Identification and Application of a Novel Immune-Related lncRNA Signature on the Prognosis and Immunotherapy for Lung Adenocarcinoma

Background: Long non-coding RNA (lncRNA) participates in the immune regulation of lung cancer. However, limited studies showed the potential roles of immune-related lncRNAs (IRLs) in predicting survival and immunotherapy response of lung adenocarcinoma (LUAD). Methods: Based on The Cancer Genome Atlas (TCGA) and ImmLnc databases, IRLs were identified through weighted gene coexpression network analysis (WGCNA), Cox regression, and Lasso regression analyses. The predictive ability was validated by Kaplan-Meier (KM) and receiver operating characteristic (ROC) curves in the internal dataset, external dataset, and clinical study. The immunophenoscore (IPS)-PD1/PD-L1 blocker and IPS-CTLA4 blocker data of LUAD were obtained in TCIA to predict the response to immune checkpoint inhibitors (ICIs). The expression levels of immune checkpoint molecules and markers for hyperprogressive disease were analyzed. Results: A six-IRL signature was identified, and patients were stratified into high- and low-risk groups. The low-risk had improved survival outcome (p = 0.006 in the training dataset, p = 0.010 in the testing dataset, p < 0.001 in the entire dataset), a stronger response to ICI (p < 0.001 in response to anti-PD-1/PD-L1, p < 0.001 in response to anti-CTLA4), and higher expression levels of immune checkpoint molecules (p < 0.001 in PD-1, p < 0.001 in PD-L1, p < 0.001 in CTLA4) but expressed more biomarkers of hyperprogression in immunotherapy (p = 0.002 in MDM2, p < 0.001 in MDM4). Conclusion: The six-IRL signature exhibits a promising prediction value of clinical prognosis and ICI efficacy in LUAD. Patients with low risk might gain benefits from ICI, although some have a risk of hyperprogressive disease.