Colorectal cancer (CRC) is the third most common malignant tumor worldwide. The incidence and mortality rates of CRC have been increasing in China, possibly due to economic development, lifestyle, ...and dietary changes. Evidence suggests that gut microbiota plays an essential role in the tumorigenesis of CRC. Gut dysbiosis, specific pathogenic microbes, metabolites, virulence factors, and microbial carcinogenic mechanisms contribute to the initiation and progression of CRC. Gut microbiota biomarkers have potential translational applications in CRC screening and early diagnosis. Gut microbiota-related interventions could improve anti-tumor therapy's efficacy and severe intestinal toxic effects. Chinese researchers have made many achievements in the relationship between gut microbiota and CRC, although some challenges remain. This review summarizes the current evidence from China on the role of gut microbiota in CRC, mainly including the gut microbiota characteristics, especially Fusobacterium nucleatum and Parvimonas micra, which have been identified to be enriched in CRC patients; microbial pathogens such as F. nucleatum and enterotoxigenic Bacteroides fragilis, and P. micra, which Chinese scientists have extensively studied; diagnostic biomarkers especially F. nucleatum; therapeutic effects, including microecological agents represented by certain Lactobacillus strains, fecal microbiota transplantation, and traditional Chinese medicines such as Berberine and Curcumin. More efforts should be focused on exploring the underlying mechanisms of microbial pathogenesis of CRC and providing novel gut microbiota-related therapeutic and preventive strategies.
The changes of gastric microbiome across stages of neoplastic progression remain poorly understood, especially for intraepithelial neoplasia (IN) which has been recognized as a phenotypic bridge ...between atrophic/intestinal metaplastic lesions and invasive cancer. The gastric microbiota was investigated in 30 healthy controls (HC), 21 non-atrophic chronic gastritis (CG), 27 gastric intestinal metaplasia (IM), 25 IN, and 29 gastric cancer (GC) patients by 16S rRNA gene profiling. The bacterial diversity, and abundances of phyla Armatimonadetes, Chloroflexi, Elusimicrobia, Nitrospirae, Planctomycetes, Verrucomicrobia, and WS3 reduced progressively from CG, through IM, IN to GC. Actinobacteria, Bacteriodes, Firmicutes, Fusobacteria, SR1, and TM7 were enriched in the IN and GC. At the community level, the proportions of Gram-positive and anaerobic bacteria increased in the IN and GC compared to other histological types, whereas the aerobic and facultatively anaerobic bacteria taxa were significantly reduced in GC. Remarkable changes in the gastric microbiota functions were detected after the formation of IN. The reduced nitrite-oxidizing phylum Nitrospirae together with a decreased nitrate/nitrite reductase functions indicated nitrate accumulation during neoplastic progression. We constructed a random forest model, which had a very high accuracy (AUC > 0.95) in predicating the histological types with as low as five gastric bacterial taxa. In summary, the changing patterns of the gastric microbiota composition and function are highly indicative of stages of neoplastic progression.
ObjectiveThis study aimed to construct prognostic models to predict the overall survival (OS) and cancer-specific survival (CSS) of patients with primary gastrointestinal melanoma (PGIM).DesignAn ...observational and retrospective study.SettingData were obtained from the Surveillance, Epidemiology and End Results (SEER) programme database, encompassing a broad geographical and demographic spectrum of patients across the USA.ParticipantsA total of 991 patients diagnosed with PGIM were included in this study.MethodsA total of 991 patients with PGIM were selected from the SEER database. They were further divided into a training cohort and a validation cohort. Independent prognostic factors were identified by Cox regression analysis. Two prognostic models were constructed based on the results of multivariable Cox regression analysis. The concordance index (C-index) and area under the time-dependent receiver operating characteristic curve (time-dependent AUC) were used to evaluate the discriminative ability. Calibration curves were plotted to evaluate the agreement between the probability as predicted by the models and the actual probability. Risk stratification was developed given the model.ResultsBy the multivariable Cox regression analysis, we identified four independent risk factors (age, stage, lymph node density and surgery) for OS, and three independent risk factors (stage, lymph node density and surgery) for CSS, which were used to construct prognostic models. C-index, time-dependent AUC, calibration curves and Kaplan-Meier curves of risk stratification indicated that these two models had good discriminative ability, predictive ability as well as clinical value.ConclusionsThe prognostic models of OS and CSS had satisfactory accuracy and were of clinical value in evaluating the prognosis of patients with PGIM.
