The Significance of Monocyte Infiltration in the Immune Microenvironment for the Prognosis and Treatment of Pancreatic Cancer

Abstract Background A large number of studies have confirmed that immunotherapy of tumor immune microenvironment is one of the important treatment methods. In pancreatic cancer, monocytes play an important role in poor prognosis, but the mechanism and prognosis prediction methods are unclear. Methods CIBERSORT was used to identify cellular immune score and evaluate the effect of each immune cell on prognosis. The gene modules related to monocytes were obtained by weighted correlation network analysis through WGCNA package. Consensus clustering was used to screen out prognostic genes. The regression signature was generated by LASSO Cox analysis, and its reliability was verified by univariate and multivariate Cox analysis. The ssGSEA and TIDE algorithms were used to predict immune status and sensitivity to immune checkpoint blockade (ICBs) in tumor microenvironment. Finally, the expression levels of each gene in the signature were verified at tissue level and single cell level. Results High infiltration of monocytes suggests poor prognosis of pancreatic cancer. After WGCNA analysis and cluster typing, 262 genes were significantly differentially expressed and prognostic. The 6 gene (MET, ITGB6, CEP55, NUSAP1, MYEOV, LY6D) prognostic signature was established by LASSO Cox analysis. It was verified to be an independent prognostic factor for pancreatic cancer. The high-risk group had high infiltration of monocytes in the immune microenvironment and was more sensitive to ICBs. At the tissue level, all 6 genes were highly expressed in cancer tissues. At the single-cell level, MET and MYEOV were significantly higher in malignant cells and lower in monocytes. Conclusions High infiltration of monocytes affects the poor prognosis of pancreatic cancer, suggesting that the immune microenvironment has a certain research prospect for the treatment of pancreatic cancer. The monocyte-related genes signature can accurately assess the prognostic risk of pancreatic cancer.