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Microbiota-derived tryptophan catabolites mediate the chemopreventive effects of statins on colorectal cancer

Nature Microbiology volume 8, pages 919–933 (2023)Cite this article

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Abstract

Epidemiological studies have indicated an association between statin use and reduced incidence of colorectal cancer (CRC), and work in preclinical models has demonstrated a potential chemopreventive effect. Statins are also associated with reduced dysbiosis in the gut microbiome, yet the role of the gut microbiome in the protective effect of statins in CRC is unclear. Here we validated the chemopreventive role of statins by retrospectively analysing a cohort of patients who underwent colonoscopies. This was confirmed in preclinical models and patient cohorts, and we found that reduced tumour burden was partly due to statin modulation of the gut microbiota. Specifically, the gut commensal Lactobacillus reuteri was increased as a result of increased microbial tryptophan availability in the gut after atorvastatin treatment. Our in vivo studies further revealed that L. reuteri administration suppressed colorectal tumorigenesis via the tryptophan catabolite, indole-3-lactic acid (ILA). ILA exerted anti-tumorigenic effects by downregulating the IL-17 signalling pathway. This microbial metabolite inhibited T helper 17 cell differentiation by targeting the nuclear receptor, RAR-related orphan receptor γt (RORγt). Together, our study provides insights into an anti-cancer mechanism driven by statin use and suggests that interventions with L. reuteri or ILA could complement chemoprevention strategies for CRC.

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Fig. 1: Statin-modulated microbiota mediates chemopreventive effects.
Fig. 2: Atorvastatin expands the gut commensal L. reuteri.
Fig. 3: Metabolically active L. reuteri suppresses CRC development.
Fig. 4: ILA is essential to the anti-cancer effects of L. reuteri.
Fig. 5: Statins induce a microenvironment with low TH17 responses.
Fig. 6: ILA suppresses TH17 differentiation by targeting the RORγt.

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Data availability

Raw reads of 16S rRNA-sequencing were uploaded to the National Center for Biotechnology Information (NCBI) Sequence Read Archive database (accession number: PRJNA831634; https://www.ncbi.nlm.nih.gov/bioproject/PRJNA831634). RNA-sequencing data have been deposited in the Gene Expression Omnibus (GEO; https://www.ncbi.nlm.nih.gov/geo/) of NCBI and are accessible through the GEO Series accession number GSE201453.

Datasets analysed during the current study are the TCGA colon and rectal cancer datasets, which are available in the TCGA database, and GSE81375, which is available in the GEO database. Source data are provided with this paper.

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Acknowledgements

We thank all patients and individuals for their participation in our study; C.-Z. Guo and the staff at the Core Facility of Basic Medical Sciences, Shanghai Jiao Tong University School of Medicine for technical support in flow cytometry; and W.-H. Jiang (CAS Center for Excellence in Molecular Plant Sciences) for electroporation system usage. This project was supported by grants from the National Key R&D Program of China (2020YFA0509200 to J.-Y.F.), the National Natural Science Foundation of China (81830081to J.-Y.F., 31970718 to J.-Y.F., 81972203 to Y.-X.C., 82250005 to J.-Y.F.), the Shanghai Municipal Health Commission, Collaborative Innovation Cluster Project (2019CXJQ02 to J.-Y.F.), the Clinical Research Plan of SHDC (SHDC2020CR1034B to J.-Y.F.), the Shanghai Sailing Program (22YF1438500 to J.-X.H., 21YF1425600 to J.-Y.F.), the Innovative Research Team of high-level local universities in Shanghai (SSMU-ZLCX20180200 to J.-Y.F.) and Major Health Science and Technology Projects in Zhejiang Province (WKJ-ZJ-2217 to H.X.). Parts of Extended Data Figs. 1–4 and 6 were generated using templates from Servier Medical Art (https://smart.servier.com/), provided by Servier and licensed under a Creative Commons Attribution 3.0 unported license (https://creativecommons.org/licenses/by/3.0/).

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Author notes

  1. These authors contributed equally: Ji-Xuan Han, Zhi-Hang Tao, Ji-Lin Wang.

Authors and Affiliations

  1. Division of Gastroenterology and Hepatology; Shanghai Institute of Digestive Disease; NHC Key Laboratory of Digestive Diseases; State Key Laboratory for Oncogenes and Related Genes; Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China

    Ji-Xuan Han, Zhi-Hang Tao, Ji-Lin Wang, Lu Zhang, Chen-Yang Yu, Zi-Ran Kang, Yuanhong Xie, Jialu Li, Shiyuan Lu, Yun Cui, Hui-Min Chen, Wenyu Su, Tian-Hui Zou, Cheng-Bei Zhou, Jie Hong, Haoyan Chen, Hua Xiong, Ying-Xuan Chen & Jing-Yuan Fang

