Li Bangjie, Hu Jialiang, Xu Hanmei
Jiangsu Province Engineering Research Center of Synthetic Peptide Drug Discovery and Evaluation, China Pharmaceutical University, Nanjing, China.
State Key Laboratory of Natural Medicines, Ministry of Education, China Pharmaceutical University, Nanjing, China.
Front Immunol. 2024 Nov 20;15:1455383. doi: 10.3389/fimmu.2024.1455383. eCollection 2024.
Liver fibrosis is a pathological response to liver damage induced by multiple etiologies including NASH and CCl, which may further lead to cirrhosis and hepatocellular carcinoma (HCC). Despite the increasing understanding of liver fibrosis and HCC, clinical prognosis and targeted therapy remain challenging.
This study integrated single-cell sequencing analysis, bulk sequencing analysis, and mouse models to identify highly expressed genes, cell subsets, and signaling pathways associated with liver fibrosis and HCC. Clinical prediction models and prognostic genes were established and verified through machine learning, survival analysis, as well as the utilization of clinical data and tissue samples from HCC patients. The expression heterogeneity of the core prognostic gene, along with its correlation with the tumor microenvironment and prognostic outcomes, was analyzed through single-cell analysis and immune infiltration analysis. In addition, the cAMP database and molecular docking techniques were employed to screen potential small molecule drugs for the treatment of liver fibrosis and HCC.
We identified 40 pathogenic genes, 15 critical cell subsets (especially Macrophages), and regulatory signaling pathways related to cell adhesion and the actin cytoskeleton that promote the development of liver fibrosis and HCC. In addition, 7 specific prognostic genes (CCR7, COL3A1, FMNL2, HP, PFN1, SPP1 and TENM4) were identified and evaluated, and expression heterogeneity of core gene SPP1 and its positive correlation with immune infiltration and prognostic development were interpreted. Moreover, 6 potential small molecule drugs for the treatment of liver fibrosis and HCC were provided.
The comprehensive investigation, based on a bioinformatics and mouse model strategy, may identify pathogenic genes, cell subsets, regulatory mechanisms, prognostic genes, and potential small molecule drugs, thereby providing valuable insights into the clinical prognosis and targeted treatment of liver fibrosis and HCC.
肝纤维化是对包括非酒精性脂肪性肝炎(NASH)和四氯化碳(CCl)在内的多种病因引起的肝损伤的病理反应,可能进一步导致肝硬化和肝细胞癌(HCC)。尽管对肝纤维化和HCC的认识不断增加,但临床预后和靶向治疗仍然具有挑战性。
本研究整合了单细胞测序分析、批量测序分析和小鼠模型,以鉴定与肝纤维化和HCC相关的高表达基因、细胞亚群和信号通路。通过机器学习、生存分析以及利用HCC患者的临床数据和组织样本,建立并验证了临床预测模型和预后基因。通过单细胞分析和免疫浸润分析,分析了核心预后基因的表达异质性及其与肿瘤微环境和预后结果的相关性。此外,利用cAMP数据库和分子对接技术筛选治疗肝纤维化和HCC的潜在小分子药物。
我们鉴定了40个致病基因、15个关键细胞亚群(特别是巨噬细胞)以及与细胞粘附和肌动蛋白细胞骨架相关的调节信号通路,这些通路促进肝纤维化和HCC的发展。此外,鉴定并评估了7个特定的预后基因(CCR7、COL3A1、FMNL2、HP、PFN1、SPP1和TENM4),并解释了核心基因SPP1的表达异质性及其与免疫浸润和预后发展的正相关性。此外,还提供了6种治疗肝纤维化和HCC的潜在小分子药物。
基于生物信息学和小鼠模型策略的综合研究,可能鉴定致病基因、细胞亚群、调节机制、预后基因和潜在小分子药物,从而为肝纤维化和HCC的临床预后和靶向治疗提供有价值的见解。