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TRAF3 loss-of-function Reveals the Non-Canonical NF-κB Pathway as a Therapeutic Target in Diffuse Large B-cell Lymphoma

GSE218750 Homo sapiens (human) RNA-seq (gene expression) 24 samples Submitted 2024/04/11 Platform GPL21697
At a glance

RNA-seq (gene expression) · human · 24 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
24 samples: 8 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
TRAF3 loss-of-function reveals the noncanonical NF-κB pathway as a therapeutic target in diffuse large B cell lymphomaProceedings of the National Academy of Sciences of the United States of America · 2024
Summary (written by the submitters)
Treatment of diffuse large B-cell lymphoma (DLBCL) remains challenging due to extensive molecular, clinical, and pathological heterogeneity. Here, we report recurrent focal deletions of the chr14q32.31-32 locus, including TRAF3, a negative regulator of NF-κB signaling, in a cohort of uniformly-treated de novo DLBCL (24/324 cases). Integrative analysis uncovered a correlation between TRAF3 copy number loss and TRAF3 reduced expression.
Read the full summary ↓
CRISPR-mediated TRAF3 loss-of-function (LOF) in DLBCL cell lines enhanced non-canonical NF-κB (NC NF-κB) signaling, rendering cells sensitive to shRNA-induced knockdown of the central NC NF-κB kinase, NIK. NIK pharmacological inhibitors differentially impaired proliferation, and induced apoptosis of TRAF3 LOF cells, further suggesting an acquired onco-addiction to NC NF-κB. Beyond these cell-intrinsic effects, co-culturing of TRAF3 LOF DLBCL cells with primary human CD8+ T-cells revealed an impairment in effector marker induction (Granzyme B, IFNγ) and proliferation in the latter. Accordingly, a reduction in T-cell infiltrates was observed in the microenvironment of TRAF3-low expressing primary DLBCL tumor samples. Neutralization of IL10 produced by TRAF3 LOF cells restored and enhanced GZMB and IFNγ expression in co-cultured CD8+ T-cells. Our findings demonstrate a direct relationship between TRAF3 genetic alterations and NC NF-κB activation, favoring pro-oncogenic cell-intrinsic effects and immune-evasive mechanisms, and highlight NIK as a therapeutic target in defined subset of DLBCL.
Published in
TRAF3 loss-of-function reveals the noncanonical NF-κB pathway as a therapeutic target in diffuse large B cell lymphoma
Li MY, Chong LC, Duns G et al. · Proceedings of the National Academy of Sciences of the United States of America 2024 · PMID 38662551 · doi:10.1073/pnas.2320421121
This dataset
Open GSE218750 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 GSE218750_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 PRJNA905397 and SRA study SRP409782. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 38662551) ↗
Study design
8 conditions, mostly in triplicate
DOHH2MUT ×3 OCI-LY1MUT ×3 HBL1MUT ×3 OCI-LY3MUT ×3 OCI-LY1WT ×2 HBL1WT ×2 DOHH2WT ×2 OCI-LY3WT ×2 +4 more

Supports a between-group comparison across 20 samples.

How we read this: 8 replicated groups read from 24 sample titles; they account for 20 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 Diffuse large B-cell lymphoma datasets

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