T-Cell Subsets as Potential Biomarkers for Hepatobiliary Cancers and Selection of Immunotherapy Regimens as a Treatment Strategy

A nomogram based on quantitative MR signal intensity predicts early response to combined systemic treatment in patients with hepatocellular carcinoma

Objective

This study aimed to develop and evaluate the value of a nomogram based on quantitative MR signal intensity to predict response to combined systemic therapy of anti-angiogenesis and immune checkpoint inhibitor (ICI) in hepatocellular carcinoma (HCC) patients.

Methods

117 HCC patients who underwent the combined systemic treatment at a tertiary hospital between September 2020 and May 2024 were enrolled and divided into a development cohort (n = 82) and a validation cohort (n = 35). The predictive value of the relative signal intensity attenuation index (rSIAI) based on enhanced MR parameters and laboratory parameters on disease control was evaluated using receiver operating characteristic (ROC) curves, with the determination of optimal cut-off values (COVs) accomplished via Youden's index. Univariate and multivariable analyses were conducted to evaluate the association between COVs and disease control. The validity of the COVs was further confirmed through chi-square testing and calculation of Cramer's V coefficient (V). A nomogram was constructed based on the multivariable logistic regression model and evaluated for clinical applicability.

Results

rSIAI from arterial to portal phase (rSI_ap) in combination with peripheral T-cell subset (CD4+) achieved the most accurate predictive performance for outcome compared to rSI_ap or CD4+ alone, with an area under the curve (AUC) of the ROC of 0.845 (95% CI, 0.748-0.915). A nomogram based on rSI_ap and CD4+ was constructed. Calibration and decision curve analyses confirmed the clinical relevance and value of the nomogram.

Conclusion

The nomogram based on rSI_ap has the potential to be a non-invasive tool for predicting disease control in advanced HCC patients who have received combined anti-angiogenesis and ICI therapies.

Nanomedicines for reversing immunosuppressive microenvironment of hepatocellular carcinoma

Although immunotherapeutic strategies such as immune checkpoint inhibitors (ICIs) have gained promising advances, their limited efficacy and significant toxicity remain great challenges for hepatocellular carcinoma (HCC) immunotherapy. The tumor immunosuppressive microenvironment (TIME) with insufficient T-cell infiltration and low immunogenicity accounts for most HCC patients' poor response to ICIs. Worse still, the current immunotherapeutics without precise delivery may elicit enormous autoimmune side effects and systemic toxicity in the clinic. With a better understanding of the TIME in HCC, nanomedicines have emerged as an efficient strategy to achieve remodeling of the TIME and superadditive antitumor effects via targeted delivery of immunotherapeutics or multimodal synergistic therapy. Based on the typical characteristics of the TIME in HCC, this review summarizes the recent advancements in nanomedicine-based strategies for TIME-reversing HCC treatment. Additionally, perspectives on the awaiting challenges and opportunities of nanomedicines in modulating the TIME of HCC are presented. Acquisition of knowledge of nanomedicine-mediated TIME reversal will provide researchers with a better opportunity for clinical translation of HCC immunotherapy.