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Dysbiosis of the Gut Microbiome Is Associated With Histopathology of Lung Cancer.

ABSTRACT: Lung cancer is a malignancy with high incidence and mortality worldwide. Previous studies have shown that the gut microbiome plays an important role in the development and progression of metabolic cancers. However, data on the characteristics of the gut microbiome with different histopathology types of lung cancer remain scant. We collected stool samples from 28 healthy people (HP) and 61 lung cancer patients. The lung cancer patients were classified into three types according to their histopathology: Atypical Adenomatous Hyperplasia/Adenocarcinoma in situ (AAH/AIS), Minimally Invasive Adenocarcinoma (MIA), and Invasive Adenocarcinoma (IA). In addition, we employed 16S rRNA gene amplicon sequencing to analyze the characteristics of the gut microbiome in these patients. Our analysis revealed that the categorized cancer patients had unique intestinal flora characteristics, and had lower density and flora diversity compared to healthy people. Besides, the structure of the flora families and genera was more complex, and each group presented specific pathogenic microbiota. The patients in the AAH/AIS group and HP group had relatively similar flora structure compared with the IA and MIA groups. In addition, we identified several flora markers that showed significant changes with the development of lung cancer. Lung cancer gut microbiota showed a decrease in short-chain fatty acids (SCFAs) producing and anti-inflammatory bacteria compared to healthy people, while some pathogenic bacteria such as proinflammatory or tumor-promoting bacteria were more abundant in lung cancer patients. On the other hand, the Kyoto Encyclopedia of Genes and Genomes (KEGG) and Clusters of Orthologous Group (COG) annotation demonstrated suppression of some dominant metabolism-related pathways in lung cancer. These findings provide new biomarkers for the diagnosis and prognostic assessment of lung cancer and lay the basis for novel targeted therapeutic strategies for the prevention and treatment of lung cancer.

Clinical trial registration

[www.ClinicalTrials.gov], identifier [NCT03244605].

SUBMITTER: Qin X

PROVIDER: S-EPMC9237568 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:A group of diseases have been shown to correlate with a phenomenon called microbiome dysbiosis, where the bacterial species composition of the gut becomes abnormal. The gut microbiome of an animal is influenced by many factors including diet, exposures to bacteria during post-gestational growth, lifestyle, and disease status. Studies also show that host genetics can affect microbiome composition. We sought to test whether host genetic background is associated with gut microbiome composition in the Norwegian Lundehund dog, a highly inbred breed with an effective population size of 13 individuals. The Lundehund has a high rate of a protein-losing enteropathy in the small intestine that is often reported as Lundehund syndrome, which negatively affects longevity and life-quality. An outcrossing project with the Buhund, Norrbottenspets, and Icelandic sheepdog was recently established to reintroduce genetic diversity to the Lundehund and improve its health. To assess whether there was an association between host genetic diversity and the microbiome composition, we sampled the fecal microbiomes of 75 dogs of the parental (Lundehund), F1 (Lundehund x Buhund), and F2 (F1 x Lundehund) generations. We found significant variation in microbiome composition from the parental Lundehund generation compared to the outcross progeny. The variation observed in purebred Lundehunds corresponded to dysbiosis as seen by a highly variable microbiome composition with an elevated Firmicutes to Bacteroidetes ratio and an increase in the prevalence of Streptococcus bovis/Streptococcus equinus complex, a known pathobiont that can cause several diseases. We tracked several other environmental factors including diet, the presence of a cat in the household, living in a farm and the use of probiotics, but we did not find evidence of an effect of these on microbiome composition and alpha diversity. In conclusion, we found an association between host genetics and gut microbiome composition, which in turn may be associated with the high incidence of Lundehund syndrome in the purebred parental dogs.

Project description:Object: Primary osteoporosis (PO) is the most common bone disease, which is characterized by decreased bone mass, damage of bone tissue microstructure, increased bone fragility, and is prone to fracture. Gut microbiome may be involved in bone metabolism of PO through gut-brain axis regulation of immune system and endocrine system, however, the specific mechanism is still unclear. The purpose of this study was to characterize the gut microbiome of patients with PO and its possible role in the occurrence and development of the disease. Methods: Fecal samples were collected from 48 PO patients and 48 healthy controls (HC). The composition of gut microbiome community was analyzed by 16s rDNA amplification sequencing, and the difference of gut microbiome composition between PO patients and HC individuals was compared. PICRUSt was also used to predict the biological function of gut microbiome in patients with PO, and to explore its possible role in the occurrence and development of this disease. The classification model is constructed by random forest algorithm so as to screen the key biomarkers. Result: The diversity of gut microorganisms in PO patients was significantly higher than that in HC group (p < 0.05) and there was significant difference in microbial composition in PO group. The abundance of Dialister (0.036 vs. 0.004, p < 0.001) and Faecalibacterium (0.331 vs. 0.132, p < 0.001) were significantly enriched which were the key flora related to PO. Although no significant correlation between bone mineral density and the richness of microbial communities are found, PICRUST results show that there are a wide range of potential pathways between gut microbiome and PO patients, including genetic information processing, metabolism, environmental information processing, cellular processes, human diseases, and organic systems. Notably, the discriminant model based on dominant microflora can effectively distinguish PO from HC (AUC = 93.56). Conclusions: The findings show that PO is related to the change of gut microbiome, especially the enriched Dialister and Faecalibacterium genera, which give new clues to understand the disease and provide markers for the diagnosis and new strategies for intervention treatment of the disease.