  2. Department of Gastrointestinal Surgery, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China

    Jia Xu, Enhao Zhao, Ming Wang, Jinxian Chen & Zheng Wang

  3. Department of Pathology, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China

    Qiang Liu

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Contributions

J.-X.H., Z.-H.T. and J.-Y.F. conceived the project; J.-X.H. and Z.-H.T. designed and performed experiments, analysed data, made figures and drafted the manuscript; J.-L.W. collected and analysed CRA recurrence data in Cohort 1; L.Z. helped with electroporation; C.-Y.Y., Z.-R.K., Y.X., S.L., H.-M.C., W.S., T.-H.Z., C.-B.Z. and J.H. provided fruitful discussions; J.L. helped with isolation of colonic lamina propria cells; Y.C. and Q.L. helped with pathological diagnosis; J.X., E.Z., M.W., J.C. and Z.W. provided faecal and tissue samples of CRC patients in Cohorts 2 and 3; H.C. performed PS matching in Cohort 1 and helped with statistical analysis; H.X., Y.-X.C. and J.-Y.F. supervised the study; J.-X.H., Z.-H.T., J.-L.W., H.X., Y.-X.C. and J.-Y.F. revised the draft with input from all authors.

Corresponding authors

Correspondence to Hua Xiong, Ying-Xuan Chen or Jing-Yuan Fang.

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Nature Microbiology thanks Robert Jenq, Peter Turnbaugh and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

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Extended data

Extended Data Fig. 1 Statin-modulated microbiota mediates chemopreventive effects.

a, Scheme for the experiment design. ApcMin mice were administered 2% Tween 80 (vehicle control), or atorvastatin (20 mg/kg). b, Body weight of ApcMin mice receiving vehicle control or atorvastatin was recorded (n = 10 mice per group). c, Representative macroscopic images of colons. (d-h) d, Scheme for the experiment design. ApcMin mice were administered 2% Tween 80 (vehicle control), or lovastatin (20 mg/kg) (n = 10 mice per group). e, Representative macroscopic images of colons. f, Colon tumor number under different treatments. g, Colon tumor volume under different treatments. h, Representative H&E staining of colons under different treatments. i-m, i, Scheme for the experiment design. ApcMin mice were administered 10% DMSO (vehicle control), or fenofibrate (100 mg/kg) (n = 10 mice per group). j, Representative macroscopic images of colons. k, Colon tumor number under different treatments. l, Colon tumor volume under different treatments. m, Representative H&E staining of colons under different treatments. n, Scheme for the experiment design. Microbiota-depleted ApcMin mice were administered vehicle control, or atorvastatin. o, Representative macroscopic images of colons. p, Scheme for the experiment design. Microbiota-depleted ApcMin mice were administered feces from mice receiving vehicle control or atorvastatin (Ator). q, Representative macroscopic images of colons. Data with error bars represent the mean ± s.d. Data were analyzed by two-tailed Welch’s t test (b, f, g), and two-tailed unpaired Student’s t test (b, k, l).

Extended Data Fig. 2 Atorvastatin expands the gut commensal L. reuteri.

a, Scheme for the experiment design. Feces were collected to perform 16S rRNA-sequencing on ApcMin mice receiving four-week vehicle control or atorvastatin. b, Venn diagram showing the genera enriched in the atorvastatin group (the current study, 13), genera decreased during CRC development (Yu et al., 8), and both (1). Venn diagram showing the genera enriched in the vehicle control group (the current study, 9), and genera increased during CRC development (Yu et al., 5). c, Real-time PCR was performed to detect the abundance of eight common Lactobacillus species in feces from ApcMin mice receiving vehicle control or atorvastatin (n = 8 or 9 mice for vehicle control or atorvastatin treatment, respectively). Lpla, L. plantarum; Lbrev, L. brevis; Lcase, L. casei; Lmuri, L. murinus; Lsalirv, L. salivarius; Lrham, L. rhamnosus; Lferm, L. fermentum; Ldelb, L. delbrueckii. d, Real-time PCR was performed to detect the abundance of L. reuteri in ApcMin mice receiving fecal microbiota from vehicle control- or atorvastatin-treated mice (n = 10 mice per group). e, Scheme for the trial design. Feces were collected from individuals before and after atorvastatin intervention. f, OD600 values for L. reuteri treated with atorvastatin (1 μM) for 16 h. All are grown in MRS broth (n = 5 biologically independent samples per group). g, Real-time PCR was performed to detect the mRNA expression of Ido1 in colonic lamina propria cells from ApcMin mice receiving vehicle control or atorvastatin (n = 5 mice per group). h, Real-time PCR was performed to detect the mRNA expression of Ido1 in mice colon organoids treated with atorvastatin (n = 3 biologically independent samples per group). Data with error bars represent the mean ± s.d. Data were analyzed by two-tailed unpaired Student’s t test (c, f, g, h), and two-tailed Welch’s t test (d).

