Construction Of Lung Adenocarcinoma Prognostic Model Based On Pyroptosis-related Genes

Background:Lung adenocarcinoma(LUAD)is the most common type of lung cancer,and the overall survival(OS)of LUAD varies greatly among different populations.The traditional anatomic TNM staging system is not enough to predict the prognosis and make treatment decisions in LUAD.Therefore,it is urgent to find new biological molecular prognostic markers to optimize risk stratification and achieve individualized treatment for patients.Additionally,despite the fact that targeted therapy and immunotherapy have brought new hopes for LUAD patients,the presence of immunosuppressive tumor microenvironment(TME)and drug resistance remain challenging problems.Pyroptosis is a type of inflammasome-induced programmed cell death depending on the formation of plasma membrane pores by members of the gasdermin protein family.Recent studies indicate that pyroptosis is closely linked to tumor development and microenvironment regulation.With the widespread availability of high-throughput sequencing technologies and bioinformatics analysis,finding prognostic molecular markers for LUAD at the genome level and exploring the underlying molecular mechanisms of prognosis has become a future research direction with broad application prospects.Objectives:The study aims to establish a prognostic riskscore based on pyroptosis-related genes(PRGs)to distinguish low-and high-risk LUAD patients and construct a prognostic nomogram for predicting the survival probability and time of LUAD patients.To explore the differences in the immune microenvironment between different risk groups and provide new ideas for screening the superior population for immunotherapy.To identify molecular markers related to drug sensitivity,providing a theoretical basis for establishing a personalized and precise treatment system for LUAD patients.Methods:In this study,transcriptome data and clinical information of LUAD patients were obtained from the Cancer Genome Atlas(TCGA)and Gene Expression Omnibus(GEO)databases.TCGA-LUAD patients were classified into subtypes with survival differences based on the differential expression of pyroptosis-related genes through consensus clustering analysis.Differentially expressed genes between subtypes were identified.Cox regression and Lasso were used to screen candidate genes and construct a prognostic riskscore to distinguish high-risk and low-risk groups of LUAD patients.The datasets in the GEO(GSE68571,GSE42127,and GSE31210)were used for external validation.The riskscore was combined with clinical data to develop a prognostic nomogram,and the accuracy of the nomogram was evaluated using calibration curves.Decision curve analysis(DCA)was used to compare the predictive efficacy of the prognostic nomogram and traditional TNM staging.Mechanisms leading to prognostic differences were explored through functional enrichment analysis and immune infiltration analysis.The Cell Miner tool was used to predict the association between risk gene expression levels and drug sensitivity.Reasults:Consensus clustering based on 52 PRGs identified two LUAD subtypes with survival differences.Based on differentially expressed genes between pyroptosisrelated subtypes,we constructed a 12-gene riskscore to distinguish low-and high-risk LUAD patients.The high-risk group demonstrated poorer survival outcomes compared to the low-risk group(Training Set: P<0.001;Validation Set: P<0.001),with the riskscore serving as an independent prognostic factor(Training Set:HR=3.333,95%CI: 2.279-4.877,P<0.001;Validation Set: HR=2.559,95%CI:1.652-3.963,P<0.001).A prognostic nomogram based riskscore and clinical features(age and stage)accurately predicted the overall survival of LUAD patients(Cindex=0.728,95%CI:0.705-0.751).Functional enrichments between high-and low-risk groups were mainly involved in the humoral immune response.The low-risk group exhibited higher levels of immune cell infiltration and more active immunerelated pathways,suggesting that these patients may derive greater benefit from immunotherapy.As a protective gene in the riskscore,high MS4A1 expression was associated with increased sensitivity to ceritinib and alectinib,providing new insights into targeted therapy for LUAD.Conclusion:The riskscore based on pyroptosis contributes to the optimization of risk stratification for survival and personalized management of LUAD.The prognostic nomogram accurately predicts the survival rates of LUAD patients.Variations in immune infiltration may account for the prognostic disparities observed between high-and low-risk groups,with low-risk patients potentially benefiting more from immunotherapy.The study provides new insights into individualized immunotherapy and precise targeted therapy for LUAD.