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Blocking immunoinhibitory receptor LILRB2 reprograms tumor-associated myeloid cells and promotes antitumor immunity
Hui-Ming Chen, … , Ping-Ying Pan, Shu-Hsia Chen
Hui-Ming Chen, … , Ping-Ying Pan, Shu-Hsia Chen
Published October 22, 2018
Citation Information: J Clin Invest. 2018;128(12):5647-5662. https://doi.org/10.1172/JCI97570.
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Research Article Oncology Article has an altmetric score of 38

Blocking immunoinhibitory receptor LILRB2 reprograms tumor-associated myeloid cells and promotes antitumor immunity

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Abstract

Tumor-associated myeloid cells maintain immunosuppressive microenvironments within tumors. Identification of myeloid-specific receptors to modulate tumor-associated macrophage and myeloid-derived suppressor cell (MDSC) functions remains challenging. The leukocyte immunoglobulin-like receptor B (LILRB) family members are negative regulators of myeloid cell activation. We investigated how LILRB targeting could modulate tumor-associated myeloid cell function. LILRB2 antagonism inhibited receptor-mediated activation of SHP1/2 and enhanced proinflammatory responses. LILRB2 antagonism also inhibited AKT and STAT6 activation in the presence of M-CSF and IL-4. Transcriptome analysis revealed that LILRB2 antagonism altered genes involved in cell cytoskeleton remodeling, lipid/cholesterol metabolism, and endosomal sorting pathways, as well as changed differentiation gene networks associated with inflammatory myeloid cells as opposed to their alternatively activated phenotype. LILRB2 blockade effectively suppressed granulocytic MDSC and Treg infiltration and significantly promoted in vivo antitumor effects of T cell immune checkpoint inhibitors. Furthermore, LILRB2 blockade polarized tumor-infiltrating myeloid cells from non–small cell lung carcinoma tumor tissues toward an inflammatory phenotype. Our studies suggest that LILRB2 can potentially act as a myeloid immune checkpoint by reprogramming tumor-associated myeloid cells and provoking antitumor immunity.

Authors

Hui-Ming Chen, William van der Touw, Yuan Shuo Wang, Kyeongah Kang, Sunny Mai, Jilu Zhang, Dayanira Alsina-Beauchamp, James A. Duty, Sathish Kumar Mungamuri, Bin Zhang, Thomas Moran, Richard Flavell, Stuart Aaronson, Hong-Ming Hu, Hisashi Arase, Suresh Ramanathan, Raja Flores, Ping-Ying Pan, Shu-Hsia Chen

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Figure 4

LILRB2 blockade alters the macrophage transcriptome distinct from conventional M1 versus M2 phenotypes.

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LILRB2 blockade alters the macrophage transcriptome distinct from conven...
(A) Volcano plots of normalized gene enrichment scores and enrichment P values of anti-LILRB2 (αLILRB2) treatment versus IgG treatment in monocyte-derived macrophage conditions M(LPS) (left) and M(IL-4) (right). Statistically significant DEGs above the enrichment cutoff (DEGs with fold change ≥ 1.5 and P < 0.01 with FDR) are shown in red. (B) Overlapping and unique DEGs from M(LPS) and M(IL-4) conditions in response to anti-LILRB2 treatment. Venn diagram (top) depicts overlap of DEGs between M(LPS) + anti-LILRB2 versus M(LPS) + IgG and M(IL-4) + anti-LILRB2 versus M(IL-4) + IgG (fold change ≥ 1.5 and P < 0.01 with FDR). Summarized gene ontology of overlapping DEGs is shown. Functional terms associated with the 66 shared LILRB2-regulated genes between M(LPS) and M(IL-4) are listed below. (C) Two-dimensional principal component analysis of Illumina BeadArray data sets. Blue, M(LPS) + IgG; red, M(LPS) + anti-LILRB2; black, M(IL-4) + IgG; green, M(IL-4) + anti-LILRB2; n = 3 per group are shown. (D) Heatmap visualization of normalized DEGs associated with immune function changes as a result of LILRB2 antagonism in M(IL-4) by comparison of M(IL-4) + anti-LILRB2 versus M(IL-4) + IgG conditions. DEGs are ranked top to bottom by fold change: red, increased; green, decreased; black, unchanged. Data are normalized by row Z score.

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ISSN: 0021-9738 (print), 1558-8238 (online)

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