Tissue-Based Transcriptomic Profiling of Gastrointestinal Graft Versus Host Disease Reveals Immune and MicroRNA Dysregulation

TL;DR

This study uses tissue profiling to uncover immune and microRNA changes in gastrointestinal graft-versus-host disease, identifying potential biomarkers and pathways involved in the condition.

Contribution

The first integration of mRNA and microRNA profiling in GI aGvHD tissue using NanoString technology to reveal disease-specific molecular signatures.

Findings

GI aGvHD is marked by upregulated inflammatory genes and immune-regulatory microRNAs.

Machine learning identified LCN2, CXCL13, and miR-1269b as top biomarker candidates.

Enriched pathways include IL2/STAT5, JAK/STAT3, TCR signaling, and antigen presentation.

Abstract

Gastrointestinal acute graft-versus-host disease (GI aGvHD) remains a leading cause of non-relapse mortality after allogeneic hematopoietic stem cell transplantation (HSCT). Current diagnostic methods rely on invasive procedures with limited sensitivity. While circulating biomarkers have been proposed, little is known about the local transcriptomic landscape within inflamed GI tissue. We performed integrated profiling of mRNA and microRNA expression in colonoscopically resected GI biopsies from n = 8 HSCT patients, including n = 3 with histologically confirmed GI aGvHD and n = 5 without. Using NanoString nCounter technology, we quantified 770 immune-related mRNAs and 799 mature human microRNAs. Differential expression analysis, pathway enrichment, cell type deconvolution, and machine learning–based biomarker prioritisation were conducted to define disease-specific molecular signatures. GI aGvHD was marked by upregulation of inflammatory genes (e.g., IL1B, IL17RA, HLA-DRA) and immune-regulatory microRNAs (e.g., miR-155-3p, miR-223-3p), alongside downregulation of epithelial and anti-inflammatory markers (ST6GAL1, THBS1, miR-1915-3p, miR-145-5p). Enrichment analyses revealed activation of IL2/STAT5, JAK/STAT3, TCR signalling, and antigen presentation pathways. Machine learning identified LCN2, CXCL13, and miR-1269b as top-ranked biomarker candidates. Cell deconvolution showed increased M0 macrophage and decreased dendritic cell signatures in aGvHD tissue. This is the first study to integrate mRNA and microRNA profiling in GI tissue using NanoString technology to characterise the immune and epithelial transcriptomic landscape of aGvHD. Our findings reveal dysregulated immune pathways, altered myeloid cell populations, and novel biomarker candidates, offering tissue-specific insights into disease pathogenesis and potential diagnostic targets. Larger validation studies and functional assays are warranted to confirm clinical utility.

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