Project description:Background: Association between oral bacteria and increased risk of lung cancer have been reported in several previous studies, however, the potential association between salivary microbiome and lung cancer in non-smoking women have not been evaluated. There is also no report on the relationship between immunocytochemistry markers and salivary microbiota. Method: In this study, we assessed the salivary microbiome of 75 non-smoking female lung cancer patients and 172 matched healthy individuals using 16S rRNA gene amplicon sequencing. We also calculated the Spearman's rank correlation coefficient between salivary microbiota and three immunohistochemical markers (TTF-1, Napsin A and CK7). Result: We analyzed the salivary microbiota of 247 subjects and found that non-smoking female lung cancer patients exhibited oral microbial dysbiosis. There was significantly lower microbial diversity and richness in lung cancer patients when compared to the control group (Shannon index, P < 0.01; Ace index, P < 0.0001). Based on the analysis of similarities, the composition of the microbiota in lung cancer patients also differed from that of the control group (r = 0.454, P < 0.001, unweighted UniFrac; r = 0.113, P < 0.01, weighted UniFrac). The bacterial genera Sphingomonas (P < 0.05) and Blastomonas (P < 0.0001) were relatively higher in non-smoking female lung cancer patients, whereas Acinetobacter (P < 0.001) and Streptococcus (P < 0.01) were higher in controls. Based on Spearman's correlation analysis, a significantly positive correlation can be observed between CK7 and Enterobacteriaceae (r = 0.223, P < 0.05). At the same time, Napsin A was positively associated with genera Blastomonas (r = 0.251, P < 0.05). TTF-1 exhibited a significantly positive correlation with Enterobacteriaceae (r = 0.262, P < 0.05). Functional analysis from inferred metagenomes indicated that oral microbiome in non-smoking female lung cancer patients were related to cancer pathways, p53 signaling pathway, apoptosis and tuberculosis. Conclusions: The study identified distinct salivary microbiome profiles in non-smoking female lung cancer patients, revealed potential correlations between salivary microbiome and immunocytochemistry markers used in clinical diagnostics, and provided proof that salivary microbiota can be an informative source for discovering non-invasive lung cancer biomarkers.

Project description:Background: Significant dysbiosis occurs in the gut microbiome of stroke patients. Condensing these broad, complex changes into one index would greatly facilitate the clinical usage of gut microbiome data. Here, we formulated a gut microbiota index in patients with acute ischemic stroke based on their gut microbiota dysbiosis patterns and tested whether the index was correlated with brain injury and early outcome. Methods: A total of 104 patients with acute ischemic stroke and 90 healthy individuals were recruited, and their gut microbiotas were compared and to model a Stroke Dysbiosis Index (SDI), which representing stroke-associated dysbiosis patterns overall. Another 83 patients and 70 controls were recruited for validation. The association of SDI with stroke severity (National Institutes of Health Stroke Scale [NIHSS] score) and outcome (modified Rankin scale [mRS] score: favorable, 0-2; unfavorable, >2) at discharge was also assessed. A middle cerebral artery occlusion (MCAO) model was used in human flora-associated (HFA) animals to explore the causal relationship between gut dysbiosis and stroke outcome. Results: Eighteen genera were significantly different between stroke patients and healthy individuals. The SDI formula was devised based on these microbiome differences; SDI was significantly higher in stroke patients than in healthy controls. SDI alone discriminated stroke patients from controls with AUCs of 74.9% in the training cohort and 84.3% in the validation cohort. SDI was significantly and positively correlated with NIHSS score on admission and mRS score at discharge. Logistic regression analysis showed that SDI was an independent predictor of severe stroke (NIHSS ≥8) and early unfavorable outcome (mRS >2). Mice receiving fecal transplants from high-SDI patients developed severe brain injury with elevated IL-17+ γδ T cells in gut compared to mice receiving transplants from low-SDI patients (all P < 0.05). Conclusions: We developed an index to measure gut microbiota dysbiosis in stroke patients; this index was significantly correlated with patients' outcome and was causally related to outcome in a mouse model of stroke. Our model facilitates the potential clinical application of gut microbiota data in stroke and adds quantitative evidence linking the gut microbiota to stroke.

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Dysbiosis of the Gut Microbiome Is Associated With Histopathology of Lung Cancer.

Clinical trial registration

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