Many components of the gastric non-Helicobacter pylori microbiota have been identified recently thanks to advances in DNA sequencing techniques. Several lines of evidence support the hypothesis that ...the gastric microbiome is essential for gastric disorders such as gastric cancer. Microbial interactions impact the pathophysiology of various gastric disorders. This chapter provides an overview of recent findings regarding general gastric microbial community profiling, microbial interactions in the stomach, and microbial characteristics in various gastric disorders.
This study aimed to investigate the intestinal microbiota in duodenal ulcer (DU) patients, effects of proton pump inhibitors,clarithromycin and amoxicillin, PCA) for Helicobacter pylori (H. pylori) ...and Bacillus subtilis and Enterococcus faecium (BSEF) on intestinal microbiota. DU patients were randomly assigned to receive either PCA (group TT) or PCA plus BSEF(group TP). The fecal microbiome was conducted using high throughput 16S rDNA gene and internal transcribed spacer sequencings. The diversity and abundance of intestinal bacteria in the DU were significantly lower than health check control (HC) group. In the TT group, the abundance and diversity of both intestinal bacteria and fungi decreased after PCA treatment, compared with those before treatment, whereas in the TP group no obvious changes were observed. In the TT group at all the time points, both the intestinal bacteria and fungi were different from those in the HC group. However, in the TP group, at 10w the bacterial flora abundance was close to that in the HC group. The results indicate that anti- H. pylori treatment induced significant decrease in the diversity of intestinal microbiota, while the combined therapy supplemented with BSEF could protect and restore the intestinal microbiota.
The fecal microbiota in pancreatic ductal adenocarcinoma (PDAC) and in autoimmune pancreatitis (AIP) patients remains largely unknown. We aimed to characterize the fecal microbiota in patients with ...PDAC and AIP, and explore the possibility of fecal microbial biomarkers for distinguishing PDAC and AIP.
32 patients with PDAC, 32 patients with AIP and 32 age- and sex-matched healthy controls (HC) were recruited and the fecal microbiotas were analyzed through high-throughput metagenomic sequencing. Alterations of fecal short-chain fatty acids were measured using gas chromatographic method.
Principal coordinate analysis (PCoA) revealed that microbial compositions differed significantly between PDAC and HC samples; whereas, AIP and HC individuals tended to cluster together. Significant reduction of phylum Firmicutes (especially butyrate-producing bacteria, including Eubacterium rectale, Faecalibacterium prausnitzii and Roseburia intestinalis) and significant increase of phylum Proteobacteria (especially Gammaproteobacteria) were observed only among PDAC samples. At species level, when compared with HC samples, we revealed 24 and 12 differently enriched bacteria in PDAC and AIP, respectively. Functional analysis showed a depletion of short-chain fatty acids synthesis associated KO modules (e.g. Wood-Ljungdahl pathway) and an increase of KO modules associated with bacterial virulence (e.g. type II general secretion pathway). Consistent with the downregulation of butyrate-producing bacteria, gas chromatographic analysis showed fecal butyrate content was significantly decreased in PDAC group. Eubacterium rectale, Eubacterium ventrisum and Odoribacter splanchnicus were among the most important biomarkers in distinguishing PDAC from HC and from AIP individuals. Receiver Operating Characteristic analysis showed areas under the curve of 90.74% (95% confidence interval CI 86.47-100%), 88.89% (95% CI 73.49-100%), and 76.54% (95% CI 52.5-100%) for PDAC/HC, PDAC/AIP and AIP/HC, respectively.
