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. 2022 Jun 1:12:886447.
doi: 10.3389/fcimb.2022.886447. eCollection 2022.

A Microbiota-Dependent Response to Anticancer Treatment in an In Vitro Human Microbiota Model: A Pilot Study With Hydroxycarbamide and Daunorubicin

Affiliations

A Microbiota-Dependent Response to Anticancer Treatment in an In Vitro Human Microbiota Model: A Pilot Study With Hydroxycarbamide and Daunorubicin

Claire Amaris Hobson et al. Front Cell Infect Microbiol. .

Abstract

Background: Anticancer drug efficacy is linked to the gut microbiota's composition, and there is a dire need to better understand these interactions for personalized medicine. In vitro microbiota models are promising tools for studies requiring controlled and repeatable conditions. We evaluated the impact of two anticancer drugs on human feces in the MiniBioReactor Array (MBRA) in vitro microbiota system.

Methods: The MBRA is a single-stage continuous-flow culture model, hosted in an anaerobic chamber. We evaluated the effect of a 5-day treatment with hydroxycarbamide or daunorubicine on the fecal bacterial communities of two healthy donors. 16S microbiome profiling allowed analysis of microbial richness, diversity, and taxonomic changes.

Results: In this host-free setting, anticancer drugs diversely affect gut microbiota composition. Daunorubicin was associated with significant changes in alpha- and beta-diversity as well as in the ratio of Firmicutes/Bacteroidetes in a donor-dependent manner. The impact of hydroxycarbamide on microbiota composition was not significant.

Conclusion: We demonstrated, for the first time, the impact of anticancer drugs on human microbiota composition, in a donor- and molecule-dependent manner in an in vitro human microbiota model. We confirm the importance of personalized studies to better predict drug-associated-dysbiosis in vivo, linked to the host's response to treatment.

Keywords: MBRA; anticancer treatment and bacteria; daunorubicin; gut microbiota; hydroxycarbamide; in vitro microbiota model.

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Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

Figure 1
Figure 1
MBRA model and experimental design. (A) The MBRA model, the input and output pumps, and the 24 culture chambers placed on a magnetic stirring plate. (B) The treatment administration, simultaneously, directly in the culture chambers. (C) The experimental design and the 6 conditions evaluated in this work.
Figure 2
Figure 2
Principal coordinate analysis (PCoA) of the Jaccard metrics, with all donors, all conditions, and all time points. Dots represent donor A and triangles donor (B) Size dots/triangles are proportional to the time of the experiment; the bigger the later in the experiment. Figure on the left-hand side represents hydroxycarbamide and daunorubicin on the right-hand side.
Figure 3
Figure 3
Change from baseline of the Shannon Diversity Index in donors A and B, in all conditions. S is considered the baseline. Solid lines represent donor (A), and dotted lines represent donor (B) Light blue represents the controls, and red represents the treated groups. Orange square represents the treatment period (average and 68% CI). All time points are normalized so that control chambers average at 1. The top figure represents hydroxycarbamide, and the bottom figure represents daunorubicin.
Figure 4
Figure 4
Beta diversity Bray–Curtis (A–C) and Jaccard metrics (B–D) representation. Each condition is compared with the control at the same time point, and S is baseline. Light blue represents the controls, and red represents the treated groups. Orange square represents the treatment period (average and 68% CI). All time points are normalized so that control chambers average at 1. (A, B) Hydroxycarbamide; (C, D) daunorubicin.
Figure 5
Figure 5
Impact of the treatments on the main 3 phyla of interest: Firmicutes (A), Bacteroidetes (B), and Proteobacteria (C). Counts were estimated from rarefied tables. Fecal bacterial composition was analyzed after 16S rRNA gene sequencing. Solid lines represent donor A, and dotted lines represent donor (B) Light blue represents the controls, and red represents the treated groups. Orange square represents the treatment period (average and 68% CI). The top figure represents hydroxycarbamide, and the bottom figure represents daunorubicin.
Figure 6
Figure 6
Firmicutes to Bacteroidetes ratio to early detect dysbiosis after treatment. Solid lines represent donor A, and dotted lines represent donor B Light blue represents the controls, and red represents the treated groups. Orange square represents the treatment period (average and 68% CI). The top figure represents hydroxycarbamide, and the bottom figure represents daunorubicin.

References

    1. Aarnoutse R., Ziemons J., Penders J., Rensen S. S., de Vos-Geelen J., Smidt M. L. (2019). The Clinical Link Between Human Intestinal Microbiota and Systemic Cancer Therapy. Int. J. Mol. Sci. 20, 1–34. doi: 10.3390/ijms20174145 - DOI - PMC - PubMed
    1. Alexander J. L., Wilson I. D., Teare J., Marchesi J. R., Nicholson J. K., Kinross J. M. (2017). Gut Microbiota Modulation of Chemotherapy Efficacy and Toxicity. Nat. Rev. Gastroenterol. Hepatol. 14, 356–365. doi: 10.1038/nrgastro.2017.20 - DOI - PubMed
    1. Auchtung J. M., Robinson C. D., Britton R. A. (2015). Cultivation of Stable, Reproducible Microbial Communities From Different Fecal Donors Using Minibioreactor Arrays (MBRAs). Microbiome 3, 42. doi: 10.1186/s40168-015-0106-5 - DOI - PMC - PubMed
    1. Babudri N., Pani B., Tamaro M., Monti-Bragadin C., Zunino F. (1984). Mutagenic and Cytotoxic Activity of Doxorubicin and Daunorubicin Derivatives on Prokaryotic and Eukaryotic Cells. Br. J. Cancer 50, 91. doi: 10.1038/bjc.1984.143 - DOI - PMC - PubMed
    1. Bilotta A. J., Ma C., Yang W., Yu Y., Yu Y., Zhao X., et al. . (2021). Propionate Enhances Cell Speed and Persistence to Promote Intestinal Epithelial Turnover and Repair. Cell. Mol. Gastroenterol. Hepatol. 11, 1023–1044. doi: 10.1016/j.jcmgh.2020.11.011 - DOI - PMC - PubMed

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