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Raw RNA-sequencing data for deriving BCR sequences from the NIH U01 project: Finding the optimal balance of immunotherapy efficacy and toxicity.

GSE296826 Homo sapiens (human) RNA-seq (gene expression) 256 samples Submitted 2025/05/12 Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 256 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
256 samples: 256 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.
Summary (written by the submitters)
IrAEs convey substantial morbidity, incur considerable costs, and in some cases may preclude further use of immune checkpoint blockades. Recent studies indicate that (1) up to 80% of individuals on ICIs experience some form of irAEs; (2) ~35% of patients require corticosteroid treatments to mitigate these events; and (3) up to 20% terminate their therapy due to irAEs.
Read the full summary ↓
As immunotherapy use extends from major centers to smaller, isolated, and less experienced community sites, predicting the development of irAEs and incorporation of this prediction into ICI treatment considerations becomes extremely valuable. Despite the substantial efforts invested in machine learning models for predicting ICI treatment responses, few studies have focused on predictive modeling for irAEs. We address this unmet need by leveraging the unique patient resources collected at UTSW and developing a BCR-based biomarker for irAEs. Moreover, irAEs can happen as short as a few weeks or as long as a few years after ICI treatment. We deployed our model longitudinally to track if the evolution of autoreactive BCRs align with the timings of irAEs.
This dataset
Open GSE296826 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 GSE296826_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 PRJNA1261702 and SRA study SRP584519. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
256 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 256 sample titles: 256 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

+ 216 more — browse all 256 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.