"Cancer is a complex and heterogeneous disease driven by gene mutations. As we enter the era of personalized medicine, the characterization of the cancer genome has begun and will continue to influence diagnostic and therapeutic decisions in the clinic."
So begins Timothy Heffernan, Ph.D., associate director of target discovery at the Institute for Applied Cancer Science (IACS), in an article discussing how cancer genome discoveries have led to recent successes in oncology drug development through the identification of genetic alterations known as driver mutations.
"The translation of genomic data into drug development endpoints requires coordinated integration across multiple scientific disciplines. Genomic technologies provide comprehensive lists of genes that are altered in human cancer. Sophisticated computational models and powerful data analytics prioritize genes with the strongest weight of genomic evidence," he notes.
"Subsequent functional studies in relevant disease models provide biological significance by identifying genes that confer a proliferative and/or survival advantage to cancer cells. Lastly, deep biological exploration is required to provide a mechanistic understanding of the gene's cancer-relevant activity," Heffernan writes.
Systematic approaches to apply genomic data
Heffernan's article in the current issue of the Insights and Developments newsletter discusses the systematic approaches implemented at IACS to functionalize genomic data and identify novel therapeutic targets.