsic molecular biological linkage between the pathogenic genes of Lung Squamous Cell Carcinoma (LUSC) and the immune cells. This phenomenon has important therapeutic implications and acts as a significant reference to understand the precise and potential immunotherapy of LUSC patients, especially in case of high-risk patients.