Objectives: We aim to identify the key biomarker of acute rejection (AR) after kidney transplantation via bioinformatics methods.
Methods: The gene expression data GSE75693 of 30 samples with stable kidney transplantation recipients and 15 AR samples were downloaded and analyzed by the limma package to identify differentially expressed genes (DEGs). Then, Gene Ontology (GO) functional enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were done to explore the biological functions and potential important pathways of DEGs. Finally, protein-protein interactions (PPIs) and literature mining were applied to construct the cocitation network and to select the hub protein.
Results: A total of 437 upregulated genes and 353 downregulated genes were selected according to P < 0.01 and |log2(fold change)| > 1.0. DEGs of AR are mainly located on membranes and impact the activation of receptors in immune responses. In the PPI network, Src kinase, lymphocyte kinase (LCK), CD3G, B2M, interferon-γ, CD3D, tumor necrosis factor, VAV1, and CD3E in the T cell receptor signaling pathway were selected as important factors, and LCK was identified as the hub protein.
Conclusion: LCK, via acting on T-cell receptor, might be a potential therapeutic target for AR after kidney transplantation.