Neoadjuvant immunotherapy for hepatocellular carcinoma: progress and perspectives

Hepatocellular carcinoma (HCC) is still one of the most challenging malignancies worldwide, ranked as the third leading cause of cancer-related mortality with over 830,000 deaths annually (1). Although hepatic resection offers potential cure chance for patients with resectable HCC, the recurrence rate attains 70% within 5 years after surgery (2). This very high recurrence rate underscores the urgent need for more effective perioperative management against recurrence. The recent success of immune checkpoint inhibitors (ICIs) in advanced-stage HCC, exemplified by combination regimens like atezolizumab-bevacizumab and durvalumab-tremelimumab, has sparked interest in their application in the neoadjuvant and adjuvant setting (3,4).

The rationale for neoadjuvant immunotherapy for HCC is particularly compelling. The presence of the primary tumor during various treatments may facilitate immune responses by providing a broader spectrum of tumor antigens and promoting T-cell activation within the cancer microenvironment. This hypothesis is supported by translational evidence showing expansion of T-cell clones and restoration of exhausted tumor-specific lymphocytes following neoadjuvant ICIs therapy (5). In addition, recent evidence from melanoma demonstrates that neoadjuvant immunotherapy is superior to adjuvant therapy alone in improving relapse-free survival, suggesting potential broader applicability of this approach across many solid tumors (6).

In this evolving landscape, the cross-trial study by D’Alessio and colleagues published in Lancet Oncol represents a significant advancement (7). By pooling patient-level data through the NeoHCC consortium, they provide the first comprehensive evaluation of pathological response patterns following neoadjuvant ICIs for patients with initially resectable HCC. Their finding that pathological response strongly correlates with improved relapse-free survival [hazard ratio (HR): 0.26 for major pathological response] could have potentially important implications for clinical practice and trial design.

A few aspects of this study by D’Alessio et al. deserve particular recognition. First, the establishment of a global consortium enabling analysis of the largest cohort to date (111 patients) provided unprecedented statistical power to evaluate outcomes. Second, their observation of a bimodal distribution in pathological response patterns (predominantly either minimal or near-complete response) offered valuable insights into tumor biology and potential resistance mechanisms. Third, their identification of 90% tumor regression as an optimal threshold for predicting improved outcomes could help standardize response assessment in future trials. Moreover, their detailed analysis of the relationship between radiological and pathological responses highlighted the limitations of conventional imaging in capturing immunotherapy benefits.

However, a few methodological considerations warrant careful attention. The absence of a control group limits interpretation of the true benefit of neoadjuvant ICIs compared to upfront surgery. The heterogeneous study population—including various Barcelona Clinic Liver Cancer (BCLC) stages, treatment regimens of neoadjuvant therapy, and treatment durations (0.7–2.9 months)—may affect the robustness of conclusions. The statistical approach using unbiased recursive partitioning for determining optimal response cutoffs, while sophisticated, may be susceptible to overfitting given the limited sample size and lack of validation cohorts.

A particularly important limitation is the lack of standardization in pathological assessment across centers. Although experienced pathologists generally show good concordance in evaluating treatment response, the absence of central review introduces potential variability. The assessment of multifocal tumors using mean values may not adequately capture response heterogeneity. The subjective nature of evaluating tumor necrosis, combined with potential sampling variability, raises concerns about the reproducibility of reported response rates.

Looking ahead, several key questions remain to be addressed. What molecular features predict response to neoadjuvant immunotherapy? Recent studies have identified distinct molecular classes of HCC associated with immunotherapy responsiveness (“inflamed”) or resistance (“excluded”) (8). Can combination strategies improve response rates in resistant tumors? Should adjuvant therapy be tailored based on pathological response? Ongoing phase III trials incorporating translational endpoints will be crucial in answering these questions.

The study by D’Alessio et al. provides valuable insights for future trial design in neoadjuvant immunotherapy for HCC. Moving forward, integration of molecular and immune profiling will be crucial to identify predictive biomarkers and understand mechanisms of resistance. This could help optimize patient selection and guide development of rational combination strategies for non-responders. The finding that patients without pathological response have significantly worse outcomes suggests they might particularly benefit from adjuvant therapy, while those achieving complete pathological response might be spared unnecessary treatment. Furthermore, as the field matures, incorporation of patient-reported outcomes and cost-effectiveness analyses will be essential to establish the value proposition of neoadjuvant immunotherapy in clinical practice. Recent advances in digital pathology and artificial intelligence might also help standardize response assessment and improve reproducibility of findings across different centers.

In conclusion, while neoadjuvant immunotherapy shows great promise for patients with HCC, careful attention to methodological rigor and standardization will be crucial as the field moves forward. The framework established by D’Alessio et al. provides a valuable foundation for future research, but their findings require validation in larger, randomized trials with standardized assessment protocols. Notably, recent advances in digital pathology and artificial intelligence might help standardize response assessment (9,10). Ultimately, success in this area could transform the treatment landscape for resectable HCC, offering hope for improved outcomes in this challenging disease.

Acknowledgments

Funding: This study was funded by the Chongqing Technology Innovation and Application Development Special Key Project (No. CSTB2023TIAD-KPX0049-4).

Footnote

Provenance and Peer Review: This article was commissioned by the editorial office, HepatoBiliary Surgery and Nutrition. The article did not undergo external peer review.

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://hbsn.amegroups.com/article/view/10.21037/hbsn-2024-642/coif). T.Y. serves as an unpaid editorial board member of HepatoBiliary Surgery and Nutrition. The other authors have no conflicts of interest to declare.

Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved.

Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/.

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