Liu Hao, Yan Hongyi, Huang Ying, Meng Xiangkun, Liu Long, Zhang Yuyuan, Xu Hui, Hu Yanchao
Department of Gastroenterology, General Hospital of Ningxia Medical University, Ningxia, 750004, People's Republic of China.
Department of Clinical Medicine, Zhengzhou University, Zhengzhou, 450052, Henan, China.
Discov Oncol. 2025 Aug 27;16(1):1643. doi: 10.1007/s12672-025-03232-5.
Molecular subtype of hepatocellular carcinoma (HCC) is primarily identified via high throughput expression profiles, largely ignoring the dynamic changes of gene expressions. Yet, biological networks remain steadily characterize disease state irrespective of time and conditions. We aim to utilize a metabolic genes interaction perturbation network-based approach to facilitate the subtyping and precision treatment of HCC patients.
We employed the metabolic genes interaction perturbation network-based approach to identify metabolic reprogramming (MR) subtypes in 922 HCC samples from four independent public datasets and further investigated their clinical and biofunctional implications, immune landscape, multi-omics features and biomarker.
We stratified patients into three unique MR subtypes: (i) MR1 ("immune-deficiency"), frequent CTNNB1 mutation, and moderate prognosis; (ii) MR2 ("immune-activated"), advanced pathological staging and histological grading, frequent TP53 mutation, response to anti-PD-1 therapy, and the worst prognosis; (iii) MR3 (high metabolic activity), low-grade pathological staging and histological grading, fewer mutations and copy number variations, and the best prognosis. Besides, CD24 was identified and validated as a biomarker for MR2 which indicated a poor prognosis with higher expression.
Taken together, the interactome taxonomy could effectively facilitate the stratified management and precise treatment of heterogeneous HCC patients.
肝细胞癌（HCC）的分子亚型主要通过高通量表达谱来识别，很大程度上忽略了基因表达的动态变化。然而，生物网络无论在何种时间和条件下都能稳定地表征疾病状态。我们旨在利用基于代谢基因相互作用扰动网络的方法来促进HCC患者的亚型分类和精准治疗。
我们采用基于代谢基因相互作用扰动网络的方法，在来自四个独立公共数据集的922个HCC样本中识别代谢重编程（MR）亚型，并进一步研究它们的临床和生物功能意义、免疫格局、多组学特征和生物标志物。
我们将患者分为三种独特的MR亚型：（i）MR1（“免疫缺陷”），CTNNB1突变频繁，预后中等；（ii）MR2（“免疫激活”），病理分期和组织学分级较高，TP53突变频繁，对抗PD-1治疗有反应，预后最差；（iii）MR3（高代谢活性），病理分期和组织学分级较低，突变和拷贝数变异较少，预后最佳。此外，CD24被鉴定并验证为MR2的生物标志物，其高表达预示预后不良。
综上所述，相互作用组分类法可以有效地促进异质性HCC患者的分层管理和精准治疗。
