Wang Donghua, Lv Long, Du Jinghu, Tian Kui, Chen Yu, Chen Manyu
Department of Coloproctological Surgery, Xiangyang Central Hospital, Affiliated Hospital of Hubei University of Arts and Science, Xiangyang, Hubei, China.
Chem Biol Drug Des. 2024 Dec;104(6):e70026. doi: 10.1111/cbdd.70026.
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.
胰腺癌（PC）是全球癌症相关死亡的主要原因，因此需要新的生物标志物、治疗靶点和候选药物。在这项研究中，分析了三个与PC相关的微阵列数据集（GSE183795、GSE28735和GSE62452）。使用R语言中的limma软件包获得PC的差异表达基因（DEG）。采用加权基因共表达网络分析（WGCNA）和机器学习方法筛选枢纽基因。利用Kaplan-Meier绘图仪和受试者工作特征（ROC）曲线分析评估枢纽基因的诊断效能。通过分子对接和分子动力学模拟评估天然生物活性成分与枢纽蛋白之间的结合能力。采用CCK-8、流式细胞术、Transwell和蛋白质印迹分析来分析PC细胞的活力、凋亡、细胞周期进程、侵袭和信号通路变化。此外，使用裸鼠模型评估PC细胞在体内的侵袭性。在本研究中，共鉴定出988个DEG，主要富集于细胞黏附及PI3K-Akt信号通路，并进一步鉴定出两个核心基因TRIM16和PRC1。TRIM16和PRC1高表达患者的总生存期较短。飞燕草素（Del）与TRIM16和PRC1均具有良好的结合亲和力，并且Del可以抑制PC细胞的活力、侵袭和转移，并诱导细胞凋亡及G0/G1期阻滞。此外，Del可以促进PC细胞中p53的激活并抑制PI3K/AKT信号通路的激活。综上所述，TRIM16和PRC1被鉴定为PC的预后生物标志物和治疗靶点，Del与它们具有良好的结合亲和力，可能是PC的潜在治疗药物。
