Li Qianqian, Shen Lili, Yang Yanguang, Tai Guomei, Zhu Qiwei, Liu Canyu, Ge Qin, Yi Qiong
Department of Radiation Oncology, Nantong Tumor Hospital, Affiliated Tumor Hospital of Nantong University, Nantong 226361, China.
Department of Oncology, Haimen People's Hospital, Nantong 226100, China.
J Cancer. 2025 Jul 24;16(11):3296-3313. doi: 10.7150/jca.113046. eCollection 2025.
Radiotherapy is a standard treatment for advanced lung cancer, but resistance remains a significant cause of treatment failure. This study aimed to investigate lactate-associated genes to identify patients likely to benefit from radiotherapy. RNA-seq data from 99 patients with lung cancer who underwent radiotherapy were analyzed to identify differentially expressed genes (DEGs) between resistant and sensitive cases. Bioinformatics tools were used to assess the prognostic relevance of lactate-related genes, and a risk score model was develpoed based on these genes. Dysregulation of these genes in patients with lung cancer undergoing radiotherapy was validated through experiments. Molecular docking was used to explore potential radiosensitizers. The analysis identified 1482 DEGs, with enrichment analysis highlighting lactate metabolism pathways. A risk score model was constructed using the lactate-related genes ADAMTS3, FADS2, and RTBDN to classify patients into high- and low-risk subgroups. Functional enrichment analysis revealed the model's impact on DNA repair and tumor immunity. A nomogram was developed for clinical implementation. Wet lab experiments further confirmed these findings. In conclusion, a novel risk score model based on lactate-related genes was developed to predict radiotherapy outcomes in lung cancer. FADS2 was identified as a potential biomarker for predicting resistance to radiotherapy. This study is the first to examine the predictive value of lactate-related genes for radiotherapy efficacy in lung cancer, offering valuable insights for personalized treatment strategies to improve therapeutic outcomes.
放射治疗是晚期肺癌的标准治疗方法，但耐药性仍然是治疗失败的一个重要原因。本研究旨在调查与乳酸相关的基因，以确定可能从放射治疗中获益的患者。对99例接受放射治疗的肺癌患者的RNA测序数据进行分析，以确定耐药和敏感病例之间的差异表达基因（DEG）。使用生物信息学工具评估与乳酸相关基因的预后相关性，并基于这些基因开发了一个风险评分模型。通过实验验证了这些基因在接受放射治疗的肺癌患者中的失调情况。使用分子对接来探索潜在的放射增敏剂。分析确定了1482个DEG，富集分析突出了乳酸代谢途径。使用与乳酸相关的基因ADAMTS3、FADS2和RTBDN构建了一个风险评分模型，将患者分为高风险和低风险亚组。功能富集分析揭示了该模型对DNA修复和肿瘤免疫的影响。开发了一个列线图用于临床应用。湿实验室实验进一步证实了这些发现。总之，开发了一种基于与乳酸相关基因的新型风险评分模型，以预测肺癌的放射治疗结果。FADS2被确定为预测放射治疗耐药性的潜在生物标志物。本研究首次探讨了与乳酸相关基因对肺癌放射治疗疗效的预测价值，为改善治疗结果的个性化治疗策略提供了有价值的见解。
