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Denfivontinib activates effector T-cells through NLRP3-inflammasome, yielding potent anticancer effects by combination with pembrolizumab

GSE276724 Mus musculus (mouse) RNA-seq (gene expression) 15 samples Submitted 2025/03/12 Platform GPL25526
At a glance

RNA-seq (gene expression) · mouse · 15 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
Mus musculus (mouse)
Samples
15 samples: 15 samples, each with a distinct title — no replicated groupsGroups 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
Denfivontinib Activates Effector T Cells Through the NLRP3 Inflammasome, Yielding Potent Anticancer Effects by Combination with PembrolizumabMolecular cancer therapeutics · 2025
Summary (written by the submitters)
Various combination therapies have been investigated to overcome the limitations of using immune checkpoint inhibitors. However, determining the optimal combination therapy remains challenging. To overcome the therapeutical limitation, we conducted a translational research to elucidate the mechanisms by which AXL inhibition enhances the anti-tumor effects when combined with anti-PD-1 antibody therapy.
Read the full summary ↓
Herein, we demonstrated improved antitumor effects through combination treatment with denfivontinib and pembrolizumab which resulted in enhanced differentiation into effector CD4+ and CD8+ memory T cells, accompanied by an increase in IFN-γ expression in the YHIM-2004 xenograft model derived from patients with NSCLC. Concurrently, a reduction in the number of immunosuppressive M2 macrophages and myeloid-derived suppressor cells was observed. Mechanistically, denfivontinib potentiated the NOD-like receptor pathway, thereby facilitating the NLRP3 inflammasome formation. This leads to macrophage activation via the NF-kB signaling pathway activation. We have confirmed that the positive interaction between macrophages and T cells arises from the enhanced antigen-presenting machinery of activated macrophages. Furthermore, the observed tumor effects in AXL knock-out mice confirmed that AXL inhibition by denfivontinib enhances the anti-tumor effects, thus opening new avenues for therapeutic interventions aimed at overcoming limitations in immunotherapy. To demonstrate the extent to which our findings reflect clinical results, we analyzed bulk-RNA sequencing data from 21 NSCLC patients undergoing anti-PD-1 immunotherapy. The NLRP3 inflammasome score influenced enhanced immune responses in patient data undergoing anti-PD-1 immunotherapy, suggesting a role for NLRP3 inflammasome in activating immune responses during treatment.
Published in
Denfivontinib Activates Effector T Cells Through the NLRP3 Inflammasome, Yielding Potent Anticancer Effects by Combination with Pembrolizumab
Kim DK, Synn CB, Lee W et al. · Molecular cancer therapeutics 2025 · PMID 39632711 · doi:10.1158/1535-7163.MCT-24-0501
This dataset
Open GSE276724 in finder → Find more 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 GSE276724_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 PRJNA1158761 and SRA study SRP532913. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 39632711) ↗
Study design
15 samples, each with a distinct title — no replicated groups

Any grouping that defines a comparison lives in the sample characteristics, which GEO records separately from the titles.

How we read this: Read from 15 sample titles: 15 distinct titles with little repetition. 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
Datasets on a similar topic

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