Single dose of CD137-Antibody Drug Conjugate protects non-human primate allogeneic HCT recipients against acute GVHD
RNA-seq (gene expression) · human · 70 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
- 70 samples: 70 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
- A single dose of a CD137 antibody-drug conjugate protects rhesus macaque allogeneic HCT recipients against acute GVHDBlood · 2025
Read the full summary ↓
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.
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.
Supplementary files
The count tables and other files the authors uploaded. Take only the samples you need, or the whole study as GSE298158_RAW.tar (it can run to tens of gigabytes).
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 PRJNA1268442 and SRA study SRP587865. Searching any of these in the dataset finder brings you back here.
Any grouping that defines a comparison lives in the sample characteristics, which GEO records separately from the titles.
How we read this: Read from 70 sample titles: 70 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.
- GSM9009208 Patient Sample, 001-002_d21_cd4
- GSM9009209 Patient Sample, 001-002_d28_cd4
- GSM9009210 Patient Sample, 001-005_d21_cd4
- GSM9009211 Patient Sample, 001-005_d28_cd4
- GSM9009212 Patient Sample, 001-008_d21_cd4
- GSM9009213 Patient Sample, 001-013_d21_cd4
- GSM9009214 Patient Sample, 001-015_d21_cd4
- GSM9009215 Patient Sample, 001-015_d28_cd4
- GSM9009216 Patient Sample, 001-017_d21_cd4
- GSM9009217 Patient Sample, 001-018_d21_cd4
- GSM9009218 Patient Sample, 001-018_d28_cd4
- GSM9009219 Patient Sample, 001-023_d28_cd4
- GSM9009220 Patient Sample, 001-024_d21_cd4
- GSM9009221 Patient Sample, 001-026_d21_cd4
- GSM9009222 Patient Sample, 001-031_d21_cd4
- GSM9009223 Patient Sample, 001-031_d28_cd4
- GSM9009224 Patient Sample, 001-039_d28_cd4
- GSM9009225 Patient Sample, 002-002_d21_cd4
- GSM9009226 Patient Sample, 002-002_d28_cd4
- GSM9009227 Patient Sample, 002-004_d28_cd4
- GSM9009228 Patient Sample, 002-006_d28_cd4
- GSM9009229 Patient Sample, 002-016_d21_cd4
- GSM9009230 Patient Sample, 002-016_d28_cd4
- GSM9009231 Patient Sample, 004-013_d21_cd4
- GSM9009232 Patient Sample, 004-013_d28_cd4
- GSM9009233 Patient Sample, 004-023_d28_cd4
- GSM9009234 Patient Sample, 004-028_d21_cd4
- GSM9009235 Patient Sample, 004-028_d28_cd4
- GSM9009236 Patient Sample, 004-029_d21_cd4
- GSM9009237 Patient Sample, 004-037_d21_cd4
- GSM9009238 Patient Sample, 004-037_d28_cd4
- GSM9009239 Patient Sample, 004-046_d21_cd4
- GSM9009240 Patient Sample, 004-046_d28_cd4
- GSM9009241 Patient Sample, 004-049_d21_cd4
- GSM9009242 Patient Sample, 004-055_d21_cd4
- GSM9009243 Patient Sample, 004-056_d21_cd4
- GSM9009244 Patient Sample, 004-056_d28_cd4
- GSM9009245 Patient Sample, 004-057_d21_cd4
- GSM9009246 Patient Sample, 004-057_d28_cd4
- GSM9009247 Patient Sample, 004-059_d21_cd4
+ 30 more — browse all 70 samples with per-sample file links →
- GSE295359 Mega-scale single-cell profiling reveals novel biomarkers associated with acute GvHD after allogeneic hematopoietic stem cell transplantation 15 samples shares gvhd, allogeneic
- GSE324345 Analysis of ER stress-induced three-dimensional enhancer network in wild-type and transcription facotr-knockout HCT116 cells [RNA-Seq] 66 samples shares hct
- GSE271991 Effect of red meat metabolites and nutrient deprivation on gene expression of HCT116 colorectal cancer cells 60 samples shares hct
- GSE249009 RNA sequencing analysis of isoginkgetin and thapsigargin treated HCT116 and HCT116 ATF4 deficient cells 48 samples shares hct
- GSE276918 RNA decay profile for eRF1 and UPF1 depletion in HCT116 cell lines 48 samples shares hct
- GSE296708 Acetyl-CoA Carboxylase-1 Inhibition Increases Regulatory T-Cell Metabolism, Mitochondrial Fusion and Graft-vs-Host Disease Treatment Efficacy [L2_cGvHD] 35 samples shares gvhd
- GSE289482 IGF2BP3 regulates RNA metabolism during unfolded protein response [HCT116] 32 samples shares hct
- GSE246047 Inflammasome-resistant IPSC-derived myeloid-derived suppressor cells (iMDSCs) ameliorate xenogeneic GVHD 28 samples shares gvhd
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.