Immunogenic cell death–related genes predict prognosis and response to immunotherapy in lung squamous cell carcinoma

Abstract

Lung squamous cell carcinoma (LUSC) is a malignancy with limited therapeutic options. Immunogenic cell death (ICD) has the potential to enhance the efficacy of cancer therapy by triggering immune responses. We aimed to explore the potential of ICD‐based classification in predicting prognosis and response to immunotherapy for LUSC. RNA‐seq information and clinical data of LUSC patients were obtained from The Cancer Genome Atlas (TCGA) dataset. ICD‐related gene expressions in LUSC samples were analyzed by consensus clustering. Subsequently, differentially expressed genes (DEGs) between different ICD‐related subsets were analyzed. Tumor mutation burden, immune cell infiltration, and survival analyses were conducted between different ICD subsets. Finally, an ICD‐related risk signature was constructed and evaluated in LUSC patients, and the immunotherapy responses based on the gene expressions were also forecasted. ICD‐high and ICD‐low groups were defined, and 1466 DEGs were identified between the two subtypes. These DEGs were mainly enriched in collagen‐containing extracellular matrix, cytokine–cytokine receptor interaction, the PI3K‐Akt signaling pathway, and neuroactive ligand–receptor interaction. Furthermore, the ICD‐low group exhibited a favorable prognosis, enhanced TTN and MUC16 mutation frequencies, increased infiltrating immune cells, and downregulated immune checkpoint expressions. Furthermore, we demonstrated that an ICD‐related model (based on CD4, NLRP3, NT5E, and TLR4 genes) could forecast the prognosis of LUSC, and ICD risk scores were lower in the responder group. In summary, the predicted values of ICD‐related genes (CD4, NLRP3, NT5E, and TLR4) for the prognosis and response to immunotherapy in LUSC were verified in the study, which benefits immunotherapy‐based interventions for LUSC patients.