BACKGROUND: Pancreatic ductal adenocarcinoma (PDAC) is among the most aggressive cancers, with rising incidence and limited responsiveness to immunotherapy due to its highly suppressive tumor microenvironment (TME). Tertiary lymphoid structures (TLS), ectopic formation structures of immune cells, are linked to better prognosis and improved immunotherapy responses in PDAC. Understanding TLS's role in PDAC could enhance immunotherapy effectiveness. METHODS: This study integrated transcriptomic and clinical data from 310 PDAC patients in GEO database. We performed consensus clustering using tumor-associated TLS (TA-TLS) genes, identifying three distinct molecular subtypes. Single-sample gene set enrichment analysis (ssGSEA) was then employed to calculate a TLS score for each patient, allowing for TLS-based evaluation. Key prognostic genes were identified using an iterative LASSO method, leading to the construction of a risk assessment model, which was validated across independent cohorts. We further analyzed the TLS score using single-cell RNA sequencing (scRNA-seq), visualized key gene expression, and validated protein expression through immunohistochemistry (IHC). Additionally, we explored the effects of DNASE1L3 on cell proliferation and migration, and its immune-related functions using Gene Set Enrichment Analysis (GSEA) and multiplex cytokine analysis. RESULTS: Consensus clustering revealed three PDAC molecular subtypes with significant differences in prognosis, TA-TLS gene expression, and TME features. The TLS score effectively stratified patients into high and low groups, correlating with survival outcomes and TME characteristics. Our risk model, validated across cohorts, reliably predicted patient outcomes. Validation studies showed lower expression of DNASE1L3 and IL33 in tumor tissues. scRNA-seq confirmed TLS score associations with immune cells. DNASE1L3 overexpression inhibited PDAC cell proliferation and migration, with cytokine analysis indicating increased immune activity. CONCLUSIONS: This study elucidated the expression profile of TA-TLS genes in PDAC, constructed a TLS gene-based scoring system, and developed a related risk model. We also explored the functions and potential antitumor mechanisms of key genes, providing evidence and new insights for enhancing TLS-targeted immunotherapy strategies in PDAC.