Exploring the Human Genome in Cancer with Genomic Approaches

Abstract

CANCER is the second leading cause of death in the United States, and despite the overall decreasing trend in cancer mortality during the past 10 years, it is expected to become the leading cause of death in the next decade. The decrease in cancer mortality has been largely attributed to prevention through the identification of environmental and genetic risk factors, early detection through populationbased screening programs, and advances in treatment (1,2). However, as environmental factors are identified and public exposure reduced, the identification of high-risk genes that result in susceptibility to cancer development has primarily been limited to forward genetics, wherein the functions of single genes are typically studied by creating a mutation or deletion in a rodent model. Although most of what is known about the pathophysiology of cancer was learned through this approach, forward genetics is too time consuming and cost inefficient to be applied to every gene responsible for the characteristics of a single cancer, and it is unknown whether the results would be applicable to human cancer. Recently, DNA microarrays have been used to profile and compare the global gene expression patterns of different cancers in human patients. Surprisingly, despite the diversification of gene expression that accompanies unregulated cell division, many similar changes were detected across the same types of cancer. This report focuses on the advances that have been made in our understanding of cancer biology with the use of functional genomics and how this knowledge translates into determining the diagnosis, prognosis, and treatment of different types of cancers. Additionally, specific areas are identified in which knowledge is deficient and further research is needed. Finally, we briefly discuss how the science of cancer genomics, also known as oncogenomics, could potentially impact the practice of interventional radiology. Although individually tailored medicine is currently economically infeasible and time inefficient, oncogenomics could allow individual patients with cancer to be categorized into molecular subgroups to optimize their treatment and improve overall patient care.