Fig. 1

Workflow of the study. Step I: PR cells in PDAC were identified through scRNA-seq, and their biological functions were assessed using GO/KEGG pathway analyses. Step II: Malignancy of PR epithelial cells was assessed using InferCNV, malignant scoring, signal visualization, and pseudo-time trajectory analyses. Step III: Cell proportions for each TCGA-PAAD sample were inferred using scDeconv algorithm. Significant differences in cell proportions between TCGA-PAAD DNAm subgroups with distinct prognoses further support the association between PR cells (epithelial and T cells) and patient prognosis. Step IV: Given the critical role of epithelial and T cells in prognosis, prognostic and nomogram models were constructed and validated leveraging the corresponding cell-type-specific signatures. Step V: Relevance analysis was conducted between risk groups determined by prognostic models, covering clinical characteristics, mutation landscapes, enrichment pathways, immune cell infiltration, ICB treatment response prediction, and drug sensitivity. PR cells, prognostic-related cells; PDAC, pancreatic ductal adenocarcinoma; scRNA-seq, single-cell RNA sequencing; GO, Gene ontology; KEGG, Kyoto Encyclopedia of Genes and Genomes; TCGA, The Cancer Genome Atlas Program; DNAm, DNA methylation; K-M, Kaplan–Meier; ROC, receiver operating characteristic; TME, tumor microenvironment; ICB, immune-checkpoint blockade