Multimodal immune phenotyping reveals microbial-T cell interactions that shape pancreatic cancer

Abstract

Microbes are an integral component of the tumor microenvironment. However, determinants of microbial presence remain ill-defined. Here, using spatial-profiling technologies, we show that bacterial and immune cell heterogeneity are spatially coupled. Mouse models of pancreatic cancer recapitulate the immune-microbial spatial coupling seen in humans. Distinct intra-tumoral niches are defined by T cells, with T cell-enriched and T cell-poor regions displaying unique bacterial communities that are associated with immunologically active and quiescent phenotypes, respectively, but are independent of the gut microbiome. Depletion of intra-tumoral bacteria slows tumor growth in T cell-poor tumors and alters the phenotype and presence of myeloid and B cells in T cell-enriched tumors but does not affect T cell infiltration. In contrast, T cell depletion disrupts the immunological state of tumors and reduces intra-tumoral bacteria. Our results establish a coupling between microbes and T cells in cancer wherein spatially defined immune-microbial communities differentially influence tumor biology.

Keywords: T cells; bacteria; cellular communities; gut microbiome; immune system; lung adenocarcinoma; pancreatic ductal adenocarcinoma; spatial heterogeneity; tumor microbiome; tumor microenvironment.

Graphical abstract

Figure 1

Microbial distribution in human solid tumors is spatially heterogeneous and coupled with CD8⁺ T cell infiltration (A) Immunofluorescence (IF) images of CK19 (green), LPS (red), and nuclei (DAPI, blue) (top row) and heatmaps of LPS (bottom row). Scale bars, 2 mm. (B and C) IF images of LPS-poor (left) and LPS-rich (right) regions. Scale bars, 200 μm. (D) Spatial variance of LPS. (E) Distribution of LPS in CK19⁺ tumor cells (yellow) and stromal cells (purple). (F) Study design. (G) Quantification of LPS. CD20 (n = 56 for CD20-poor and n = 11 for CD20-enriched nests pooled from 7 PDAC specimens), CD68 (n = 43 for CD68-poor and n = 28 for CD68-enriched nests pooled from 8 PDAC specimens), and FOXP3 (n = 49 for FOXP3-poor and n = 16 for FOXP3-enriched nests pooled from 9 PDAC specimens). Scale bars, 100 μm. (H) IF images of CD8 (yellow), tumor cells (green, CK19), LPS (red), and nuclei (blue, DAPI). Scale bars, 100 μm. (I) Quantification of LPS in PDAC tumor nests (left; n = 110 for CD8-poor nests and n = 39 for CD8-enriched nests pooled from 10 PDAC specimens). (J) Quantification of LPS in LUAC tumor nests (right; n = 100 for CD8-poor nests and n = 50 for CD8-enriched nests pooled from 10 LUAC specimens). For (D) and (E), n = 9 for PDAC and n = 9 for LUAC. Statistical significance was calculated using a two-tailed Mann-Whitney test (E, G, I, and J). Data are represented as violin plots (center line, median; top and bottom lines, upper and lower quartiles) and scatterplots (mean ± SD). PDAC, pancreatic ductal adenocarcinoma; LUAC, lung adenocarcinoma; NS, not significant.

Figure 2

T cell and microbial co-localization define distinct cellular neighborhoods in human pancreatic cancer (A) Study design for (B)–(D) (n = 185 for cold nests and n = 77 for hot nests pooled from 16 specimens). (B) Images of CD8 (yellow), CD68 (brown), tumor epithelium (teal, CK19), FOXP3 (purple), and nuclei (blue, hematoxylin). Scale bars, 1 mm (top) and 50 μm (bottom). (C) Quantification of CD8⁺ (left), FOXP3⁺ (middle), and CD68⁺ (right) cells. (D) Ratio of CD8⁺ cells to FOXP3⁺ cells. (E) Study design for (F) and (H)–(J). (F) Principal-component analysis (n = 5 for hot and cold tumor nests from 1 specimen). (G) 16S rRNA levels (n = 14 for cold and hot tumor nests from 3 patient specimens). (H and I) Heatmap (H) and enrichment score (I) for the relative expression of genes associated with response to bacterium (GO: 0009617) in hot and cold stroma. (J) Volcano plot of DEGs. (K) Multiplex immunohistochemistry images of CD8 (yellow), PIGR (purple), and nuclei (blue, hematoxylin). (L) Quantification of PIGR (n = 49 for cold nests and n = 46 for hot nests pooled from 7 specimens). (M) Multiplex immunohistochemistry images of CD8 (teal), CD20 (yellow), CD74 (purple), and nuclei (blue, hematoxylin). (N) Quantification of CD74 (n = 71 for cold nests and n = 45 for hot nests pooled from 10 specimens). (O) Summary of cell markers and proteins. For (K) and (M), scale bars, 2 mm (left) and 50 μm (right), and dashed lines indicate tumor epithelium. Statistical significance was calculated using a two-tailed Mann-Whitney test. Data are represented as violin plots (center line, median; top and bottom lines, upper and lower quartiles) and scatterplots (mean + SD or mean). PDAC, pancreatic ductal adenocarcinoma.

