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SUMOylation inhibitor TAK-981 potentiates rituximab activity by Type I IFN-dependent macrophage and NK cell stimulation

GSE185841 Homo sapiens (human) RNA-seq (gene expression) 12 samples Submitted 2024/04/24 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)
Samples
12 samples
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
The SUMOylation inhibitor subasumstat potentiates rituximab activity by IFN1-dependent macrophage and NK cell stimulationBlood · 2022
Summary (written by the submitters)
SUMOylation is a reversible post-translational modification that has been implicated in the regulation of various cellular processes including inflammatory responses and expression of Type I interferons (IFN1). In this report, we have explored the activity of the selective small molecule SUMOylation inhibitor TAK-981 in promoting antitumor innate immune responses.
Read the full summary ↓
We demonstrate that treatment with TAK-981 results in IFN1-dependent macrophage and NK cell activation, promoting macrophage phagocytosis and NK cell cytotoxicity in ex vivo assays. Furthermore, pre-treatment with TAK-981 enhanced macrophage phagocytosis or NK cell cytotoxicity against CD20-positive target cells in combination with the anti-CD20 antibody rituximab. In vivo studies demonstrated synergistic antitumor activity of TAK-981 and rituximab in CD20-positive lymphoma xenograft models. TAK-981 is currently being studied in phase 1 clinical trials (NCT03648372, NCT04074330, NCT04776018, and NCT04381650) for the treatment of patients with lymphomas and solid tumors.
Published in
The SUMOylation inhibitor subasumstat potentiates rituximab activity by IFN1-dependent macrophage and NK cell stimulation
Nakamura A, Grossman S, Song K et al. · Blood 2022 · PMID 35226739 · doi:10.1182/blood.2021014267
This dataset
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.

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 GSE185841_RAW.tar (it can run to tens of gigabytes).

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.

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 PRJNA770982 and SRA study SRP341217. Searching any of these in the dataset finder brings you back here.

Samples in this study

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+ 12 more — browse all 12 samples with per-sample file links →

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