Using structural controllability in detecting effective immune system
elements against cancer cells
Abstract
Motivation: Cancer, a leading cause of death worldwide, is
intertwined with immune system. Changing the state of immune system, as
a complex network of cells and molecules interacting in a hierarchical
mode, holds considerable fascination to fight cancer. This alteration
can involve debilitating pro-tumorigenic and reinvigorating
anti-tumorigenic functions by the help of driver vertices. The
utilization of network controllability and control centrality-based
analysis will aid in the identification of driver vertices to control
target proteins that play significant roles in the anti-tumorigenic and
pro-tumorigenic functions of immune cells. In this study, a weighted
generalization of the control centrality was constructed, in which the
control power of each vertex in the network is obtained based on the
importance of a set of under control vertices. Results:
Screening all homo sapiens-related pathways in KEGG database, we find
that “Immune and cancer pathways” subnetwork showed the greatest
number of edges and nodes in relation to positive and negative target
proteins. The first five driver vertices obtained for positive targets
are ICAM2, TLR2, MAP2K4, ELK1, SIRT1 and for negative targets are ELK4,
RBX1, NFATC1, NFATC2, NFATC3. Our results suggest that exposing the
external signal to reinvigorate driver vertices of positive targets and
debilitate driver vertices of negative target will result in changing
the immune system state to fight cancer.