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Osteopontin links acquired resistance to hypoxia-inducing antiangiogenics with refractoriness to anti-PD-L1 agents in breast cancer

GSE241539 Mus musculus (mouse) RNA-seq (gene expression) 13 samples Submitted 2026/05/05 Platform GPL21626
At a glance

RNA-seq (gene expression) · mouse · 13 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
13 samples: 7 × RNAseq data from intratumoral CD45+ cells from B20-4.1.1 treated MMTV-PyMT breast tumors sample vs 6 × RNAseq data from intratumoral CD45-EPCAM+ cells from B20-4.1.1 treated MMTV-PyMT breast tumors sampleGroups 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
Osteopontin mediates acquired resistance to hypoxia-inducing antiangiogenics and promotes anti-PD-L1 refractoriness in breast cancer modelsThe Journal of clinical investigation · 2026
SuperSeries — this record groups several sub-series.
Summary (written by the submitters)
This SuperSeries is composed of the SubSeries listed below.
Published in
Osteopontin mediates acquired resistance to hypoxia-inducing antiangiogenics and promotes anti-PD-L1 refractoriness in breast cancer models
Ruiz-Sepulveda JL, Bueno MJ, Mouron S et al. · The Journal of clinical investigation 2026 · PMID 42454487 · doi:10.1172/JCI174092
This dataset
Open GSE241539 in finder → Find more mouse 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 GSE241539_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 PRJNA1008613 and SRA study SRP456666. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 42454487) ↗
Study design
7 × RNAseq data from intratumoral CD45+ cells from B20-4.1.1 treated MMTV-PyMT breast tumors sample vs 6 × RNAseq data from intratumoral CD45-EPCAM+ cells from B20-4.1.1 treated MMTV-PyMT breast tumors sample

Supports a between-group comparison across 13 samples.

How we read this: 2 replicated groups read from 13 sample titles; they account for 13 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

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