Literature DB >> 31238062

Comparative transcriptome analysis of peripheral blood mononuclear cells in renal transplant recipients in everolimus- and tacrolimus-based immunosuppressive therapy.

Simona Granata1, Gloria Santoro1, Lorenzo Signorini1, Giovanni Malerba2, Cristina Patuzzo2, Giovanni Gambaro1, Giovanni Stallone3, Gianluigi Zaza4.   

Abstract

To better define the biological impact of immunosuppression on peripheral blood mononuclear cells (PBMC), we employed RNASeq analysis to compare the whole transcriptomic profile of a group of renal transplant recipients undergoing maintenance treatment with Everolimus (EVE) with those treated with Tacrolimus (TAC). Then, obtained results were validated by classical biomolecular methodologies. The statistical analysis allowed the identification of four genes discriminating the 2 study groups: Sushi Domain Containing 4 (SUSD4, P = 0.02), T Cell Leukemia/Lymphoma 1A (TCL1A, P = 0.02), adhesion G protein-coupled receptor E3 (ADGRE3, P = 0.01), Immunoglobulin Heavy Constant Gamma 3 (IGHG3, P = 0.03). All of them were significantly down-regulated in patients treated with EVE compared to TAC. The Area under Receiver Operating Characteristic (AUROC) of the final model based on these 4 genes was 73.1% demonstrating its good discriminative power. RT-PCR and ELISA validated transcriptomic results. Additionally, an in vitro model confirmed that EVE significantly down-regulates (P<0.001) TCL1A, SUSD4, ADGRE3 and IgHG3 in PBMCs as well as in T cells and monocytes isolated from healthy subjects. Taken together, our data, revealed, for the first time, a new four gene-based transcriptomic fingerprint down-regulated by EVE in PBMCs of renal transplant patients that could improve the available knowledge regarding some of the biological/cellular effects of the mTOR-Is (including their antineoplastic and immune-regulatory properties).
Copyright © 2019 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Everolimus; RNASeq; Renal transplantation; Tacrolimus; Transcriptome

Mesh:

Substances:

Year:  2019        PMID: 31238062     DOI: 10.1016/j.ejphar.2019.172494

Source DB:  PubMed          Journal:  Eur J Pharmacol        ISSN: 0014-2999            Impact factor:   4.432


  1 in total

1.  Bioinformatics Identification of Candidate Biomarkers in Endomyocardial Biopsy and Peripheral Blood for Cardiac Allograft Rejection.

Authors:  Kang Luo; Lin Li; Mingyao Meng; Yan Chen; Zongliu Hou
Journal:  Ann Transplant       Date:  2022-03-29       Impact factor: 1.530

  1 in total

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