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EZH2 INHIBITION ENHANCES T CELL IMMUNOTHERAPIES BY INDUCING LYMPHOMA IMMUNOGENICITY AND IMPROVING T CELL FUNCTION (RNA-Seq)

GSE255548 Homo sapiens (human) RNA-seq (gene expression) 35 samples Submitted 2025/01/10 Platform GPL24247Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 35 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
Follicular lymphomaThis series is part of our curated briefing on it.
Samples
35 samples: 8 conditions, mostly with about 5 replicates eachGroups 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
EZH2 inhibition enhances T cell immunotherapies by inducing lymphoma immunogenicity and improving T cell functionCancer cell · 2025
Summary (written by the submitters)
While T cell immunotherapies have demonstrated effectiveness in a subset of patients with diffuse large B cell lymphoma (DLBCL) and follicular lymphoma (FL), they are currently administered without guidance regarding whether the underlying biology or immunology is conducive to a durable response. Moreover, mechanisms explaining CAR-T resistance in B cell lymphomas remain largely unknown, and suitable systems to study lymphomas are currently unavailable, making it infeasible.
Read the full summary ↓
To address these unmet needs, we developed syngeneic animal models reflecting the genetics, epigenetics, and immunology of human FL and DLBCL. We show that treatment of these models with EZH2 inhibitors reprogrammed them to re-express T cell engagement genes and rendered them highly immunogenic. Notably, EZH2 inhibitors did not exhibit deleterious effects on T cells. Instead, they promoted a memory CAR CD8 phenotype and reduced exhaustion, resulting in a superior elimination of lymphoma B cells and decreased tumor burden. Intravital 2-photon imaging of transformed FL bearing mice showed that EZH2 inhibition increased the recruitment of CAR-T into the tumor microenvironment and enhanced the quality of interactions with lymphoma cells, leading to increased killing. Therefore, inhibition of EZH2 enhances CAR-T cell activity through direct effects on CAR-T cells, in addition to rendering lymphoma B cells immunogenic. This offers an innovative approach for enhancing the prognosis of patients with refractory B cell lymphomas, and is currently under evaluation in a clinical trial (NCT05934838)
Published in
EZH2 inhibition enhances T cell immunotherapies by inducing lymphoma immunogenicity and improving T cell function
Isshiki Y, Chen X, Teater M et al. · Cancer cell 2025 · PMID 39642889 · doi:10.1016/j.ccell.2024.11.006
This dataset
Open GSE255548 in finder → Find more RNA-seq datasets → Follicular 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 GSE255548_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 PRJNA1075425 and SRA study SRP489271. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 39642889) ↗
Study design
8 conditions, mostly with about 5 replicates each
GCB_WT_RNAseq ×5 GCB_BCL2_RNAseq ×5 GCB_Ezh2BCL2_RNAseq ×5 PDX_DLBCL-EZB_vehicle_RNAseq ×5 PDX_DLBCL-EZB_tazemetostat_RNAseq ×5 GCB_Ezh2_RNAseq ×4 tFL-P6_cellLine_DMSO_RNAseq ×3 tFL-P6_cellLine_tazemetostat_RNAseq ×3

Supports a between-group comparison across 35 samples.

How we read this: 8 replicated groups read from 35 sample titles; they account for 35 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 Follicular lymphoma datasets

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