Wu Ziman, Yang Haiyan, Xu Yafei, Ji Xiang, Chen Dayang, Zhang Chuang, Liang Mingjie, Li Xinying, Zhang Xiuming, Xiong Dan
School of Medical Technology, Xinxiang Medical University, Xinxiang, 453003, China.
Department of Clinical Laboratory Medicine, The Third Affiliated Hospital of Shenzhen University, Shenzhen, 518001, China.
Discov Oncol. 2025 Aug 22;16(1):1595. doi: 10.1007/s12672-025-03349-7.
Nasopharyngeal carcinoma (NPC) is a malignant tumor with high incidence in Southeast Asia and Southern China, characterized by difficulties in early diagnosis and high recurrence rates after treatment. Metabolic reprogramming plays a crucial role in the development and progression of tumors. In-depth studies on the metabolic characteristics and molecular mechanisms of NPC are essential to identify novel diagnostic and therapeutic targets.
This study aimed to systematically reveal the metabolic characteristics and molecular mechanisms of NPC cell lines by integrating untargeted metabolomics, transcriptomics, and confocal micro-Raman spectroscopy (CMRS), and to explore potential biomarkers for prognostic evaluation and precision treatment of NPC.
We performed an integrated analysis of transcriptomic, metabolomic, and Raman spectral data on five NPC cell lines (CNE1, CNE2, 5-8 F, 6-10B, and SUNE1) and the immortalized nasopharyngeal epithelial cell line NPEC1-BMI1. The analysis included association analysis of differentially expressed metabolites (DEMs) and differentially expressed genes (DEGs), pathway enrichment analysis, and network analysis to elucidate the interplay between gene expression and metabolic alterations. Furthermore, we employed machine learning models to achieve efficient discrimination between NPC cell lines and NPEC1-BMI1 using Raman spectroscopy. Finally, we validated the expression levels of selected DEGs using quantitative polymerase chain reaction (qPCR), Western blotting (WB), and immunohistochemistry (IHC).
Significant differences in metabolic and gene expression profiles were observed between NPC cells and normal cells. CMRS analysis, combined with a multilayer perceptron (MLP) model, achieved high-precision discrimination between NPC cells and normal cells (accuracy 99.3%, AUC = 1.00). Further integrated analysis revealed significant correlations between KYNU and other DEGs, multiple DEMs, and specific Raman spectral features, suggesting their potential as diagnostic and prognostic biomarkers. Validation using the The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases showed high KYNU expression in head and neck squamous cell carcinoma (HNSCC) and NPC tissues. Consistent high expression of KYNU was confirmed in NPC cell lines and tissues by qPCR, WB, and IHC.
This study elucidated the unique metabolic characteristics and molecular signatures of NPC, clarified how molecular changes regulate gene expression, and provided new potential targets for prognostic evaluation and precision treatment of NPC.
鼻咽癌（NPC）是东南亚和中国南方高发的恶性肿瘤，其特点是早期诊断困难且治疗后复发率高。代谢重编程在肿瘤的发生和发展中起着关键作用。深入研究鼻咽癌的代谢特征和分子机制对于确定新的诊断和治疗靶点至关重要。
本研究旨在通过整合非靶向代谢组学、转录组学和共聚焦显微拉曼光谱（CMRS）系统揭示NPC细胞系的代谢特征和分子机制，并探索用于鼻咽癌预后评估和精准治疗的潜在生物标志物。
我们对五种NPC细胞系（CNE1、CNE2、5-8 F、6-10B和SUNE1）以及永生化鼻咽上皮细胞系NPEC1-BMI1进行了转录组学、代谢组学和拉曼光谱数据的综合分析。分析包括差异表达代谢物（DEM）和差异表达基因（DEG）的关联分析、通路富集分析和网络分析，以阐明基因表达与代谢改变之间的相互作用。此外，我们使用机器学习模型通过拉曼光谱实现NPC细胞系与NPEC1-BMI1之间的有效区分。最后，我们使用定量聚合酶链反应（qPCR）、蛋白质免疫印迹（WB）和免疫组织化学（IHC）验证了所选DEG的表达水平。
在NPC细胞和正常细胞之间观察到代谢和基因表达谱的显著差异。CMRS分析结合多层感知器（MLP）模型实现了NPC细胞与正常细胞之间的高精度区分（准确率99.3%，AUC = 1.00）。进一步的综合分析揭示了犬尿氨酸酶（KYNU）与其他DEG、多个DEM和特定拉曼光谱特征之间的显著相关性，表明它们作为诊断和预后生物标志物的潜力。使用癌症基因组图谱（TCGA）和基因表达综合数据库（GEO）进行的验证显示，KYNU在头颈部鳞状细胞癌（HNSCC）和NPC组织中高表达。通过qPCR、WB和IHC在NPC细胞系和组织中证实了KYNU的持续高表达。
本研究阐明了NPC独特的代谢特征和分子特征，阐明了分子变化如何调节基因表达，并为NPC的预后评估和精准治疗提供了新的潜在靶点。
