June 2013
Volume 54, Issue 15
Free
ARVO Annual Meeting Abstract  |   June 2013
Gene expression analysis between retinoblastoma with exophytic and endophytic growth patterns. Preliminary analysis
Author Affiliations & Notes
  • Carlos-Alberto Rodriguez-Barrientos
    Ophthalmology Research Chair, Tecnológico de Monterrey, Monterrey, Mexico
  • Judith Zavala
    Ophthalmology Research Chair, Tecnológico de Monterrey, Monterrey, Mexico
  • Jorge Valdez
    Ophthalmology Research Chair, Tecnológico de Monterrey, Monterrey, Mexico
  • Victor Treviño
    Bioinformatics Group, Tecnológico de Monterrey, Monterrey, Mexico
  • Juan Martinez-Ledesma
    Bioinformatics Group, Tecnológico de Monterrey, Monterrey, Mexico
  • Footnotes
    Commercial Relationships Carlos-Alberto Rodriguez-Barrientos, None; Judith Zavala, None; Jorge Valdez, None; Victor Treviño, None; Juan Martinez-Ledesma, None
  • Footnotes
    Support None
Investigative Ophthalmology & Visual Science June 2013, Vol.54, 1173. doi:
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      Carlos-Alberto Rodriguez-Barrientos, Judith Zavala, Jorge Valdez, Victor Treviño, Juan Martinez-Ledesma, ; Gene expression analysis between retinoblastoma with exophytic and endophytic growth patterns. Preliminary analysis. Invest. Ophthalmol. Vis. Sci. 2013;54(15):1173.

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      © ARVO (1962-2015); The Authors (2016-present)

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Abstract

Purpose: To determine with a preliminary analysis the main gene expression difference between samples of retinoblastoma with exophytic and endophytic growth and samples of normal retina selecting specific biomarkers for growth patterns in retinoblastoma.

Methods: Seven data sets from samples of normal human retina, seven data sets from samples of retinoblastoma with endophytic growth and seven data set from samples of retinoblastoma with exophytic growth patterns from the same platform (GPL570) were obtained from GEO databases. The mean differential expression among samples (exophytic vs normal retina and endophytic vs normal retina) was calculated and a list of 100 significant genes for exophytic and endophytic growth were obtained. From this list we selected the 50 most significant genes based on their p value (4.13X10-10 for endophytic and 3.64X10-11 for endophytic).

Results: Among the most significant genes for exophythic retinoblastoma growth we found: adenomatous polyposis coli, N-cadherin (neuronal), immunoglobulin mu binding protein 2, protein phosphatase 1, regulatory (inhibitor) subunit 9B, synuclein and rhodopsin are associated with cellular component for cell projection, particularly to nerve cell. Stathmin 1, syntaxin 17, Rho guanine nucleotide exchange factor (GEF) 12, TAO kinase 1 and trinucleotide repeat containing 6C also were found to be related with exophytic growth pattern. In contrast, the most significant genes found in endophytic retinoblastoma samples were: ZW10 interactor, cyclin B1, kinesin family member 11, non-SMC condensin I complex, subunit G, pituitary tumor-transforming 1 and pituitary tumor-transforming 2. All these genes are implicated in cellular processes such as organelle fission, nuclear division and M phase of mitotic cell cycle.

Conclusions: This preliminary analysis provides a general idea of the difference in the gene expression patterns between retinoblastoma tumors with endophytic and exophytic growths and normal retina. This study sets the guideline to do an extensive study to identify biomarkers that characterize growth patterns of retinoblastoma

Keywords: 688 retina • 703 retinoblastoma • 533 gene/expression  
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