Systems biology approaches to pancreatic cancer detection, prevention and treatment

Abstract

Pancreatic cancer [PC] is a complex disease harboring multiple genetic alterations. It is now well known that deregulation in the expression and function of oncogenes and tumor suppressor genes contributes to the development and progression of PC. The last 40 years have not seen any major improvements in the dismal overall cure rate for PC where drug resistance is an emerging and recurring obstacle for successful treatment of PC. Additionally, the lack of molecular biomarkers for patient selection limits drug availabilities for tailored therapy for patients diagnosed with PC. The very high failure rate of new drugs in Phase III clinical trials in PC calls for a more robust pre-clinical and clinical testing of new compounds. In order to rationally choose combinations of targeted agents that may improve therapeutic outcome by overcoming drug resistance, one needs to apply newer research tools such as systems and network biology. These newer tools are expected to assist in the design of effective drug combinations for the treatment of PC and are expected to become an important part in any future clinical trials. In this review we will provide background information on the current state of PC research, the reasons for drug failure and how to overcome these issues using systems sciences. We conclude this review with an example on how systems and network methodologies can help in the design efficacious drug combinations for this deadly and by far incurable disease.