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Humanized mouse tumor models for evaluation of ILT2 and ILT4 antagonist antibodies

GSE255649 Homo sapiens (human) RNA-seq (gene expression) 73 samples Submitted 2025/02/12 Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 73 samples

What it is
RNA-seq (gene expression)Gene activity measured by sequencing. The summary does not mention single-cell work, so this is most likely bulk: one average per sample, the usual starting point for comparing groups.
Organism
Homo sapiens (human)
Samples
73 samples: 12 conditions, mostly with about 4 replicates eachGroups are read from the sample names, not from the paper. Check the list below.
Data you can get
A processed table (series matrix) and supplementary files from NCBI; the raw sequencing reads from ENA. Which of these hold counts depends on the study, so check the file list.
Paper
ILT2 and ILT4 Drive Myeloid Suppression via Both Overlapping and Distinct MechanismsCancer immunology research · 2024
Summary (written by the submitters)
Solid tumors are dense three-dimensional (3D) multi-cellular structures that enable efficient receptor–ligand trans interactions via close cell–cell contact. Immunoglobulin-like transcript (ILT)2 and ILT4 are related immune suppressive receptors that play a role in the inhibition of myeloid cells within the tumor microenvironment. The relative contributions of ILT2 and ILT4 to immune inhibition in the context of solid tumor tissue has not been fully explored.
Read the full summary ↓
We present evidence that both ILT2 and ILT4 contribute to myeloid inhibition. We found that while ILT2 inhibits myeloid cell activation in the context of trans-engagement by MHC-I, ILT4 efficiently inhibits myeloid cells in the presence of either cis- or trans-engagement. In a 3D spheroid tumor model, dual ILT2/ILT4 blockade was required for optimal activation of myeloid cells, including the secretion of CXCL9 and CCL5, upregulation of CD86 on dendritic cells, and downregulation of CD163 on macrophages. Humanized mouse tumor models showed increased immune activation and cytolytic T cell activity with combined ILT2 and ILT4 blockade, including evidence of the generation of immune niches, which have been shown to correlate with clinical response to immune checkpoint blockade. In a human tumor explant histoculture system, dual ILT2/ILT4 blockade increased CXCL9 secretion, downregulated CD163 expression, and increased the expression of M1 macrophage, IFN-γ, and cytolytic T cell gene signatures. Thus, we have revealed distinct contributions of ILT2 and ILT4 to myeloid cell biology and provide proof-of-concept data supporting the combined blockade of ILT2 and ILT4 to therapeutically induce optimal myeloid cell reprogramming in the tumor microenvironment.
Published in
ILT2 and ILT4 Drive Myeloid Suppression via Both Overlapping and Distinct Mechanisms
Tian J, Ashique AM, Weeks S et al. · Cancer immunology research 2024 · PMID 38393969 · doi:10.1158/2326-6066.CIR-23-0568
This dataset
Open GSE255649 in finder → Find more human RNA-seq datasets →
Download · which file do I need?

Direct links to NCBI and ENA, no account and no request form. Pick by what you want to do: take the small processed table to look, the supplementary files to re-analyse, or the original raw data to start over.

1 · Just have a look

Processed table

The series matrix: one table of values per sample as the submitters processed it. The smallest download, and it opens in Excel or R. Start here to see what the data look like.

Series matrix ↓
2 · Re-analyse it

Supplementary files

The count tables and other files the authors uploaded. Take only the samples you need, or the whole study as GSE255649_RAW.tar (it can run to tens of gigabytes).

All supplementary files ↗ Whole study · RAW.tar ↓
3 · Start from the raw reads

Raw sequencing reads

The original FASTQ files, straight from the sequencer, held at ENA. Large, and you align them yourself, so only choose this if you need to re-process the study from scratch.

Raw reads on ENA ↗

What the files usually look like: For RNA-seq the counts are usually a table among the supplementary files (look for 'counts', 'expression', 'FPKM' or 'TPM' in the file name). The series matrix of a sequencing study is sometimes nearly empty.

Also filed as BioProject PRJNA1075843 and SRA study SRP489445. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 38393969) ↗
Study design
12 conditions, mostly with about 4 replicates each
NB099_Isotype ×10 NB099_PD1 ×10 NB099_27F9 ×9 NB099_ILT2_ILT4 ×9 NB099_48A5 ×7 NB099_27F9_48A5 ×5 NB099_ILT2_ILT4_PD1 ×5 NB094_Isotype ×4 +4 more

Supports a between-group comparison across 73 samples.

How we read this: 12 replicated groups read from 73 sample titles; they account for 73 of them. These groups are guessed from the sample names, not taken from the paper, so check them against the sample list below before relying on them.

Samples in this study

+ 33 more — browse all 73 samples with per-sample file links →

Datasets on a similar topic

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