Xu Ziyuan, Huang Wei, Zou Xi, Liu Shenlin
Department of Oncology, Affiliated Hospital of Nanjing University of Chinese Medicine, Nanjing, China.
No. 1 Clinical Medical College, Nanjing University of Chinese Medicine, Nanjing, China.
Transl Cancer Res. 2025 Mar 30;14(3):1799-1823. doi: 10.21037/tcr-24-1155. Epub 2025 Mar 18.
Circadian rhythm (CR) coordinates a variety of internal biological processes with the external daily cycles of light and dark. However, the implications of CR-related regulator in hepatocellular carcinoma (HCC) are quite obscure. Here, we aimed to identify pivotal CR-related markers in HCC for predicting survival and treatment outcomes.
The prognostic value of CR regulators in HCC was analyzed. Multi-step machine learning feature selection approaches were employed to establish a model. Thereafter, we evaluated its capacity of clinical prediction and treatment guidance.
First, we depicted the prognostic stratification value of CR regulators in HCC. Two CR-related phenotypes were identified, revealing a distinct clinical outcome, biological pathways and drug sensitivity. Subsequently, via four topological approaches and differentially expressed genes (DEGs) from real-world cohorts, we screened out CRY2 as the pivotal CR regulator with significant prognostic value in HCC. We performed the relevant basic assay validation for CRY2. Overexpression of CRY2 inhibited the proliferation and migration abilities of Huh7 and Hep3B cells. Moreover, three machine learning algorithms [random forest (RF), extreme gradient boosting (XGBoost) and least absolute shrinkage and selection operator (LASSO)] were implemented to construct a risk-scoring model named CR predictor, which exhibited clinical benefits and therapeutic advantages for HCC. An online nomogram based on CR predictor was developed for predicting individualized survival (https://lihc.shinyapps.io/CR_predictor/). Finally, Mendelian randomization (MR) was performed. Among model genes in CR predictor, PPARGC1A revealed a significant causal effect on HCC.
We proposed a CR-related risk classifier in HCC, to predict patients' overall survival (OS) and therapeutic response. Targeting CR could be a promising treatment modality against HCC.
昼夜节律（CR）将各种内部生物过程与外部的昼夜光暗循环协调起来。然而，CR相关调节因子在肝细胞癌（HCC）中的意义尚不清楚。在此，我们旨在识别HCC中关键的CR相关标志物，以预测生存和治疗结果。
分析CR调节因子在HCC中的预后价值。采用多步机器学习特征选择方法建立模型。此后，我们评估了其临床预测和治疗指导能力。
首先，我们描述了CR调节因子在HCC中的预后分层价值。识别出两种CR相关表型，揭示了不同的临床结果、生物学途径和药物敏感性。随后，通过四种拓扑方法和来自真实世界队列的差异表达基因（DEG），我们筛选出CRY2作为在HCC中具有显著预后价值的关键CR调节因子。我们对CRY2进行了相关的基础实验验证。CRY2的过表达抑制了Huh7和Hep3B细胞的增殖和迁移能力。此外，实施了三种机器学习算法[随机森林（RF）、极端梯度提升（XGBoost）和最小绝对收缩和选择算子（LASSO）]来构建一个名为CR预测器的风险评分模型，该模型对HCC具有临床益处和治疗优势。开发了一个基于CR预测器的在线列线图，用于预测个体生存（https://lihc.shinyapps.io/CR_predictor/）。最后，进行了孟德尔随机化（MR）分析。在CR预测器的模型基因中，PPARGC1A对HCC显示出显著的因果效应。
我们提出了一种HCC中与CR相关的风险分类器，以预测患者的总生存期（OS）和治疗反应。靶向CR可能是一种有前景的HCC治疗方式。
