Abstract
PURPOSE: This study aims to integrate pancreatic cancer TCGA, GEO, and single-cell RNA-sequencing (scRNA-seq) datasets, and explore the potential prognostic markers and underlying mechanisms of the immune microenvironment of pancreatic cancer through bioinformatics methods, in vitro and in vivo assays. METHODS: Expression data and clinicopathological data of pancreatic cancer TCGA, GEO (GSE131050), single cell sequencing (PAAD_CRA001160) dataset were downloaded. We used R/Bioconductor edgeR for differential expression analysis. ClusterProfiler was utilized to perform GO enrichment analysis on differentially expressed genes. The online software CIBERSORT was used to reanalyze the mRNA expression data of pancreatic cancer. CellRanger, RunPCA, FindNeighbors, FindClusters, RunTSNE and RunUMAP were used to perform preprocessing, cell clustering and expression profile analysis on single-cell sequencing data sets. We analyzed intracellular pH with or without CA9 inhibitor SLC-0111. Indirect co-culture model of human pancreatic cancer cell lines and healthy individual-derived PBMCs were used to determine the effect of CA9-related Acidic Microenvironment on CD8+ T cells. RESULTS: The CIBERSORT analysis of TCGA pancreatic cancer transcriptome sequencing data showed that among the 22 immune microenvironment components, CD8+ T cell infiltration was significantly correlated with the prognosis of pancreatic cancer patients. The differential expression analysis of the TCGA data grouped by the level of CD8+ T cell infiltration indicates that the expression of carbonic anhydrase 9 (CA9) is the most significant, and the survival analysis suggests that CA9 is associated with the overall survival of pancreatic cancer. TCGA data and GEO data set GSE131050 expression correlation analysis suggests that CA9 and CD8 expression are closely related. Pancreatic cancer single-cell sequencing data set PAAD_CRA001160 analysis results show that CA9 is mainly expressed in pancreatic cancer cell clusters, and the expression of the cancer cell subgroup CA9 in the single-cell data set is correlated with CD8+ T cell infiltration. CONCLUSION: Pancreatic cancer cells may inhibit the infiltration of CD8+ T cells through CA9. Further exploration of its related mechanisms can be used to explore the immune escape pathway of pancreatic cancer and provides new perspectives immune targeted therapy.