Identification of an Immune-Related Long Noncoding RNA Pairs Model to Predict Survival and Immune Features in Gastric Cancer

Abstract

Background: Gastric cancer (GC) remains one of the most malignant tumors around the world, and an accurate model that reliably predicts survival and therapeutic efficacy is urgently needed. As a novel predictor for prognosis in a variety of cancers, immune-related long noncoding RNA pairs (IRlncRNAPs) have been reported to predict tumor prognosis. Herein, we integrated an IRlncRNAPs model to predict the clinical outcome, immune features, and chemotherapeutic efficacy of GC.Methods: Based on the GC data obtained from The Cancer Genome Atlas (TCGA) database and the Immunology Database and Analysis Portal (ImmPort), differentially expressed immune-related long noncoding RNAs (DEIRlncRNAs) were identified. Least absolute shrinkage and selection operator (LASSO) regression and Cox regression analysis were used to select the most appropriate overall survival (OS)-related IRlncRNAPs to develop a prognostic signature. The riskScore of each sample was calculated by comparing the long noncoding RNA expression level in each IRlncRNAP. Based on the riskScore for each patient, GC patients were divided into high- and low-risk groups. Then, the correlation of the signature and riskScore with OS, clinical features, immune cell infiltration, immune-related gene (IRG) expression and chemotherapeutic efficacy in GC was analyzed.Results: A total of 107 DEIRlncRNAs were identified which formed 4297 IRlncRNAPs. Fifteen OS-related IRlncRNAPs were selected to develop a prognostic model. GC patients could be accurately classified into high- and low-risk groups according to the riskScore of the prognostic model. The 1-, 2-, 3-, and 5-year receiver operating characteristic (ROC) curves for the riskScore were drawn and the area under the curve (AUC) values were found to be 0.788, 0.810, 0.825, and 0.868, respectively, demonstrating a high sensitivity and accuracy of this prognostic signature. Moreover, the immune-related riskScore was an independent risk factor. Patients showed a poorer outcome within the high-risk group. In addition, the riskScore was found to be significantly correlated with the clinical features, immune infiltration status, IRG expression, and chemotherapeutic efficacy in GC.Conclusion: The prognostic model of IRlncRNAPs offers great promise in predicting the prognosis, immune infiltration status, and chemotherapeutic efficacy in GC, which might be helpful for the selection of chemo- and immuno-therapy of GC.

Identification of Novel Tumor Microenvironment-Related Long Noncoding RNAs to Determine the Prognosis and Response to Immunotherapy of Hepatocellular Carcinoma Patients

“…For instance, lncRNA-ROR, a stress-responsive lncRNA highly expressed in HCC cells and enriched in extracellular vesicles derived from tumor cells, could induce primary chemoresistance by activating the TGF-β pathway in HCC (Takahashi et al, 2014). Moreover, immune-related lncRNA signatures have been reported as prognostic biomarkers and therapeutic targets in several tumors, including lung adenocarcinoma, bladder cancer, esophageal cancer, gastric cancer, rectal cancer, cervical cancer, and HCC (Chen et al, 2021;Lai et al, 2021;Liu et al, 2021;Nie et al, 2021;Pang et al, 2021;Song et al, 2021;Xing et al, 2021;Ye et al, 2021), indicating that immune-related lncRNAs could effectively be applied to determine the survival, prognosis, and treatment response. However, all these studies focused on excerpting the immune-related lncRNA profiles from the obtained immune-related genes based on co-expression analysis while ignoring the important role of the stromal components in tumor progression; immune-related genes remain inconclusive in different research studies, and there are no uniform criteria for filtering immune-related lncRNAs, which may limit the generalization of the predictive model.…”

An Immune-Related Long Noncoding RNA Pair as a New Biomarker to Predict the Prognosis of Patients in Breast Cancer

“…Based on the data acquired above, irlncRNAs were screened from the TCGA-BRCA database, and the limma R package (version 3.6.3, https://www.r-project.org ) was used to perform the differential expression analysis among irlncRNAs ( Song S. et al, 2021 ), aiming to select DEirlncRNAs with the criteria of |log Fold Change (logFC)| 1.5 and P 0.05. Then, univariate Cox regression analysis was conducted based on the clinical survival time to extract DEirlncRNAs with significance, using p < 0.01 as an identifying threshold.…”

Analysis of Pyroptosis-Related Immune Signatures and Identification of Pyroptosis-Related LncRNA Prognostic Signature in Clear Cell Renal Cell Carcinoma

“…For example, lncRNA-XIST can inhibit pyroptosis to promote non-small cell lung cancer ( Liu et al, 2019 ) and lncRNA ADAMTS9-AS2 restrains gastric cancer and increases the drug sensitivity of cisplatin by promoting pyroptosis ( Ren et al, 2020 ). Pyroptosis-related lncRNA (PRlncRNA) signature has been established as a model to predict the treatment effect and prognoses of various cancers ( Hong et al, 2020 ; Bu et al, 2021 ; Lv et al, 2021 ; Ping et al, 2021 ; Song S. et al, 2021 ; Tang et al, 2021 ). However, as a result of the differences in data processing, it is impossible to directly compare the difference in absolute expression levels of lncRNAs among different data sets.…”

“…Fortunately, the researchers found a way to normalize based on the relative ranking of lncRNAs. For instance, an example of applying these methods was long noncoding RNA pairs (lncRNAPs), which have proved to be reliable ( Hong et al, 2020 ; Song S. et al, 2021 ).…”