肝细胞癌（HCC）中的肿瘤干细胞与不良预后有关。然而，现有的干性相关生物标记和预后模型有限。干细胞相关标志是通过在批量RNA-seq和单细胞RNA-seq水平上执行WGCNA和CytoTRACE分析并取结果的并集得出的。单变量Cox回归和LASSO法用于过滤与预后相关的标志并选择变量。最后，我们确定了十个基因标志来构建预后模型。我们评估了高风险组和低风险组的生存差异、基因组改变、生物过程和免疫细胞浸润程度。我们使用pRRophetic和Tumor Immune Dysfunction and Exclusion（TIDE）算法预测化疗敏感性和免疫治疗反应。人蛋白质图谱数据库（HPA）用于评估蛋白质表达。构建了一个包含十个基因（YBX1、CYB5R3、CDC20、RAMP3、LDHA、MTHFS、PTRH2、SRPRB、GNA14和CLEC3B）的干细胞相关预后模型。Kaplan-Meier和ROC曲线分析显示高风险组的预后较差，模型在四个数据集中的AUC大于0.64。多变量Cox回归分析验证了该模型在预测总生存期上的独立预测指标，然后建立了一个临床应用的直观图，用于预测HCC的预后。此外，化疗药物敏感性和免疫治疗反应分析显示高风险组有更大的受益可能性。这个新型干细胞相关预后模型是估计HCC总生存期的有希望的生物标记。© 2023. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.

Cancer stem cells are associated with unfavorable prognosis in hepatocellular carcinoma (HCC). However, existing stemness-related biomarkers and prognostic models are limited.The stemness-related signatures were derived from taking the union of the results obtained by performing WGCNA and CytoTRACE analysis at the bulk RNA-seq and scRNA-seq levels, respectively. Univariate Cox regression and the LASSO were applied for filtering prognosis-related signatures and selecting variables. Finally, ten gene signatures were identified to construct the prognostic model. We evaluated the differences in survival, genomic alternation, biological processes, and degree of immune cell infiltration in the high- and low-risk groups. pRRophetic and Tumor Immune Dysfunction and Exclusion (TIDE) algorithms were utilized to predict chemosensitivity and immunotherapy response. Human Protein Atlas (HPA) database was used to evaluate the protein expressions.A stemness-related prognostic model was constructed with ten genes including YBX1, CYB5R3, CDC20, RAMP3, LDHA, MTHFS, PTRH2, SRPRB, GNA14, and CLEC3B. Kaplan-Meier and ROC curve analyses showed that the high-risk group had a worse prognosis and the AUC of the model in four datasets was greater than 0.64. Multivariate Cox regression analyses verified that the model was an independent prognostic indicator in predicting overall survival, and a nomogram was then built for clinical utility in predicting the prognosis of HCC. Additionally, chemotherapy drug sensitivity and immunotherapy response analyses revealed that the high-risk group exhibited a higher likelihood of benefiting from these treatments.The novel stemness-related prognostic model is a promising biomarker for estimating overall survival in HCC.© 2023. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.