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Identification of recurrent tumor-specific markers in patient-matched ovarian cancer samples

GSE295041 Homo sapiens (human) RNA-seq (gene expression) 48 samples Submitted 2026/01/15 Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 48 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
48 samples: 24 × ovary, primary, patient vs 24 × ovary, recurrent, patientGroups 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
Integrative Multi-Omics Analysis Reveals Molecular Signatures of Recurrence in Paired Primary and Recurrent High-Grade Serous Ovarian CancerInternational journal of molecular sciences · 2026
Summary (written by the submitters)
In this study, we performed a transcriptomic comparative analysis on formalin-fixed paraffin-embedded (FFPE) specimens, collecting both primary ovarian cancer tissue and recurrent ovarian cancer tissue in a series from the same patients in real-world settings. Our aim was to identify clinically significant Differentially Expressed Genes (DEGs) associated with the recurrence of HGSOC .
Published in
Integrative Multi-Omics Analysis Reveals Molecular Signatures of Recurrence in Paired Primary and Recurrent High-Grade Serous Ovarian Cancer
Kim MA, Nam J, Shin HY et al. · International journal of molecular sciences 2026 · PMID 41596598 · doi:10.3390/ijms27020948
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 GSE295041_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 PRJNA1252700 and SRA study SRP579686. Searching any of these in the dataset finder brings you back here.

Study design
24 × ovary, primary, patient vs 24 × ovary, recurrent, patient

Supports a between-group comparison across 48 samples.

How we read this: 2 replicated groups read from 48 sample titles; they account for 48 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

+ 8 more — browse all 48 samples with per-sample file links →

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.