A pyroptosis expression pattern score predicts prognosis and immune microenvironment of lung squamous cell carcinoma

Pyroptosis has been proved to significantly influence the development of lung squamous cell carcinoma (LUSC). To better predict overall survival (OS) and provide guidance on the selection of therapy for LUSC patients, we constructed a novel prognostic biomarker based on pyroptosis-related genes. The dataset for model construction were obtained from The Cancer Genome Atlas and the validation dataset were obtained from Gene Expression Omnibus. Differential expression genes between different pyroptosis expression patterns were identified. These genes were then used to construct pyroptosis expression pattern score (PEPScore) through weighted gene co-expression network analysis, univariate and multivariate cox regression analysis. Afterward, the differences in molecule and immune characteristics and the effect of different therapies were explored between the subgroups divided by the model. The PEPScore was constructed based on six pyroptosis-related genes (CSF2, FGA, AKAP12, CYP2C18, IRS4, TSLP). Compared with the high-PEPScore subgroup, the low-PEPScore subgroup had significantly better OS, higher TP53 and TTN mutation rate, higher infiltration of T follicular helper cells and CD8 T cells, and may benefit more from chemotherapeutic drugs, immunotherapy and radiotherapy. PEPScore is a prospective prognostic model to differentiate prognosis, molecular and immune microenvironmental features, as well as provide significant guidance for selecting clinical therapies.

Automated summary

This study constructed a novel prognostic biomarker (PEPScore) based on pyroptosis-related genes to predict overall survival and guide therapy selection for lung squamous cell carcinoma (LUSC) patients. The low-PEPScore subgroup had better overall survival, higher mutation rate, and increased immune cell infiltration, indicating potential benefits from chemotherapy, immunotherapy, and radiotherapy.