A Novel Necroptosis-Related lncRNA Signature Predicts the Prognosis of Lung Adenocarcinoma

Abstract

Background: Necroptosis is closely related to the tumorigenesis and development of cancer. An increasing number of studies have demonstrated that targeting necroptosis could be a novel treatment strategy for cancer. However, the predictive potential of necroptosis-related long noncoding RNAs (lncRNAs) in lung adenocarcinoma (LUAD) still needs to be clarified. This study aimed to construct a prognostic signature based on necroptosis-related lncRNAs to predict the prognosis of LUAD.Methods: We downloaded RNA sequencing data from The Cancer Genome Atlas database. Co-expression network analysis, univariate Cox regression, and least absolute shrinkage and selection operator were adopted to identify necroptosis-related prognostic lncRNAs. We constructed the predictive signature by multivariate Cox regression. Kaplan–Meier analysis, time-dependent receiver operating characteristics, nomogram, and calibration curves were used to validate and evaluate the signature. Subsequently, we used gene set enrichment analysis (GSEA) and single-sample gene set enrichment analysis (ssGSEA) to explore the relationship between the predictive signature and tumor immune microenvironment of risk groups. Finally, the correlation between the predictive signature and immune checkpoint expression of LUAD patients was also analyzed.Results: We constructed a signature composed of 7 necroptosis-related lncRNAs (AC026355.2, AC099850.3, AF131215.5, UST-AS2, ARHGAP26-AS1, FAM83A-AS1, and AC010999.2). The signature could serve as an independent predictor for LUAD patients. Compared with clinicopathological variables, the necroptosis-related lncRNA signature has a higher diagnostic efficiency, with the area under the receiver operating characteristic curve being 0.723. Meanwhile, when patients were stratified according to different clinicopathological variables, the overall survival of patients in the high-risk group was shorter than that of those in the low-risk group. GSEA showed that tumor- and immune-related pathways were mainly enriched in the low-risk group. ssGSEA further confirmed that the predictive signature was significantly related to the immune status of LUAD patients. The immune checkpoint analysis displayed that low-risk patients had a higher immune checkpoint expression, such as CTLA-4, HAVCR2, PD-1, and TIGIT. This suggested that immunological function is more active in the low-risk group LUAD patients who might benefit from checkpoint blockade immunotherapies.Conclusion: The predictive signature can independently predict the prognosis of LUAD, helps elucidate the mechanism of necroptosis-related lncRNAs in LUAD, and provides immunotherapy guidance for patients with LUAD.

Construction and validation model of necroptosis-related gene signature associates with immunity for osteosarcoma patients

“…In addition to the above pathway processes, some immune-related pathways, such as Th17 cell differentiation also enriched. These results also focus on apoptosis and inflammation, consistent with our findings, compared with NRGs functional enrichment in other tumors 20 , 48 , 49 . These results demonstrate that osteosarcoma and normal tissue differ in genes associated with cell death and contribute to activating inflammatory, apoptotic and necroptosis signaling pathways.…”

“…In addition, necroptosis modifies the tumor immune microenvironment by regulating immune checkpoints 19 . Last, necroptosis-related lncRNA and miRNAs gene sets have been reported to predict lung cancer prognosis 20 , 21 . However, whether necroptosis-related genes (NRGs) play a role in the occurrence and development of osteosarcoma disease is still unknown.…”

A Novel Necroptosis-Related lncRNA Signature for Osteosarcoma

“…Currently, studies show that necroptosisrelated lncRNAs (NRlncRNAs) are associated with poor prognoses in a variety of tumors, including lung adenocarcinoma, gastric cancer, breast cancer, and head and neck squamous cells. However, the function of NRlncRNAs in OS and their association with patient prognosis remain unknown [14][15][16][17].…”

N1-methyladenosine methylation-related metabolic genes signature and subtypes for predicting prognosis and immune microenvironment in osteosarcoma

“…Immune checkpoint inhibitors (ICIs) are an emerging and effective therapeutic strategy for a variety of tumours. While most studies suggest that immune checkpoints are used by tumour cells to evade immune destruction, others suggest that immune checkpoint expression positively correlates with the efficacy of immunotherapy ( Marin-Acevedo et al, 2021 ; Lu et al, 2022 ). Therefore, we aimed to verify the ability of MRmetabolism in predicting the effective of immunotherapy.…”