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Bendamustine combined with rituximab induces pyroptosis to shape an "immunologically hot" tumor microenvironment in DLBCL cells via the STING pathway

GSE249466 Homo sapiens (human) RNA-seq (gene expression) 12 samples Submitted 2024/08/01 Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 12 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
12 samples: 3 × OCI-LY1 cells, control vs 3 × OCI-LY1 cells, Rituximab vs 3 × OCI-LY1 cells, Bendamustine vs 3 × OCI-LY1 cells, Bendamustine+RituximabGroups 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
Bendamustine-rituximab elicits dual tumoricidal and immunomodulatory responses via cGAS-STING activation in diffuse large B-cell lymphomaJournal for immunotherapy of cancer · 2024
Summary (written by the submitters)
Bendamustine plus rituximab (BR) therapy has demonstrated favorable clinical outcomes in the treatment of DLBCL patients who are intolerant to R-CHOP therapy. In vitro, BR therapy exhibits a synergistic cytotoxic effect on DLBCL cell lines. Mechanistically, BR induces pyroptosis in DLBCL cells by activating the cGAS-STING pathway, leading to the release of inflammatory factors and the formation of an "immunologically hot" microenvironment. Additionally, BR therapy upregulates MHC molecules on the tumor cell surface, thereby augmenting T cell activation and function.
Published in
Bendamustine-rituximab elicits dual tumoricidal and immunomodulatory responses via cGAS-STING activation in diffuse large B-cell lymphoma
Xiao R, Zhao W, Lin W et al. · Journal for immunotherapy of cancer 2024 · PMID 39521616 · doi:10.1136/jitc-2024-009212
This dataset
Open GSE249466 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 GSE249466_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 PRJNA1049338 and SRA study SRP476125. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 39521616) ↗
Study design
3 × OCI-LY1 cells, control vs 3 × OCI-LY1 cells, Rituximab vs 3 × OCI-LY1 cells, Bendamustine vs 3 × OCI-LY1 cells, Bendamustine+Rituximab

Supports a between-group comparison across 12 samples.

How we read this: 4 replicated groups read from 12 sample titles; they account for 12 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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