← BioTransfer GEO Dataset Finder
GEO series

Interferon activation in bone marrow long-lived plasma cells in systemic lupus erythematosus

GSE278120 Homo sapiens (human) RNA-seq (gene expression) 48 samples Submitted 2024/12/30 Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 48 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
48 samples: 48 samples, each with a distinct title — no replicated groupsGroups 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
Interferon activation in bone marrow long-lived plasma cells in systemic lupus erythematosusFrontiers in immunology · 2024
Summary (written by the submitters)
While durable antibody responses from long-lived plasma cell (LLPC) populations are important for protection against pathogens, LLPC may be harmful if they produce antibodies against self-proteins or self-nuclear antigens as occurs in autoimmune diseases such as systemic lupus erythematosus (SLE). Thus, the elimination of autoreactive LLPC may improve the treatment of antibody-driven autoimmune diseases.
Read the full summary ↓
However, LLPC remain a challenging therapeutic target. Here, we compare the matched bone marrow and blood plasma cell compartments of SLE and healthy donors (HD). We show a similar distribution of CD138- and CD138+ plasma cells (PC), including putative LLPC (CD19- CD138+ CD38+), between SLE and HD bone marrow (BM). For both SLE and HD, CD138+ PC are at a higher frequency in BM than peripheral blood (PBL). Expression of Ki-67 associates with the PBL compartment where it is found on all PC subsets regardless of CD19 or CD138 expression. Transcriptomic analysis identifies an interferon gene signature in transitional B cells in the SLE BM, but surprisingly also in the BM PC derived from SLE. PC phosphorylate STAT1 in response to type I IFN stimulation in vitro. Circulating PC bind type I IFN receptor-blocking antibody anifrolumab, though to a lesser degree than circulating B cells. Anti-nuclear autoantibodies are found in the BM supernatant and PBL serum of SLE patients. SLE BM-derived PC have increased survival compared to their PBL counterparts when treated with selinexor. In summary, these findings show evidence of IFN activation in BM PC from SLE.
Published in
Interferon activation in bone marrow long-lived plasma cells in systemic lupus erythematosus
Alzamareh DF, Meednu N, Nandedkar-Kulkarni N et al. · Frontiers in immunology 2024 · PMID 39867907 · doi:10.3389/fimmu.2024.1499551
This dataset
Open GSE278120 in finder → Find more human 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 GSE278120_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 PRJNA1165733 and SRA study SRP535107. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 39867907) ↗
Study design
48 samples, each with a distinct title — no replicated groups

Any grouping that defines a comparison lives in the sample characteristics, which GEO records separately from the titles.

How we read this: Read from 48 sample titles: 48 distinct titles with little repetition. 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

+ 8 more — browse all 48 samples with per-sample file links →

Datasets on a similar topic

Search all human RNA-seq datasets in GEO →

Share this dataset

Metadata from NCBI GEO, cached and refreshed periodically — the NCBI page above is authoritative. Downloads link straight to NCBI/ENA; nothing is proxied through BioTransfer.