Li Katrina, Mathew Brandon, Saldanha Ethan, Ghosh Puja, Krainer Adrian R, Dasarathy Srinivasan, Huang Hai, Xiang Xiyan, Mishra Lopa
The Institute for Bioelectronic Medicine, Feinstein Institutes for Medical Research & Cold Spring Harbor Laboratory, Department of Medicine, Division of Gastroenterology and Hepatology, Northwell Health, NY, 11030, USA.
Cold Spring Harbor Laboratory, Cold Spring Harbor, NY, 11724, USA.
Mol Med. 2025 Apr 23;31(1):152. doi: 10.1186/s10020-025-01194-6.
Hepatocellular carcinoma (HCC) is the third major cause of cancer death worldwide, with more than a doubling of incidence over the past two decades in the United States. Yet, the survival rate remains less than 20%, often due to late diagnosis at advanced stages. Current HCC screening approaches are serum alpha-fetoprotein (AFP) testing and ultrasound (US) of cirrhotic patients. However, these remain suboptimal, particularly in the setting of underlying obesity and metabolic dysfunction-associated steatotic liver disease/steatohepatitis (MASLD/MASH), which are also rising in incidence. Therefore, there is an urgent need for novel biomarkers that can stratify risk and predict early diagnosis of HCC, which is curable. Advances in liver cancer biology, multi-omics technologies, artificial intelligence, and precision algorithms have facilitated the development of promising candidates, with several emerging from completed phase 2 and 3 clinical trials. This review highlights the performance of these novel biomarkers and algorithms from a mechanistic perspective and provides new insight into how pathological processes can be detected through blood-based biomarkers. Through human studies compiled with animal models and mechanistic insight in pathways such as the TGF-β pathway, the biological progression from chronic liver disease to cirrhosis and HCC can be delineated. This integrated approach with new biomarkers merit further validation to refine HCC screening and improve early detection and risk stratification.
肝细胞癌（HCC）是全球癌症死亡的第三大主要原因，在美国，其发病率在过去二十年中增加了一倍多。然而，其生存率仍低于20%，这通常是由于晚期诊断所致。目前的HCC筛查方法是对肝硬化患者进行血清甲胎蛋白（AFP）检测和超声（US）检查。然而，这些方法仍然不够理想，尤其是在存在潜在肥胖和代谢功能障碍相关脂肪性肝病/脂肪性肝炎（MASLD/MASH）的情况下，而MASLD/MASH的发病率也在上升。因此，迫切需要能够对HCC风险进行分层并预测早期诊断的新型生物标志物，因为早期HCC是可治愈的。肝癌生物学、多组学技术、人工智能和精确算法的进展促进了有前景的候选生物标志物的开发，其中一些已从完成的2期和3期临床试验中脱颖而出。本综述从机制角度突出了这些新型生物标志物和算法的性能，并为如何通过基于血液的生物标志物检测病理过程提供了新的见解。通过结合动物模型的人体研究以及对TGF-β途径等通路的机制性深入了解，可以描绘出从慢性肝病到肝硬化和HCC的生物学进展过程。这种采用新生物标志物的综合方法值得进一步验证，以优化HCC筛查并改善早期检测和风险分层。
