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ICAM1 expression and associated clinical parameters as predictive biomarkers for acute celluar rejection

GSE319886 Homo sapiens Expression profiling by high throughput sequencing 6 samples Submitted 2026/06/30 Platform GPL24676
Summary
Background: Acute cellular rejection (ACR) remains a significant complication after liver transplantation (LT). To identify pre-transplant biomarkers and elucidate the underlying immune mechanisms predisposing recipients to ACR, LT recipients were enrolled. Methods: Clinical parameters were analyzed pre- and post-LT. Single-cell RNA sequencing (scRNA-seq) was performed on pre-LT liver biopsies to characterize the immune microenvironment. Functional assays were performed in vitro and in vivo. Results: Pre-LT hepatitis virus infection was an independent risk factor for ACR. scRNA-seq revealed a distinct pre-LT immune landscape in patients who developed into ACR with a reduced proportion of T/NK cells but an enrichment of highly cytotoxic NK subsets (e.g., NK⁺_GNLY⁺), which was associated with downregulation of key adhesion molecules, particularly the ICAM1-ITGB2 (LFA-1) axis. ICAM1 knockdown impaired macrophage migration and synapses formation in vitro and suppressed the MAPK-ERK pathway. Clinically, low intrahepatic ICAM1 expression pre-LT correlated with diminished leukocyte infiltration (CD45⁺, CD18⁺), increased post-transplant collagen deposition, and more severe ACR. Furthermore, recipient ICAM1 levels strongly correlated with distinct serum parameter profiles, negatively with early post-LT ALT and positively with pre-LT bilirubin levels. Conclusion: Results suggest that a pre-LT state of dysregulated cytotoxicity and impaired immune cell adhesion/migration, characterized by low ICAM1 expression and a suppressed MAPK pathway, predisposes patients to ACR. ICAM1 expression, combined with specific bilirubin and liver enzyme profiles, emerges as a promising integrated biomarker for predicting rejection risk.
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Also filed as BioProject PRJNA1425483 and SRA study SRP678033. Searching any of these in the dataset finder brings you back here.

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