Hu Jinyu, Xu Qinxuan, Fei Yuchang, Tan Zhengwei, Pan Lei
Department of Oncology, First Affiliated Hospital of Zhejiang Chinese Medical University, Zhejiang Provincial Hospital of Traditional Chinese Medicine, Hangzhou, Zhejiang, China.
Department of Oncology, Department of Integrated Chinese and Western Medicine, The First People's Hospital of Jiashan, Jiaxing, Zhejiang, China.
Curr Mol Med. 2025;25(5):637-651. doi: 10.2174/0115665240290237240424054233.
Gastric Cancer (GC) has become one of the most important causes of cancer-related deaths worldwide due to its intractability. Studying the mechanisms of gastric carcinogenesis, recurrence, and metastasis, and searching for new therapeutic targets have become the main directions of today's gastric cancer research. Lactate is considered a metabolic by-product of tumor aerobic glycolysis, which can regulate tumor development through various mechanisms, including cell cycle regulation, immunosuppression, and energy metabolism. However, the effects of genes related to lactate metabolism on the prognosis and tumor microenvironmental characteristics of GC patients are unknown.
In this study, we have collected gene expression data of gastric cancer from The Cancer Genome Atlas (TCGA) and identified differentially expressed genes in gastric cancer using the "Limma" software package.
76 differentially expressed lactate metabolism-related genes were screened, and then the Least Absolute Shrinkage and Selection Operator (LASSO) and Cox regression analysis were employed that identified 8 genes, constructed Lactate Metabolism-related gene signals (LMRs), and verified the reliability of the prognostic risk mapping by using TCGA training set and TCGA internal test set. Finally, the functional enrichment analysis was employed to identify the molecular mechanism.
Eight lactate metabolism-related genes were constructed into a new predictive signal that better predicted the overall survival of gastric cancer patients and can guide clinical decisions for more precise and personalized treatment.
由于其难治性，胃癌（GC）已成为全球癌症相关死亡的最重要原因之一。研究胃癌发生、复发和转移的机制，并寻找新的治疗靶点已成为当今胃癌研究的主要方向。乳酸被认为是肿瘤有氧糖酵解的代谢副产物，它可以通过多种机制调节肿瘤发展，包括细胞周期调节、免疫抑制和能量代谢。然而，乳酸代谢相关基因对GC患者预后和肿瘤微环境特征的影响尚不清楚。
在本研究中，我们收集了来自癌症基因组图谱（TCGA）的胃癌基因表达数据，并使用“Limma”软件包鉴定了胃癌中差异表达的基因。
筛选出76个差异表达的乳酸代谢相关基因，然后采用最小绝对收缩和选择算子（LASSO）和Cox回归分析，鉴定出8个基因，构建了乳酸代谢相关基因信号（LMRs），并使用TCGA训练集和TCGA内部测试集验证了预后风险图谱的可靠性。最后，采用功能富集分析来确定分子机制。
八个乳酸代谢相关基因被构建成一个新的预测信号，能更好地预测胃癌患者的总生存期，并可指导临床决策以实现更精确和个性化的治疗。
