揭示肠道微生物组在预测食管鳞癌新辅助免疫化疗反应中的作用

IF 11 1区 综合性期刊 Q1 Multidisciplinary Research Pub Date : 2024-11-14 eCollection Date: 2024-01-01 DOI:10.34133/research.0529
Le Liu, Liping Liang, YingJie Luo, Jimin Han, Di Lu, RuiJun Cai, Gautam Sethi, Shijie Mai
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引用次数: 0

摘要

肠道微生物组在提高化疗和放疗等抗癌治疗效果方面的作用已得到广泛认可。然而,有关肠道微生物组对食管鳞状细胞癌(ESCC)新辅助免疫化疗(NICT)反应的预测能力的实证证据却很有限。我们的研究通过全面分析肠道微生物组对 NICT 结果的影响填补了这一空白。我们分析了 NICT 前后 68 名 ESCC 患者的 136 份粪便样本以及 19 份健康对照组样本的 16S rRNA 基因序列。NICT 后,微生物群组成发生了明显变化,包括 ESCC 相关病原体的减少和有益微生物(如低乳酸杆菌、乳酸酶杆菌和葡萄球菌)的增加。基线微生物群谱能有效区分应答者和非应答者,应答者体内的短链脂肪酸(SCFA)产生菌(如粪杆菌、Eubacterium_eligens_group、Anaerostipes 和 Odoribacter)水平较高,而非应答者体内的Veillonella、弯曲杆菌、Atopobium 和毛球菌水平较高。然后,我们按 4:1 的比例将患者队列分为训练集和测试集,并利用 XGBoost-RFE 算法确定了 7 个关键微生物生物标记物--粪杆菌、亚多形菌、维氏菌、洪氏菌、臭杆菌、丁酸球菌和 HT002。利用 LightGBM 建立的预测模型在训练集上的接收者操作特征曲线下面积 (AUC) 为 86.8% [95% 置信区间 (CI),73.8% 至 99.4%],在验证集上为 76.8%(95% CI,41.2% 至 99.7%),在测试集上为 76.5%(95% CI,50.4% 至 100%)。我们的研究结果表明,肠道微生物组是预测 ESCC 中 NICT 反应的一种新型生物标记物来源,突出了它在增强个性化治疗策略和推动将微生物组图谱分析纳入临床实践以调节癌症治疗反应方面的潜力。
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Unveiling the Power of Gut Microbiome in Predicting Neoadjuvant Immunochemotherapy Responses in Esophageal Squamous Cell Carcinoma.

The role of the gut microbiome in enhancing the efficacy of anticancer treatments like chemotherapy and radiotherapy is well acknowledged. However, there is limited empirical evidence on its predictive capabilities for neoadjuvant immunochemotherapy (NICT) responses in esophageal squamous cell carcinoma (ESCC). Our study fills this gap by comprehensively analyzing the gut microbiome's influence on NICT outcomes. We analyzed 16S rRNA gene sequences from 136 fecal samples from 68 ESCC patients before and after NICT, along with 19 samples from healthy controls. After NICT, marked microbiome composition changes were noted, including a decrease in ESCC-associated pathogens and an increase in beneficial microbes such as Limosilactobacillus, Lacticaseibacillus, and Staphylococcus. Baseline microbiota profiles effectively differentiated responders from nonresponders, with responders showing higher levels of short-chain fatty acid (SCFA)-producing bacteria such as Faecalibacterium, Eubacterium_eligens_group, Anaerostipes, and Odoribacter, and nonresponders showing increases in Veillonella, Campylobacter, Atopobium, and Trichococcus. We then divided our patient cohort into training and test sets at a 4:1 ratio and utilized the XGBoost-RFE algorithm to identify 7 key microbial biomarkers-Faecalibacterium, Subdoligranulum, Veillonella, Hungatella, Odoribacter, Butyricicoccus, and HT002. A predictive model was developed using LightGBM, which achieved an area under the receiver operating characteristic curve (AUC) of 86.8% [95% confidence interval (CI), 73.8% to 99.4%] in the training set, 76.8% (95% CI, 41.2% to 99.7%) in the validation set, and 76.5% (95% CI, 50.4% to 100%) in the testing set. Our findings underscore the gut microbiome as a novel source of biomarkers for predicting NICT responses in ESCC, highlighting its potential to enhance personalized treatment strategies and advance the integration of microbiome profiling into clinical practice for modulating cancer treatment responses.

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来源期刊
Research
Research Multidisciplinary-Multidisciplinary
CiteScore
13.40
自引率
3.60%
发文量
0
审稿时长
14 weeks
期刊介绍: Research serves as a global platform for academic exchange, collaboration, and technological advancements. This journal welcomes high-quality research contributions from any domain, with open arms to authors from around the globe. Comprising fundamental research in the life and physical sciences, Research also highlights significant findings and issues in engineering and applied science. The journal proudly features original research articles, reviews, perspectives, and editorials, fostering a diverse and dynamic scholarly environment.
期刊最新文献
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