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Non-targeted metabolomics screen comparing metabolite profiles of serum from PDAC-bearing mice that received metronidazole using high-resolution, high-performance LC-MS/MS analysis.

ABSTRACT: The composition of the gut microbiome controls innate and adaptive immunity and has emerged as a key regulator of tumor growth and the success of immune checkpoint blockade (ICB) therapy. However, the underlying mechanisms remain unclear. Pancreatic ductal adenocarcinoma (PDAC) tends to be refractory to therapy, including ICB. We found that the gut microbe-derived metabolite trimethylamine N-oxide (TMAO) enhances anti-tumor immunity to PDAC. Delivery of TMAO given intraperitoneally or via dietary choline supplement to PDAC-bearing mice reduces tumor growth and is associated with an immunostimulatory tumor-associated macrophage (TAM) phenotype and activated effector T cell response in the tumor microenvironment. Mechanistically, TMAO signals through potentiating type-I interferon (IFN) pathway and confers anti-tumor effects in a type-I IFN dependent manner. Notably, delivering TMAOprimed macrophages alone produced similar anti-tumor effects. Combining TMAO with ICB (anti-PD1 and/or anti-Tim3) significantly reduced tumor burden and improved survival beyond TMAO or ICB alone. Finally, the levels of trimethylamine (TMA)- producing bacteria and of CutC gene expression correlate with improved survivorship and response to anti-PD1 in cancer patients. Together, our study identifies the gut microbial metabolite TMAO as an important driver of anti-tumor immunity and lays the groundwork for new therapeutic strategies.

ORGANISM(S): Mouse Mus Musculus

TISSUE(S): Blood

DISEASE(S): Cancer

SUBMITTER: Rahul Shinde

PROVIDER: ST002216 | MetabolomicsWorkbench | Mon Jul 11 00:00:00 BST 2022

REPOSITORIES: MetabolomicsWorkbench

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Project description:Pancreatic cancer is the 3rd most prevalent cause of cancer related deaths in United states alone, with over 55000 patients being diagnosed in 2019 alone and nearly as many succumbing to it. Late detection, lack of effective therapy and poor understanding of pancreatic cancer systemically contributes to its poor survival statistics. Obesity and high caloric intake linked co-morbidities like type 2 diabetes (T2D) have been attributed as being risk factors for a number of cancers including pancreatic cancer. Studies on gut microbiome has shown that lifestyle factors as well as diet has a huge effect on the microbial flora of the gut. Further, modulation of gut microbiome has been seen to contribute to effects of intensive insulin therapy in mice on high fat diet. In another study, abnormal gut microbiota was reported to contribute to development of diabetes in Db/Db mice. Recent studies indicate that microbiome and microbial dysbiosis plays a role in not only the onset of disease but also in its outcome. In colorectal cancer, Fusobacterium has been reported to promote therapy resistance. Certain intra-tumoral bacteria have also been shown to elicit chemo-resistance by metabolizing anti-cancerous agents. In pancreatic cancer, studies on altered gut microbiome have been relatively recent. Microbial dysbiosis has been observed to be associated with pancreatic tumor progression. Modulation of microbiome has been shown to affect response to anti-PD1 therapy in this disease as well. However, most of the studies in pancreatic cancer and microbiome have remained focused om immune modulation. In the current study, we observed that in a T2D mouse model, the microbiome changed significantly as the hyperglycemia developed in these animals. Our results further showed that, tumors implanted in the T2D mice responded poorly to Gemcitabine/Paclitaxel (Gem/Pac) standard of care compared to those in the control group. A metabolomic reconstruction of the WGS of the gut microbiota further revealed that an enrichment of bacterial population involved in drug metabolism in the T2D group.

Dataset Information

Non-targeted metabolomics screen comparing metabolite profiles of serum from PDAC-bearing mice that received metronidazole using high-resolution, high-performance LC-MS/MS analysis.

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