An Integrated Immune-Related Bioinformatics Analysis in Lung Squamous Cell Carcinoma Patients

Abstract

Through combined bioinformatics analysis, the goal of untrrec research was to develop and confirm the immune-related prognostic signature in LUSC (lung squamous cell carcinoma). We constructed an optimized prognostic risk model consisting of five PIR-lncRNAs (AC107884.1, LCMT1-AS1, AL163051.1, AC005730.3 and LINC02635). To evaluate and verify the prognostic value of the model, we subsequently conducted independent prognostic and mortality analysis on the prognostic risk model. Additionally, we conducted a distinct study of immune cell infiltration in the model among high- and low individuals. By using co-expression network analysis, we were able to identify 654 immune-related lncRNAs (IR-lncRNAs) and 18 prognostic IR-lncRNAs (PIR-lncRNAs) and derive 546 differently expressed genes and 21 immune-related genes. We proved that the impact of immunotherapy in individuals in the high-risk category may be lessened through the study of immune escape and immunotherapy. Our findings elucidate the intrinsic molecular biological link between the pathogenic genes of 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.