Identification of the Immune Subtypes for the Prediction of Metastasis in Pancreatic Neuroendocrine Tumors

Abstract

Introduction: Most patients with pancreatic neuroendocrine tumors (pNETs) present with unresectable or metastatic disease. Increasing evidence shows that the immune cell infiltration patterns play a pivotal role in tumor progression in pNETs. Nonetheless, there has been no comprehensive analysis of the effect of immune infiltration patterns on metastasis. Methods: The gene expression profiling dataset and clinical data were obtained from the Gene Expression Omnibus database. Estimation of Stromal and Immune Cells in Malignant Tumors using the Expression Data and single-sample Gene Set Enrichment Analysis were used to uncover the landscape of the tumor immune microenvironment. Subtypes based on the immune infiltration patterns were identified by the unsupervised clustering algorithm. Differentially expressed genes were identified using the limma packages of R. Functional enrichment analyses of these genes were carried out using STRING, Kyoto Encyclopedia of Genes and Genomes, and Reactome. Results: The landscape of immune cells in pNET samples was constructed, and three immune cell infiltration subtypes (Immunity-H, Immunity-M, and Immunity-L) were identified. Immune cell infiltration degrees and metastasis were positively correlated. A protein-protein interaction network containing 80 genes was constructed, and functional enrichment revealed that these genes were mainly enriched in immune-related pathways. Eleven metastasis-related genes were differentially expressed among three subtypes, including MMP14, MMP2, MMP12, MMP7, SPARC, MMP19, ITGAV, MMP23B, MMP1, MMP25, and MMP9. There is a certain consistency of immune infiltration pattern between the primary tumor and metastatic tumor samples. Conclusion: Our findings may deepen the understanding of the immune-mediated regulatory mechanisms underlying pNETs and may provide some promising targets for immunotherapy.