Abstract:: The most often occurring primary liver cancer, hepatocellular carcinoma (HCC), continues to be a major worldwide health burden due to few treatment choices and high rates of recurrence and death. Though frequently hampered by acquired resistance and dose-limiting toxicity, sorafenib—a first-in-class oral multikinase inhibitor—is still a standard systemic treatment for late-stage HCC. The pharmacological effects of sorafenib in HCC are critically analysed in this review, along with their molecular mechanisms, resistance pathways, and genetic and epigenetic elements affecting response. Using databases including PubMed, Scopus, Embase, and Web of Science, an extensive literature review was carried out to include FDA-approved medications, clinical trials, and peer-reviewed research concentrating on mechanisms of resistance, therapeutic combinations, and artificial intelligence (AI)-based precision medicine approaches. While VEGFR-mediated angiogenesis is the main target of sorafenib, resistance comes via compensatory activation of alternate pathways, including PI3K/AKT/mTOR and JAK/STAT, as well as efflux transporter upregulation. Preclinical research shows that combining sorafenib with natural compounds like berberine, wogonin, and quercetin improves pro-apoptotic effects and lowers toxicity. Second-generation kinase inhibitors, including Regorafenib and lenvatinib, provide better survival; immune checkpoint inhibitors, including Nivolumab and atezolizumab, show promise in combination treatments. Moreover, artificial intelligence (AI) applications in radiomics, genomics, and predictive modelling are showing high accuracy in helping to optimize HCC diagnosis and therapy selection. Overcoming the constraints of sorafenib demands the development of combination therapies, biomarker-based personalization, and validated artificial intelligence integration into clinical practice, even if it is still a mainstay of advanced HCC treatment.
Sharma et al. (Tue,) studied this question.