Liang Fei, Sun Yichu, Yang Jing, Shen Ziqiang, Wang Guangfeng, Zhu Jiangrui, Zhou Chong, Xia Youyou
Department of Radiation Oncology, the First People's Hospital of Lianyungang/ Lianyungang Clinical College of Nanjing Medical University, Lianyungang, Jiangsu, China.
Department of Radiation Oncology, The Affiliated Lianyungang Hospital of Xuzhou Medical University/ The First People's Hospital of Lianyungang, Lianyungang, Jiangsu, China.
Front Cell Infect Microbiol. 2025 Mar 10;15:1562831. doi: 10.3389/fcimb.2025.1562831. eCollection 2025.
To investigate the gut microbiome of lung cancer patients with brain metastases undergoing radiotherapy, identify key microorganisms associated with radiotherapy response, and evaluate their potential as biomarkers.
This study enrolled 55 newly diagnosed lung cancer patients with brain metastases. Fecal samples were collected before radiotherapy and analyzed by 16S rRNA sequencing to assess the gut microbiome's composition and function. Patients were categorized into response (n=28) and non-response (n=27) groups based on treatment efficacy, and α-diversity, β-diversity, and functional pathways were compared between them. Linear Discriminant Analysis Effect Size was used to identify microbial features associated with treatment efficacy. Logistic regression analyses were performed to evaluate the predictive capacity of clinical and microbial factors for treatment outcomes.
No significant difference in α-diversity was observed between the groups (P > 0.05), but β-diversity differed significantly (P = 0.036). Twelve characteristic microorganisms were identified in the response group, including and , and nine in the non-response group, such as and . Metabolic pathways associated with treatment response included ketone body metabolism and pathways related to amyotrophic lateral sclerosis. Multivariate analysis identified (odds ratio [OR] = 6.680, P = 0.004), (OR = 3.862, P = 0.014), C-reactive protein (OR = 1.054, P = 0.017), and systemic inflammation response index (OR = 1.367, P = 0.043) as independent predictors of radiotherapy response. The nomogram and microbiome models achieved area under the curve (AUC) values of 0.935 and 0.866, respectively, demonstrating excellent predictive performance. Decision curve analysis further confirmed these models provided significant net benefits across risk thresholds.
The composition and functional characteristics of the gut microbiome in lung cancer patients with brain metastases prior to radiotherapy are associated with therapeutic response and possess potential as predictive biomarkers. Further studies are warranted to validate these findings.
研究接受放疗的脑转移肺癌患者的肠道微生物群,确定与放疗反应相关的关键微生物,并评估它们作为生物标志物的潜力。
本研究纳入了55例新诊断的脑转移肺癌患者。在放疗前收集粪便样本,并通过16S rRNA测序进行分析,以评估肠道微生物群的组成和功能。根据治疗效果将患者分为反应组(n = 28)和无反应组(n = 27),并比较两组之间的α多样性、β多样性和功能途径。使用线性判别分析效应大小来识别与治疗效果相关的微生物特征。进行逻辑回归分析以评估临床和微生物因素对治疗结果的预测能力。
两组之间未观察到α多样性的显著差异(P > 0.05),但β多样性存在显著差异(P = 0.036)。在反应组中鉴定出12种特征微生物,包括 和 ,在无反应组中鉴定出9种,如 和 。与治疗反应相关的代谢途径包括酮体代谢和与肌萎缩侧索硬化相关的途径。多变量分析确定 (比值比[OR] = 6.680,P = 0.004)、 (OR = 3.862,P = 0.014)、C反应蛋白(OR = 1.054,P = 0.017)和全身炎症反应指数(OR = 1.367,P = 0.043)为放疗反应的独立预测因子。列线图和微生物群模型的曲线下面积(AUC)值分别为0.935和0.866,显示出优异的预测性能。决策曲线分析进一步证实这些模型在不同风险阈值下均提供了显著的净效益。
放疗前脑转移肺癌患者肠道微生物群的组成和功能特征与治疗反应相关,并具有作为预测生物标志物的潜力。有必要进行进一步研究以验证这些发现。