Gut Microbiota Modulate CD8 T Cell Responses to Influence Colitis-Associated Tumorigenesis

Abstract

There is increasing evidence that gut microbiome perturbations, also known as dysbiosis, can influence colorectal cancer development. To understand the mechanisms by which the gut microbiome modulates cancer susceptibility, we examine two wild-type mouse colonies with distinct gut microbial communities that develop significantly different tumor numbers using a mouse model of inflammation-associated tumorigenesis. We demonstrate that adaptive immune cells contribute to the different tumor susceptibilities associated with the two microbial communities. Mice that develop more tumors have increased colon lamina propria CD8⁺ IFNγ⁺ T cells before tumorigenesis but reduced CD8⁺ IFNγ⁺ T cells in tumors and adjacent tissues compared with mice that develop fewer tumors. Notably, intratumoral T cells in mice that develop more tumors exhibit increased exhaustion. Thus, these studies suggest that microbial dysbiosis can contribute to colon tumor susceptibility by hyperstimulating CD8 T cells to promote chronic inflammation and early T cell exhaustion, which can reduce anti-tumor immunity.

Keywords: CD8 T cells; T cell exhaustion; colitis; colon cancer; inflammation; microbiome.

Figure 1.. Two Colonies of C57BL/6J WT Mice Have Different Colon Tumor Burdens in the AOM/DSS Model of Inflammation-Associated Colon Tumorigenesis

(A) Schema of AOM/DSS model. (B) Representative photo of WT1 and WT2 tumors. Scale bar, 1 cm. (C) Representative micrographs of H&E stains of colon tissue at the tumor endpoint at 40× magnification. Tumors are denoted by black arrows. Scale bar, 100 μm. (D and E) Tumor numbers (D) and sizes (E) are shown. WT1, n = 42; WT2, n = 36. (F) Representative graph of percentage weight change during AOM/DSS treatment compared with day 0. n = 5 mice/group. Data are mean ± SEM and are representative of or pooled from at least three experiments. *p < 0.05 by Mann-Whitney test. See also Figure S1.

Figure 2.. Gut Microbiome Compositions in WT1 and WT2 Mice Are Significantly Different

(A–C) 16S rRNA sequencing of naive WT1 and WT2 fecal microbiota was performed, and richness (A) and alpha diversity (B) were measured. Beta diversity (C) is shown as a nonmetric dimensional scaling (NMDS) plot. *p < 0.05 by Mann-Whitney test. (D) Microbiome composition dissimilarity based on thetaYC distances. *p < 0.05 by AMOVA. (E) Relative bacteria family abundances of naive WT1 and WT2 mice. n = 15/group (F) The most differentially abundant OTUs between WT1 (blue) or WT2 (red) microbiomes were determined using LEfSe pairwise analysis. OTUs with LDA scores greater than 4 are shown. Data are pooled from at least five experiments; WT1, n = 51; WT2, n = 45, unless otherwise noted.

Figure 3.. The Gut Microbiomes of WT1 and WT2 Mice Directly Contribute to Tumor Susceptibility

(A and B) Tumor number (A) and sizes (B) of AOM/DSS-treated GF WT mice that were colonized with SPF WT1 or WT2 whole-stool and cecal homogenates or anaerobically cultivable WT1 or WT2 stool and cecal bacteria for 4 weeks. Tumors were counted 10 days after the last DSS round. Data are mean ± SEM. n = 4 or 5/group. *p < 0.05 by Mann-Whitney test. (C) Representative micrographs of H&E stains of colon tissue at the tumor endpoint at 40× magnification. Tumors are denoted by black arrows. Scale bar, 1 mm. See also Figure S2.

Figure 4.. Specific Bacterial Populations Correlate with High or Low Tumor Susceptibilities

(A) WT1 and WT2 mice were cohoused in a 2:2 ratio(coh) for 4 weeks or a 1:1 ratio (oto) for 6 weeks or cross-fostered (CF). Mice were treated with AOM/DSS and sacrificed for tumor counting on days 60–70 depending on the experiment. (B) Number of tumors in indicated mice after AOM/DSS treatment. The control group includes pooled control mice from all cohousing and cross-fostering experiments. Data are mean ± SEM; controls: WT1, n = 27; WT2, n = 20; coh: n = 9/group; oto: n = 10/group; CF: WT1(WT2), n = 18; WT2(WT1), n = 14. *p < 0.05 by Mann-Whitney test. (C) Phylogenetic tree of nine bacterial candidates associated with low (blue) or high (red) tumor burdens on the basis of sequence similarity. (D and E) Relative bacterial abundances in mice at the time of AOM injection that were associated with low (D) or high (E) tumor burdens. Black lines denote mean relative abundances. Poisson regression p values are shown. LDA scores were determined using LEfSe analyses. Low, n = 85; high, n = 38. Data shown are pooled from at least two independent experiments per microbiome transfer method. See also Figure S2.

Figure 5.. Adaptive Immune Cells Contribute to Increased Tumor Susceptibility of WT2 Mice

(A) Colon LP immune cells from untreated WT1 andWT2 mice were analyzed using flow cytometry. Data are pooled from at least two independent experiments. n = 5–7/group. (B) GF Rag1^−/− mice were gavaged with SPF WT1 or WT2 stool and cecal contents followed by AOM/DSS treatment after 4 weeks of colonization. Mice were sacrificed on day 61 for tumor counting. (C and D) Tumor number (C) and sizes (D) are shown. n = 4–6/group. Data are mean ± SEM. *p < 0.05 by Mann-Whitney test. See also Figure S3.

Figure 6.. Naive WT2 Mice Exhibit Increased CD8⁺ IFNγ T Cells in LP, which Partly Mediates Increased Tumor Susceptibility

(A) Numbers of CD4 and CD8 T cells in colon LP T cells of WT1 and WT2 mice as determined using flow cytometry. Data are pooled from at least two independent experiments. n = 8/group. (B) Colon LP immune cells were ex vivo-stimulated with PMA and ionomycin with monensin for 4 h, and IFNγ, FoxP3, and IL-17 were measured using flow cytometry. Representative flow plots are shown. Data are pooled from at least two independent experiments. n = 8 or 9/group. (C) SPF Cd8^−/− mice were treated with antibiotics for 1 week prior to three consecutive gavages of SPF WT1 or WT2 microbiota followed by AOM and three rounds of 2% DSS after 4 weeks of bacteria colonization. (D and E) Tumor number (D) and sizes (E) were measured on day 62 of AOM/DSS. n = 4–6/group. Data are mean ± SEM. *p < 0.05 by Mann-Whitney test. See also Figures S3–S7.

Figure 7.. Intratumoral WT2 T Cells Display Decreased IFNγ Activity and Increased Exhaustion

(A and B) Numbers of T cells (A) and CD4 and CD8 T cells (B) in tumor (“tum”) and adjacent (“adj”) tissue from AOM/DSS-treated WT1 and WT2 mice as analyzed using flow cytometry on day 60. n = 6–10/group. (C–F) Representative flow plots after ex vivo stimulation of cells for 4 h and analysis of IFNγ (N = 8–10/group), FoxP3, and IL-17 (n = 4–6/group). (G and H) Representative flow plots and quantification of PD-1, Tim-3, and Lag-3 on CD8 (G) or CD4 T (H) cells. n = 5–7/group. n = 5–7/group. Data are mean ± SEM and are pooled from at least two independent experiments. *p < 0.05 by Mann-Whitney test.