School of Life Sciences, Hainan University, Hainan, 570100, People's Republic of China.
Institute of Biological Anthropology of Jinzhou Medical University, Liaoning, 110000, People's Republic of China.
Apoptosis. 2023 Jun;28(5-6):860-880. doi: 10.1007/s10495-023-01832-6. Epub 2023 Mar 30.
Cancer stem cells (CSCs) and long non-coding RNAs (lncRNAs) are particularly important for tumor cell growth and migration, and recurrence and drug resistance, including head and neck squamous cell carcinoma (HNSCC). The purpose of this study was to explore stemness-related lncRNAs (SRlncRNAs) that could be used for prognosis of patients with HNSCC. HNSCC RNA sequencing data and matched clinical data were obtained from TCGA database, and stem cell characteristic genes related to HNSCC mRNAsi were obtained from the online database by WGCNA analysis, respectively. Further, SRlncRNAs were obtained. Then, the prognostic model was constructed to forecast patient survival through univariate Cox regression and LASSO-Cox method based on SRlncRNAs. Kaplan-Meier, ROC and AUC were used to evaluate the predictive ability of the model. Moreover, we probed the underlying biological functions, signalling pathways and immune status hidden within differences in prognosis of patients. We explored whether the model could guide personalized treatments included immunotherapy and chemotherapy for HNSCC patients. At last, RT-qPCR was performed to analyze the expressions levels of SRlncRNAs in HNSCC cell lines. A SRlncRNAs signature was identified based on 5 SRlncRNAs (AC004943.2, AL022328.1, MIR9-3HG, AC015878.1 and FOXD2-AS1) in HNSCC. Also, risk scores were correlated with the abundance of tumor-infiltrating immune cells, whereas HNSCC-nominated chemotherapy drugs were considerably different from one another. The final finding was that these SRlncRNAs were abnormally expressed in HNSCCCS according to the results of RT-qPCR. These 5 SRlncRNAs signature, as a potential prognostic biomarker, can be utilized for personalized medicine in HNSCC patients.
癌症干细胞 (CSCs) 和长非编码 RNA (lncRNA) 对于肿瘤细胞的生长、迁移、复发和耐药性，包括头颈部鳞状细胞癌 (HNSCC) 尤为重要。本研究旨在探讨与 HNSCC 相关的干性相关 lncRNA (SRlncRNA) ，可用于预测 HNSCC 患者的预后。从 TCGA 数据库中获取 HNSCC RNA 测序数据和匹配的临床数据，通过 WGCNA 分析从在线数据库中获取与 HNSCC mRNAsi 相关的干细胞特征基因，进一步获得 SRlncRNA。然后，基于 SRlncRNA 构建预后模型，通过单因素 Cox 回归和 LASSO-Cox 方法预测患者生存。Kaplan-Meier、ROC 和 AUC 用于评估模型的预测能力。此外，我们探讨了隐藏在患者预后差异中的潜在生物学功能、信号通路和免疫状态。我们探索了该模型是否可以指导包括免疫治疗和化疗在内的个性化治疗。最后，通过 RT-qPCR 分析 HNSCC 细胞系中 SRlncRNAs 的表达水平。基于 5 个 SRlncRNAs (AC004943.2、AL022328.1、MIR9-3HG、AC015878.1 和 FOXD2-AS1) 在 HNSCC 中确定了一个 SRlncRNAs 特征。此外，风险评分与肿瘤浸润免疫细胞的丰度相关，而 HNSCC 指定的化疗药物则存在显著差异。根据 RT-qPCR 的结果，最终发现这些 SRlncRNAs 在 HNSCCCS 中异常表达。这些 5 个 SRlncRNAs 特征作为一种潜在的预后生物标志物，可用于 HNSCC 患者的个体化医学。
