BioSysBio:abstracts/2007/Abhijit Banerjee

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Gene Network Analysis in Oral Premalignancy

'Author(s): Abhijit G. Banerjee'
Affiliations: University of Manitoba
Keywords: 'dysplasia' 'oncogenomics' 'network' 'gene regulation'


Transcriptional profiling using oligonucleotide arrays and biological pathway network analysis is a first step towards understanding systems level biology in a physiological system or disease states. We performed U133A gene chip microarray studies on oral premalignant tissues and reported differential gene expression profiles with validation of few candidate genes recently (Banerjee AG et al., 2005). This data forms the basis of further analysis of gene networks to understand the complex biology responsible for malignant progression of oral epithelial cells. Different approaches and resultant network crosstalk is discussed.


Crosstalk between several biological networks resulting in a signaling cascade relates to transcriptional regulation in oral cancer progression

Objectives & Methods

To identify and delineate themes underlying the transcriptomics data that would help understand systems level biology in oral cancer development using computational tools and pathway analysis software's such as Ingenuity (3), PANTHER(4) and EASE (5). Affymetrix DMT probe lists as raw datasets of fold change in expression along with significance analysis values were used as input files in the abovementioned software based data mining projects


Six networks comprising of 113 cancer related genes were identified in the premalignant oral tissues. Highly significant top functions included tissue dedifferentiation, cell morphology, cell proliferation, cell cycle, cell motility and invasion, antigen presentation and immune response, angiogenesis and tumor morphology. Several signaling cascades pointed towards genetic reprogramming events that facilitates tumor progression. Control of inflammatory processes as a central theme emerged at all levels. Bioenhanced flavonoids based prevention strategies may be an important approach at population level.


1.Banerjee AG et al, 2005: Mol. Cancer Ther. :4(6):865-875. 2.Chung CH et al, 2005: Head & Neck: 28: 360–368. 3.Ingenuity pathways knowledge database ( 4.Thomas PD et al., 2003: Genome Res., 13: 2129-2141. 5.Hosack DA et al., 2003: Genome Biology, 4:R70.