Identification of tumour immune microenvironment-related alternative splicing events for the prognostication of pancreatic adenocarcinoma

Abstract

Purpose Pancreatic adenocarcinoma (PAAD) is characterized by low antitumour immune cell infiltration in an immunosuppressive microenvironment. This study aimed to systematically explore the impact on prognostic alternative splicing events (ASs) of tumour immune microenvironment (TIME) in PAAD. Methods The ESTIMATE algorithm was implemented to compute the stromal/immune-related scores of each PAAD patient, followed by Kaplan–Meier (KM) survival analysis of patients with different scores grouped by X-tile software. TIME-related differentially expressed ASs (DEASs) were determined and evaluated through functional annotation analysis. In addition, Cox analyses were implemented to construct a TIME-related signature and an AS clinical nomogram. Moreover, comprehensive analyses, including gene set enrichment analysis (GSEA), immune infiltration, immune checkpoint gene expression, and tumour mutation were performed between the two risk groups to understand the potential mechanisms. Finally, Cytoscape was implemented to illuminate the AS-splicing factor (SF) regulatory network. Results A total of 437 TIME-related DEASs significantly related to PAAD tumorigenesis and the formation of the TIME were identified. Additionally, a robust TIME-related prognostic signature based on seven DEASs was generated, and an AS clinical nomogram combining the signature and four clinical predictors also exhibited prominent discrimination by ROC (0.762 ~ 0.804) and calibration curves. More importantly, the fractions of CD8 T cells, regulatory T cells and activated memory CD4 T cells were lower, and the expression of four immune checkpoints—PD-L1, CD47, CD276, and PVR—was obviously higher in high-risk patients. Finally, functional analysis and tumour mutations revealed that aberrant immune signatures and activated carcinogenic pathways in high-risk patients may be the cause of the poor prognosis. Conclusion We extracted a list of DEASs associated with the TIME through the ESTIMATE algorithm and constructed a prognostic signature on the basis of seven DEASs to predict the prognosis of PAAD patients, which may guide advanced decision-making for personalized precision intervention.

Mining of clinical and prognosis related genes in the tumor microenvironment of endometrial cancer

“…In this study, we comprehensively analyzed TME in ltrating immune cells, stromal cells, and their related genes in EC, and analyzed the correlation between the data and clinicopathological information and prognosis.The sequencing data and clinical information of EC were obtained from TCGA database.The ESTIMATE algorithm was used to calculate the immune/stromal scores and analyze the relationship between the scores and prognosis and clinicopathological information of EC. The ESTIMATE algorithm is a reliable and widely accepted algorithm, which is used in various cancers, such as lung cancer [19],osteosarcoma [29],breast cancer [30],bladder cancer [31], pancreatic carcinoma [32].Our data showed that the immune score was positively correlated with EC prognosis, and patients with high immune score had a longer survival time, while patients with low immune score had a shorter survival time. In addition,the immune score was correlated with tumor grade.Patients with high immune score had good tumor differentiation, while those with low immune score had poor tumor differentiation.This was consistent with the results of previous studies that the clinical outcome of G1 and G2 EC patients was better than that of G3 patients [33].Current studies shown that TME components affected the clinical outcome of EC, and the immune cells in TME may be one of the mechanisms contributing to the good prognosis of well-differentiated EC.…”

Alternative splicing event associated with immunological features in bladder cancer

“…AS was considered an essential mechanism of mRNA variation and proteomic diversity of many cancers ( 24 ). Increasing studies have provided strong evidence to support that AS could be an effective biomarker for predicting prognosis and immunotherapy immunotherapeutic outcomes in a series of tumors, such as hepatocellular carcinoma ( 25 ), pancreatic adenocarcinoma ( 26 ), and breast cancer ( 27 ). However, the relationship between AS events and immunological features in BLCA is still under investigation.…”

Cellular Membrane Localization of Innate Immune Checkpoint Molecule CD47 Is Regulated by Radixin in Human Pancreatic Ductal Adenocarcinoma Cells

“…In this study, we confirmed that KP-2 cells derived from human PDAC had sufficient expression of CD47, ezrin, and radixin at both the mRNA and protein levels, while displaying a lack of moesin ( Figure 1 ; Figure S3 ). Previous studies have found that CD47 is highly expressed in clinical PDAC samples and numerous human PDAC cell lines [ 18 , 44 , 45 , 46 , 47 ]. Furthermore, several studies on clinical human PDAC tissues and freshly isolated primary human PDAC have revealed the presence of ezrin and radixin, but not moesin, at the mRNA and protein levels [ 40 , 41 , 42 , 43 ], implying that KP-2 cells have expression profiles similar to those of the ERM family found in patients with PDAC.…”