摘要
Abstract
Objective To construct a prognostic risk model for pancreatic cancer based on necroptosis-related long non-coding RNA(NRL).Methods The gene expression data and clinical data were from the Cancer Genome Atlas(TCGA)and GTEx databases,including 171 normal pancreas and 178 pancreatic cancer samples.LASSO regression and Cox regression analysis were used to identify NRL associated with pancreatic cancer prognosis to construct the risk model.The predictive value of the model was evaluated using receiver operating characteristic(ROC)curves and validated in the Clinical Proteomic Tumor Analysis Consortium(CPTAC)database.Gene enrichment analysis,immune infiltration analysis,and chemotherapy drug sensitivity analysis were also conducted.Results The eight NRL(LINC01559,TMEM161B-AS1,AL157392.3,AC099850.3,AC136475.3,AL162274.2,MIR217HG,UNC5B-AS)were screened for constructing the NRL risk model.Survival analysis indicated that patients in the high-risk group had poorer prognosis(P<0.001).ROC curves were both>0.6,confirming the accuracy of the model.Regression analysis confirmed that the model was an independent prognostic factor for pancreatic cancer patients(P<0.05),and CPTAC data showed that the effectiveness of this model was good.Additionally,there were significant differences(P<0.05)in pathway enrichment,immune cell infiltration,tumor mutation burden,expression of immune checkpoints,and chemotherapy drug sensitivity between the high risk and low risk groups.Conclusions The risk model constructed based on 8 NRL can effectively predicts the prognosis of pancreatic cancer,and strongly correlated with the level of immune infiltration in pancreatic cancer which may provide new reference for immunotherapy and chemotherapy drug selection.关键词
胰腺癌/lncRNA/坏死性凋亡/生物信息学/TCGA/风险模型Key words
Pancreatic cancer/lncRNA/Necroptosis/Bioinformatics/TCGA/Risk model分类
医药卫生
