← BioTransfer GEO Dataset Finder
GEO series

Identification of Therapeutic Targets for Low-Grade Serous Ovarian Carcinoma

GSE313802 Homo sapiens (human) RNA-seq (gene expression) 28 samples Submitted 2026/03/30 Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 28 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
28 samples: 14 conditions, mostly in duplicateGroups 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
Identifying therapeutic targets in low-grade serous ovarian carcinomas with no specific molecular profileThe Journal of pathology · 2026
Summary (written by the submitters)
Low-grade serous ovarian carcinoma (LGSOC) is a rare, indolent ovarian cancer subtype with limited effective therapies. Approximately 40% of cases lack canonical MAPK/ERK or PI3K/AKT/mTOR pathway alterations and are classified as having no specific molecular profile (NSMP). These patients have poor responses to chemotherapy, MEK inhibitors, and hormonal therapies, highlighting the need for alternative strategies.
Read the full summary ↓
This study aimed to identify novel therapeutic targets in NSMP LGSOC. A high-throughput drug screen of over 3,500 compounds (including FDA-approved, clinically tested, and investigational agents) was conducted across 12 LGSOC and one control ovarian epithelial cell line. EGFR inhibitors emerged as selective hits in NSMP cell lines and were further tested in two NSMP and two MAPK-mutant lines in combination with standard-of-care chemotherapy agents, carboplatin and paclitaxel. EGFR expression was assessed using RNA sequencing, DNA methylation profiling, and immunohistochemistry in primary tumours, followed by survival analysis based on expression levels.
Published in
Identifying therapeutic targets in low-grade serous ovarian carcinomas with no specific molecular profile
Pishas KI, Cowley KJ, Marinovic E et al. · The Journal of pathology 2026 · PMID 42138099 · doi:10.1002/path.70075
This dataset
Open GSE313802 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 GSE313802_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 PRJNA1381606 and SRA study SRP655291. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 42138099) ↗
Study design
14 conditions, mostly in duplicate
VOA-3723 ×2 VOA-14202 ×2 IOSE-523 ×2 VOA-7681 ×2 VOA-1056 ×2 AOCS2 ×2 VOA-4698 ×2 VOA-4627 ×2 +6 more

Supports a between-group comparison across 28 samples.

How we read this: 14 replicated groups read from 28 sample titles; they account for 28 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

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.