Self-associated molecular patterns mediate cancer immune evasion by engaging Siglecs on T cells

自相关分子模式通过与T细胞上的Siglecs结合来介导癌症的免疫逃逸

阅读:2
作者:Michal A Stanczak ,Shoib S Siddiqui ,Marcel P Trefny ,Daniela S Thommen ,Kayluz Frias Boligan ,Stephan von Gunten ,Alexandar Tzankov ,Lothar Tietze ,Didier Lardinois ,Viola Heinzelmann-Schwarz ,Michael von Bergwelt-Baildon ,Wu Zhang ,Heinz-Josef Lenz ,Younghun Han ,Christopher I Amos ,Mohammedyaseen Syedbasha ,Adrian Egli ,Frank Stenner ,Daniel E Speiser ,Ajit Varki ,Alfred Zippelius ,Heinz Läubli

Abstract

First-generation immune checkpoint inhibitors, including anti-CTLA-4 and anti-programmed death 1 (anti-PD-1) antibodies, have led to major clinical progress, yet resistance frequently leads to treatment failure. Thus, new targets acting on T cells are needed. CD33-related sialic acid-binding immunoglobulin-like lectins (Siglecs) are pattern-recognition immune receptors binding to a range of sialoglycan ligands, which appear to function as self-associated molecular patterns (SAMPs) that suppress autoimmune responses. Siglecs are expressed at very low levels on normal T cells, and these receptors were not until recently considered as interesting targets on T cells for cancer immunotherapy. Here, we show an upregulation of Siglecs, including Siglec-9, on tumor-infiltrating T cells from non-small cell lung cancer (NSCLC), colorectal, and ovarian cancer patients. Siglec-9-expressing T cells coexpressed several inhibitory receptors, including PD-1. Targeting of the sialoglycan-SAMP/Siglec pathway in vitro and in vivo resulted in increased anticancer immunity. T cell expression of Siglec-9 in NSCLC patients correlated with reduced survival, and Siglec-9 polymorphisms showed association with the risk of developing lung and colorectal cancer. Our data identify the sialoglycan-SAMP/Siglec pathway as a potential target for improving T cell activation for immunotherapy.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。