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. 2022 Jan 1;13(3):764-774.
doi: 10.7150/jca.63490. eCollection 2022.

Non-absorbable antibiotic treatment inhibits colorectal cancer liver metastasis by modulating deoxycholic acid metabolism by intestinal microbes (VSports)

Junjie Deng  1   2 , Wei Yuan  1 , Qin Tan  2 , Xundong Wei  2 , Jie Ma  2
Affiliations

Non-absorbable antibiotic treatment inhibits colorectal cancer liver metastasis by modulating deoxycholic acid metabolism by intestinal microbes (V体育官网入口)

Junjie Deng et al. J Cancer. .

Abstract

Emerging evidence suggests that intestinal microbes influence the occurrence and development of colorectal cancer (CRC). However, few studies have examined the relationship between gut bacteria and liver metastasis of CRC. In this study, we found that administration of non-absorbable antibiotics inhibited liver metastasis of CRC in a mouse model compared with a control group. To elucidate the underlying mechanism, immune cell infiltration analysis, 16S rRNA sequencing, and metabolomics were performed. Differential analysis revealed that non-absorbable antibiotic treatment significantly altered gut microbial diversity and decreased the concentration of deoxycholic acid (DCA) in feces and liver tissues VSports手机版. Furthermore, we verified that bacteria capable of converting cholic acid (CA) to DCA via 7α-dehydroxylation were reduced in mice treated with non-absorbable antibiotics. Finally, in vitro and in vivo experiments confirmed that DCA accelerated the proliferation and metastasis of CRC cells. .

Keywords: Colorectal cancer; Deoxycholic acid; Microbes; Tumor metastasis. V体育安卓版.

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Conflict of interest statement

Competing Interests: The authors have declared that no competing interest exists.

Figures

Figure 1
Figure 1
Non-absorbable antibiotic treatment inhibits tumor liver metastasis in mouse models. (A) Flowchart of the antibiotic treatment model. (B) HE staining of mouse liver tissues and analysis of mouse blood ALT levels revealed no significant changes after two weeks of antibiotic treatment. Sections were observed under a microscope at 400×. (C) Liver metastasis in BALB/c mice after spleen injection of 1.5×106 CT26luc cells. (D) Metastasis indexes and (E) luminescence intensities showed that antibiotic treatment significantly reduced liver metastasis in BALB/c mice. (F) Liver metastasis in C57BL/6J mice after spleen injection of 2×106 MC38 cells. (G) Metastasis indexes showed that antibiotic treatment significantly decreased liver metastasis in C57BL/6J mice. N.S., no significance; *P < 0.05, **P < 0.01.
Figure 2
Figure 2
Non-absorbable antibiotic treatment alters the composition of the gut microbiota. (A) PCA showed that OTU diversity changed significantly after antibiotic treatment. Anosim analysis was used to obtain P-values. (B) Rarefaction curves of microbes at the OTU level. (C) Bar plot of microbial diversity at the order level. (D) Ratio of the relative abundances of Bacteroidales to Clostridiales. (E) PCA analysis and (F) rarefaction curve of microbes in lung tissues at the OTU level after antibiotic treatment. (G) Quantitative PCR showed that two weeks of antibiotic treatment reduced the levels of gram-negative bacteria. (H) ELISA demonstrated that blood LPS levels were reduced after antibiotic treatment. (I) Heatmap of top 15 altered KEGG pathways according to PICRUST analysis. *P < 0.05, **P < 0.01, *** P < 0.001.
Figure 3
Figure 3
Non-targeted metabolomics analysis reveals changes in bile acid metabolism. (A) Fecal and (B) liver metabolites were altered after antibiotic treatment. (C) Venn plot of common differentially expressed metabolites between fecal and liver tissue samples. (D) Volcano plot of non-targeted metabolomics results in fecal samples and (E) liver tissues. (F) KEGG enrichment analysis of fecal metabolites showed that antibiotic treatment influenced the bile acid pathway. *P < 0.05, **P <0.01, *** P < 0.001.
Figure 4
Figure 4
Metabolomics analysis reveals that DCA is a key metabolite. (A) Bile acid metabolism pathway. The red upward arrow indicates increasing levels of metabolites in serum after two weeks of treatment with non-absorbable antibiotics. The green downward arrow indicates decreasing levels of metabolites in serum after two weeks of treatment with non-absorbable antibiotics. (B) Ratio of conjugated primary bile acids to primary bile acids. (C) Ratios of primary bile acids. (D) Expression of bile acid synthesis-related genes in transcripts per million (TPM). (E) Quantitative PCR analysis of the BaiJ gene of Clostridium XIVa showed that antibiotic treatment significantly reduced its expression. (F) Relative expression of bile acid metabolites in mouse fecal samples and (G) liver tissues. *P < 0.05, ** P < 0.01, *** P < 0.001; CA, cholic acid; CDCA, chenodeoxycholic acid; αMCA, alpha-muricholic acid; βMCA, beta-muricholic acid; TCA, taurocholic acid; GCA, glycine cholic acid; TCDCA, taurochenodeoxycholic acid; GCDCA, glycochenodeoxycholic acid; TαMCA, tauro-α-muricholic acid; TβMCA, tauro-β-muricholic acid; DCA, deoxycholic acid; LCA, lithocholic acid; ωMCA, omega-muricholic acid; HDCA, hyodeoxycholic acid; MDCA, murideoxycholic acid.
Figure 5
Figure 5
DCA promotes cell proliferation and metastasis in vitro. (A) DCA concentration in plasma of CRC patients. CCK8 assays of (B) CT26luc and (C) MC38 cells. (D) Transwell analysis showed that DCA promoted tumor cell migration. The results were observed under a microscope at 100×. Barplot of Transwell results of (E) CT26luc and (F) MC38 cells. *P < 0.05, **P < 0.01, *** P < 0.001.
Figure 6
Figure 6
DCA promotes cell proliferation and metastasis in vivo. (A) Flowchart of mouse treatment with DCA. (B) DCA treatment promoted colorectal cancer liver metastasis in the mouse model. Analysis of (C) the average number of tumors per liver and (D) metastasis indexes showed that DCA promoted liver metastasis in vivo. (E) Schematic illustration of the experimental results. *P < 0.05.
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