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Transcriptional profiling of isolated T cells of healthy individuals after treatment with supernatant of peripheral blood mononuclear cells (PBMCs) of the same individuals treated overnight with soluble CD14 (sCD14)

GSE277708 Homo sapiens (human) RNA-seq (gene expression) 12 samples Submitted 2026/01/14 Platform GPL34284
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: 12 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
Soluble CD14 promotes Th17 expansion and differentiation through gamma-aminobutyric acid and expands infidel innate lymphoid cellsPNAS nexus · 2026
Summary (written by the submitters)
In this study, we treated PBMCs of 6 healthy individuals with sCD14 overnight. The day after, the supernatant of treated PBMCs was collected and isolated T cells from the same individuals were stimulated with anti-CD3/CD28 and cultured with collected supernatant. RNA from T cells was isolated after 6 hours and submitted for RNAseq analysis.
Published in
Soluble CD14 promotes Th17 expansion and differentiation through gamma-aminobutyric acid and expands infidel innate lymphoid cells
Shahbaz S, Rahmati A, Syed H et al. · PNAS nexus 2026 · PMID 41522693 · doi:10.1093/pnasnexus/pgaf406
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 GSE277708_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 PRJNA1163401 and SRA study SRP533917. Searching any of these in the dataset finder brings you back here.

Study design
12 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 12 sample titles: 12 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
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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.