Li Hanqi, Zhang Jiayi, Shi Yu, Wang Huanhuan, Yang Ruida, Wu Shaobo, Li Yue, Yang Xue, Liu Qingguang, Sun Liankang
Department of Hepatobiliary Surgery, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, 710061, PR China.
Department of Oncology, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, 710061, PR China.
J Transl Med. 2025 Jul 1;23(1):716. doi: 10.1186/s12967-025-06733-7.
Matrix stiffness is strongly associated with hepatocarcinogenesis and significantly influences the properties of hepatocellular carcinoma (HCC). Investigating matrix stiffness-related signatures provides crucial insights into HCC prognosis and therapeutic response.
Multi-omics data from liver hepatocellular carcinoma (LIHC) were integrated using 10 clustering algorithms, identifying three subgroups with distinct survival outcomes and treatment responses. A matrix stiffness-related signature comprising 57 genes was constructed by evaluating 101 machine learning algorithm combinations. PPARG, the key gene with the greatest contribution to the model, was selected for validation. Single-cell RNA sequencing (scRNA-seq) and spatial transcriptomics (ST) analyses assessed matrix stiffness activity scores across different cell subgroups and examined PPARG spatial localization within tissues. Experimental studies and bioinformatics analyses further explored the role of PPARG in HCC carcinogenesis and the immune microenvironment.
The matrix stiffness-related signature demonstrated superior prognostic prediction performance in both training and validation cohorts compared to other existing HCC signatures. Distinct immune and mutation landscape characteristics were observed between patients categorized into high and low matrix stiffness groups. PPARG functioned in tumorigenesis through HSC activation and immune suppression. Furthermore, increased matrix stiffness was found to upregulate PPARG expression, promoting cell proliferation, activating lipid metabolism, and enhancing the stemness of HCC cells through the MAPK signaling pathway. Targeting PPARG with trametinib displayed an enhanced therapy response.
The matrix stiffness-related signature not only serves as a robust prognostic tool but also aids in identifying immune characteristics and optimizing therapeutic strategies, thus advancing personalized medicine for patients with HCC.
基质硬度与肝癌发生密切相关，并显著影响肝细胞癌（HCC）的特性。研究与基质硬度相关的特征为了解HCC的预后和治疗反应提供了关键见解。
使用10种聚类算法整合来自肝细胞癌（LIHC）的多组学数据，确定了三个具有不同生存结果和治疗反应的亚组。通过评估101种机器学习算法组合，构建了一个包含57个基因的与基质硬度相关的特征。选择对模型贡献最大的关键基因PPARG进行验证。单细胞RNA测序（scRNA-seq）和空间转录组学（ST）分析评估了不同细胞亚组的基质硬度活性评分，并检查了PPARG在组织内的空间定位。实验研究和生物信息学分析进一步探讨了PPARG在HCC致癌作用和免疫微环境中的作用。
与其他现有的HCC特征相比，与基质硬度相关的特征在训练和验证队列中均表现出卓越的预后预测性能。在分为高基质硬度组和低基质硬度组的患者之间观察到明显不同的免疫和突变格局特征。PPARG通过激活肝星状细胞（HSC）和免疫抑制在肿瘤发生中发挥作用。此外，发现增加的基质硬度会上调PPARG表达，通过丝裂原活化蛋白激酶（MAPK）信号通路促进细胞增殖、激活脂质代谢并增强HCC细胞的干性。用曲美替尼靶向PPARG显示出增强的治疗反应。
与基质硬度相关的特征不仅可作为一种强大的预后工具，还有助于识别免疫特征和优化治疗策略，从而推动HCC患者的个性化医疗。
