Commensal bacteria control cancer response to therapy by modulating the tumor microenvironment

Abstract

The gut microbiota influences both local and systemic inflammation. Inflammation contributes to development, progression, and treatment of cancer, but it remains unclear whether commensal bacteria affect inflammation in the sterile tumor microenvironment. Here, we show that disruption of the microbiota impairs the response of subcutaneous tumors to CpG-oligonucleotide immunotherapy and platinum chemotherapy. In antibiotics-treated or germ-free mice, tumor-infiltrating myeloid-derived cells responded poorly to therapy, resulting in lower cytokine production and tumor necrosis after CpG-oligonucleotide treatment and deficient production of reactive oxygen species and cytotoxicity after chemotherapy. Thus, optimal responses to cancer therapy require an intact commensal microbiota that mediates its effects by modulating myeloid-derived cell functions in the tumor microenvironment. These findings underscore the importance of the microbiota in the outcome of disease treatment.

Figures

Fig. 1.. Oral administration of anti biotics impai rs CpG-ODN-based immunotherapy.

(A) MC38 tumor growth kinetics in H2O-drinking (left) or ABX-treated animals (right) treated once with intratumoral injection of CpG-ODN in combination with anti-IL-10R antibody injected intraperitoneally a day earlier (anti-IL10R/CpG-ODN) or left untreated (control). Data show individual mice combined from multiple independent experiments. (B) Combined tumor volume data from the mice shown in (A) (left; means ± SEM) and corresponding survival data (right). (C) Macroscopic appearance of MC38 tumors in WT, Tnf−/−, and Rag1−/− mice, drinking H2O or ABX, 72 hours after anti-IL10R/CpG-ODN treatment. Scale bars, 1 cm. (D) Quantification of necrotic area in tumors from WT, Tnf−/−, and Ragl−/− mice 48 hours after anti-IL10R/CpG-ODN treatment analyzed in hematoxylin and eosin stained sections. Data are means±SEM from two experiments combined. The right inset shows an an example of the histological appearance, with the area of necrosis outlined in black. Scale bar, 200 μm. *p < 0.05, **p < 0.01, and ***p < 0.001.

Fig. 2.. Commensal bacteria and TLR4 are necessary for optimal TNF production by tumor myeloid cells after anti-IL-10R/CpG treatment.

(A) Tnf mRNA (Nanostring nCounter) in MC38 tumors from H2O− or ABX-treatedmice exposed or not to anti-IL-10R/CpG-ODN therapy. (B) TNF-producing MC38 tumor infiltrating CD45+ cells in H2O− or ABX-treated mice. (C to E) Tnf mRNA [real-time polymerase chain reaction (RT-PCR)] (C) and percentage TNF− (D) or IL-12p40− (E) producing CD45+ cells (flow cytometry) in MC38 tumors from SPF or GF mice. (F) MC38 tumor Tnf mRNA in WT mice or in Tlr4−/− mice orally gavaged or not with LPS (25 mg per kg of weight, three times per week, 2 weeks before and 1 week after tumor injection). (G) MC38 tumor growth in H2O− or ABX-treated WT mice or Tlr4−/− mice treated or not with anti-IL-10R/CpG-ODN. Data show individual mice [(A) to (F)] or means T SEM (G). *P < 0.05, **P < 0.01, and ***P < 0.001.

Fig. 3.. Commensal microbiota composition correlates with tumor TNF response.

(A and B) MC38 tumors were subcutaneously implanted 1, 2, or 4 weeks after the cessation of a 3-week ABX treatment. Control mi ce continuously drinking H2O or ABX were included. (A) Eubacteria 16S ribosomal RNA gene copy number in feces was determined by RT-PCR. (B) 16S-sequence frequencies were analyzed by pyrosequencing in fecal microbi ota. Data are shown as heat map of OTUs (97% similarity) normalized to copy number of 16S per gram of feces (OTUs represented by <0.1% of total reads were removed from the analysi s). (C) Principal-component analysis of unweighted Unifrac di stances. (D) Tumor Tnf mRNA expression 3 hours after anti-IL-10R/CpG-ODN treatment was determined by RT-PCR. (E) Control H2O-drinking mice or 1 week after cessation of ABX treatment were exposed to anti-IL-10R/CpG-ODN therapy. A group of ABX pre-exposed mice was subjected to oral gavage with A. shahii. Mice were killed 3 hours after CpG-ODN treatment, and intracellular TNF was measured in the indicated tumor-associated myeloid cell subsets. Data show individual mice and means ± SEM from one representative experiment out of two performed [(A) and (D)] or combined data from two experiments (E).

Fig. 4.. Commensal bacteria control oxaliplatin therapy response by modulating ROS production.

(A) Subcutaneous EL4 tumor-bearing H2O− or ABX-treated mice were treated with oxaliplatin (10 mg per kg of weight); tumor growth (top) and survival (bottom) are shown. (B) Global gene expression (q < 0.1, >2-fold change compared to time 0, two-way analysis of variance analysis) in tumors from H2O− and ABX-treated mice before (0 hours) and after (6 and 18 hours) oxaliplatin treatment. (C and D) ROS production 24 hours after oxaliplatin injection in subcutaneous EL4 tumors from H2O− or ABX-treated WT mice and Cybb−/− mice was measured in vivo by bioluminescence (probe L-012) [inset in (C) shows a representative mouse with tumor area marked in red] and ex vivo in tumor-infiltrating cells (D, fluorescent probe, flow cytometry). (E and F) EL4-bearing WT and Cybb−/− mice (E) and Gr-1 antibody− or immunoglobulin G isotype-treated mice (F) were treated with oxaliplatin. (A), (C), and (E) show data combined from several independent experiments; (D) and (F) show a representative experiment out of two.