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Gene expression analysis identifies two distinct molecular clusters of idiopatic epiretinal membranes.

Authors :
Coltrini D
Belleri M
Gambicorti E
Romano D
Morescalchi F
Krishna Chandran AM
Calza S
Semeraro F
Presta M
Source :
Biochimica et biophysica acta. Molecular basis of disease [Biochim Biophys Acta Mol Basis Dis] 2020 Dec 01; Vol. 1866 (12), pp. 165938. Date of Electronic Publication: 2020 Aug 20.
Publication Year :
2020

Abstract

Idiopathic epiretinal membranes (ERMs) are fibrocellular membranes containing extracellular matrix proteins and epiretinal cells of retinal and extraretinal origin. iERMs lead to decreased visual acuity and their pathogenesis has not been completely defined. Aim of this study was to provide a molecular characterization of iERMs by gene expression analysis. To this purpose, 56 iERMs obtained by pars plana vitrectomy were analyzed for the expression levels of genes encoding biomarkers of the cellular and molecular events occurring in iERMs. RT-qPCR analysis showed significant differences in the levels of cell population, extracellular matrix and cytokine/growth factor biomarkers among the iERMs investigated. Hierarchical clustering of RT-qPCR data identified two distinct iERM clusters, Cluster B samples representing transcriptionally "activated" iERMs when compared to transcriptionally "quiescent" Cluster A specimens. Further, Cluster B could be subdivided in two subgroups, Cluster B1 iERMs, characterized by a marked glial cell activation, and Cluster B2 samples characterized by a more pro-fibrotic phenotype. Preoperative decimal best-corrected visual acuity and post-surgery inner segment/outer grading values were higher in Cluster A patients, that showed a prevalence of fovea-attached type iERMs with near-normal inner retina, than in Cluster B patients, that presented more severe clinical and spectral domain optical coherence tomography (SD-OCT) features. In conclusion, this molecular characterization has identified two major clusters of iERM specimens with distinct transcriptional activities that reflect different clinical and SD-OCT features of iERM patients. This retrospective work paves the way to prospective whole-genome transcriptomic studies to allow a molecular classification of iERMs and for the identification of molecular signature(s) of prognostic and therapeutic significance.<br /> (Copyright © 2020 Elsevier B.V. All rights reserved.)

Details

Language :
English
ISSN :
1879-260X
Volume :
1866
Issue :
12
Database :
MEDLINE
Journal :
Biochimica et biophysica acta. Molecular basis of disease
Publication Type :
Academic Journal
Accession number :
32827649
Full Text :
https://doi.org/10.1016/j.bbadis.2020.165938