Liu Jianmin, Wang Juan, Wang Jia, Wu Meng, Yu Jinming, Chen Dawei
Affiliated Hospital of Weifang Medical University, School of Clinical Medicine, Weifang Medical University, Weifang, China; Department of Radiation Oncology and Shandong Provincial Key Laboratory of Radiation Oncology, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, Shandong, China.
Department of Radiation Oncology and Shandong Provincial Key Laboratory of Radiation Oncology, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, Shandong, China; Department of Oncology, The Affiliated Hospital of Southwest Medical University, Luzhou, Sichuan, China.
Transl Oncol. 2025 Aug 20;61:102496. doi: 10.1016/j.tranon.2025.102496.
NSCLC has an extremely high mortality rate, and limitations exist in the efficacy of current therapeutic modalities and the choice of treatment strategies. Cells overexpressing cystine/glutamate transporter proteins and experiencing a glucose shortage could lead to NADPH deficiency and excessive disulfide buildup, causing stress responses and cell death, which affects patient's prognosis.
Based on TCGA and GEO datasets, consensus clustering of NSCLC patients was performed to identify disulfidptosis-related genes and construct a prognostic model. The predictive ability of the model was validated in multiple datasets. Survival analysis, genomic mutations, and immune infiltration were used to characterize epigenetic alterations in different risk groups. Multiple radiotherapy-associated NSCLC datasets and radioresistant cell lines were employed to explore the relationship between disulfidptosis-related genes and radiotherapy.
We identified nine disulfidptosis-associated prognostic genes (DAPGs) and calculated the disulfidptosis-relevant risk score (DRRS). The risk groups showed a difference in prognosis, genomic mutations, and immune infiltration. CAFs and epithelial-mesenchymal transition significantly enriched in the high DRRS group. The prognostic model also effectively predicted the prognosis of patients receiving radiotherapy, and expression of DAPGs, especially KIF14, is strongly associated with DNA damage and repair, and high expression of KIF14 was observed in radioresistant cells.
Our findings imply that a prognostic model related to disulfidptosis could distinguish the prognostic differences among patients, allowing for more personalized treatment strategies. The mechanisms of KIF14 may provide a basis for combating radioresistance and a better understanding of the interaction between disulfidptosis and radiotherapy.
非小细胞肺癌(NSCLC)死亡率极高,当前治疗方式的疗效及治疗策略的选择存在局限性。过表达胱氨酸/谷氨酸转运蛋白且经历葡萄糖缺乏的细胞会导致烟酰胺腺嘌呤二核苷酸磷酸(NADPH)缺乏和二硫键过度积累,引发应激反应和细胞死亡,这会影响患者预后。
基于癌症基因组图谱(TCGA)和基因表达综合数据库(GEO)数据集,对NSCLC患者进行一致性聚类,以识别二硫键化相关基因并构建预后模型。该模型的预测能力在多个数据集中得到验证。采用生存分析、基因组突变和免疫浸润来表征不同风险组中的表观遗传改变。使用多个与放疗相关的NSCLC数据集和放疗抗性细胞系来探究二硫键化相关基因与放疗之间的关系。
我们鉴定出9个与二硫键化相关的预后基因(DAPGs),并计算了二硫键化相关风险评分(DRRS)。风险组在预后、基因组突变和免疫浸润方面存在差异。癌症相关成纤维细胞(CAFs)和上皮-间质转化在高DRRS组中显著富集。该预后模型还能有效预测接受放疗患者预后,且DAPGs的表达,尤其是驱动蛋白家族成员14(KIF14),与DNA损伤和修复密切相关,在放疗抗性细胞中观察到KIF14高表达。
我们的研究结果表明,与二硫键化相关的预后模型可区分患者之间的预后差异,从而制定更具个性化的治疗策略。KIF14的作用机制可能为对抗放疗抗性及更好地理解二硫键化与放疗之间的相互作用提供依据。