Establishment of a Novel Signature to Predict Prognosis and Immune Characteristics of Pancreatic Cancer Based on Necroptosis-Related Long Non-Coding RNA

Abstract

Background Necroptosis plays an important role in tumor genesis and progression. Long non-coding RNAs (IncRNAs) have been proven a regulatory factor of necroptosis in various tumors. However, the real role of necroptosis-related lncRNAs (NRLs) and their potential to predict the prognosis of pancreatic cancer (PC) remain largely unclear. Methods 178 PC patients' RNA sequencing data and clinical profiles were downloaded from The Cancer Genome Atlas (TCGA) database. NRLs were identified using Pearson correlation analysis. Then, patients were divided into the training set and the validation set at a 1 : 1 ratio. Subsequently, Cox and LASSO regression analyses were conducted to establish a prognostic NRLs signature in the training set and validation set. The predictive efficacy of the 5-NRLs signature was assessed by survival analysis, nomogram, COX regression, clinicopathological features correlation analysis, and the operating characteristic (ROC) curve. Furthermore, correlations between the risk score (RS) and immune cell infiltration, immune checkpoint molecules, somatic gene mutations, and anticancer drug sensitivity were analyzed. Results A 5-NRLs signature was established to predict the prognostic of PC, including LINC00857, AL672291.1, PTPRN2-AS1, AC141930.2, and MEG9. The 5-NRLs signature demonstrated a high degree of predictive power according to ROC and Kaplan-Meier curves, and was revealed to be an independent risk factor for prognosis via stratified survival analysis. Nomogram and calibration curves indicated the clinical adaptability of the signature. Additionally, immune cell infiltration, immune checkpoint molecules, somatic gene mutations and half-inhibitory concentration were significantly different between two risk subtypes. Conclusions The novel 5-NRLs signature is helpful for assessing the prognosis of PC patients and improving therapy options, so it can be further applied clinically.