Developing Pathway Collection for Personalized Anti-cancer Therapy

We describe methodology for developing personalized anti-cancer
drug therapy using pathway analysis. We successfully applied this
methodology to treat several cancer patients that were terminally
diagnosed by standard of care criteria at the hospital. Our
approach consists of profiling patient tumor using gene expression
microarray and calculating pathways responsible for the differential
expression between tumor and normal control tissue. Pathways
are selected for treatment targeting based on their enrichment with
major expression regulators identified by sub-network enrichment
analysis (SNEA) in Pathway Studio. We then select FDA approved
drugs inhibiting activated pathways and prescribe them to the
patient. To facilitate interpretation of patient data we built collection
of cancer pathways based on ten cancer hallmarks described in
the literature. This collection explains function of more than half of
expression regulators identified in patient’s tumors by SNEA. This
paper focuses on description of pathways built for interpretation of
expression profiles of cancer patients.