Extended Data Fig. 3 Metabolically-active L. reuteri suppresses CRC development.

a, Scheme for the experiment design. Microbiota-depleted ApcMin mice were administered PBS, heat-killed L. reuteri (108 CFU/100 μL), or live L. reuteri (108 CFU/100 μL). b, Representative macroscopic images of colons. c, Scheme for the experiment design. ApcMin mice were administered PBS, L. reuteri cell-free supernatant (CFS), or L. reuteri cell-free supernatant treated with proteinase K (CFSK). d, Representative macroscopic images of colons. e, Tryptophan metabolism through the host pathways (serotonin and kynurenine pathways) and microbial pathway (indole pathway). IDO1: Indoleamine 2,3-Dioxygenase 1; TPH1: Tryptophan hydroxylase 1; TMO: Tryptophan 2-Monooxygenase; TrD: Tryptophan Decarboxylase; IAM: Indole-3-Acetamide; IAA: Indole−3−Acetic Acid; IAld: Indole-3-Aldehyde; IAAld: Indole-3-Acetaldehyde; ArAT: Aromatic amino acid aminotransferase; IPYA: Indole-3-Pyruvate; ILA: Indole-3-Lactic Acid; IA: Indoleacrylic Acid; IPA: Indole-3-Propionic Acid; TNA: Tryptophanase. f, Heatmap showing hierarchical clustering of Spearman correlation coefficients between fecal bacterial abundance and selected tryptophan catabolites. *P < 0.05; **P < 0.01.

Extended Data Fig. 4 ILA is essential to the anti-cancer effects of L. reuteri.

a, Scheme for the experiment design. ApcMin mice were administered 0.01% DMSO (vehicle control), or ILA (0.1 mg/kg). b, Quantification of fecal ILA in feces from ApcMin mice receiving vehicle control or ILA (n = 6). c, Representative macroscopic images of colons. d, Schematic for the generation of L. reuteri ∆ArAT by homologous recombination. e, PCR was performed to verify the mutant. f, Sanger sequencing was performed to validate the mutant. g, Scheme for the experiment design. Microbiota-depleted ApcMin mice were administered PBS, WT L. reuteri (108 CFU/ 100 μL), or L. reuteri ΔArAT (108 CFU/ 100 μL). h, Representative macroscopic images of colons. Data with error bars represent the mean ± s.d. Data were analyzed by two-tailed unpaired Student’s t test (b).

Extended Data Fig. 5 Statins induce a microenvironment with low TH17 responses.

a, b, KEGG pathway analysis of (a) colonic epithelium and (b) lamina propria cells listed by P value. c, d, Gene Set Enrichment Analysis (GSEA) was performed on (a) colonic epithelium and (b) lamina propria cells using the web tool from Broad Institute. NES, normalized enrichment score. e, The correlation between the L. reuteri abundance and IL-17A expression in adjacent normal tissues from CRC patients (Cohort 3). f, Real-time PCR analysis for Rorc expression in lamina propria under different treatments (n = 5). g, h, j, l, and m, Representative dot plots gated on CD4+ T cells. i, k, Statistical analysis of the percentages of IFNγ+ CD4+ T cells (i) and FOXP3+ CD4+ T cells (k) in colon lamina propria under different treatments. (n = 5). Data with error bars represent the mean ± s.d. Data were analyzed by two-tailed Spearman correlation analysis (e), and two-tailed unpaired Student’s t test (f, i, k).

Extended Data Fig. 6 ILA suppresses TH17 differentiation by targeting the RORγt.

a, Schematic of in vitro TH17 polarization. b, Representative dot plots showing IL-17A production by naive CD4+ T cells cultured in TH17-polarizing conditions. c, Real-time PCR analysis for Rorc expression in in vitro polarized TH17 cells (n = 3). d, Schematic of MST. e, Flow cytometry of IL-17A production by naive CD4+ T cells cultured in TH17-polarizing conditions and treated with ILA, CH-223191 (an AHR antagonist), or both. f, g, Real-time PCR analysis for Cyp1a1 expression in colon epithelium under different treatments (n = 5). h, i, Representative confocal images showing ZO-1 expression under different treatments. ZO-1 (green), and DAPI (blue). j-m, (j) Scheme for the experiment design. The protective effect of ILA on CRC initiation was assessed in the context of AHR blockade (n = 10 mice per group). (k) Representative macroscopic images of colons. (l) Colon tumor number under different treatments. (m) Colon tumor volume under different treatments. n, Schematic diagram of the relationship among atorvastatin, L. reuteri-derived ILA, TH17 cells, and tumorigenesis. Data with error bars represent the mean ± s.d. Data were analyzed by two-tailed unpaired Student’s t test (c, f, g), and one-way ANOVA with Holm-Sidak or Tukey’s test (l, m).

Supplementary information

Supplementary Information

Supplementary Figs. 1 and 2, and the full trial protocol.

Reporting Summary

Supplementary Tables

Supplementary Table 1. Baseline characteristics of Cohort 1. Table 2. Detailed information of healthy participants. Table 3. Genes regulated by atorvastatin in the current study and in GSE81375. Table 4. Concentrations of tryptophan and tryptophan catabolites in faeces from mice. Table 5. List of PCR primers.

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Han, JX., Tao, ZH., Wang, JL. et al. Microbiota-derived tryptophan catabolites mediate the chemopreventive effects of statins on colorectal cancer. Nat Microbiol 8, 919–933 (2023). https://doi.org/10.1038/s41564-023-01363-5

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