Tool matches cancer genetics to approved treatments

The system, known as IMPACT, is able to take whole exome sequence data from tumors, and use it to identify treatments that are most likely to successfully tackle the disease

When treating cancer, it's difficult to know whether a chosen treatment is proving effective. While new breakthroughs may give doctors faster indications of whether drugs are working, by the time a new treatment is attempted, it might be too late to achieve a positive outcome. A new tool, developed by researchers at the University of Colorado, could have a big impact on which treatment doctors decide to use, using data from whole exome sequencing to pick out drugs likely to prove effective at tackling tumors on a case-by-case basis.

The tool, known as Integrating Molecular Profiles with Actionable Therapeutics (IMPACT), is designed to take data from whole exome sequencing of tumors, then mapping it onto the human genome to create segments that correspond to each of the body's roughly 20,000 genes. It then looks at those results against normal gene patterns, identifying variations that might play a factor in cancer occurrence.

With that list of candidate genes, IMPACT then uses publicly-available data to determine which already FDA-approved drugs target those specific genes, and might therefore be effective therapies for tackling the specific cancer occurrence.

To test whether the tool works as intended, the researchers took whole exome sequencing data from The Cancer Genome Atlas for patients with EGFR-mutated non-small cell lung cancer. The tool took the data, and was able to successfully identify the gene EGFR as a major factor in the cancer, recommending that approved EGFR inhibitors be used as a treatment.

The tool was also used to analyze exome sequences from melanoma patients, successfully identifying the responsible gene, and once again recommending an approved drug that targets it. Furthermore, when one patient's tumor relapsed two years later, resequencing it revealed a new mutation, leading to the administering of a combination of drugs to tackle both genetic issues.

The treatment controlled the tumor for a further two years, at which point it relapsed once more. The third analysis revealed a loss of the gene CDKN2a, which is a known tumor suppressor. No drug is currently FDA-approved to tackle the problem in melanoma patients, but a medication called palbocicilib was recently approved for breast cancer treatment. The researchers believe that that drug, in combination with the existing treatments, could suppress the tumor once more.

Such personalized treatment plans wouldn't be possible without tools such as IMPACT. Overall, the researchers believe that it could be an important step towards a more personal approach to cancer treatment.

"We hope that IMPACT proves to be an important tool in empowering the shift towards precision medicine," said senior paper author Aik Choon Tan, PhD.

The findings of the work were published in the Journal of American Medical Informatics Association.

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