Inhibition of the NF-κB/HIF-1α signaling pathway in colorectal cancer by tyrosol: a gut microbiota-derived metabolite

Abstract

Background: The development and progression of colorectal cancer (CRC) are influenced by the gut environment, much of which is modulated by microbial-derived metabolites. Although some research has been conducted on the gut microbiota, there have been limited empirical investigations on the role of the microbial-derived metabolites in CRC.

Methods: In this study, we used LC-MS and 16S rRNA sequencing to identify gut microbiome-associated fecal metabolites in patients with CRC and healthy controls. Moreover, we examined the effects of Faecalibacterium prausnitzii and tyrosol on CRC by establishing orthotopic and subcutaneous tumor mouse models. Additionally, we conducted in vitro experiments to investigate the mechanism through which tyrosol inhibits tumor cell growth.

Results: Our study revealed changes in the gut microbiome and metabolome that are linked to CRC. We observed that Faecalibacterium prausnitzii, a bacterium known for its multiple anti-CRC properties, is significantly more abundant in the intestines of healthy individuals than in those of individuals with CRC. In mouse tumor models, our study illustrated that Faecalibacterium prausnitzii has the ability to inhibit tumor growth by reducing inflammatory responses and enhancing tumor immunity. Additionally, research investigating the relationship between CRC-associated features and microbe-metabolite interactions revealed a correlation between Faecalibacterium prausnitzii and tyrosol, both of which are less abundant in the intestines of tumor patients. Tyrosol demonstrated antitumor activity in vivo and specifically targeted CRC cells without affecting intestinal epithelial cells in cell experiments. Moreover, tyrosol treatment effectively reduced the levels of reactive oxygen species (ROS) and inflammatory cytokines in MC38 cells. Western blot analysis further revealed that tyrosol inhibited the activation of the NF-κB and HIF-1 signaling pathways.

Conclusions: This study investigated the relationship between CRC development and changes in the gut microbiota and microbial-derived metabolites. Specifically, the intestinal metabolite tyrosol exhibits antitumor effects by inhibiting HIF-1α/NF-κB signaling pathway activation, leading to a reduction in the levels of ROS and inflammatory factors. These findings indicate that manipulating the gut microbiota and its metabolites could be a promising approach for preventing and treating CRC and could provide insights for the development of anticancer drugs.

Keywords: Colon Cancer; Colorectal Cancer; T cell.

Figure 1. Patients with colorectal cancer have distinct gut microbiota compositions. (A) The alpha diversity in terms of chao 1, pielou_e, Simpson index, and Shannon index. (B) The rarefaction Curve in terms of chao 1, pielou_e, Simpson index, and Shannon index. (C) Principal co-ordinates analysis based on the weighted UniFrac distance. (D) Changes in the gut bacterial community at the phylum level. (E) Changes in the gut bacterial community at the genus level. (F) Changes in the gut bacterial community at the species level.Data are presented as the mean±SEM. *p<0.05; ***p<0.001.

Figure 2. Faecalibacteriumprausnitzii inhibits tumor growth by regulating tumor immunity. (A) Experimental setting of the approach of Faecalibacterium prausnitzii in the CRC model. (B) The antitumor activity of Faecalibacterium prausnitzii in the subcutaneous tumor model. Tumor volume and tumor weight represent excised tumor at day 16. (C) Experimental setting of the Faecium prevotella approach in a CRC model after antibiotic treatment. (D) The antitumor activity of Faecalibacterium prausnitzii in the subcutaneous tumor model after antibiotic treatment. (E) Levels of proinflammatory cytokines, including IL-1β, IL-6, and TNF-α. (F) Dot plots showing the CD8+ T cells in the blood by flow cytometry. (G) The CD8+ T cells within tumor tissues by flow cytometry. CRC, colorectal cancer. FP, Faecalibacterium prausnitzii group. Data are presented as the mean±SEM. *p<0.05; **p<0.01;****p<0.0001.

Figure 3. Metabolic profiles of health and colorectal cancer patients. (A) Partial least squares discrimination analysis, PLS-DA score plots for gut samples. (B) Volcano plot for differential metabolites in comparison between CM and TM. (C) Bubble map of KEGG enrichment. Abscissa is a p value, and smaller p values are statistically more significant. The ordinate is the KEGG pathway. The size of the bubbles in the figure represents enriched metabolic concentrations. (D) Metabome-16s association analysis Heatmap of Correlation Analysis. The relative abundance of each differential microbiota and the correlation coefficient r and p values between different differential metabolites were calculated using the Pearson statistical method. The heatmap of the results indicates the significance level with * marking for p values ≤0.05. (E) Tyrosol content in serum and feces after stimulation with Faecalibacterium prausnitzii. (F) Tyrosol content in serum and feces of mice in EVOO tumor model. PLS-DA, partial least squares discriminant analysis.Data are presented as the mean±SEM. **p<0.01; ***p<0.001; ****p<0.0001. FP, Faecalibacterium prausnitzii group. EVOO, extra virgin olive oil group. CM, control group fecal metabolomics. TM, tumor group fecal metabolomics.

Figure 4. Tyrosol inhibits CRC cell viability and reduces colony formation. (A) No effect of tyrosol on normal intestinal epithelium. (B and C) Inhibitors of murine and human colorectal cancer growth by tyrosol. (D) Effect of the tyrosol in the colony formation of MC38 and HCT116. (E) Levels of proinflammatory cytokines, including IL-1β, IL-6, and TNF-α in in cell culture supernatant samples. (F) ROS levels and SOD levels of MC38 and HCT116 were measured. (G) Representative protein levels of p-p65, p-IκB, HIF-1α, and HIF-1β and intensity analysis of HIF-1α, HIF-1β, p-p65, and p-IκB. The values presented are the means±SEM of three independent experiments. An asterisk is placed above differences with a significance exceeding *p<0.05; **p<0.01; ***p<0.001; ****p<0.0001. CRC, colorectal cancer.

Figure 5. Effect of tyrosol on tumor growth in both the subcutaneous tumor model and the orthotopic CRC model. (A) The antitumor activity of tyrosol in the subcutaneous tumor model. (B) Tumor volume and tumor weight (C) represent excised tumor at day 18. (D) In vivo bioluminescent images in the orthotopic CRC model. (E) Representative photographs and tumor weight of mice in different groups. (F) Experimental setting of the approach of EVOO in the CRC model. (G) The antitumor activity of Faecalibacterium prausnitzii in the subcutaneous tumor model after EVOO treatment. In this figure, the data shown are average±SEM. An asterisk is placed above differences with a significance exceeding *p<0.05; ^∗∗p<0.01; ^∗∗∗p<0.001. CRC, colorectal cancer. FP, Faecalibacterium prausnitzii group. EVOO, extra virgin olive oil group.

Figure 6. Tyrosol enhances tumor immunity and inhibits NF-κB/HIF-1 pathways. (A) Dot plots showing the CD8+ T cells in the blood by flow cytometry. (B) The CD8+ T cells within tumor tissues by flow cytometry. (C) Representative protein levels of p-p65, p-IκB, HIF-1α, and HIF-1β. (D) The intensity analysis of HIF-1α, HIF-1β, p-p65, and p-IκB. (F) Immunohistochemistry staining assessed the HIF-1α level in tumor tissues (scale bar, 50 μm). The positive-stained areas are shown in brown. In this figure, the data shown are average±SEM. An asterisk is placed above differences with a significance exceeding ^∗∗p<0.01; ^∗∗∗p< 0.001; ****p<0.0001.