Pancreatic cancer (PCa) is a highly lethal and aggressive disease, characterized by high mortality rates. Although necroptosis plays a vital role in tumor progression, cancer metastasis, prognosis of cancer patients, necroptosis-related gene (NRG) sets have rarely been analyzed in PCa. Therefore, definition of novel necroptosis-related prognostic markers for PCa patients is urgently needed. Here, we screened 159 NRGs and identified 132 differentially expressed NRGs in The Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression (GTEx) cohorts. Next, we employed univariate and multivariate Cox proportional regression models to establish a prognostic-related NRG signature comprising five NRGs that could stratify patients into high-risk and low-risk groups. Results from survival analysis showed that patients in the high-risk had dramatically shorter overall survival (OS) rates compared with their low-risk counterparts. Results from univariate and multivariate Cox regression analysis further confirmed the independent prognostic value of the established necroptosis-related signature, and the area under receiver (AUC) of the operating curve (ROC) for 1-, 3-, 5-years was 0.72, 0.74, and 0.75, respectively. Finally, we validated the signature efficacy using an independent cohort from the Gene Expression Omnibus (GEO) database. The ROC curve confirmed the predictive capacity of the five-gene signature. Furthermore, we validated expression of the signature proteins using the Human Protein Atlas (HPA) database. In conclusion, we successfully constructed a novel necroptosis-related signature for prognosis of patients with pancreatic cancer.

Background: Extensive evidence has shown that immune cell infiltration is associated with the pathogenesis of Crohn’s disease (CD). Methods: Differentially expressed genes (DEGs) from the GSE179285 dataset in the intestinal mucosa of CD patients and healthy individuals were then identified. The infiltration pattern of 22 immune cell types was assessed using the CIBERSORT algorithm. The DEGs and 22 immune cell types were combined to find the key gene network using weighted gene co-expression network analysis (WGCNA). A linear regression model for the relationship between the expression of the hub genes in CD patients and infiltration of immune cells was also developed. The utility and accuracy of the hub genes for CD diagnosis were assessed using receiver operating characteristic (ROC) analysis. The accuracy of the model was validated using the GSE20881 dataset. Results: There were 1135 DEGs between the intestinal mucosal tissue of CD patients and healthy individuals. Of these DEGs, 711 genes were upregulated, whereas 424 of them were downregulated. There was also a significant difference in the infiltration of immune cells to the intestinal mucosal between the CD patients and healthy individuals. WGCNA revealed that the turquoise module genes were strongly correlated with the infiltration of M1 macrophages (cor =0.68, p = 10−16). Finally, the expression of GBP4, the identified hub gene, strongly correlated with the infiltration of M1 macrophages (adjusted r-squared =0.661, p < 2×10−16), and is a relatively good marker for CD diagnostic prediction (AUC =0.736). The relationship between GBP4 expression and infiltration of M1 macrophages (adjusted r-squared =0.435, p < 2×10−16) and diagnostic value of the gene (AUC =0.702) were verified using the GSE20881 validation dataset. Conclusion: The expression of GBP4 is associated with the infiltration of M1 macrophages to the intestinal mucosa of CD patients.