Systematic Analysis of Molecular Subtypes Based on the Expression Profile of Immune-Related Genes in Pancreatic Cancer.

Abstract

Immunotherapy has a good therapeutic effect and provides a new approach for cancer treatment. However, only limited studies have focused on the use of molecular typing to construct an immune characteristic index for gene expression in pancreatic adenocarcinoma (PAAD) and to assess the effectiveness of immunotherapy in patients with PAAD. Clinical follow-up data and gene expression profile of PAAD patients were retrieved from The Cancer Genome Atlas (TCGA) database. Based on 184 immune features, molecular subtypes of pancreatic cancer were found by the "ConsensusClusterPlus" package, and the association between clinical features and immune cell subtype distribution was analysed. In addition, the relationship between the proportion of immune subtypes and the expression of immune checkpoints was analysed. The CIBERSORT algorithm was introduced to evaluate the immune scores of different molecular subtypes. We used the tumor immune dysfunction and exclusion (TIDE) algorithm to assess the potential clinical effect of immunotherapy interventions on single-molecule subtypes. In addition, the oxidative stress index was constructed by linear discriminant analysis DNA (LDA), and weighted correlation network analysis was performed to identify the core module of the index and its characteristic genes. Expression of hub genes was verified by immunohistochemical analysis in an independent PAAD cohort. Pancreatic cancer is divided into three molecular subtypes (IS1, IS2, and IS3), with significant differences in prognosis between multiple cohorts. Expression of immune checkpoint-associated genes was significantly reduced in IS3 and higher in IS1 and IS2, suggesting that the three subgroups have different responsiveness to immunotherapy interventions. The results of the CIBERSORT analysis showed that IS1 exhibited the highest levels of immune infiltration, whereas the results of the TIDE analysis showed that the T-cell dysfunction score of IS1 was higher than that of IS2 and IS3. Furthermore, IS3 was found to be more sensitive to 5-FU and to have a higher immune signature index than IS1 and IS2. Based on WGCNA analysis, 10 potential gene markers were identified, and their expression at the protein level was verified by immunohistochemical analysis. Specific molecular expression patterns in pancreatic cancer can predict the efficacy of immunotherapy and influence the prognosis of patients.