← BioTransfer GEO Dataset Finder
GEO series

PARP inhibitors differentially regulate immune responses in distinct genetic backgrounds of high-grade serous tubo-ovarian carcinoma

GSE285827 Homo sapiens (human) RNA-seq (gene expression) 18 samples Submitted 2025/01/03 Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 18 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
18 samples: 18 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
PARP Inhibitors Differentially Regulate Immune Responses in Distinct Genetic Backgrounds of High-Grade Serous Tubo-Ovarian CarcinomaCancer research communications · 2025
Summary (written by the submitters)
Immune checkpoint inhibitors (ICIs) have revolutionized treatment for several tumor indications without demonstrated benefit for ovarian cancer patients. To improve the therapeutic ratio of ICIs in ovarian cancer patients, several different clinical trials are testing combinations with poly (ADP-ribose) polymerase (PARP) inhibitors. Comparing the immunomodulatory effects of clinically advanced PARP inhibitors may help to identify the best partner to combine with ICIs.
Read the full summary ↓
We examined the treatment effect of talazoparib (a PARP trapper) and veliparib (a solely PARP enzymatic inhibitor) in homologous recombination deficient (HRD) and homologous recombination proficient (HRP) high-grade serous tubo-ovarian carcinoma (HGSC) cell lines on immune-related gene expression. We discovered and validated that CXCL8, IL-6, and TNF gene expression were upregulated after talazoparib treatment in both OVCAR3 (HRD) and CAOV3 (HRP) HGSC cell lines. In contrast, veliparib treatment slightly elevated similar genes exclusively in a HRD HGSC cell line model. We expanded these studies to include olaparib, a PARP trapper less potent than talazoparib, and found effects specific to COV361 (BRCA1 mutant) and OVCAR8 (BRCA1 methylated) HGSC cells but not all HRD HGSC cell lines. Our studies also identified differences among PARP trappers versus veliparib on augmenting CXCL10 expression. Finally, we show that talazoparib modulates the CXCL10 response in cGAS-defective cell lines, independent of the cGAS-STING pathway. These mechanistic studies advance our understanding of how different PARP inhibitors affect the immune system in various genetic backgrounds.
Published in
PARP Inhibitors Differentially Regulate Immune Responses in Distinct Genetic Backgrounds of High-Grade Serous Tubo-Ovarian Carcinoma
Doro Pereira L, Wielgos-Bonvallet M, Misirlioglu S et al. · Cancer research communications 2025 · PMID 39851178 · doi:10.1158/2767-9764.CRC-24-0515
This dataset
Open GSE285827 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 GSE285827_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 PRJNA1206162 and SRA study SRP555163. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 39851178) ↗
Study design
18 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 18 sample titles: 18 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
More Ovarian cancer datasets

Search all human 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.