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Cancer cells avoid ferroptosis induced by immune cells via fatty acid binding proteins

GSE285215 Mus musculus (mouse) Expression microarray 12 samples Submitted 2025/01/31 Platform GPL1261
At a glance

Expression microarray · mouse · 12 samples

What it is
Expression microarrayGene activity read on a chip (the older technology that RNA-seq replaced).
Organism
Mus musculus (mouse)
Samples
12 samples: 3 × Sen+IgG vs 3 × Sen+PD1 vs 3 × Res+IgG vs 3 × Res+PD1Groups are read from the sample names, not from the paper. Check the list below.
Data you can get
A processed expression table (series matrix) and the array files, from NCBI.
Paper
Cancer cells avoid ferroptosis induced by immune cells via fatty acid binding proteinsMolecular cancer · 2025
Summary (written by the submitters)
Cancer creates an immunosuppressive environment that hampers immune responses, allowing tumors to grow and resist therapy. One way the immune system fights back is by inducing ferroptosis, a type of cell death, in tumor cells through CD8+ T cells. This involves lipid peroxidation and enzymes like lysophosphatidylcholine acyltransferase 3 (Lpcat3), which makes cells more prone to ferroptosis.
Read the full summary ↓
However, the mechanisms by which cancer cells avoid immunotherapy-mediated ferroptosis are unclear. Our study reveals how cancer cells evade ferroptosis and anti-tumor immunity through the upregulation of fatty acid-binding protein 7 (Fabp7). Methods To explore how cancer cells resist immune cell-mediated ferroptosis, we used a comprehensive range of techniques. We worked with cell lines including PD1-sensitive, PD1-resistant, B16F10, and QPP7 glioblastoma cells, and conducted in vivo studies in syngeneic 129 Sv/Ev, C57BL/6, and conditional knockout mice with Rora deletion specifically in CD8+ T cells, Cd8 cre;Rorafl mice. Methods included mass spectrometry-based lipidomics, targeted lipidomics, Oil Red O staining, Seahorse analysis, quantitative PCR, immunohistochemistry, PPARγ transcription factor assays, ChIP-seq, untargeted lipidomic analysis, ROS assay, ex vivo co-culture of CD8+ T cells with cancer cells, ATAC-seq, RNA-seq, Western blotting, co-immunoprecipitation assay, flow cytometry and Imaging Mass Cytometry. Results PD1-resistant tumors upregulate Fabp7, driving protective metabolic changes that shield cells from ferroptosis and evade anti-tumor immunity. Fabp7 decreases the transcription of ferroptosis-inducing genes like Lpcat3 and increases the transcription of ferroptosis-protective genes such as Bmal1 through epigenetic reprogramming. Lipidomic profiling revealed that Fabp7 increases triglycerides and monounsaturated fatty acids (MUFAs), which impede lipid peroxidation and ROS generation. Fabp7 also improves mitochondrial function and fatty acid oxidation (FAO), enhancing cancer cell survival. Furthermore, cancer cells increase Fabp7 expression in CD8+ T cells, disrupting circadian clock gene expression and triggering apoptosis through p53 stabilization. Clinical trial data revealed that higher FABP7 expression correlates with poorer overall survival and progression-free survival in patients undergoing immunotherapy. Conclusions Our study uncovers a novel mechanism by which cancer cells evade immune-mediated ferroptosis through Fabp7 upregulation. This protein reprograms lipid metabolism and disrupts circadian regulation in immune cells, promoting tumor survival and resistance to immunotherapy. Targeting Fabp7 could enhance immunotherapy effectiveness by re-sensitizing resistant tumors to ferroptosis.
Published in
Cancer cells avoid ferroptosis induced by immune cells via fatty acid binding proteins
Freitas-Cortez MA, Masrorpour F, Jiang H et al. · Molecular cancer 2025 · PMID 39901247 · doi:10.1186/s12943-024-02198-2
This dataset
Download · which file do I need?

Direct links to NCBI, 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.

All supplementary files ↗
3 · The original raw files

Whole study · RAW.tar

Everything the authors deposited as one archive (GSE285215_RAW.tar), including the raw array or instrument files. Can be large; the picker in step 2 takes just the samples you need.

What the files usually look like: For arrays the series matrix is normally the normalised expression table you want; the raw array files (CEL and similar) are in the RAW.tar.

Also filed as BioProject PRJNA1202038. Searching any of these in the dataset finder brings you back here.

Study design
3 × Sen+IgG vs 3 × Sen+PD1 vs 3 × Res+IgG vs 3 × Res+PD1

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
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