Scientists at Washington University School of Medicine in St. Louis are using powerful DNA sequencing technology both to identify mutations at the root of a patient’s tumor — considered key to personalizing cancer treatment — and to map the genetic evolution of disease and monitor response to treatment. The work is helping to guide the design of future cancer clinical trials in which treatment decisions are based on results of sequencing.
Already, information gleaned through whole-genome sequencing is pushing researchers to reclassify tumors based on their genetic makeup rather than their location in the body. Using “deep digital sequencing” these WashU scientists sequenced individual mutations in patients’ tumor samples more than 1,000 times each. This provides a read-out of the frequency of each mutation in a patient’s tumor genome and allowed the researchers to map the genetic evolution of cancer cells as the disease progressed.
They found that as cancer evolves, tumors acquire new mutations but always retain the original cluster of mutations that made the cells cancerous in the first place. Their discovery suggests that drugs targeted to cancer may be more effective if they are directed toward genetic changes that occur early in the course of cancer. Drugs that target mutations found exclusively in later-evolving cancer cells likely may not have much effect on the disease because they would not kill all the tumor cells.
In addition, the researchers have identified a series of mutations in the breast tumors that have corresponding small-molecule inhibitor drugs that target defective proteins. This finding indicates that for women who are not responding to aromatase inhibitors, treatment options may include combining conventional chemotherapy with the indicated small-molecule inhibitor.
The researchers felt it was important to show there could be therapeutic options available to patients who are resistant to aromatase inhibitors,” Mardis says. In the future, they think sequencing will contribute crucial information to determining the best treatment options for patients.”