Revealing roles of PANoptosis-related genes in prognosis and molecular subtypes in lung squamous cell carcinoma by integrated bioinformatic analyses and experiments.

Abstract

The purpose of current study was to reveal the role of PANoptosis-associated genes in lung squamous cell carcinoma (LUSC) and their potential as prognostic biomarkers. We analyzed RNA-seq data from TCGA-LUSC and GEO datasets to identify differentially expressed genes (DEGs) between LUSC and normal samples, followed by VENN analysis to reveal PANoptosis-related DEGs. Functional enrichment analyses were performed by clusterProfiler package. Distinct LUSC subtypes were identified by consensus clustering based on PANoptosis-related DEGs. Univariate Cox and LASSO regression were utilized to identify key prognostic genes, and a prognostic model was developed based on selected genes. Immune infiltration status was evaluated by CIBERSORT and ESTIMATE algorithms. Expression of key prognostic genes was tested in three LUSC cell lines by RT-qPCR and Western blot. Roles of TLR3 in LUSC progression were determined by functional experiments. A total of 76 PANoptosis-related DEGs were identified, with significant enrichment in apoptosis pathways. The clustering analysis revealed four subtypes, in which survival and immune microenvironment were dramatically different. From the 76 genes, four key prognostic genes (CHEK2, PDK4, TLR3, and IL1B) were identified to establish prognostic risk model, which could reflect the survival status and immune cells composition variations for LUSC patients. Besides, these four genes showed significant correlations with infiltrating levels of various immune cells. TLR3 was identified as a more weighted prognostic risk gene in LUSC. Functional assays demonstrated that genes like TLR3 modulated cell proliferation, migration, and inflammatory responses in LUSC cells. This study highlighted the potential of the four key PANoptosis genes as biomarkers or targets in LUSC, and the risk model based on these four genes provided novel insights to develop personalized treatment strategy for patients with LUSC.