Chen Di, Huang Ju, Yang Aiming, Xiong Zhifan
Department of Gastroenterology, Yantai Yuhuangding Hospital, Qingdao University, Yantai, China.
Department of Gastroenterology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing, 100730, China.
Biol Direct. 2025 Mar 24;20(1):35. doi: 10.1186/s13062-025-00636-9.
Protein kinases are essential cellular signal modulators involved in tumorigenesis, metastasis, immune response, and drug resistance. However, the comprehensive features and clinical significance of protein kinases in gastric cancer (GC) remain inconclusive.
We analyzed the transcriptional profiles of protein kinases in GC patients from the GEO and TCGA databases. Based on differentially expressed kinase genes (DE-KGs), a novel cluster was identified to assess its association with patient survival and the tumor microenvironment (TME) in GC. Subsequently, an optimal DE-KGs-based model (DE-KGsM) was determined using 101 machine-learning algorithm combinations. This model was evaluated using multi-omics data to investigate its associations with patient prognosis, clinical features, tumor microenvironment, tumor-infiltrating immune cells (TIICs), and immunotherapy response. Furthermore, scRNA-seq analysis and TIMER algorithm were applied to determine the correlation between the hub gene (ABL2) in the DE-KGsM and Macrophages. Finally, in vitro experiments were performed to explore the immune-related mechanisms of ABL2 in GC.
We identified two molecular subtypes of GC patients based on 64 DE-KGs expression. Significant differences were observed in overall survival and TIIC characteristics between Cluster 1 and Cluster 2. Among these 64 DE-KGs, we identified an optimal DE-KGsM that could be a prognostic indicator in GC. TIICs and TIDE analyses exhibited that GC patients in the high-DE-KGsM score group had a higher proportion of M2 macrophages and lower response rates to ICI treatment. scRNA-seq analysis indicated that ABL2 might play an indispensable role in tumor immunity. Furthermore, in vitro experiments demonstrated that ABL2 accelerated the proliferation, migration, and invasion of GC cells, as well as the polarization of M2 macrophages.
The DE-KGsM could be a powerful predictor of GC patients' survival and might facilitate the development of personalized therapy. Furthermore, as a hub gene in the DE-KGsM, ABL2 could be an immunological biomarker that modulates the polarization of M2 macrophages, thereby promoting GC progression.
Not applicable.
蛋白激酶是参与肿瘤发生、转移、免疫反应和耐药性的重要细胞信号调节剂。然而,蛋白激酶在胃癌(GC)中的综合特征和临床意义仍不明确。
我们分析了来自GEO和TCGA数据库的GC患者中蛋白激酶的转录谱。基于差异表达激酶基因(DE-KGs),鉴定了一个新的聚类,以评估其与GC患者生存和肿瘤微环境(TME)的关联。随后,使用101种机器学习算法组合确定了基于最佳DE-KGs的模型(DE-KGsM)。使用多组学数据对该模型进行评估,以研究其与患者预后、临床特征、肿瘤微环境、肿瘤浸润免疫细胞(TIICs)和免疫治疗反应的关联。此外,应用scRNA-seq分析和TIMER算法确定DE-KGsM中的枢纽基因(ABL2)与巨噬细胞之间的相关性。最后,进行体外实验以探索ABL2在GC中的免疫相关机制。
我们基于64个DE-KGs的表达鉴定了GC患者的两种分子亚型。在Cluster 1和Cluster 2之间观察到总生存期和TIIC特征存在显著差异。在这64个DE-KGs中,我们鉴定了一个最佳的DE-KGsM,它可能是GC的一个预后指标。TIICs和TIDE分析表明,高DE-KGsM评分组的GC患者M2巨噬细胞比例较高,对ICI治疗的反应率较低。scRNA-seq分析表明,ABL2可能在肿瘤免疫中发挥不可或缺的作用。此外,体外实验表明,ABL2促进了GC细胞的增殖、迁移和侵袭,以及M2巨噬细胞的极化。
DE-KGsM可能是GC患者生存的有力预测指标,并可能促进个性化治疗的发展。此外,作为DE-KGsM中的枢纽基因,ABL2可能是一种免疫生物标志物,可调节M2巨噬细胞的极化,从而促进GC进展。
不适用。