Lactylation-Associated Prognostic Model and Role of ANLN in Pancreatic Ductal Adenocarcinoma

Abstract Background Pancreatic ductal adenocarcinoma (PDAC) is a malignancy tumor with poor prognosis. Lactylation, a recently discovered post-translational protein modification, plays a critical role in tumor initiation and progression. Identifying reliable prognostic markers for PDAC is of significant clinical importance.This study aims to evaluate the prognostic impact of lactylation-associated genes in PDAC. Methods Single-cell sequencing data of PDAC (GSE235452) was processed for dimensionality reduction, clustering, and cell-type annotation using the “Seurat” R package. In the Ductal cell subsets, the “CopyKAT” R package was used to identify and distinguish malignant ductal cells.Lactylation activity scores were calculated using the “AUCell” R package to classify PDAC samples into high- and low-lactylation groups. Differentially expressed genes (DEGs) between these groups were identified, and a lactylation-related prognostic model was developed using machine learning algorithms on the training dataset (GSE183795) and validated with GSE62452 and GSE28735. Immune infiltration was assessed using the “CIBERSORT” R package, and differences in immune checkpoint expression and biological characteristics were analyzed. ANLN and SLC4A4 expression levels in PDAC and adjacent normal tissues, as well as their prognostic significance, were validated using the GEPIA2 database. Western blot was performed on PDAC and normal cell lines. Following ShRNA-mediated knockdown, immunofluorescence, lactate production, colony formation, transwell, wound healing, and CCK8 assays were used to assess the role of ANLN-mediated lactylation in promoting PDAC cell proliferation, migration, and gemcitabine resistance. Immunohistochemistry was performed to analyze ANLN expression in PDAC tissues and its association with patient prognosis. Results This study identified 320 differentially expressed lactylation-associated genes (LRGs) at malignant ductal cells. The StepCox[forward] + RSF model achieved the highest c-index and identified ANLN and SLC4A4 as key prognostic LRGs. Significant differences were observed between high- and low-risk groups in immune cell infiltration, immune checkpoint expression, and biological functions. ANLN was further validated to be significantly associated with PDAC progression and prognosis using the GEPIA2 database. Clinical tissue samples and in vitro experiments confirmed that ANLN was highly expressed in PDAC and was associated with poor prognosis. ANLN regulated lactylation modification levels in PDAC cells, promoting proliferation, migration, and gemcitabine resistance. Targeting the ANLN/lactylation signaling pathway could serve as a potential therapeutic strategy for PDAC. Conclusion We developed a novel lactylation-related prognostic model that accurately identifies high-risk patients. Additionally, we demonstrated that ANLN promotes PDAC progression and gemcitabine resistance via lactylation, providing a new therapeutic strategy for PDAC management.