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Injured epithelial cell states impact kidney allograft survival after T-cell-mediated rejection

GSE284715 Homo sapiens (human) Single-nucleus RNA-seq 14 samples Submitted 2025/11/21 Platform GPL21103Platform GPL34284
At a glance

Single-nucleus RNA-seq · human · 14 samples

What it is
Single-nucleus RNA-seqGene activity measured in individual nuclei (used when whole cells are hard to isolate, for example from frozen tissue). Read from the summary: GEO's own type field only says 'expression profiling by sequencing', so confirm it in the paper.
Organism
Homo sapiens (human)
Samples
14 samples: 5 conditions, mostly in triplicateGroups 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
Injured epithelial cell states impact kidney allograft survival after T-cell-mediated rejectionNature communications · 2026
Summary (written by the submitters)
Background: T-cell mediated rejection (TCMR) remains a significant challenge after kidney transplantation and is associated with reduced allograft outcome. Previous research highlighted the critical role of TCMR-induced renal epithelial injury. Yet, the detailed cellular origin of these injury responses and the associated clinical implications remain poorly understood.
Read the full summary ↓
Methods: To induce acute TCMR, we used mouse models of allogeneic (C57BL/6 to BALB/c and BALB/c to C57BL/6) kidney transplantation and syngeneic controls (C57BL/6 to C57BL/6 and BALB/c to BALB/c). Molecular changes were analyzed 7 days post-transplant using single-nucleus RNA sequencing and spatial transcriptomics. Results were compared with snRNA-seq data from three human TCMR biopsies and three stable allografts without rejection. The clinical impact of TCMR-induced epithelial injury was evaluated using marker gene sets on bulk transcriptomic data from 1292 kidney allografts, including 95 TCMR samples, with allograft outcome. Results: Mouse kidneys from allogeneic transplants exhibited all hallmark histological features of TCMR. Single-nucleus RNA sequencing revealed TCMR-induced injured cell states and significant gene expression changes particularly in proximal tubules (PT) and thick ascending limbs (TAL). Spatial transcriptomics showed a heterogeneous spatial distribution of these injured cell states and proximity to leukocytes. Cross-species analysis confirmed similar injured PT and TAL cell states in human TCMR. Signatures of a severely injured TCMR-induced TAL cell state correlated strongly with allograft survival in a large kidney transplant cohort specifically after TCMR. Conclusion: This is the first study showing kidney allograft outcome with distinct injured epithelial cell states. We found a particularly strong correlation between kidney allograft survival and TAL injury in TCMR, which occurred with reduced proximity to leukocytes, suggesting potential epithelial injury driven by non-immune mechanisms.
Published in
Injured epithelial cell states impact kidney allograft survival after T-cell-mediated rejection
Pfefferkorn AM, Jahn L, Gauthier PT et al. · Nature communications 2026 · PMID 41605921 · doi:10.1038/s41467-026-68397-1
This dataset
Open GSE284715 in finder → Find more 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 GSE284715_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: Single-cell studies usually ship their counts as 10x files (matrix.mtx, barcodes.tsv, features.tsv), an .h5 file, or an .rds / .h5ad object that Seurat or Scanpy can open. Look for those among the supplementary files.

Also filed as BioProject PRJNA1200092. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 41605921) ↗
Study design
5 conditions, mostly in triplicate
single- nuclei RNA sequencing data from mouse… ×3 single- nuclei RNA sequencing data from human… ×3 single- nuclei RNA sequencing data from human… ×3 single- nuclei RNA sequencing data from mouse… ×2 single- nuclei RNA sequencing data from mouse… ×2 single- nuclei RNA sequencing data from mouse… ×1

Supports a between-group comparison across 13 samples.

How we read this: 5 replicated groups read from 14 sample titles; they account for 13 of them. 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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