← BioTransfer GEO Dataset Finder
GEO series

DOT1L and EZH2 cooperatively repress PRC2 targets to maintain the GC B cell identity in DLBCL [RNA-seq]

GSE277665 Homo sapiens (human) RNA-seq (gene expression) 48 samples Submitted 2025/01/22 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
Diffuse large B-cell lymphomaThis series is part of our curated briefing on it.
Samples
48 samples: 16 conditions, mostly in triplicateGroups 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
Targeting DOT1L and EZH2 synergizes in breaking the germinal center identity of diffuse large B-cell lymphomaBlood · 2025
Summary (written by the submitters)
Previous published data suggested that DOT1L indirectly represses PRC2 target genes in murine B cell model. To address whether this relationship persists in human GCB-DLBCL, by integration of transcriptomic and epigenetic analysis, we defined the candidate direct targets of PRC2. GSEA of this genes list showed that DOT1L inhibition was able to significantly derepress candidate PRC2-target genes in Oci-Ly7 and Oci-Ly8.
Read the full summary ↓
This effect was also observed upon combination treatment of DOT1Li and EZH2i, suggesting that DOT1L indirectly regulates the repression of PRC2 target genes. Moreover, it has been established that in the absence of Dot1l or Ezh2, GC B cells cannot maintain their identity and instead differentiate into a dysfunctional plasma cell-like state. We therefore, investigated whether the combined inhibition of DOT1L and EZH2 enhances plasma cell differentiation. We first established differentiation-state specific signatures unique for NBC, CB, MBC, PB, and BMPC using the GenomicScape database. Unsupervised clustering of the GSVA scores revealed that all the cell lines treated with the combination treatment were clustered together and gained a BMPC signature at the expense of a CB-signature. This crosstalk between DOT1L and EZH2 appeared to be conserved among different GCB-DLBCL cell lines and was independent of their responsiveness to the treatments.
Published in
Targeting DOT1L and EZH2 synergizes in breaking the germinal center identity of diffuse large B-cell lymphoma
Göbel C, Niccolai R, de Groot MHP et al. · Blood 2025 · PMID 39792929 · doi:10.1182/blood.2024025500
This dataset
Open GSE277665 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 GSE277665_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 PRJNA1163315 and SRA study SRP533841. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 39792929) ↗
Study design
16 conditions, mostly in triplicate
Oci-Ly7, DMSO ×3 Oci-Ly7, DOT1Li ×3 Oci-Ly7, EZH2i ×3 Oci-Ly7, Combo, ×3 Oci-Ly8, DMSO ×3 Oci-Ly8, DOT1Li ×3 Oci-Ly8, EZH2i ×3 Oci-Ly8, Combo, ×3 +8 more

Supports a between-group comparison across 48 samples.

How we read this: 16 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 Diffuse large B-cell lymphoma 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.