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FABP4 Mediated Fatty Acid Transport Promotes Proliferation and Survival of Platinum-Resistant Ovarian Cancer Cells

GSE295220 Homo sapiens (human) RNA-seq (gene expression) 15 samples Submitted 2026/04/21 Platform GPL20301
At a glance

RNA-seq (gene expression) · human · 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
Homo sapiens (human)
Topic
Ovarian cancerThis series is part of our curated briefing on it.
Samples
15 samples: 5 conditions, mostly in triplicateGroups 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
Oleic acid fuels cisplatin-resistant ovarian cancer through FABP4-driven lipid uptakeMolecular metabolism · 2026
Summary (written by the submitters)
Background: Ovarian cancer (OC) depends on fat as fuel for metastasis and growth. We previously demonstrated that cisplatin resistant (Pt-R) OC cells uptake higher amounts of fatty acids (FAs) compared to sensitive (Pt-S) cells– a process which facilitates cancer cell survival under cisplatin-induced oxidative stress. Results: Here we report that Pt-R OC cells are dependent on unsaturated FAs compared to Pt-S cells and upregulate key lipid transporters to allow increased uptake of FAs.
Read the full summary ↓
Cell viability assays showed Pt-R cells were less viable under serum depletion, with oleic acid (OA, unsaturated) promoting proliferation of OC cells. OA alone rescued the inhibition of cell proliferation under conditions of serum depletion exerting more significant effects in Pt-R vs Pt-S cells. OA also reduced apoptosis, as shown by Annexin V assays, and decreased Caspase-3 and -8 cleavage. RNA-sequencing analysis linked OA-rescued cell proliferation to upregulation of cell cycle-related pathways, including G2/M checkpoints, driven by E2F1. OA increased S- and G2/M phase cell populations (6.95% to 11.6%; p<0.05), while E2F1 inhibition reduced OA-induced cell proliferation. Pt-R cells also expressed higher levels of FA transporter proteins FABP4 and CD36. Inhibiting FABPs reduced the IC50 to Pt and blocked OC growth in vivo. FABP4 was overexpressed in metastatic and recurrent vs. primary ovarian tumors. Implication: Pt-R OC cells are dependent on unsaturated FAs compared to Pt-S cells and upregulate key transporters to increase FAs uptake. OA supports proliferation of Pt-R cells by promoting cell cycle progression from G1 to S- and G2/M phases. Inhibiting FA transport reduces OC progression in vivo.
Published in
Oleic acid fuels cisplatin-resistant ovarian cancer through FABP4-driven lipid uptake
Isac AM, Valdivia A, Zha D et al. · Molecular metabolism 2026 · PMID 42025693 · doi:10.1016/j.molmet.2026.102374
This dataset
Open GSE295220 in finder → Find more human RNA-seq datasets → Ovarian cancer landscape →
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 GSE295220_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 PRJNA1253716 and SRA study SRP580284. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 42025693) ↗
Study design
5 conditions, mostly in triplicate
OVCAR5 Pt-S control n ×3 OVCAR5 Pt-S OA n ×3 OVCAR5 Pt-S PA n ×3 OVCAR5 Pt-R control n ×3 OVCAR5 Pt-R OA n ×3

Supports a between-group comparison across 15 samples.

How we read this: 5 replicated groups read from 15 sample titles; they account for 15 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
More Ovarian cancer datasets

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