bioRxivCancer BiologyPreprint
A cancer cell-intrinsic GOT2-PPARδ axis suppresses antitumor immunity
H. Sanford-Crane, J. Abrego, C. Oon, X. Xiao, S. Nagarajan, S. Bhattacharyya, P. Tontonoz, M. H. Sherman
Abstract
Despite significant recent advances in precision medicine1,2, pancreatic ductal adenocarcinoma (PDAC) remains near-uniformly lethal. While the most frequent genomic alterations in PDAC are not presently druggable3 and conventional therapies are often ineffective in this disease4, immune-modulatory therapies hold promise to meaningfully improve outcomes for PDAC patients. Development of such therapies requires an improved understanding of the immune evasion mechanisms that characterize the PDAC microenvironment, including frequent exclusion of antineoplastic T cells and abundance of immune-suppressive myeloid cells5-9. Here we show that cancer cell-intrinsic glutamic-oxaloacetic transaminase 2 (GOT2) shapes the immune microenvironment to suppress antitumor immunity. Mechanistically, we find that GOT2 functions beyond its established role in the malate-aspartate shuttle10-13 and promotes the transcriptional activity of nuclear receptor peroxisome proliferator-activated receptor delta (PPAR{delta}), facilitated by direct fatty acid binding. While GOT2 in PDAC cells is dispensable for cancer cell proliferation in vivo, GOT2 loss results in T cell-dependent suppression of tumor growth, and genetic or pharmacologic activation of PPAR{delta} restores PDAC progression in the GOT2-null context. This cancer cell-intrinsic GOT2-PPAR{delta} axis promotes spatial restriction of both CD4+ and CD8+ T cells from the tumor microenvironment, and fosters the immune-suppressive phenotype of tumor-infiltrating myeloid cells. Our results demonstrate a non-canonical function for an established mitochondrial enzyme in transcriptional regulation of immune evasion, which may be exploitable to promote a productive antitumor immune response.
- organism: human
- assay: bulk RNA-seq
- research focus: cancer & tumor microenvironment
- research focus: cell-cell communication
- research focus: spatial domain detection
- approach: experimental assay
- approach: genetic perturbation / CRISPR
- approach: mechanistic / dynamical model
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