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.

Objective: The aim of this study is to investigate the dysbiosis characteristics of gut microbiota in patients with cerebral infarction (CI) and its clinical implications. Methods: Stool samples were collected from 79 CI patients and 98 healthy controls and subjected to 16S rRNA sequencing to identify stool microbes. Altered compositions and functions of gut microbiota in CI and its correlation with clinical features were investigated. Random forest and receiver operating characteristic analysis were used to develop a diagnostic model. Results: Microbiota diversity and structure between CI patients and healthy controls were overall similar. However, butyrate-producing bacteria (BPB) were significantly reduced in CI patients, while lactic acid bacteria (LAB) were increased. Genetically, BPB-related functional genes were reduced in CI patients, whereas LAB-related genes were enhanced. The interbacterial correlations among BPB in CI patients were less prominent than those in healthy controls. Clinically, BPB was negatively associated with the National Institutes of Health Stroke Scale (NIHSS), while LAB was positively correlated with NIHSS. Both BPB and LAB played leading roles in the diagnostic model based on 47 bacteria. Conclusions: The abundance and functions of BPB in CI patients were significantly decreased, while LAB were increased. Both BPB and LAB displayed promising potential in the assessment and diagnosis of CI.

The aim of this study was to investigate the gut microbial signatures and related pathophysiological implications in patients with Cushing’s disease (CD). 27 patients with CD and 45 healthy controls were enrolled. Based on obtained metagenomics data, we performed correlation, network study and genome interaction group (GIG) analysis. Fecal metabolomics and serum ELISA analysis were conducted in dichotomized CD patients. Caco-2 cells were incubated with gradient concentrations of cortisol for subsequent transepithelial electrical resistance (TEER) measurement, FITC-dextran transwell permeability assay, qPCR and western blot analysis. Gut microbial composition in patients with CD was notably different from that in healthy controls. Network analysis revealed that Eubacterium siraeum might serve as the core specie in the gut microbial system of CD patients. Subsequent GIG analysis identified the positive correlations between GIG9 and UFC. Further serum ELISA and fecal metabolomics uncovered that CD patients with elevated UFC levels were characterized with increased lipopolysaccharide binding protein (LBP). Moreover, remarkable positive association was found between LBP level and relative abundance of Eubacterium siraeum. TEER and FITC-Dextran transwell assays demonstrated that hypercortisolism induced increased gut permeability. Further qPCR and western blot analysis suggested that dysregulated AhR/Claudin 2 axis might be involved in the development of hypercortisolism-induced defective gut barrier function Disease activity associated dysbiosis and defective gut barrier might jointly facilitate the development of systemic inflammation in patients with CD.