Bioinformatics Tool May Aid in Selection of Targeted Therapeutics

Researchers at the University of Colorado Cancer have created a new tool that will help oncologists match the right therapy to cancer type based on the patient's genetic data.

Aik Choon Tan, PhD, investigator at the CU Cancer Center and his team have developed the Integrating Molecular Profiles with Actionable Therapeutics (IMPACT) data tool, linking variants detected from whole-exome sequencing (WES) to cancer therapies.

These findings were recently published in the Journal of the American Medical Informatics Association (JAMIA).

IMPACT works by mining National Cancer Institute's NCI-MATCH clinical trial data through My Cancer Genome and other publicly available data to discover which US Food and Drug Administration (FDA)-approved therapies would best target specific cancer genes. The tool then compares the code of these genes to noncancerous (i.e., normal) gene patterns to determine which normal genes may mutate to become cancerous. IMPACT then counts the number of gene repeats, which when adjusted higher or lower, can drive cancer growth.

Dr. Tan, along with William A. Robinson, MD, PhD, and colleagues, used the tool to retrospectively analyze a series of exome-sequences from existing patients diagnosed with melanoma, to see how successful IMPACT may be in observing a patient’s activating mutation and pair it with useful treatment.

“For example, a patient was found to have a BRAF mutation and was put on a clinical trial of the drug vemurafenib, which targets BRAF alterations,” Dr. Tan said in a news release. The drug controlled the patient’s tumor. However, 2 years later the tumor relapsed. At this point, the group resequenced the tumor and found that in addition to the BRAF mutation, the patient had developed a NRASmutation. The neuroblastoma RAS viral (v-ras) oncogene homolog gene provides instructions for making a protein called N-Ras that is involved primarily in regulating cell division.

Dr. Tan is hopeful they can learn how cancer cells become resistant to treatment by looking at tumor samples over time.

The IMPACT tool may eventually be able to evaluate how cancer evolves and to assist with the selection of personalized therapies for newly diagnosed patients and those experiencing relapse or drug resistance. Further investigation will provide more information about the usefulness of this emerging technology.