ABSTRACT
Objective:To explore a new method of diagnosing and identifying renal transplantation clinical almost tolerance through a diagnostic model using plasma proteomics.Methods:From November 2011 to November 2012, plasma samples from 43 subjects were collected and divided into the groups of clinical almost tolerance(18 cases), rejection(12 cases)and healthy control(13 cases). Protemic analysis of plasma samples was performed by surface enhanced laser desorption/ionization time of flight mass spectrometry (SELDI-TOF-MS). Differential mass spectrometry peaks were screened and diagnostic model was established by Biomarker Wizard and Biomarker Pattern software. Identification of mass spectrometric peaks of nodes in the diagnostic model was carried out by searching the databases of SWISS-PROT and TrEMBL using ExPASy's TagIdent tool.Results:A total of 21 differential proteins peaks were obtained( P<0.05). Diagnostic model was composed of five mass spectrum peaks of 2 565.15, 1 966.28, 6 674.78, 1 103.27, 1 716.69 and 1 966.28.The sensitivity, specificity and area under the ROC curve of model were 83.3%, 92.0% and 0.951 respectively for diagnosing clinical almost tolerance.Bioinformatic identification results of mass spectrometric peaks of nodes in model were proteins of ANFB, MCH, TFF1, PDYN and PSME3. Conclusions:Establishing a diagnostic mode by plasma proteomics may be effectively employed for diagnosing clinical almost tolerance in kidney transplant.
ABSTRACT
<p><b>OBJECTIVE</b>To investigate the differences in the gene expression profiles of the peripheral blood immune cells between liver and kidney transplantation recipients.</p><p><b>METHODS</b>A dataset containing the gene expression profiles of 27 liver transplantation recipients and 25 kidney transplantation recipients (from GSE22229 and GSE28842, respectively) was downloaded from the GEO database. By combining gene set enrichment analysis (GSEA) and biological network analysis of the differentially expressed genes using Cytoscape software, we analyzed the core genes closely related to liver or kidney transplantations.</p><p><b>RESULTS</b>GSEA identified 20 highly overlapping genes for liver transplantation and another 20 for kidney transplantation using leading edge analysis. Fourteen hub nodes (gene) for liver transplantation and 13 for kidney transplantation were identified by cytoscape software using interaction network analysis. Five core genes related to liver transplantation and 5 to kidney transplantation were obtained by integrating GSEA and biological network analysis.</p><p><b>CONCLUSION</b>Controlling the transcription and translation of the genes of the peripheral blood immune cells is the main immune regulation mechanism in liver transplantation recipients, but in the recipients of kidney transplantation, the protein interaction network plays a more prominent role. Energy metabolism and functional regulation of the immune cells are closely related. The core genes in peripheral blood immune cells related to liver or kidney transplantation may play key roles in regulating immune functions.</p>