Li Yi, Hong Xinyi, Xu Wenqian, Guo Jinhong, Su Yongyuan, Li Haolan, Xie Yingjie, Chen Xing, Zheng Xiong, Qiu Sufang
Clinical Oncology School of Fujian Medical University, Fujian Cancer Hospital (Fujian Branch of Fudan University Shanghai Cancer Center), Fuzhou, China; Fujian Provincial Key Laboratory of Translational Cancer Medicine, Fuzhou, China.
Fujian Medical University, Fuzhou, China.
Transl Oncol. 2025 Feb;52:102243. doi: 10.1016/j.tranon.2024.102243. Epub 2024 Dec 15.
Despite advancements with intensity-modulated radiation therapy (IMRT), about 10 % of nasopharyngeal carcinoma (NPC) patients remain resistant to radiotherapy, leading to recurrence and poor prognosis. This study aims to identify radiosensitivity-related genes in NPC and develop a prognostic model to predict patient outcomes.
We analyzed 179 NPC samples from Fujian Cancer Hospital using RNA sequencing. Differentially expressed genes (DEGs) were identified between radiotherapy-sensitive and resistant samples. Machine learning algorithms and Cox regression were used to construct a prognostic risk model, validated in the GSE102349 dataset. Additional analyses included functional pathway, immune infiltration, and drug sensitivity.
A risk model based on six genes (LCN8, IGSF1, RIMS2, RBP4, TBX10, ETV4) was developed. Kaplan-Meier analysis showed significantly shorter progression-free survival (PFS) in the high-risk group. The model's AUC values were 0.872, 0.807, and 0.802 for 1-year, 3-year, and 5-year predictions. A nomogram including clinical factors was created, and enrichment analysis linked the high-risk group to radiotherapy resistance mechanisms.
This study established a novel radiosensitivity-related prognostic model, offering insights into NPC prognosis and radiotherapy resistance mechanisms.
尽管调强放射治疗（IMRT）取得了进展，但约10%的鼻咽癌（NPC）患者对放疗仍有抗性，导致复发和预后不良。本研究旨在识别鼻咽癌中与放射敏感性相关的基因，并建立一个预测模型来预测患者的预后。
我们使用RNA测序分析了福建医科大学附属肿瘤医院的179份鼻咽癌样本。在放疗敏感和抗性样本之间鉴定出差异表达基因（DEG）。使用机器学习算法和Cox回归构建预后风险模型，并在GSE102349数据集中进行验证。其他分析包括功能通路、免疫浸润和药物敏感性。
建立了一个基于六个基因（LCN8、IGSF1、RIMS2、RBP4、TBX10、ETV4）的风险模型。Kaplan-Meier分析显示，高危组的无进展生存期（PFS）显著缩短。该模型在1年、3年和5年预测中的AUC值分别为0.872、0.807和0.802。创建了一个包含临床因素的列线图，富集分析将高危组与放疗抗性机制联系起来。
本研究建立了一种新的与放射敏感性相关的预后模型，为鼻咽癌的预后和放疗抗性机制提供了见解。
