Construction of an algorithm based on oncosis-related LncRNAs comprising the molecular subtypes and a risk assessment model in lung adenocarcinoma.

BACKGROUND: As an important non-apoptotic cell death method, oncosis has been reported to be closely associated with tumors in recent years. However, few research reported the relationship between oncosis and lung cancer. METHODS: In this study, we established an oncosis-based algorithm comprised of cluster grouping and a risk assessment model to predict the survival outcomes and related tumor immunity of patients with lung adenocarcinomas (LUAD). We selected 11 oncosis-related lncRNAs associated with the prognosis (CARD8-AS1, LINC00941, LINC01137, LINC01116, AC010980.2, LINC00324, AL365203.2, AL606489.1, AC004687.1, HLA-DQB1-AS1, and AL590226.1) to divide the LUAD patients into different clusters and different risk groups. Compared with patients in clsuter1, patients in cluster2 had a survival advantage and had a relatively more active tumor immunity. Subsequently, we constructed a risk assessment model to distinguish between patients into different risk groups, in which low-risk patients tend to have a better prognosis. GO enrichment analysis revealed that the risk assessment model was closely related to immune activities. In addition, low-risk patients tended to have a higher content of immune cells and stromal cells in tumor microenvironment, higher expression of PD-1, CTLA-4, HAVCR2, and were more sensitive to immune checkpoint inhibitors (ICIs), including PD-1/CTLA-4 inhibitors. The risk score had a significantly positive correlation with tumor mutation burden (TMB). The survival curve of the novel oncosis-based algorithm suggested that low-risk patients in cluster2 have the most obvious survival advantage. CONCLUSION: The novel oncosis-based algorithm investigated the prognosis and the related tumor immunity of patients with LUAD, which could provide theoretical support for customized individual treatment for LUAD patients.

Identification of an Autophagy-Related lncRNA Prognostic Signature and Related Tumor Immunity Research in Lung Adenocarcinoma.

Autophagy is closely associated with the tumor immune microenvironment (TIME) and prognosis of patients with lung adenocarcinoma (LUAD). In the present study, we established a signature on the basis of long noncoding RNAs (lncRNAs) related to autophagy (ARlncRNAs) to investigate the TIME and survival of patients with LUAD. We selected ARlncRNAs associated with prognosis to construct a model and divided each sample into different groups on the basis of risk score. The ARlncRNA signature could be recognized as an independent prognostic factor for patients with LUAD, and patients in the low-risk group had a greater survival advantage. Kyoto Encyclopedia of Genes and Genomes and Gene Ontology enrichment analysis suggested that several immune functions and pathways were enriched in different groups. A high-risk score correlated significantly negatively with high abundance of immune cells and stromal cells around the tumor and high tumor mutational burden. Low-risk patients had a higher PD-1, CTLA-4, and HAVCR2 expression and had a better efficacy of immune checkpoint inhibitors, including PD-1/CTLA-4 inhibitor. A reliable signature on the basis of ARlncRNAs was constructed to explore the TIME and prognosis of patients with LUAD, which could provide valuable information for individualized LUAD treatment.

Construction of an immune-related lncRNA signature as a novel prognosis biomarker for LUAD.

The tumor immune microenvironment of lung cancer is associated with prognosis and immunotherapy efficacy. Long noncoding RNAs are identified as prognostic biomarkers associated with immune functions. We constructed a signature comprising differentially expressed immune-related lncRNAs to predict the prognosis of patients with lung adenocarcinoma. We established the immune-related lncRNA signature by pairing immune-related lncRNAs regardless of expression level and lung adenocarcinoma patients were divided into high- and low-risk groups. The prognosis of patients in the two groups was significantly different; The immune-related lncRNA signature could serve as an independent lung adenocarcinoma prognostic indicator. The signature correlated negatively with B cell, CD4+ T cell, M2 macrophage, neutrophil, and monocyte immune infiltration. Patients with low risk scores had a higher abundance of immune cells and stromal cells around the tumor. Gene set enrichment analysis showed that samples from low-risk group were more active in the IgA production in intestinal immune network and the T and B cell receptor signaling pathway. High-risk groups had significant involvement of the cell cycle, DNA replication, adherens junction, actin cytoskeleton regulation, pathways in cancer, and TGF-ß signaling pathways. High risk scores correlated significantly negatively with high CTLA-4 and HAVCR2 expression and higher median inhibitory concentration of common anti-tumor chemotherapeutics (e.g., cisplatin, paclitaxel, gemcitabine) and targeted therapy (e.g., erlotinib and gefitinib). We identified a reliable immune-related lncRNA lung adenocarcinoma prognosis model, and the immune-related lncRNA signature showed promising clinical prediction value.