Self-associated molecular patterns mediate cancer immune evasion by engagement of Siglec receptors. Self-associated molecular patterns mediate cancer immune evasion by engagement of Siglec receptors
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https://www.ncbi.nlm.nih.gov/bioproject/PRJNA474508
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Cancer immunotherapy targeting inhibitory receptors on T cells has changed the landscape of oncological practice, but most patients do not respond to current approaches. Thus, new targets on T cells for cancer immunotherapy are needed. CD33-related Siglecs are pattern recognition immune receptors binding to a broad range of sialoglycan ligands, which appear to function as self-associated molecular patterns (SAMPs) to dampen unwanted immune responses against self. Naïve T cells in humans have very low levels of inhibitory Siglec expression. Here, we show Siglec-9 in non-small cell lung cancer (NSCLC) are significantly upregulated on tumor-infiltrating T cells. These findings were confirmed in other tumor types including colorectal cancer, and ovarian cancer. Characterization of Siglec-9 expressing T cells showed a co-expression of inhibitory receptors including PD-1 and a distinct phenotype with increased cytokine production upon restimulation, compared to Siglec negative T cells. Functional analysis by reduction of sialoglycan-SAMPs on tumor cells in vitro and in vivo demonstrated an increased tumor cell killing and an inhibition of tumor growth. Overexpression of inhibitory Siglecs on T cells enhanced tumor growth in mice and exchange of inhibitory Siglecs on mouse T cells with an activating Siglec enhanced anti-cancer immunity. Increased T cell expression of Siglec-9 in NSCLC patients also correlated with survival, and analysis of Siglec-9 polymorphisms showed an association with the risk of developing lung and colorectal cancer. Our data identify the sialoglycan-SAMP/Siglec pathway as potential new target to improve T cell activation and cancer immunotherapy. Overall design: Six non-small cell lung cancer tumor infiltrating CD8+ T cells (CD45+ CD3+ CD8+ CD4-) were sorted by flow cytometry according to their Siglec9 staining into Siglec9+ and Siglec9- samples.
创建时间:
2018-06-04



