Specific gut microbiome signature predicts the early-stage lung cancer
Specific gut microbiome signature predicts the early-stage lung cancer
复制标题
特定的肠道微生物组特征可预测早期肺癌
DOI：
10.1080/19490976.2020.1737487
复制
发表时间：
2020-04-04
期刊：
影响因子：
12.2
通讯作者：
Ji, Hongbin
中科院分区：
文献类型：
--
作者：
Zheng, Yajuan;Fang, Zhaoyuan;Ji, Hongbin
摘要肠道菌群的改变与包括癌症在内的多种疾病有关。然而，肺癌中的肠道微生物群谱在很大程度上仍然未知。在这里，我们通过16 S核糖体RNA（rRNA）基因测序分析，分析了包含42名早期肺癌患者和65名健康个体的发现队列中的肠道微生物群组成。我们发现，与健康人群相比，肺癌患者的微生物群组成发生了显着变化。为了识别用于非侵入性诊断目的的最佳微生物群特征，我们利用支持向量机（SVM），发现具有13个基于操作分类单位（OTU）的生物标志物的预测模型在肺癌预测中实现了高准确性（曲线下面积，AUC = 97.6%）。该特征在验证组群中表现相当好（AUC = 76.4%），该验证组群包含34名肺癌患者和40名健康个体。为了促进潜在的临床实践，我们进一步构建了“患者区分指数”（PDI），其在很大程度上保留了发现队列（AUC = 92.4%）和验证队列（AUC = 67.7%）中的预测效率。我们的研究共同揭示了肺癌患者的微生物群谱，并建立了特定的肠道微生物特征，用于早期肺癌的潜在预测。
ABSTRACT Alterations of gut microbiota have been implicated in multiple diseases including cancer. However, the gut microbiota spectrum in lung cancer remains largely unknown. Here we profiled the gut microbiota composition in a discovery cohort containing 42 early-stage lung cancer patients and 65 healthy individuals through the 16S ribosomal RNA (rRNA) gene sequencing analysis. We found that lung cancer patients displayed a significant shift of microbiota composition in contrast to the healthy populations. To identify the optimal microbiota signature for noninvasive diagnosis purpose, we took advantage of Support-Vector Machine (SVM) and found that the predictive model with 13 operational taxonomic unit (OTU)-based biomarkers achieved a high accuracy in lung cancer prediction (area under curve, AUC = 97.6%). This signature performed reasonably well in the validation cohort (AUC = 76.4%), which contained 34 lung cancer patients and 40 healthy individuals. To facilitate potential clinical practice, we further constructed a ‘patient discrimination index’ (PDI), which largely retained the prediction efficiency in both the discovery cohort (AUC = 92.4%) and the validation cohort (AUC = 67.7%). Together, our study uncovered the microbiota spectrum of lung cancer patients and established the specific gut microbial signature for the potential prediction of the early-stage lung cancer.