Systems biology is relatively a new field of study in cancer research.
However, this approach has gained much attention as it can be used to understand the
molecular level of a system under diseased or healthy condition and under dynamic or
static condition. The approach allows understanding the interaction of DNA, RNA,
protein and metabolite levels of a cell. Since, the cancer micro-environment consists of
highly heterogeneous population of cells, systems biology is the robust tool that can be
applied to understand this complex environment in the presence of perturbed condition
using small molecules or targeted drugs like immunotherapy. Systems biology is
already applied by drug design and discovery companies as well as by drug regulatory
agencies to monitor safety and toxicity of the drug. The high throughput (HT)
technological platforms generate un-biased datasets. However, data–mining is a
problem for this approach. Despite this drawback, systems biology has been used in
cancer immunotherapy to some extent. In this chapter, we discuss the known
application of systems biology in cancer immunotherapy in particular to its application
in biomarker identification, vaccine development, application in combination therapy,
use in the development of validation models and future application in personalized
medicine.
Keywords: Biomarkers, Drug discovery, Omics platforms, Personalized
medicine, Systems biology.
