Identification and validation of a prognostic risk model based on radiosensitivity-related genes in nasopharyngeal carcinoma

• Published in: Translational oncology 2025-02, Vol.52, p.102243, Article 102243
• Main Authors: Li, Yi, Hong, Xinyi, Xu, Wenqian, Guo, Jinhong, Su, Yongyuan, Li, Haolan, Xie, Yingjie, Chen, Xing, Zheng, Xiong, Qiu, Sufang
• Format: Article
• Language: English
• Subjects: NPC; Prognostic model; Radiation resistance; Radiotherapy sensitivity
• ISSN: 1936-5233; 1936-5233
• DOI: 10.1016/j.tranon.2024.102243

•This study identified six genes associated with radiosensitivity in NPC and established a prognostic risk model to predict patient prognosis.•Comprehensive clinical follow-up data and patient tissue samples were collected for sequencing, with the findings validated in external datasets to ensure the authenticity and reliability of the results.•This study leveraged a large NPC sequencing dataset and, for the first time, proposed a prognostic risk model based on radiosensitivity-related genes.•An in-depth analysis was conducted to explore the correlation between the risk score and the mechanisms underlying radiotherapy resistance in NPC. 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.