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Human Lung Allografts Experience Persistent Fibrogenic Shift Following Acute Cellular Rejection

GSE274199 Homo sapiens (human) ChIP-seq / ATAC-seq (genome binding and open chromatin) 69 samples Submitted 2026/02/27 Platform GPL34281Platform GPL24676
At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · human · 69 samples

What it is
ChIP-seq / ATAC-seq (genome binding and open chromatin)Where proteins bind the genome, or which regions are open and active.
Organism
Homo sapiens (human)
Samples
69 samples: 56 distinct titles, 2 of them repeatedGroups 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
Human lung allografts experience persistent fibrogenic shift following acute cellular rejectionThe Journal of heart and lung transplantation : the official publication of the International Society for Heart Transplantation · 2026
Summary (written by the submitters)
Rationale: Acute cellular rejection (ACR) remains a significant challenge in lung transplantation, with incomplete understanding of its molecular mechanisms and pathways linking ACR to chronic lung allograft dysfunction (CLAD). Objectives: To characterize the cellular and molecular mechanisms underlying ACR in lung allografts using single cell genomics and identify potential therapeutic targets for CLAD.
Read the full summary ↓
Methods: Single cell RNA-sequencing of freshly collected lung tissue was performed across 8 pediatric and young adult patients with ACR, Resolved ACR, and surveillance biopsies without ACR. Validation included gene microarray analysis, immunofluorescence, and single cell ATAC-seq. Measurements and Main Results: Gene set enrichment analysis revealed persistent TGF-β signaling and PI3K/AKT/mTOR pathway activation in both ACR and Resolved samples, validated by immunofluorescence showing sustained elevation of mTOR activation marker phosphorylated-S6 ribosomal protein and COL3A1. Fibrogenic cells exhibited myofibroblast gene signatures via mesenchymal state transitions rather than epithelial- or endothelial-to-mesenchymal transition. Cell communication analysis showed increased Type II Interferon signaling, with Jak/Stat pathway activation in endothelial and basal cells, and reduced VE-Cadherin staining in ACR. Compositional analysis revealed increased cytotoxic, memory T cells and dendritic cells, with persistent reduction of natural killer cells in ACR and Resolved. Donor/recipient analysis revealed predominantly recipient-derived immune cells in ACR. Conclusions: Persistent TGF-β and mTOR pathway activation following histologic ACR resolution provides molecular insight into ACR-CLAD linkage and suggests mTOR inhibition and TGF-β blockade as potential therapeutic mechanisms to prevent CLAD.
Published in
Human lung allografts experience persistent fibrogenic shift following acute cellular rejection
Potter AS, Sharma NS, Goda Y et al. · The Journal of heart and lung transplantation : the official publication of the International Society for Heart Transplantation 2026 · PMID 41740941 · doi:10.1016/j.healun.2026.02.1666
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 GSE274199_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: Look for peak files (.bed, .narrowPeak) and signal tracks (.bigWig) among the supplementary files; the raw reads are on ENA.

Also filed as BioProject PRJNA1145391. Searching any of these in the dataset finder brings you back here.

Study design
56 distinct titles, 2 of them repeated
TBBx, A0, biopsy ×13 TBBx, A3, biopsy ×2

How we read this: Read from 69 sample titles: 56 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

+ 29 more — browse all 69 samples with per-sample file links →

Datasets on a similar topic

Search all human RNA-seq datasets in GEO →

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