分子靶向治疗和免疫治疗的应用显著延长了肝细胞癌（HCC）患者的生存时间。然而，HCC的多药耐药性和高分子异质性仍然限制了临床效益的进一步改善。肿瘤浸润的自然杀伤（NK）细胞功能障碍与HCC进展和HCC患者的生存效益密切相关。因此，建立了与NK细胞相关的预后标志来预测HCC患者的预后和免疫治疗反应。NK细胞标记物是从GSE162616数据集中获取的单细胞RNA测序数据中选择的。采用一共77个算法的共识机器学习框架，用于在TCGA-LIHC数据集、GSE14520数据集、GSE76427数据集和ICGC-LIRI-JP数据集中建立基因签名。此外，使用GSE91061数据集和PRJEB23709数据集对ICI反应的预测效力进行了外部验证。在77个算法中排名最高的C索引下，通过LASSO和CoxBoost算法的组合建立了一个由11个基因组成的签名，将患者分为高风险组和低风险组。预后标志显示了较好的整体生存率预测性能，预测准确性适中到高，并且是TCGA、GEO和ICGC队列中HCC患者预后的独立危险因素。与高风险组相比，低风险患者显示出更高的IPS-PD1阻断剂、IPS-CTLA4阻断剂、常见免疫检查点表达，但更低的TIDE评分，这表明低风险患者可能更容易受益于ICI治疗。此外，一个真实世界的队列PRJEB23709也显示出低风险组对免疫治疗的反应更好。总的来说，本研究基于NK细胞相关基因建立了一个基因签名，为HCC患者的预后和免疫治疗反应评估提供了一个新平台。 © 2023 BioMed Central Ltd., Springer Nature的一部分。

The application of molecular targeting therapy and immunotherapy has notably prolonged the survival of patients with hepatocellular carcinoma (HCC). However, multidrug resistance and high molecular heterogeneity of HCC still prevent the further improvement of clinical benefits. Dysfunction of tumor-infiltrating natural killer (NK) cells was strongly related to HCC progression and survival benefits of HCC patients. Hence, an NK cell-related prognostic signature was built up to predict HCC patients' prognosis and immunotherapeutic response.NK cell markers were selected from scRNA-Seq data obtained from GSE162616 data set. A consensus machine learning framework including a total of 77 algorithms was developed to establish the gene signature in TCGA-LIHC data set, GSE14520 data set, GSE76427 data set and ICGC-LIRI-JP data set. Moreover, the predictive efficacy on ICI response was externally validated by GSE91061 data set and PRJEB23709 data set.With the highest C-index among 77 algorithms, a 11-gene signature was established by the combination of LASSO and CoxBoost algorithm, which classified patients into high- and low-risk group. The prognostic signature displayed a good predictive performance for overall survival rate, moderate to high predictive accuracy and was an independent risk factor for HCC patients' prognosis in TCGA, GEO and ICGC cohorts. Compared with high-risk group, low-risk patients showed higher IPS-PD1 blocker, IPS-CTLA4 blocker, common immune checkpoints expression but lower TIDE score, which indicated low-risk patients might be prone to benefiting from ICI treatment. Moreover, a real-world cohort, PRJEB23709, also revealed better immunotherapeutic response in low-risk group.Overall, the present study developed a gene signature based on NK cell-related genes, which offered a novel platform for prognosis and immunotherapeutic response evaluation of HCC patients.© 2023. BioMed Central Ltd., part of Springer Nature.