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Genomic-based identification of novel potential biomarkers and molecular signaling networks in response to diesel exhaust particles in human middle ear epithelial cells

Authors
Kwon, Jee YoungPark, Moo KyunSeo, Young RokSong, Jae-Jun
Issue Date
31-3월-2014
Publisher
KOREAN SOCIETY TOXICOGENOMICS & TOXICOPROTEOMICS-KSTT
Keywords
Diesel exhaust particles; Gene expression profile; Human middle ear epithelial cells; Molecular signaling network
Citation
MOLECULAR & CELLULAR TOXICOLOGY, v.10, no.1, pp.95 - 105
Indexed
SCIE
SCOPUS
KCI
Journal Title
MOLECULAR & CELLULAR TOXICOLOGY
Volume
10
Number
1
Start Page
95
End Page
105
URI
https://scholar.korea.ac.kr/handle/2021.sw.korea/98971
DOI
10.1007/s13273-014-0012-0
ISSN
1738-642X
Abstract
Otitis media (OM) is the most common inflammatory disease of the middle ear cavity. Several factors including viral and bacterial infection, biofilm formation, congenital anomalies, and environmental factors have been recognized as the main causes of OM. Recent epidemiological studies showed that children living in areas with high concentrations of air pollutant including particulate matter and SO2 have significantly higher rates of OM compared with those in the control area. Another study reported that air pollutant exposure results in significant increases in pediatric OM. A large cohort study in Germany suggested that the prevalence of OM is related to air quality. Diesel exhaust particles (DEPs) are among the major toxic air pollutants of motor vehicle emissions. Hence, identifying the biomarkers of a signaling network for air pollutant (particularly DEPs)-mediated inflammatory responses would be meaningful. In this study, we identified novel biomarkers and potential molecular signaling networks induced by DEPs in human middle ear epithelial cells (HMEECs). Genomic expression analysis via microarray was used to discover novel biomarkers. A total of 254 genes were differentially expressed in DEPs-exposed HMEECs; 86 genes and 168 genes were up-and down-regulated, respectively. To verify reliable biomarkers and define meaningful signaling networks in the entire genome profiling, the in silico approach was applied. Based on genomic profiling analysis, we found several novel key molecular biomarkers, including SRC, MUC5AC, MUC2, MMP14, EIF1AK3, KITLG, NOD1, and TP53. Our findings suggested novel biomarkers for DEPs-responsive genes in HMEECs. Furthermore, we provided scientific evidence for the establishment of novel molecular signaling pathway associated with DEPs exposure in HMEECs.
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