癌干细胞（CSC）和长链非编码RNA（lncRNA）对肿瘤细胞的生长、迁移、复发和药物耐药性尤为重要，包括头颈鳞状细胞癌（HNSCC）在内。本研究旨在探索与干细胞特性相关的lncRNA（SRlncRNAs），并用于预测HNSCC患者的预后。 HNSCC RNA测序数据和临床数据从TCGA数据库中获得，与HNSCC mRNAsi相关的干细胞特征基因从在线数据库中通过WGCNA分析分别获得。然后获得了SRlncRNAs。然后根据SRlncRNAs通过单变量Cox回归和基于LASSO-Cox方法构建预测模型预测患者生存。使用Kaplan Meier，ROC和AUC评估模型的预测能力。此外，我们探讨了患者预后差异中隐藏的潜在生物学功能、信号通路和免疫状态，并研究了该模型是否能指导HNSCC患者的个性化治疗，包括免疫治疗和化疗。最后，进行RT-qPCR以分析HNSCC细胞系中SRlncRNA的表达水平。基于HNSCC的5个SRlncRNA（AC004943.2，AL022328.1，MIR9-3HG，AC015878.1和FOXD2-AS1）识别出一个SRlncRNAs特征，而风险评分与肿瘤浸润免疫细胞的丰度相关，而HNSCC指定的化疗药物之间存在显着差异。最后发现，根据RT-qPCR的结果，这些SRlncRNAs在HNSCCCS中异常表达。这5个SRlncRNAs特征作为潜在的预后生物标志物，可用于HNSCC患者的个性化医疗。 ©2023.作者与施普林格科技媒体股份有限公司的独家许可。

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.© 2023. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.