In conclusion, alterations in fecal microbiota and butyrate of patients with PDAC suggest an underlying role of gut microbiota for the pathogenesis of PDAC. Fecal microbial and butyrate as potential biomarkers may facilitate to distinguish patients with PDAC from patients with AIP and HCs which worth further validation.
To characterize the salivary microbiota in patients at different progressive histological stages of gastric carcinogenesis and identify microbial markers for detecting gastric cancer, two hundred and ...ninety-three patients were grouped into superficial gastritis (SG; n = 101), atrophic gastritis (AG; n = 93), and gastric cancer (GC; n = 99) according to their histology. 16S rRNA gene sequencing was used to access the salivary microbiota profile. A random forest model was constructed to classify gastric histological types based on the salivary microbiota compositions. A distinct salivary microbiota was observed in patients with GC when comparing with SG and AG, which was featured by an enrichment of putative proinflammatory taxa including
and
. Among the significantly decreased oral bacteria in GC patients including
,
,
,
,
, and
,
, and
are known to reduce nitrite, which may consequently result in an accumulation of carcinogenic N-nitroso compounds. We found that GC can be distinguished accurately from patients with AG and SG (AUC = 0.91) by the random forest model based on the salivary microbiota profiles, and taxa belonging to
and
have potential as diagnostic biomarkers for GC. Remarkable changes in the salivary microbiota functions were also detected across three histological types, and the upregulation in the isoleucine and valine is in line with a higher level of these amino acids in the gastric tumor tissues that reported by other independent studies. Conclusively, bacteria in the oral cavity may contribute gastric cancer and become new diagnostic biomarkers for GC, but further evaluation against independent clinical cohorts is required. The potential mechanisms of salivary microbiota in participating the pathogenesis of GC may include an accumulation of proinflammatory bacteria and a decline in those reducing carcinogenic N-nitroso compounds.
Several studies based on 16SrDNA analysis have revealed certain unique characteristics of gut microbiome in centenarians. We established a prospective cohort of fecal microbiota and conducted the ...first metagenomics-based study among centenarians. The objective was to explore the dynamic changes of gut microbiota in healthy centenarians and centenarians approaching end of life and to unravel the characteristics of aging-associated microbiome. Seventy-five healthy centenarians residing in three regions of Hainan participated in follow-up surveys and collection of fecal samples at intervals of 3 months. Data pertaining to dietary status, health status scores, cause of disease and death, and fecal specimens were collected for 15 months. Twenty participants died within 20 months during the follow-up period. The median survival time was 8-9 months (range, 1-17) and the mortality rate was 14.7% per year. The health status scores before death were significantly lower than those at 3 months before the end of the follow-up period median score: 3 (range, 1-5), P < 0.05. At this time, the participants mainly exhibited symptoms of anorexia and reduced dietary intake and physical activity. Metagenomics sequencing and analysis were carried out to characterize the gut microbiota changes in the centenarians during their transition from healthy status to death. Anosim analysis showed a significant change in gut microbiota from 7 months prior to death (R = 0.10, P = 0.02). All participants were grouped with 7 months before death as cut-off; no significant difference in α diversity was found between the two groups (P = 0.45). Semi-supervised monitoring and log rank sum analysis revealed significant changes in the abundance of ten bacterial species before death; of these, eight species were significantly reduced (Akkermansia muciniphila, Alistipes finegoldii, Alistipes shahii, Bacteroides faecis, Bacteroides intestinalis, Butyrivibrio crossotus, Bacteroides stercoris, and Prevotella stercorea) while two were significantly increased before death (Bifidobacterium longum and Ruminococcus bromii). Compared to centenarians in northern Italy, Hainan centenarians exhibited unique characteristics of gut microbiome. The abundance of ten bacterial species showed significant changes starting from 7 months before death. We speculate that these changes might occur before the clinical symptoms of deterioration in health status.
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