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CD91 on dendritic cells governs immunosurveillance of nascent, emerging tumors
Abigail L. Sedlacek, … , Ion I. Mandoiu, Robert J. Binder
Abigail L. Sedlacek, … , Ion I. Mandoiu, Robert J. Binder
Published April 4, 2019
Citation Information: JCI Insight. 2019;4(7):e127239. https://doi.org/10.1172/jci.insight.127239.
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Research Article Immunology

CD91 on dendritic cells governs immunosurveillance of nascent, emerging tumors

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Abstract

The immune system detects aberrant, premalignant cells and eliminates them before the development of cancer. Immune cells, including T cells, have been shown to be critical components in eradicating these aberrant cells, and when absent in the host, incidence of cancer increases. Here, we show that CD91, a receptor expressed on antigen-presenting cells, is required for priming immune responses to nascent, emerging tumors. In the absence of CD91, effector immune responses are subdued, and tumor incidence and progression are amplified. We also show that, consequently, tumors that arise in the absence of CD91 express neo-epitopes with indices that are indicative of greater immunogenicity. Polymorphisms in human CD91 that are expected to affect ligand binding are shown to influence antitumor immune responses in cancer patients. This study presents a molecular mechanism for priming immune responses to nascent, emerging tumors that becomes a predictor of cancer susceptibility and progression.

Authors

Abigail L. Sedlacek, Theodore P. Younker, Yu Jerry Zhou, Lisa Borghesi, Tatiana Shcheglova, Ion I. Mandoiu, Robert J. Binder

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Figure 4

Effect of predicted high-impact SNVs on receptor stability, HSP docking, and antitumor effector response.

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Effect of predicted high-impact SNVs on receptor stability, HSP docking,...
(A) Distribution of 1233 candidate SNVs binned into 89 exons of the CD91/LRP1 gene. Individual ligand binding domains are indicated. Interdomain regions that play no binding or membrane anchoring role are colored uniformly black. The inset figure shows the number of mutations per base in each domain. Vertical height of each bar indicates the number of SNPs falling within that exon. (B) Visualization of high-impact SNV –log(P value) score of change in stability energy between the SNV-altered CD91 and WT. Higher scores represent increased magnitude of change in stability energy compared with all other candidate SNVs. Red line was chosen at a Z score of 1.96, and points above this threshold have a P < 0.05. (C) Scatter plot of high-impact SNV effect on hsp90-CD91 binding interactions. Negative and positive scores represent increased binding or decreased ligand binding, respectively, in hsp90-altered CD91 receptors compared with WT reference binding energies. The 4 ligand binding domains of CD91 are color coded as indicated. Black arrows represent SNVs that appear in 4 individual patients with lung squamous cell carcinoma, and red arrows represent SNVs that appear in 4 individual patients with skin cutaneous melanoma. The position of each SNV is indicated by a number next to each arrow. (D and E) Stacked bar plot showing predicted high-impact SNVs in human samples of lung squamous cell carcinomas (D) or skin cutaneous melanoma (E) and the associated presence of CD8+ immune cells from transcriptomic data. RNA-Seq expression levels (in FPKM) are used as a proxy for CD8+ T cell presence. Solid bars indicate SNVs with –ΔΔG docking impact, and hatched bars indicate SNVs with +ΔΔG docking impact.

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ISSN 2379-3708

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