Pathway simulations in common oncogenic drivers of leukemic and rhabdomyosarcoma cells: a systems biology approach

A part of current research has intensively been focused on the proliferation and metabolic processes governing biological systems. Since the advent of high throughput methodologies such as microarrays, the load of genomic data has increased geometrically and along with that the need for computational methods to interpret these data. In the present study, we investigated in?vitro the common proliferation and metabolic processes, associated with common oncogenic pathways, as far as gene expression is concerned, between the T-cell acute lymphoblastic leukemia (CCRF-CEM) and the rhabdomyosarcoma (TE-671) cell lines. We present a computational approach, using cDNA microarrays, in order to identify commonalities between diverse biological systems. Our analysis predicted that JAK1, STAT1, PIAS2 and CDK4 are the driving forces in the two cell lines. This type of analysis may lead to the understanding of the common mechanisms that transform physiological cells to malignant, and may reveal a new holistic approach to understanding the dynamics of tumor onset as well as the mechanistics behind oncogenic drivers.