Preprint Article Version 1 Preserved in Portico This version is not peer-reviewed

Integrative Bioinformatic Analysis of Transcriptomic Data Identifies Conserved Molecular Pathways Underlying Ionizing Radiation-Induced Bystander Effects (RIBE)

Constantinos Yeles
ORCID logo ,
Efstathios-Iason Vlachavas
,
Olga Papadodima
,
Eleftherios Pilalis
,
Constantinos E. Vorgias
,
Alexandros G. Georgakilas
ORCID logo ,
Aristotelis Chatziioannou
* ORCID logo
Version 1 : Received: 6 November 2017 / Approved: 6 November 2017 / Online: 6 November 2017 (15:02:00 CET)

A peer-reviewed article of this Preprint also exists.

Yeles, C.; Vlachavas, E.-I.; Papadodima, O.; Pilalis, E.; Vorgias, C.E.; Georgakilas, A.G.; Chatziioannou, A. Integrative Bioinformatic Analysis of Transcriptomic Data Identifies Conserved Molecular Pathways Underlying Ionizing Radiation-Induced Bystander Effects (RIBE). Cancers 2017, 9, 160. Yeles, C.; Vlachavas, E.-I.; Papadodima, O.; Pilalis, E.; Vorgias, C.E.; Georgakilas, A.G.; Chatziioannou, A. Integrative Bioinformatic Analysis of Transcriptomic Data Identifies Conserved Molecular Pathways Underlying Ionizing Radiation-Induced Bystander Effects (RIBE). Cancers 2017, 9, 160.

Abstract

Ionizing radiation-induced bystander effects (RIBE) encompass a number of effects with potential for a plethora of damages in adjacent non-irradiated tissue. The cascade of molecular events is initiated in response to the exposure to ionizing radiation (IR), something that may occur during diagnostic or therapeutic medical applications. In order to better investigate these complex response mechanisms, we employed a unified framework integrating statistical microarray analysis, signal normalization and translational bioinformatics functional analysis techniques. This approach was applied to several microarray datasets from Gene Expression Omnibus (GEO) related to RIBE. The analysis produced lists of differentially expressed genes, contrasting bystander and irradiated samples versus sham-irradiated controls. Furthermore, comparative molecular analysis through BioInfoMiner, which integrates advanced statistical enrichment and prioritization methodologies, revealed discrete biological processes, at the cellular level. For example, negative regulation of growth, cellular response to Zn2+- Cd2+, Wnt and NIK/NF-kappaB signalling, which refine the description of the phenotypic landscape of RIBE. Our results provide a more solid understanding of RIBE cell-specific response patterns, especially in the case of high-LET radiations like α-particles and carbon-ions.

Keywords

Bioinformatics; Ionizing radiation; Microarrays; Radiation-induced bystander effects; Transcriptomics

Subject

Biology and Life Sciences, Biochemistry and Molecular Biology

Copyright: This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Download PDF

Comments (0)

We encourage comments and feedback from a broad range of readers. See criteria for comments and our Diversity statement.

Leave a public comment
Send a private comment to the author(s)
* All users must log in before leaving a comment
Views 0
Downloads 0
Comments 0
Metrics 0
Get PDF Cite Share 0
Bookmark BibSonomy Mendeley Reddit Delicious
×
Alerts
Notify me about updates to this article or when a peer-reviewed version is published.
We use cookies on our website to ensure you get the best experience.
Read more about our cookies here.