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.