以阿特珠单抗加贝伐单抗为代表的联合免疫疗法已成为无法手术的肝细胞癌 (HCC) 的标准治疗方法。然而，缺乏预测性生物标志物和对反应机制的了解有限仍然是一个挑战。利用 IMbrave150plus 队列的数据，我们应用免疫特征评分 (ISS) 预测因子将接受阿特珠单抗加贝伐单抗或单独使用索拉非尼治疗的 HCC 患者分层为潜在高水平和低反应组。通过应用包括贝叶斯协变量预测算法在内的多种统计方法，我们将签名细化为 10 个关键基因 (ISS10) 以供临床使用，同时保持与完整模型类似的预测能力。我们在接受纳武单抗加伊匹单抗治疗的独立 HCC 队列中进一步验证了 ISS10。该研究发现 ISS 与治疗反应之间存在显着关联。在高反应患者中，与索拉非尼治疗的患者相比，接受阿特珠单抗加贝伐单抗联合治疗的患者总体生存期和无进展生存期有所改善，客观缓解率也更高。我们还观察到 ISS10 与纳武单抗加伊匹单抗治疗的反应之间存在显着相关性。对免疫细胞亚群的分析揭示了与 ISS 亚型相关的独特特征。特别是，ISS10 高亚型表现出更有利的免疫环境，具有更高比例的抗肿瘤巨噬细胞和活化 T 细胞，这可能解释了其更好的反应。我们的研究表明 ISS 和 ISS10 是有希望的预测生物标志物，可增强 HCC 的治疗效果接受联合免疫治疗的患者。这些标志物对于完善患者分层和个性化治疗方法以提高标准护理方案的有效性至关重要。

Combination immunotherapy, exemplified by atezolizumab plus bevacizumab, has become the standard of care for inoperable hepatocellular carcinoma (HCC). However, the lack of predictive biomarkers and limited understanding of response mechanisms remain a challenge.Using data from the IMbrave150plus cohort, we applied an immune signature score (ISS) predictor to stratify HCC patients treated with atezolizumab plus bevacizumab or with sorafenib alone into potential high and low response groups. By applying multiple statistical approaches including a Bayesian covariate prediction algorithm, we refined the signature to 10 key genes (ISS10) for clinical use while maintaining similar predictive power to the full model. We further validated ISS10 in an independent HCC cohort treated with nivolumab plus ipilimumab.The study identified a significant association between the ISS and treatment response. Among patients classified as high responders, those treated with the atezolizumab plus bevacizumab combination exhibited improved overall and progression-free survival as well as better objective response rate compared to those treated with sorafenib. We also observed a significant correlation between ISS10 and response to nivolumab plus ipilimumab treatment. Analysis of immune cell subpopulations revealed distinct characteristics associated with ISS subtypes. In particular, the ISS10 high subtype displayed a more favorable immune environment with higher proportions of anti-tumor macrophages and activated T-cells, potentially explaining its better response.Our study suggests that ISS and ISS10 are promising predictive biomarkers for enhanced therapeutic outcomes in HCC patients undergoing combination immunotherapy. These markers are crucial for refining patient stratification and personalized treatment approaches to advance the effectiveness of standard-of-care regimens.