Integrated analysis of necroptosis-related lncRNAs for prognosis and immunotherapy of patients with pancreatic adenocarcinoma

Abstract

Accumulating studies have revealed that necroptosis plays a vital role in the occurrence and development of pancreatic adenocarcinoma (PAAD). We aimed to construct a prognostic model for PAAD on the basis of necroptosis-related lncRNAs (NRLs). A coexpression network between necroptosis-related mRNAs and NRLs based on The Cancer Genome Atlas (TCGA) was constructed. Then, differentially expressed necroptosis-related lncRNAs (DENRLs) were screened from TCGA and Genotype-Tissue Expression project (GTEx) datasets. Univariate Cox regression (uni-Cox) analysis was performed on these DENRLs to identify lncRNAs significantly correlated with prognosis. Least absolute shrinkage and selection operator (LASSO) regression was performed for preventing overfitting on these lncRNAs. Multivariate Cox analysis (multi-Cox) was performed to establish a risk model based on lncRNAs that served as an independent prognostic factor. Next, the Kaplan–Meier analysis, time-dependent receiver operating characteristics (ROC), uni-Cox, multi-Cox regression, nomogram, and calibration curves were constructed to support the accuracy of the model. Gene set enrichment analysis (GSEA) and single-sample GSEA (ssGSEA) were also performed on risk groups, and it was found that the low-risk group was closely correlated with immune infiltration and immunotherapy. To further evaluate the immune differences between different clusters, we divided the patients into two clusters. Cluster 2 was more significantly infiltrated with immune cells and had higher immune scores. These results shed new light on the pathogenesis of PAAD based on NRLs and develop a prognostic model for diagnosing and guiding personalized immunotherapy of PAAD patients.