Li Wang, Zhu Xiaoyi, Fang Jieying
NHC Key Laboratory of Hormones and Development, Tianjin Key Laboratory of Metabolic Diseases, Chu Hsien-I Memorial Hospital & Tianjin Institute of Endocrinology, Tianjin Medical University, Tianjin, 300134, China.
Sci Rep. 2025 Jul 1;15(1):20738. doi: 10.1038/s41598-025-08583-1.
Hepatocellular carcinoma (HCC) is one of the most common tumors worldwide, posing a significant threat to the life and health of people globally. LKB1-AMPK signaling pathway plays a significant role in the regulation of cellular metabolism, proliferation and survival in cancer. To construct a LKB1-AMPK signaling-related gene signature (LRS), an ensemble of ten machine learning algorithms was applied across four datasets. Several indicators were employed to assess the effectiveness of LRS in forecasting immunological responses. Additionally, in vitro studies were conducted to investigate the biological roles of LKB1 in HCC. The optimal LRS developed using the Lasso algorithm served as a significant risk factor for HCC patients. HCC patients with a high LRS score exhibited poorer prognoses, with 1-, 3-, and 5-year ROC AUC values of 0.863, 0.826, and 0.831, respectively. Conversely, a low LRS score was associated with higher levels of CD8 T cells, NK cells, macrophages M1, cytolytic activity, T cell co-stimulation and ESTIMATE scores. Additionally, HCC cases with lower LRS score showed elevated PD1&CTLA4 immunophenoscores, and TMB scores, while exhibiting reduced TIDE and tumor escape scores. The IC50 values for several chemotherapy and targeted therapy were found to be lower in HCC cases with higher LRS score. Furthermore, gene set enrichment analysis revealed that pathways related to angiogenesis and NOTCH signaling were more active in the high LRS score group. Over-expression of LKB1 led to decreased proliferation, migration, and invasion in HCC cells by regulating AMPK and PD-L1 expression. Our investigation developed a novel LRS for HCC, serving as an indicator for predicting clinical outcome and immunotherapy response.
肝细胞癌（HCC）是全球最常见的肿瘤之一，对全球人民的生命和健康构成重大威胁。LKB1-AMPK信号通路在癌症细胞代谢、增殖和存活的调节中发挥着重要作用。为构建与LKB1-AMPK信号相关的基因特征（LRS），在四个数据集中应用了十种机器学习算法的集成。采用了几个指标来评估LRS在预测免疫反应方面的有效性。此外，还进行了体外研究以探讨LKB1在HCC中的生物学作用。使用套索算法开发的最佳LRS是HCC患者的一个重要危险因素。LRS评分高的HCC患者预后较差，1年、3年和5年的ROC AUC值分别为0.863、0.826和0.831。相反，低LRS评分与较高水平的CD8 T细胞、NK细胞、M1巨噬细胞、细胞溶解活性、T细胞共刺激和ESTIMATE评分相关。此外，LRS评分较低的HCC病例显示PD1&CTLA4免疫表型评分和TMB评分升高，而TIDE和肿瘤逃逸评分降低。在LRS评分较高的HCC病例中，发现几种化疗和靶向治疗的IC50值较低。此外，基因集富集分析表明，与血管生成和NOTCH信号相关的通路在高LRS评分组中更活跃。LKB1的过表达通过调节AMPK和PD-L1的表达导致HCC细胞的增殖、迁移和侵袭减少。我们的研究为HCC开发了一种新型LRS，作为预测临床结果和免疫治疗反应的指标。
