bioRxivCancer Biology
Microenvironmental Ammonia Enhances T cell Exhaustion in Colorectal Cancer
Y. M. Shah, H. Bell, A. K. Huber, R. Singhal, R. J. Rebernick, R. Kumar, N. K. Das, S. A. Kerk, P. Sajjakulnukit, S. Solanki, J. G. James, D. Kim, L. Zhang, M. O. El-derany, T. L. Frankel, B. Gyorffy, E. R. Fearon, M. Pasca di Magliano, F. J. Gonzalez, R. Banerjee, C. A. Lyssiotis, M. Green
Abstract
Effective therapies are lacking for patients with advanced colorectal cancer (CRC). The CRC tumor microenvironment has elevated metabolic waste products due to altered metabolism and proximity to the microbiota. The role of metabolite waste in tumor development, progression, and treatment resistance is unclear. We generated an autochthonous metastatic mouse model of CRC and unbiased multi-omic analyses in this model reveals a robust accumulation of tumoral ammonia. The high ammonia levels induce T cell metabolic reprogramming, increase exhaustion and decrease proliferation. CRC patients have increased serum ammonia, and our ammonia-related gene signature correlates with altered T cell response, adverse patient outcomes, and lack of response to immune checkpoint blockade. We demonstrate that enhancing ammonia clearance reactivates T cells, decreases tumor growth, and extends survival. Moreover, decreasing tumor-associated ammonia enhances anti-PD-L1 efficacy. Our findings indicate that ammonia detoxification can reactivate T cells, highlighting a new approach to enhance the efficacy of immunotherapies. Statement of SignificanceWe demonstrate that ammonia accumulates in the microenvironment of colorectal cancer. Ammonia alters T-cells redox singling leading to a decrease in T cell proliferation and an increase in T cell exhaustion. Enhancing ammonia clearance reduces tumor size, increases survival, and increases the efficacy to immunotherapies.
- organism: mouse
- organism: human
- assay: bulk RNA-seq
- assay: metabolomics
- research focus: cancer & tumor microenvironment
- research focus: cell signaling & trafficking
- research focus: drug response / drug discovery
- approach: experimental assay
- approach: statistical model
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