Figure 3

The tumor microbiome is linked to T cell infiltration in murine PDAC (A) Study design for (B)–(D) (n = 5–6 for mice orthotopically injected with cold [69] and hot [2838c3] PDAC cells). (B) Quantification of intra-tumoral CD8⁺ and FOXP3⁺ T cells. (C) Representative heatmap (left) of CD8⁺ T cells in murine hot PDAC tumor and corresponding multiplex immunohistochemistry images (right) of CD8 (brown), FOXP3 (purple), tumor cells (yellow, CK19), and nuclei (blue, hematoxylin). Scale bars, 1 mm and 100 μm (insets). (D) 16S rRNA levels in cold and hot orthotopic tumors (left) and stool (right). (E–G) Mice (n = 3–5 per group) were orthotopically injected with cold (n = 3) and hot (n = 2) PDAC cell lines. Principal-component analysis (E) of immune and bacterial determinants displayed in heatmap (F). (G) Correlation plot. (H) Study design for (I)–(M) (n = 6 for mice orthotopically injected with cold [69] and hot [2838c3] tumor cells). (I) Principal-component analysis. (J–M) Volcano plots. Data are representative of three independent experiments (B–D) or two independent experiments (H–M). Statistical significance was calculated using a two-tailed Mann-Whitney test (B and D). Data are represented as scatterplots (mean ± SD). FDR, false discovery rate; NS, not significant.

Figure 4

Intra-tumoral microbial composition and diversity distinguish T cell-enriched and T cell-poor tumors (A) Study design for (B)–(I) (n = 5, 5, and 6 for mice orthotopically injection with PBS, cold [69], and hot [2838c3] PDAC cells, respectively). (B) Percentage of composition of gram-negative and gram-positive bacteria in cold and hot tumors. (C) Linear discriminant analysis. (D) Heatmap of bacterial features at the genus level. (E) Taxonomic compositions at the class and genus levels. (F) α-Diversity in tumor. (G) Principal-coordinate analysis (PCoA) of tumor. (H) α-Diversity in stool. (I) PCoA of stool. Data are representative of two independent experiments (B–I). Statistical significance was calculated using a two-tailed Mann-Whitney test (B and F) and a Kruskal-Wallis test (C and H). Data are represented as scatterplots (mean ± SD).

Figure 5

T cell infiltration into tumors occurs independent of the gut and tumor microbiome (A) Study design for (B)–(K). (B) 16S rRNA levels in tumor and stool from mice orthotopically injected with cold (69) tumor cells (n = 10) or hot (2838c3) tumor cells and treated with (n = 15) and without (n = 20) antibiotics. (C and D) Quantification of CD3⁺ (C) and CD8⁺ and FOXP3⁺ (D) T cells from hot tumors of mice treated with (n = 19) or without (n = 13) antibiotics. (E) 16S rRNA levels in tumor from mice orthotopically injected with cold (69) tumor cells and treated with (n = 5) and without (n = 5) antibiotics. (F) Quantification of CD8⁺ and FOXP3⁺ T cells from cold tumors of mice treated with (n = 5) and without (n = 5) antibiotics. (G) Number of DEGs. (H) Bar graph displaying overrepresentation analysis of DEGs in indicated gene sets. (I and J) Tumor weights at day 20. (K) Quantification of intra-tumoral CD19⁺ cells. (L and M) Mean fluorescence intensity (MFI) of MHC class II (L) and CD206 (M) on CD11b⁺ F4/80⁺ intra-tumoral macrophages. Data were pooled from two to three experiments (B–D and J–M) or are representative of two independent experiments (E–I). Statistical significance was calculated using one-way ANOVA with Dunnett’s test (B, L, and M) and a two-tailed Mann-Whitney test (C–F and I–K). Data are represented as scatterplots (mean ± SD). NS, not significant.

Figure 6

T cells promote the accumulation of intra-tumoral microbes without affecting microbial composition (A) Study design for (B)–(H). (B) Principal-component analysis of mRNA sequencing data. (C) Enrichment score for the relative expression of genes associated with response to bacterium (GO: 0009617). (D–F) Tumor weights at day 20 (D) and 16S rRNA levels in tumor (E) and stool (F) from mice orthotopically injected with cold (69) tumor cells (n = 10) or hot (2838c3) tumor cells and treated with (n = 20) or without (n = 12–13) anti-CD4/CD8 antibodies. (G) Taxonomic compositions at the genus level. (H) PCoA of tumor. (I) α-Diversity in tumor. Data were pooled from two experiments (D–F). Statistical significance calculated using a two-tailed Mann-Whitney test. Data are represented as scatterplots (mean ± SD). NS, not significant.