越来越多的证据表明，肝细胞癌（HCC）干细胞（LCSCs）在HCC复发、转移、化疗和放疗抵抗中起着至关重要的作用。多项研究已经证明，干细胞相关基因促进肿瘤的进展。然而，干细胞相关基因在HCC中的作用机制尚不明确。在本研究中，我们旨在构建一个与干细胞相关得分（SRscores）模型，深入分析干细胞相关基因，帮助HCC患者的预后和个体化治疗。此外，通过免疫组化实验证实，基因LPCAT1在肿瘤组织中高表达，并且通过球形形成实验发现，抑制LPCAT1可以抑制肝细胞癌细胞的球形形成能力。我们利用TCGA-LIHC数据集从MSigDB数据库筛选出HCC的干细胞相关基因，对预后情况、肿瘤微环境、免疫检查点、肿瘤免疫功能障碍、排斥、治疗敏感性和假设的生物通路进行了研究。随机森林构建了SRscores模型。比较了高危组和低危组之间的抗PD-1/抗CTLA4免疫疗法、肿瘤突变负荷、药物敏感性和肿瘤干细胞指数。我们还使用单细胞RNA测序数据对不同细胞类型的风险得分进行了检验，并将癌干细胞中的转录因子活性与SRscores基因进行了相关性分析。最后，我们检测了核心标记基因的表达和生物功能。根据TCGA-LIHC数据集对11个干细胞相关基因进行识别，将患者分为两个亚型（Cluster1和Cluster2）。此外，基于亚型建立了SRscores。Cluster2和SRscores最低的组与Cluster1和SRscores最高的组相比，具有更好的生存率和免疫疗效。SRscores最高的组在肿瘤经典通路中显著更丰富。多个转录因子与SRscores基因相关。核心基因LPCAT1在大鼠肝癌组织中高表达，并促进肿瘤细胞球形形成。SRscores模型可以用于预测HCC患者的预后以及对免疫疗法的反应。© 2023. BioMed Central Ltd., part of Springer Nature.

Increasing evidence suggests that hepatocellular carcinoma (HCC) stem cells (LCSCs) play an essential part in HCC recurrence, metastasis, and chemotherapy and radiotherapy resistance. Multiple studies have demonstrated that stemness-related genes facilitate the progression of tumors. However, the mechanism by which stemness-related genes contribute to HCC is not well understood. Here, we aim to construct a stemness-related score (SRscores) model for deeper analysis of stemness-related genes, assisting with the prognosis and individualized treatment of HCC patients.Further, we found that the gene LPCAT1 was highly expressed in tumor tissues by immunohistochemistry, and sphere-forming assay revealed that knockdown of LPCAT1 inhibited the sphere-forming ability of hepatocellular carcinoma cells.We used the TCGA-LIHC dataset to screen stemness-related genes of HCC from the MSigDB database. Prognosis, tumor microenvironment, immunological checkpoints, tumor immune dysfunction, rejection, treatment sensitivity, and putative biological pathways were examined. Random forest created the SRscores model. The anti-PD-1/anti-CTLA4 immunotherapy, tumor mutational burden, medication sensitivity, and cancer stem cell index were compared between the high- and low-risk score groups. We also examined risk scores for different cell types using single-cell RNA sequencing data and correlated transcription factor activity in cancer stem cells with SRscores genes. Finally, we tested core marker expression and biological functions.Patients can be divided into two subtypes (Cluster1 and Cluster2) based on the TCGA-LIHC dataset's identification of 11 stemness-related genes. Additionally, a SRscores was developed based on subtypes. Cluster2 and the group with the lowest SRscores had superior survival and immunotherapy response than Cluster1 and the group with the highest SRscores. The group with a high SRscores was significantly more enriched in classical tumor pathways than the group with a low SRscores. Multiple transcription factors and SRscores genes are correlated. The core gene LPCAT1 is highly expressed in rat liver cancer tissues and promotes tumor cell sphere formation.A SRscores model can be utilized to predict the prognosis of HCC patients as well as their response to immunotherapy.© 2023. BioMed Central Ltd., part of Springer Nature.