Development and validation of a prognostic risk signature for lung adenocarcinoma constructed by six ferroptosis, necroptosis, and pyroptosis-related lncRNAs

BACKGROUND: Identifying populations that benefit from immune checkpoint blockade (ICB) therapy remains a major challenge in the treatment of lung adenocarcinoma (LUAD). Existing programmed cell death (PCD) related prognostic models only consider a single mechanism, such as ferroptosis, necroptosis, and pyroptosis, and do not reflect the interaction of multiple mechanisms. This study aims to explore lncRNAs associated with multiple modes of PCD and reveal a risk signature to assess prognosis and treatment outcomes in LUAD patients. METHODS: Based on expression data in The Cancer Genome Atlas (TCGA) database, ferroptosis, necroptosis, and pyroptosis-related lncRNAs (FNPRlncRNAs) were obtained by taking the intersection of ferroptosis-related lncRNAs (FRlncRNAs), necroptosis-related lncRNAs (NRlncRNAs), and pyroptosis-related lncRNAs (PRlncRNAs) differentially expressed in LUAD and normal tissues. Patients with complete survival information and expression data from TCGA database were randomly assigned to training and testing sets (1:1). Univariate, LASSO, and multivariate Cox regression analyses were performed on the training set, and a risk signature was established. Kaplan-Meier survival curves were used to verify the prognostic ability of risk signature, and receiver operating characteristic (ROC) curves were used to assess the predictive accuracy. We then analyzed molecular and immune profile differences between high and low-risk subgroups. T-cell dysfunction and Exclusion (TIDE) scores were used to assess the response to immunotherapy in each risk subgroup. Finally, three LUAD clusters (C1, C2, and C3) were identified according to the risk signature. RESULTS: Patients in the low-risk subgroup had higher overall survival (OS) than that in the high-risk subgroup in the K-M survival curve. The area under ROC curves (AUC) of 1-, 3-, and 5-year ROC were 0.742, 0.762, and 0.749 in the training set, and 0.672, 0.642, and 0.563 in the testing set, respectively. Compared with the high-risk subgroup, patients in the low-risk subgroup have beneficial tumor immune microenvironment and molecular characteristics, but are less likely to benefit from immunotherapy. Finally, the three LUAD clusters (C1, C2, C3) identified by risk signature had different responses to drug treatment. CONCLUSIONS: The prognosis risk signature constructed using FNPRlncRNAs is helpful to predict the prognosis of LUAD and may contribute to its individualized treatment.