Xu Zifan, Lei Zi, Peng Shilan, Li Sha, Kong Dehui, Duan Hongqiong, Zhang Man, Su Guomiao, Pan Guoqing
Department of Pathology, Kunming Medical University, Kunming, Yunnan, China.
Department of Pathology, First Affliated Hospital of Kunming Medical University, Kunming, China.
Front Genet. 2025 Jul 2;16:1541489. doi: 10.3389/fgene.2025.1541489. eCollection 2025.
The progression of gastric cancer (GC) is closely linked to macrophage polarization and protein lactylation; however, its underlying mechanisms remain poorly understood. This study aimed to elucidate the molecular mechanisms of GC using transcriptomic analysis.
Candidate genes were identified by intersecting differentially expressed genes with key module genes associated with protein lactylation and macrophage polarization. Protein-protein interaction analysis was performed to uncover interacting genes. Prognostic genes were determined using univariate Cox regression and machine learning techniques, with model accuracy assessed via training and validation datasets. Further, enrichment analysis, immune infiltration profiling, gene mutation analysis, and drug sensitivity assessments were conducted for high- and low-risk groups. Chromosomal localization, gene-gene interaction network analysis, and expression validation of prognostic genes were also performed.
Two prognostic genes, ERCC6L and MYB, were identified as significant markers of prognosis through comprehensive analyses. A risk model based on these genes accurately predicted survival in patients with GC. Enrichment analysis revealed pathways such as the muscle myosin complex and adipogenesis as significantly involved in GC. Immune infiltration analysis identified 13 immune cell types, including monocytes, with strong associations to the prognostic genes. TTN, TP53, and MUC16 exhibited the highest mutation rates in both risk groups. Drug sensitivity analysis highlighted AZD.0530, CCT007093, DMOG, JNJ.26854165, and LFM.A13 as promising therapeutic candidates. ERCC6L is located on chromosome X, while MYB is located on chromosome 6. Gene-gene interaction network analysis revealed interactions between prognostic genes and other key genes. In both datasets, expression of prognostic genes was significantly higher in the GC cohort.
This study identified ERCC6L and MYB as key prognostic genes, facilitating the development of a risk model that offers novel insights into potential therapeutic strategies for GC.
胃癌（GC）的进展与巨噬细胞极化和蛋白质乳酰化密切相关；然而，其潜在机制仍知之甚少。本研究旨在通过转录组分析阐明GC的分子机制。
通过将差异表达基因与与蛋白质乳酰化和巨噬细胞极化相关的关键模块基因进行交叉，鉴定候选基因。进行蛋白质-蛋白质相互作用分析以揭示相互作用基因。使用单变量Cox回归和机器学习技术确定预后基因，并通过训练和验证数据集评估模型准确性。此外，对高风险和低风险组进行了富集分析、免疫浸润分析、基因突变分析和药物敏感性评估。还进行了预后基因的染色体定位、基因-基因相互作用网络分析和表达验证。
通过综合分析，鉴定出两个预后基因ERCC6L和MYB作为预后的重要标志物。基于这些基因的风险模型准确预测了GC患者的生存率。富集分析显示肌肉肌球蛋白复合体和脂肪生成等途径与GC密切相关。免疫浸润分析确定了13种免疫细胞类型，包括与预后基因有强关联的单核细胞。TTN、TP53和MUC16在两个风险组中均表现出最高的突变率。药物敏感性分析突出了AZD.0530、CCT007093、DMOG、JNJ.26854165和LFM.A13作为有前景的治疗候选药物。ERCC6L位于X染色体上，而MYB位于6号染色体上。基因-基因相互作用网络分析揭示了预后基因与其他关键基因之间的相互作用。在两个数据集中，GC队列中预后基因的表达均显著更高。
本研究确定ERCC6L和MYB为关键预后基因，有助于开发风险模型，为GC的潜在治疗策略提供新见解。
