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• W4256272045 abstract "Abstract Background: Immune-related long noncoding RNAs (irlncRNAs) have been demonstrated to be actively involved in the regulation of immune status. With this study, we aimed to establish a risk model of irlncRNAs and further investigate the roles of irlncRNAs in prognosis prediction and the immune landscape in pancreatic cancer. Methods: The transcriptome profiles and clinical information of pancreatic cancer patients were retrieved from The Cancer Genome Atlas (TCGA). Immune-related genes (irgenes) downloaded from ImmPort were used to screen the lncRNAs by correlation analysis (R>0.5, p<0.001). Random survival forest (RSF) and survival tree analysis showed that 9 irlncRNAs were highly correlated with overall survival (OS) according to the variable importance (VIMP) and the minimal depth. Then, Cox regression was used to establish a risk model with 3 irlncRNAs, which was evaluated by Kaplan-Meier analysis. In addition, we performed Cox regression analysis to establish the clinical prognostic model, which showed that the risk score was the only independent prognostic factor (p<0.001). A nomogram was drawn to visualize the clinical features. Wilcoxon signed-rank test and analysis of the correlations between the risk score and immune cells was applied to explore the potential irlncRNAs related to immune status. Results: A total of 176 samples were randomly divided into a training set (n=123) and a test set (n=53). A total of 1903 irlncRNAs were identified after Pearson correlation analysis between irgenes and lncRNAs. A total of 9 irlncRNAs were identified in the survival tree analysis, and 3 irlncRNAs (LINC00462, LINC01887, RP11-706C16.8) were used to establish a risk model. The areas under curve (AUC) of the receiver operating characteristic (ROC) for 36 months, 30 months, 24 months, 18 months, 12 months and 6 months were 0.778, 0.774, 0.751, 0.753, 0.780 and 0.756, respectively, with a concordance index (C-index) of 0.696. In the clinical prognostic model, the C-index increased from 0.599 to 0.682 after combining the risk scores. Furthermore, a high risk was associated with increased infiltration of CD4+ T cells, M0 macrophages and M1 macrophages. Conclusions: We established a novel three-irlncRNA risk model. The clinical evaluation showed its robustness in predicting the prognosis and immune landscape of pancreatic cancer." @default.
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• W4256272045 date "2021-05-05" @default.
• W4256272045 modified "2023-09-29" @default.
• W4256272045 title "Construction of a Novel Risk Model Based on the Random Forest Algorithm to Distinguish Pancreatic Cancers with Different Prognoses and Immune Microenvironment Features" @default.
• W4256272045 doi "https://doi.org/10.21203/rs.3.rs-454599/v1" @default.
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