肝细胞癌（HCC）是一种高度异质性的恶性肿瘤，与不良预后相关，在全球是导致癌症相关死亡的常见原因，尽管目前存在治疗突破，但患者的存活受益有限。2019年冠状病毒病（COVID-19）是一种由严重急性呼吸综合症冠状病毒2型（SARS-CoV-2）引起的严重传染病，是全球大流行病和对人类健康的严重威胁。肝细胞癌患者易感SARS-CoV-2感染以及预后不良，有必要探索两者之间的潜在联系。目前尚无研究调查COVID-19基因与HCC患者预后和肿瘤发展之间的关系。本研究筛选了在HCC中与预后相关的COVID-19基因，进行了分子类型鉴定，建立了稳定可靠的COVID-19基因签名以预测存活，对HCC患者的免疫微环境进行了表征，并探索了新的分子靶点治疗。从癌症基因组图谱（TCGA）、国际癌症基因组协会（ICGC）和基因表达杂志（GEO）数据库中获取了HCC患者的数据集，包括RNA测序数据和临床信息。借助单变量Cox分析鉴定了与预后相关的COVID-19基因。采用共识非负矩阵分解方法（cNMF）进行HCC的分子类型鉴定，并进行了每个亚型的生存分析、肿瘤微环境分析和通路富集分析。利用LASSO-Cox回归模型构建了预后标记物，并利用接受者操作特性（ROC）曲线验证了标记物的预测性能。同样的方法用于测试集和外部验证集。采用七种软件包确定了HCC患者的免疫浸润程度，并研究其与风险评分的关系。采用基因集富集分析（GSEA）探索COVID-19基因影响肝癌发生和预后的潜在机制。结合三种机器学习方法，鉴定了标记物中最关键的基因，并在单个细胞水平定位其表达。我们鉴定出了53个与预后相关的COVID-19基因，并通过NMF方法将HCC分为C1和C2两种分子亚型。C2亚型的预后明显优于C1亚型，并且两个亚型在肿瘤免疫微环境和生物功能方面有显著差异。通过LASSO回归方法筛选了17个COVID-19基因，构建了一个17个COVID-19基因的签名，该签名对HCC患者的1、2和3年生存预测具有良好的性能。风险评分作为HCC的独立预后因子，比传统临床变量具有更好的预测准确性。将TCGA队列中的患者根据风险评分分为高风险组和低风险组，发现高风险组主要富集在免疫调控相关通路，而低风险组主要富集在代谢相关通路，表明COVID-19基因可能通过调节肿瘤免疫微环境和代谢影响疾病进展和预后。我们还发现NOL10是该签名中最关键的基因，并推测其可能是HCC的潜在治疗靶点。客观地说，本研究开发的COVID-19基因签名作为HCC患者的独立预后因子，与HCC患者的预后和肿瘤免疫微环境密切相关，表明它们可能通过多种方式调节HCC的发展，为我们理解HCC的分子机制和寻找有效的治疗靶点提供了新的视角。© 2023年。该作者（作者），获得Springer Nature旗下Springer-Verlag GmbH Germany的独家许可。

Hepatocellular carcinoma (HCC), a highly heterogeneous malignant tumor associated with a poor prognosis, is a common cause of cancer-related deaths worldwide, with a limited survival benefit for patients despite ongoing therapeutic breakthroughs. Coronavirus disease 2019 (COVID-19), a severe infectious disease caused by severe acute respiratory syndrome coronavirus type 2 (SARS-CoV-2), is a global pandemic and a serious threat to human health. The increased susceptibility to SARS-CoV-2 infection and a poor prognosis in patients with cancer necessitate the exploration of the potential link between the two. No studies have investigated the relationship of COVID-19 genes with the prognosis and tumor development in patients with HCC. We screened prognosis-related COVID-19 genes in HCC, performed molecular typing, developed a stable and reliable COVID-19 genes signature for predicting survival, characterized the immune microenvironment in HCC patients, and explored new molecular therapeutic targets. Datasets of HCC patients, including RNA sequencing data and clinical information, were obtained from The Cancer Genome Atlas (TCGA), International Cancer Genome Consortium (ICGC), and Gene Expression Omnibus (GEO) databases. Prognosis-related COVID-19 genes were identified by univariate Cox analysis. Molecular typing of HCC was performed using the consensus non-negative matrix factorization method (cNMF), followed by the analysis of survival, tumor microenvironment, and pathway enrichment for each subtype. Prognostic signatures were constructed using LASSO-Cox regression models, and receiver operating characteristic (ROC) curves were used to validate the predictive performance of the signature. The same approach was used for the test and external validation sets. Seven software packages were applied to determine the abundance of immune infiltration in HCC patients and investigate its relationship with the risk scores. Gene set enrichment analysis (GSEA) was used to explore the potential mechanisms by which the COVID-19 genes affect hepatocarcinogenesis and prognosis. Three types of machine learning methods were combined to identify the most critical genes in the signature and localize their expression at the single cell level. We identified 53 prognosis-related COVID-19 genes and classified HCC into two molecular subtypes (C1, C2) by using the NMF method. The prognosis of C2 was significantly better than that of C1, and the two subtypes differed remarkably in terms of the tumor immune microenvironment and biological functions. The 17 COVID-19 genes were screened using the LASSO regression method to develop a 17 COVID-19 genes signature, which demonstrated a good predictive performance for 1-, 2- and 3-year OS of patients with HCC. The risk score as an independent prognostic factor for HCC has better predictive accuracy than traditional clinical variables. Patients in the TCGA cohort were categorized by risk score into the high- and low-risk groups, with the high-risk group mainly enriched in the immune modulation-related pathways and the low-risk group mainly enriched in the metabolism-related pathways, suggesting that the COVID-19 genes may affect disease progression and prognosis by regulating the tumor immune microenvironment and metabolism in HCC. NOL10 was identified as the most critical gene in the signature and hypothesized to be a potential therapeutic target for HCC. Objectively, the COVID-19 genes signature developed in this study, as an independent prognostic factor in HCC patients, is closely associated with the prognosis and tumor immune microenvironment of HCC patients and indicates that they may regulate the development of HCC in multiple ways, providing us with new perspectives for understanding the molecular mechanisms of HCC and finding effective therapeutic targets.© 2023. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.