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April 19, 2026SHILAP Revista de lepidopterología0 citationsOpen Access

Drug resistance mechanisms of immunotherapy and translational strategies for reversing resistance for hepatocellular carcinoma: from bench to bedside

CZChenfang ZhangDZDan ZhangXWXin Wen

Key Points

  • The review seeks to summarize research on immunotherapy for hepatocellular carcinoma (HCC) and its associated drug resistance mechanisms.
  • Systematic review of current literature on immunotherapy for HCC
  • Identification of drug resistance mechanisms including tumor microenvironment and intrinsic factors
  • Exploration of combination therapy strategies and novel therapeutic approaches
  • Primary and acquired drug resistance are significant obstacles in immunotherapy for HCC
  • Identified multiple factors contributing to resistance, such as the tumor microenvironment
  • Discussed innovative strategies like targeted agents and personalized treatment options

Abstract

Hepatocellular carcinoma (HCC) is the most common primary malignancy of the liver and remains a major therapeutic challenge. In recent years, immune checkpoint inhibitors (ICIs), represented by PD-1/PD-L1 and CTLA-4 inhibitors, have revolutionized the field of HCC treatment and become the cornerstone of standard immunotherapy regimens, drastically altering the treatment landscape for advanced and unresectable HCC. However, primary and/or acquired drug resistance remains the leading cause of treatment failure, severely limiting the long-term clinical benefits of immunotherapy for HCC patients. This review aims to systematically summarize current research on immunotherapy for HCC, with a focus on drug resistance mechanisms across multiple dimensions: immunosuppressive tumor microenvironment, intrinsic tumor cell factors, and systemic and environmental influences. Potential strategies to overcome resistance are discussed, such as rational combination therapy with antiangiogenic or targeted agents, novel immune targets, nanotechnology-enabled precise delivery, and tumor organoid models for personalized treatment. Future advancements should focus on precision multimodal combinations, innovative therapeutic platforms, and individualized strategies guided by multi-omics and AI, aiming to overcome efficacy bottlenecks and improve patient survival.

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Cite This Study

Zhang et al. (2026) studied this question.

synapsesocial.com/papers/69e4702d010ef96374d8d666https://doi.org/10.3389/fimmu.2026.1808109
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