A data mining approach to identify key radioresponsive genes in mouse model of radiation-induced intestinal injury.

Abstract

Background: Radiation-mediated GI injury (RIGI) is observed in humans either due to accidental or intentional exposures. This can only be managed with supporting care and no approved countermeasures are available till now. Early detection and monitoring of RIGI is important for effective medical management and improve survival chances of exposed individuals.

Objective: The present study aims to identify new signatures of RIGI using data mining approach followed by validation of selected hub genes in mice.

Methods: Data mining study was performed using microarray datasets from Gene Expression Omnibus database. The differentially expressed genes were identified and further validated in total-body irradiated mice.

Results: Based on KEGG pathway analysis, lipid metabolism was found as one of the predominant pathways altered in irradiated intestine. Extensive alteration in lipid profile and lipid modification was observed in this tissue. A protein-protein interaction network revealed top 08 hub genes related to lipid metabolism, namely Fabp1, Fabp2, Fabp6, Npc1l1, Ppar-α, Abcg8, Hnf-4α, and Insig1. qRT-PCR analysis revealed significant up-regulation of Fabp6 and Hnf-4α and down-regulation of Fabp1, Fabp2 and Insig1 transcripts in irradiated intestine. Radiation dose and time kinetics study revealed that the selected 05 genes were altered differentially in response to radiation in intestine.

Conclusion: Finding suggests that lipid metabolism is one of the key targets of radiation and its mediators may act as biomarkers in detection and progression of RIGI.