← BioTransfer GEO Dataset Finder
GEO series

Particle Reprogramming of the TLR–Ferroptosis Axis and Immunometabolic Pathways Inhibits Myeloid Suppression to Improve Checkpoint Blockade in Prostate Cancer [RNA-Seq Hi-Myc mice]

GSE319419 Mus musculus (mouse) RNA-seq (gene expression) 12 samples Submitted 2026/05/11 Platform GPL34290
At a glance

RNA-seq (gene expression) · mouse · 12 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
12 samples: 3 × Control (Saline treatment) tumo vs 3 × C' dot treatment tumo vs 3 × ICB treatment tumo vs 3 × Dual Tx treatment tumoGroups 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.
Summary (written by the submitters)
The limited efficacy of immunotherapies (IT) in advanced prostate cancer (PCa) stems from a tumor microenvironment where myeloid-driven immune suppression, stromal remodeling, and metabolic barriers converge to limit antitumor immunity. We highlight the immuno-metabolic properties of an ultrasmall PSMA-targeting silica particle therapy as a first-in-class strategy to reprogram the Toll-like receptor (TLR)–ferroptosis axis in Myc-driven PCa.
Read the full summary ↓
As single agents, these particles suppress lipid and steroid biosynthesis, disrupt lipid peroxidation control, and impair nutrient flux, sensitizing tumors to ferroptosis. Coordinated redox remodeling, stromal reprogramming, and innate immune activation reverse myeloid suppression and promote CD8⁺ T cell infiltration. When combined with CSF-1R inhibition and/or immune checkpoint blockade, particles suppress tumor growth, extend survival beyond 100 days, and achieve up to 50% complete remissions in Myc-overexpressing models. These findings position TLR–ferroptosis axis remodeling as a mechanistic blueprint for rational, particle-driven ITs with broad translational potential in PCa and other immunologically refractory malignancies.
This dataset
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.

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 GSE319419_RAW.tar (it can run to tens of gigabytes).

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.

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 PRJNA1423265 and SRA study SRP676850. Searching any of these in the dataset finder brings you back here.

Study design
3 × Control (Saline treatment) tumo vs 3 × C' dot treatment tumo vs 3 × ICB treatment tumo vs 3 × Dual Tx treatment tumo

Supports a between-group comparison across 12 samples.

How we read this: 4 replicated groups read from 12 sample titles; they account for 12 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
Datasets on a similar topic

Search all mouse RNA-seq datasets in GEO →

Share this dataset

Metadata from NCBI GEO, cached and refreshed periodically — the NCBI page above is authoritative. Downloads link straight to NCBI/ENA; nothing is proxied through BioTransfer.