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Transcriptomic profiles of ovarian cancer cells isolated from paired cancer ascites before and after chemotherapy

GSE241908 Homo sapiens (human) RNA-seq (gene expression) 14 samples Submitted 2024/04/24 Platform GPL16791
At a glance

RNA-seq (gene expression) · human · 14 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)
Samples
14 samples: 14 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
Therapy-induced secretion of spliceosomal components mediates pro-survival crosstalk between ovarian cancer cellsNature communications · 2024
Summary (written by the submitters)
Chemotherapy in complex with surgical removal remain the most common approaches in cancer treatment, but their effectiveness is limited by the emergence of chemoresistance. In order to reveal changes in transcriptomic profiles of cancer cells remaining after platinum-based chemotherapy, we created primary cultures of cancer cells isolated from paired ascites of ovarian cancer patients taken at the time of diagnosis and after neoadjuvant chemotherapy.
Read the full summary ↓
Enrichment analysis revealed significant activation of genes associated with DNA repair and cell cycle regulation in tumor cells after chemotherapy.
Published in
Therapy-induced secretion of spliceosomal components mediates pro-survival crosstalk between ovarian cancer cells
Shender VO, Anufrieva KS, Shnaider PV et al. · Nature communications 2024 · PMID 38898005 · doi:10.1038/s41467-024-49512-6
This dataset
Open GSE241908 in finder → Find more human RNA-seq datasets →
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 GSE241908_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 PRJNA1010738 and SRA study SRP457541. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 38898005) ↗
Study design
14 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 14 sample titles: 14 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
Datasets on a similar topic

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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.