TRIM16 and PRC1 Are Involved in Pancreatic Cancer Progression and Targeted by Delphinidin

• Published in: Chemical biology & drug design 2024-12, Vol.104 (6), p.e70026-n/a
• Main Authors: Wang, Donghua, Lv, Long, Du, Jinghu, Tian, Kui, Chen, Yu, Chen, Manyu
• Format: Article
• Language: English
• Subjects: Animals; Anthocyanins - chemistry; Anthocyanins - metabolism; Anthocyanins - pharmacology; Apoptosis - drug effects; cell cycle; Cell Cycle Proteins - drug effects; Cell Cycle Proteins - metabolism; Cell Line, Tumor; Cell Movement - drug effects; Cell Proliferation - drug effects; delphinidin; Gene Expression Regulation, Neoplastic - drug effects; Humans; machine learning; Mice; Mice, Inbred BALB C; Mice, Nude; molecular docking; Molecular Docking Simulation; Molecular Dynamics Simulation; pancreatic cancer; Pancreatic Neoplasms - drug therapy; Pancreatic Neoplasms - metabolism; Pancreatic Neoplasms - pathology; Signal Transduction - drug effects; Tripartite Motif Proteins - drug effects; Tripartite Motif Proteins - metabolism; Ubiquitin-Protein Ligases - drug effects; Ubiquitin-Protein Ligases - metabolism
• ISSN: 1747-0277; 1747-0285; 1747-0285
• DOI: 10.1111/cbdd.70026

ABSTRACT Pancreatic cancer (PC) is the leading cause of cancer‐related death worldwide, and new biomarkers, therapeutic targets, and candidate drugs are needed. In this work, three PC‐related microarray datasets (GSE183795, GSE28735, and GSE62452) were analyzed. The differentially expressed genes (DEGs) of PC were obtained with the limma package in R. Weighted gene co‐expression network analysis (WGCNA) and machine learning approaches were used to screen the hub genes. Kaplan–Meier plotter and receiver operating characteristic (ROC) curve analysis were utilized to assess the diagnostic efficacy of the hub genes. The binding ability between natural bioactive ingredients and hub proteins was evaluated by molecular docking and molecular dynamics simulation. CCK‐8, flow cytometry, transwell, and western blot assays were used to analyze the viability, apoptosis, cell cycle progression, invasion, and pathway change of PC cells. Additionally, a nude mice model was used to evaluate the aggressive properties of PC cells in vivo. In this study, a total of 988 DEGs were identified, which were mainly enriched in cell adhesion and PI3K‐Akt signaling pathway, and two core genes TRIM16 and PRC1 were further identified. The overall survival of patients with high expression of TRIM16 and PRC1 was shorter. Delphinidin (Del) had good binding affinity with both TRIM16 and PRC1, and Del could inhibit the viability, invasion, and metastasis of PC cells and induce cell apoptosis and G0/G1 phase arrest. In addition, Del could promote the activation of p53 and inhibit the activation of the PI3K/AKT signaling pathway in PC cells. In summary, TRIM16 and PRC1 are identified as prognostic biomarkers and therapeutic targets for PC, and Del has good binding affinity with them and may be a potential therapeutic agent for PC. Three pancreatic cancer‐related microarray datasets (GSE183795, GSE28735, and GSE62452) were integrated. Analysis of differentially expressed genes, WGCNA, and machine learning algorithms (LASSO, XGboost, and random forest) were combined to identify genes associated with the progression of pancreatic cancer. Natural drugs, including delphinidin, which target the core genes, tripartite motif containing 16 (TRIM16), and protein regulator of cytokinesis 1 (PRC1), were then identified. Finally, the effects of delphinidin on the phenotypes of PC cells were investigated by in vitro and in vivo experiments.