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An epigenetic pathway regulates MHC-II expression and function in B cell lymphoma models

GSE276031 Homo sapiens (human) ChIP-seq / ATAC-seq (genome binding and open chromatin) 77 samples Submitted 2024/12/20 Platform GPL24676Platform GPL18573Platform GPL24247
At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · human · 77 samples

What it is
ChIP-seq / ATAC-seq (genome binding and open chromatin)Where proteins bind the genome, or which regions are open and active.
Organism
Homo sapiens (human)
Samples
77 samples: 26 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
An epigenetic pathway regulates MHC-II expression and function in B cell lymphoma modelsThe Journal of clinical investigation · 2025
Summary (written by the submitters)
There is a growing recognition of the prognostic significance associated with the expression of major histocompatibility complex (MHC) class II in tumor cells within the context of anti-cancer immunity. Mutations or homozygous deletions of MHC-II genes are frequently encountered in B-cell lymphomas that develop in immune-privileged sites, and therefore have been linked to the survival of patients with B-cell lymphoma.
Read the full summary ↓
However, the understanding of the regulation of MHC class II expression by epigenetic and genetic factors remains incomplete. In this study, we have identified a crucial signaling pathway comprised of the histone H2AK119 deubiquitinase BAP1, the interferon regulatory factor IRF1, and the MHC-II transactivator CIITA, which directly activates the expression of MHC-II cluster genes. Disruption of the BAP1/IRF1/CIITA axis leads to a functional attenuation of MHC-II expression without affecting expression of the genes involved in cell cycle or proliferation. Notably, loss of BAP1 has no effect on B cell lymphoma cell growth in vitro while significantly accelerates tumor growth in immunocompetent mice in vivo. Indeed, by utilizing single-cell RNA-seq, a significant reduction in immune cell infiltration was observed in BAP1-depleted tumors, indicating a potential tumor suppressive function of BAP1 by regulating the tumor microenvironment and immune response. Finally, we demonstrated that pharmacological inhibition of PRC1, which deposits histone H2K119Ub and functions as an antagonist of BAP1, could rescue the MHC-II genes in BAP1 deficient B-cell lymphoma cells. These findings establish the rationale for therapeutic strategies aimed at restoring tumor-specific MHC class II expression and enhancing immunotherapy outcomes at epigenetic levels in B-cell lymphoma treatment.
Published in
An epigenetic pathway regulates MHC-II expression and function in B cell lymphoma models
Zhang T, Beytullahoglu O, Tulaiha R et al. · The Journal of clinical investigation 2025 · PMID 39817454 · doi:10.1172/JCI179703
This dataset
Open GSE276031 in finder → Find more 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 GSE276031_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: Look for peak files (.bed, .narrowPeak) and signal tracks (.bigWig) among the supplementary files; the raw reads are on ENA.

Also filed as BioProject PRJNA1154324 and SRA study SRP529513. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 39817454) ↗
Study design
26 conditions, mostly in duplicate
MP65_GFP ×2 MP65_BAP1_WT ×2 MP65_BAP1_C91S ×2 HEK293T_WT ×2 HEK293T_C91S_Clone 1 ×2 HEK293T_C91S_Clone 2 ×2 A20_BAP1_WT ×2 A20_BAP1_KO_Clone 1 ×2 +43 more

Supports a between-group comparison across 52 samples.

How we read this: 26 replicated groups read from 77 sample titles; they account for 52 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

+ 37 more — browse all 77 samples with per-sample file links →

Datasets on a similar topic

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