Cancer Gene TherapyCancer BiologyPeer-reviewed journal article
Targeting mTORC2 in lung squamous cell carcinoma improves anti-tumor immunity through the PSGL-1-VISTA axis
Verra M. NgwaiD, Yoonha HwangiD, Wenqiang SongiD, Deanna N. EdwardsiD, Jin CheniD
- Citations
- 1
- FWCI
- 0.41
- Field percentile
- top 39%
Abstract
Targeted therapies have improved survival for lung adenocarcinoma patients. However, similar advances are lacking for lung squamous carcinoma (LUSC). Advances in immunotherapy have shown some promise, but the overall response rate remains low in LUSC. Here, we demonstrate that the mTORC2 signaling pathway represents an actionable target in LUSC to improve anti-tumor immune responses. We show that genetic alterations affecting the mTORC2 pathway are common among patients with LUSC tumors, and targeting mTORC2 reduces LUSC tumor growth in mouse models. Transcriptomics reveal that mTORC2-deficient LUSC cells exhibit reduced expression of glycolytic and hypoxia-related genes. In agreement, loss of mTORC2 signaling decreases lactate levels in tumor-interstitial fluid, creating reduced acidity within the tumor microenvironment. Interestingly, mTORC2-deficient LUSC cells also exhibited reduced expression of the pH-sensitive VISTA ligand PSGL-1 in a HIF-2 dependent mechanism. LUSC patients, but not those with LUAD, display a positive correlation in expression between HIF-2 and PSGL-1, suggesting a distinct association among mTORC2, HIF-2, and immune responses in LUSC. Indeed, mTORC2 loss-of-function enhanced CD8+ T cell activation in tumors, while use of anti-VISTA immunotherapy reduced LUSC tumor burden only in the presence of intact mTORC2 signaling. Collectively, these data describe an important role of mTORC2 signaling in LUSC tumors and demonstrate the therapeutic potential of targeting the mTORC2/PSGL-1/VISTA axis in patients that are non-responsive to current therapies.
- organism: mouse
- organism: human
- assay: bulk RNA-seq
- research focus: cancer & tumor microenvironment
- research focus: cell-cell communication
- research focus: gene regulatory network inference
- approach: experimental assay
- approach: statistical model
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