British journal of cancer · 2026
Lactylation-related prognostic signature characterized in pancreatic ductal adenocarcinoma through public scRNA-seq dataset and machine learning algorithms: the TOP2A-H3K18la-NQO1 axis orchestrates malignant progression.
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Tang Haodong, Xu Tonglei, Liu Li, Du Yusheng, Liu Dan, Tan Siyuan, Shen Peiyuan, Hu Aozhong, Shi Xiangxu, Ma Hongqin, Wang Ji, Zhao Wenxing
Аннотация
BACKGROUND: Lactate promotes histone lactylation, which affects protein transcription and translation, thereby influencing tumour cell progression. However, the role of lactylation in pancreatic ductal adenocarcinoma (PDAC) remains underexplored and warrants further investigation.
METHODS: Single-cell RNA sequencing (scRNA-seq) data (GSE154778) underwent quality control, dimensionality reduction, and clustering. Lactylation scores were computed using the "AUCell" R package, and differential expression between high and low lactylation groups was analysed. A risk score model based on lactylation was developed using TCGA-PAAD, GSE57495, and GSE79668 datasets. The relationships between risk scores, clinical features, immune profiles, mutation burden, and biological functions were assessed. CUT&Tag analysis was employed to identify the target of TOP2A mediated by H3K18la. In vitro experiments, including CCK-8 assay, colony formation assay, wound healing assay, transwell migration assay, lactate quantification, Western blotting, and qRT‒PCR, in combination with subcutaneous xenograft models, were conducted to further validate the findings.
RESULTS: We successfully established a lactylation-based prognostic risk score model for PDAC, which effectively distinguishes patient survival and biological characteristics. Additionally, we demonstrated that the lactate-TOP2A-H3K18la-NQO1 signalling axis forms a positive feedback loop that accelerates the malignant progression of PDAC.
CONCLUSIONS: This study presents a lactylation-related risk score model with significant potential for improving the management of PDAC patients. The identification of the lactate-TOP2A-H3K18la-NQO1 axis enhances the understanding of lactylation mechanisms in PDAC, thereby providing a foundation for targeted therapeutic approaches.
METHODS: Single-cell RNA sequencing (scRNA-seq) data (GSE154778) underwent quality control, dimensionality reduction, and clustering. Lactylation scores were computed using the "AUCell" R package, and differential expression between high and low lactylation groups was analysed. A risk score model based on lactylation was developed using TCGA-PAAD, GSE57495, and GSE79668 datasets. The relationships between risk scores, clinical features, immune profiles, mutation burden, and biological functions were assessed. CUT&Tag analysis was employed to identify the target of TOP2A mediated by H3K18la. In vitro experiments, including CCK-8 assay, colony formation assay, wound healing assay, transwell migration assay, lactate quantification, Western blotting, and qRT‒PCR, in combination with subcutaneous xenograft models, were conducted to further validate the findings.
RESULTS: We successfully established a lactylation-based prognostic risk score model for PDAC, which effectively distinguishes patient survival and biological characteristics. Additionally, we demonstrated that the lactate-TOP2A-H3K18la-NQO1 signalling axis forms a positive feedback loop that accelerates the malignant progression of PDAC.
CONCLUSIONS: This study presents a lactylation-related risk score model with significant potential for improving the management of PDAC patients. The identification of the lactate-TOP2A-H3K18la-NQO1 axis enhances the understanding of lactylation mechanisms in PDAC, thereby providing a foundation for targeted therapeutic approaches.