Chen Jin-Wei, Shen Run-Nan, Zhu Jiang-Quan, Wang Ying-Hang, Fu Liang-Min, Chen Yu-Hang, Cao Jia-Zheng, Wei Jin-Huan, Luo Jun-Hang, Li Jia-Ying, Gui Cheng-Peng
Department of Urology, Institute of Precision Medicine, First Affiliated Hospital, Sun Yat-Sen University, Guangzhou, Guangdong, China.
Department of Urology, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou, China.
Funct Integr Genomics. 2025 Mar 7;25(1):56. doi: 10.1007/s10142-025-01561-w.
Nasopharyngeal carcinoma (NPC) recurrence, distant metastasis, and drug resistance remain significant obstacles in clinical prognosis. Cancer stemness is hypothesized to be a key contributor, though direct evidence is sparse. We utilized bioinformatics and machine learning techniques on single-cell RNA-seq and bulk transcriptomic datasets, complemented by basic experiments, to investigate stemness-based characteristics in NPC. Our analysis identified two potential developmental trajectories of nasopharyngeal cancer cells, each exhibiting varying levels of stemness. We subsequently identified and validated a cancer stemness-related signature (STEM-signature). Single-cell profiling revealed enrichment of LAYN + CD8 + , CTLA4 + CD4 + , CXCL13 + CD4 + T cells, tumor-associated macrophages, and CD14 + monocytes in NPC patients with high stemness. NicheNet analysis suggested these immune cells regulate cancer stemness. Bulk transcriptomic analysis corroborated these findings, indicating a poor therapeutic response in high-stemness NPC. We predicted 13 potential drugs and identified 13 stemness-related miRNAs for NPC with high stemness. A Least Absolute Shrinkage and Selection Operator (LASSO) Cox regression model, based on this miRNA signature, predicted overall survival with an AUC of 0.71 and 0.72 in validation and testing sets, respectively. The miRNA-based stemness signature outperformed previous established signatures. Multivariate Cox regression analysis indicated that our prognostic signature could serve as an independent prognostic factor (p < 0.001). Basic experiments showed that miR-300, miR-361-5p, miR-1246, and miR-1290 enhanced the stemness characteristics of NPC cells, promoting proliferation, invasion, and migration. These findings suggest that these four stemness-related miRNAs could serve as therapeutic targets, potentially improving therapeutic responses by targeting stemness-related genes.
鼻咽癌（NPC）的复发、远处转移和耐药性仍然是临床预后的重大障碍。尽管直接证据稀少，但癌症干性被认为是一个关键因素。我们利用生物信息学和机器学习技术对单细胞RNA测序和批量转录组数据集进行分析，并辅以基础实验，以研究NPC中基于干性的特征。我们的分析确定了鼻咽癌细胞的两种潜在发育轨迹，每种轨迹都表现出不同程度的干性。随后，我们鉴定并验证了一种与癌症干性相关的特征（STEM特征）。单细胞分析显示，干性较高的NPC患者中，LAYN + CD8 +、CTLA4 + CD4 +、CXCL13 + CD4 + T细胞、肿瘤相关巨噬细胞和CD14 +单核细胞富集。NicheNet分析表明，这些免疫细胞调节癌症干性。批量转录组分析证实了这些发现，表明高干性NPC的治疗反应较差。我们预测了13种潜在药物，并确定了13种与高干性NPC相关的干性miRNA。基于此miRNA特征的最小绝对收缩和选择算子（LASSO）Cox回归模型在验证集和测试集中分别以0.71和0.72的曲线下面积（AUC）预测总生存期。基于miRNA的干性特征优于先前建立的特征。多变量Cox回归分析表明，我们的预后特征可作为独立的预后因素（p < 0.001）。基础实验表明，miR-300、miR-361-5p、miR-1246和miR-1290增强了NPC细胞的干性特征，促进了细胞增殖、侵袭和迁移。这些发现表明，这四种与干性相关的miRNA可作为治疗靶点，通过靶向干性相关基因可能改善治疗反应。
