Table_2_Construction and Validation of an Immune Cell Signature Score to Evaluate Prognosis and Therapeutic Efficacy in Hepatocellular Carcinoma.xlsx

Background: Hepatocellular carcinoma (HCC) is the most common primary liver malignancy with high morbidity and mortality worldwide. Tumor immune microenvironment (TIME) plays a pivotal role in the outcome and treatment of HCC. However, the effect of immune cell signatures (ICSs) representing the characteristics of TIME on the prognosis and therapeutic benefit of HCC patients remains to be further studied.Materials and methods: In total, the gene expression profiles of 1,447 HCC patients from several databases, i.e., The Cancer Genome Atlas (TCGA), International Cancer Genome Consortium, and Gene Expression Omnibus, were obtained and applied. Based on a comprehensive collection of marker genes, 182 ICSs were evaluated by single sample gene set enrichment analysis. Then, by performing univariate and multivariate Cox analysis and random forest modeling, four significant signatures were selected to fit an immune cell signature score (ICSscore).Results: In this study, an ICSscore-based prognostic model was constructed to stratify HCC patients into high-risk and low-risk groups in the TCGA-LIHC cohort, which was successfully validated in two independent cohorts. Moreover, the ICSscore values were found to positively correlate with the current American Joint Committee on Cancer staging system, indicating that ICSscore could act as a comparable biomarker for HCC risk stratification. In addition, when setting the four ICSs and ICSscores as features, the classifiers can significantly distinguish treatment-responding and non-responding samples in HCC. Also, in melanoma and breast cancer, the unified ICSscore could verify samples with therapeutic benefits.Conclusion: Overall, we simplified the tedious ICS to develop the ICSscore, which can be applied successfully for prognostic stratification and therapeutic evaluation in HCC. This study provides an insight into the therapeutic predictive efficacy of prognostic ICS, and a novel ICSscore was constructed to allow future expanded application.

背景：肝细胞癌（HCC）是全球最常见的原发性肝癌，具有高发病率和死亡率。肿瘤免疫微环境（TIME）在HCC的预后和治疗中发挥着至关重要的作用。然而，代表TIME特征的免疫细胞特征（ICSs）对HCC患者预后和治疗效益的影响尚需进一步研究。材料与方法：本研究共获取了来自多个数据库（如癌症基因组图谱（TCGA）、国际癌症基因组联盟和基因表达综合数据库）的1,447例HCC患者的基因表达谱，并应用于分析。基于对标记基因的全面收集，通过单样本基因集富集分析评估了182个ICSs。随后，通过进行单因素和多因素Cox分析和随机森林建模，选出了四个显著特征，以拟合免疫细胞特征评分（ICSscore）。结果：在本研究中，构建了一个基于ICSscore的预后模型，将TCGA-LIHC队列中的HCC患者分为高风险和低风险组，并在两个独立的队列中得到成功验证。此外，发现ICSscore值与当前美国癌症联合委员会分期系统呈正相关，表明ICSscore可以作为HCC风险分层的可比生物标志物。此外，当将四个ICSs和ICSscores设置为特征时，分类器可以显著区分HCC中的治疗反应性和非反应性样本。在黑色素瘤和乳腺癌中，统一的ICSscore可以验证具有治疗益处的样本。结论：总体而言，本研究简化了繁琐的ICS，开发了ICSscore，该评分在HCC的预后分层和治疗评估中成功应用。本研究揭示了预后ICS的治疗预测效能，并构建了一个新的ICSscore，以允许未来更广泛的应用。