Abstract
Pancreatic ductal adenocarcinoma (PDAC) is a malignant tumor characterized by rapid progression, early metastasis, high recurrence, and limited responsiveness to conventional therapies. The 5-year survival rate of PDAC is extremely low (<8%), which lacks effective prognostic evaluation indicators. In this study, we used xCell to analyze infiltrating immune cells in a tumor and through the univariate and multivariate Cox analyses screened out two prognosis-related immune cells, CD4+TN and common lymphoid progenitor (CLP), which were used to construct a Cox model and figure out the risk-score. It was found that the constructed model could greatly improve the sensitivity of prognostic evaluation, that the higher the risk-score, the worse the prognosis. In addition, the risk-score could also identify molecular subtypes with poor prognosis and immunotherapy sensitivity. Through transcriptome and whole-exome sequencing analysis of PDAC dataset from The Cancer Genome Atlas (TCGA), it was found that copy number deletion and low expression of CCL19 might be crucial factors to affect the risk-score. Lastly, validation of the above findings was confirmed not only in Gene Expression Omnibus (GEO) datasets but also in our PDAC patient samples, Peking2020 cohort.