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RNA-seq analysis of DLBCL cell lines in response to chemotherapy

GSE224867 Homo sapiens (human) RNA-seq (gene expression) 36 samples Submitted 2024/10/29 Platform GPL20301
At a glance

RNA-seq (gene expression) · human · 36 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
Diffuse large B-cell lymphomaThis series is part of our curated briefing on it.
Samples
36 samples: 36 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
Senescence-associated lineage-aberrant plasticity evokes T-cell-mediated tumor controlNature communications · 2025
Summary (written by the submitters)
Despite the long-standing role of standard chemotherapy in human diffuse large B cell lymphoma (DLBCL), the basis for individual tumor responses and how they associate with different transcriptional programs are incompletely understood. Hence we aimed to classify DLBCL cell lines by their ability to undergo therapy-induced senescence (TIS) in response to adriamycin (aka doxorubicin) and acquire gene expression profiles before and after chemotherapy by RNA-seq.
Published in
Senescence-associated lineage-aberrant plasticity evokes T-cell-mediated tumor control
Belenki D, Richter-Pechanska P, Shao Z et al. · Nature communications 2025 · PMID 40159497 · doi:10.1038/s41467-025-57429-x
This dataset
Open GSE224867 in finder → Find more human RNA-seq datasets → Diffuse large B-cell lymphoma 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 GSE224867_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 PRJNA932818 and SRA study SRP421535. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 40159497) ↗
Study design
36 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 36 sample titles: 36 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 Diffuse large B-cell lymphoma datasets

Search all human RNA-seq datasets in GEO →

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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.