Will rapid genomic prediction lead to better treatments for cancer?

Columbia University Medical Center researchers have created a computational tool that accurately and rapidly predicts the genes involved in an individual’s cancer to identify the best treatments.

The new tool is called integrated CAncer GEnome Score (iCAGES), and it identifies personal cancer “drivers” 77 percent of the time—drivers are mutations within a gene that promote cancer development. Other computational tools have a success rate of about 51 percent. 

In just 30 minutes, iCAGES can identify FDA-approved or experimental drugs likely to target that individual’s genetic causes of cancer. In a retrospective test involving a patient with lung cancer, iCAGES selected the top drug candidate out of 122 possible treatments, arriving at the same conclusion the patient’s oncologists reached through a much lengthier process.

Among the most comprehensive tools of its kind, iCAGES is also the first to incorporate a user-friendly web interface that requires little knowledge of bioinformatics, making it accessible to clinicians. Learn More

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