Because of its intrinsic tumor heterogeneity, poor response to traditional chemotherapy, and lack of viable molecular targets, liver cancer mostly hepatocellular carcinoma (HCC) continues to be a major worldwide health concern. With a focus on molecular processes, resistance routes, and combination therapy approaches, this review provides a thorough analysis of the status and new advancements in targeted therapeutics for liver cancer. By blocking the mechanisms that lead to angiogenesis and tumor growth, first-line systemic treatments, such the multi-tyrosine kinase inhibitors (TKIs) lenvatinib and sorafenib, have shown moderate improvements in survival. However, their long-term efficacy is significantly reduced by intrinsic and acquired resistance, which is why second-line medications like regorafenib, cabozantinib, and ramucirumab are being studied. When combined with anti-VEGF treatments, parallel developments in immunotherapy, in particular immune checkpoint inhibitors (ICIs) such as atezolizumab and nivolumab, have shown promising outcomes. The review highlights the role of the tumor microenvironment, epigenetic regulators including EZH2 and HDACs, and key oncogenic drivers and aberrant signaling cascades in HCC, such as the Wnt/β-catenin, PI3K/AKT/mTOR, and RAS/RAF/MEK/ERK pathways. It also covers metabolic vulnerabilities, DNA damage response pathways, and new targets including FGFR4, AXL, and c-MET. To get around resistance mechanisms and improve therapeutic effectiveness, special attention is paid to logical combination treatments, which include combining targeted medicines with ICIs, irradiation, or synthetic lethality techniques. In the end, the review promotes the combination of dynamic molecular profiling and biomarker-driven precision medicine to enhance patient stratification, improve treatment decision-making, and provide long-lasting clinical effects. A strategic foundation for future advancements and individualized treatment of hepatocellular carcinoma is provided by this comprehensive synthesis.
Qian Wang (Sun,) studied this question.