Metagenomic analysis of gut microbiome reveals a dynamic change in Alistipes onderdonkii in the preclinical model of pancreatic cancer, suppressing its proliferation

Lee, Kihak; Oh, Hyo Jae; Kang, Min-Su; Kim, Sinae; Ahn, Sehee; Kim, Myung Ji; Kim, Seon-Won; Chang, Suhwan

doi:10.1007/s00253-021-11617-z

Cited by 6 publications

(4 citation statements)

References 73 publications

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“…Along those lines, higher Clostridium citronia was found in our data to be linked with poorer prognosis, which was not previously reported. Interestingly, Alistipes onderdonkii , significantly correlated with DCB in our dataset, was found to be attenuated in the gut of a mouse model of pancreatic cancer, and the supernatant of this microbe suppressed the proliferation of the pancreatic cancer cells 43 .…”

Section: Discussionmentioning

confidence: 70%

Gut microbial signature in lung cancer patients highlights specific taxa as predictors for durable clinical benefit

Haberman

Kamer

Almasi‐Hashiani

et al. 2023

Sci Rep

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We aimed to determine microbial signature linked with lung cancer (LC) diagnosis and to define taxa linked with durable clinical benefit (DCB) of advanced LC patients. Stool samples for microbial 16S amplicon sequencing and clinical data were collected from 75 LC patients (50 of which were treated with checkpoint inhibitors) and 31 matched healthy volunteers. We compared LC to healthy controls and patients with DCB to those without. LC patients had lower α-diversity and higher between-subject diversity. Random Forests model to differentiate LC cases from controls ROC-AUC was 0.74. Clostridiales, Lachnospiraceae, and Faecalibacterium prausnitzii taxa abundance was decreased in LC compared to controls. High Akkermansia muciniphila correlated with DCB (HR 4.26, 95% CI 1.98–9.16), not only for the immunotherapy-treated patients. In addition, high Alistipes onderdonkii (HR 3.08, 95% CI 1.34–7.06) and high Ruminococcus (HR 7.76, 95% CI 3.23–18.65) correlated with DCB.Our results support the importance of gut microbiome in LC. We have validated the apparent predictive value of Akkermansia muciniphila, and highlighted Alistipes onderdonkii and Ruminococcus taxa correlation with DCB. Upon additional validations those can be used as biomarkers or as targets for future therapeutic interventions.

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Section: Discussionmentioning

confidence: 70%

Gut microbial signature in lung cancer patients highlights specific taxa as predictors for durable clinical benefit

Haberman

Kamer

Almasi‐Hashiani

et al. 2023

Sci Rep

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“…For example, change in the bacterial species Alistipes onderdonkii was positively associated with PPT adherence and negatively with change in clinical readouts of triglycerides, body weight, BMI and BMR. Notably, this species was recently suggested to suppress proliferation of pancreatic primary cancer cells 39…”

Section: Resultsmentioning

confidence: 99%

“…Notably, this species was recently suggested to suppress proliferation of pancreatic primary cancer cells. 39…”

Section: Ppt Intervention Increases Microbiome Diversity and Richness...mentioning

confidence: 99%

Gut microbiome modulates the effects of a personalised postprandial-targeting (PPT) diet on cardiometabolic markers: a diet intervention in pre-diabetes

Ben-Yacov

Godneva

Rein

et al. 2023

Gut

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ObjectiveTo explore the interplay between dietary modifications, microbiome composition and host metabolic responses in a dietary intervention setting of a personalised postprandial-targeting (PPT) diet versus a Mediterranean (MED) diet in pre-diabetes.DesignIn a 6-month dietary intervention, adults with pre-diabetes were randomly assigned to follow an MED or PPT diet (based on a machine-learning algorithm for predicting postprandial glucose responses). Data collected at baseline and 6 months from 200 participants who completed the intervention included: dietary data from self-recorded logging using a smartphone application, gut microbiome data from shotgun metagenomics sequencing of faecal samples, and clinical data from continuous glucose monitoring, blood biomarkers and anthropometrics.ResultsPPT diet induced more prominent changes to the gut microbiome composition, compared with MED diet, consistent with overall greater dietary modifications observed. Particularly, microbiome alpha-diversity increased significantly in PPT (p=0.007) but not in MED arm (p=0.18). Post hoc analysis of changes in multiple dietary features, including food-categories, nutrients and PPT-adherence score across the cohort, demonstrated significant associations between specific dietary changes and species-level changes in microbiome composition. Furthermore, using causal mediation analysis we detect nine microbial species that partially mediate the association between specific dietary changes and clinical outcomes, including three species (fromBacteroidales,Lachnospiraceae,Oscillospiralesorders) that mediate the association between PPT-adherence score and clinical outcomes of hemoglobin A1c (HbA1c), high-density lipoprotein cholesterol (HDL-C) and triglycerides. Finally, using machine-learning models trained on dietary changes and baseline clinical data, we predict personalised metabolic responses to dietary modifications and assess features importance for clinical improvement in cardiometabolic markers of blood lipids, glycaemic control and body weight.ConclusionsOur findings support the role of gut microbiome in modulating the effects of dietary modifications on cardiometabolic outcomes, and advance the concept of precision nutrition strategies for reducing comorbidities in pre-diabetes.Trial registration numberNCT03222791.

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“…A clinical study collecting the data from NSCLC patients who received anti-PD1 Abs treatment demonstrated that Alistipes putredinis together with another two bacteria were enriched in the responding patients, which was accompanied with a higher level of memory CD8 + T cells and NKT cells in the periphery blood [ 15 ]. A recent metagenomic analysis of the gut microbiota observed a reduced relative abundance of Alistipes onderdonkii in an orthotopic, patient-derived xenograft model; the data in vitro demonstrated that Alistipes onderdonkii was able to inhibit pancreatic tumor cells’ proliferation and suppress the growth of pancreatic primary cancer cells [ 81 ].…”

Section: The Bacteria Species Associated With Both Favorable and Unfa...mentioning

confidence: 99%

The Species of Gut Bacteria Associated with Antitumor Immunity in Cancer Therapy

Liu

Hussein

et al. 2022

Cells

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Both preclinical and clinical studies have demonstrated that the modulation of gut microbiota could be a promising strategy for enhancing antitumor immune responses and reducing resistance to immunotherapy in cancer. Various mechanisms, including activation of pattern recognition receptors, gut commensals-produced metabolites and antigen mimicry, have been revealed. Different gut microbiota modulation strategies have been raised, such as fecal microbiota transplantation, probiotics, and dietary selection. However, the identification of gut bacteria species that are either favorable or unfavorable for cancer therapy remains a major challenge. Herein, we summarized the findings related to gut microbiota species observed in the modulation of antitumor immunity. We also discussed the different mechanisms underlying different gut bacteria’s functions and the potential applications of these bacteria to cancer immunotherapy in the future.

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Metagenomic analysis of gut microbiome reveals a dynamic change in Alistipes onderdonkii in the preclinical model of pancreatic cancer, suppressing its proliferation

Cited by 6 publications

References 73 publications

Gut microbial signature in lung cancer patients highlights specific taxa as predictors for durable clinical benefit

Gut microbial signature in lung cancer patients highlights specific taxa as predictors for durable clinical benefit

Gut microbiome modulates the effects of a personalised postprandial-targeting (PPT) diet on cardiometabolic markers: a diet intervention in pre-diabetes

The Species of Gut Bacteria Associated with Antitumor Immunity in Cancer Therapy

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