Study Finds Protein Markers May Better Predict Drug Response in Patients With AML Than Genetic Mutations

A mutation on the gene FLT3 may not be a good predictor of the patients with leukemia who could benefit from midostaurin, according to a new study published in Leukemia. Midostaurin has been approved by the FDA only for patients who have a mutation on the FLT3 gene.

The study’s findings offer new insights into why some patients respond better to new cancer drugs and why other patients are resistant. Traditionally, genetic alterations, which cause errors in the DNA code and allow cancer cells to rapidly divide, grow, and spread, have been used to predict drug response.

The study was funded by Barts Charity, Cancer Research UK, and the Biotechnology and the Biological Sciences Research Council.

Researchers at Queen Mary University of London, United Kingdom, analyzed cell samples from 36 patients with acute myeloid leukemia (AML) and determined that protein markers are a more accurate predictor of which patients would respond to midostaurin. This led the researchers to believe that some patients with AML are missing out on new treatments.

“Currently about 30% of AML patients are eligible for midostaurin, and about 50% of those benefit,” lead author Pedro Cutillas, PhD, said in a statement. “With our markers, we expect the number of patients treated would double.”

The finding that protein markers are a better predictor than genetic mutations could have implications for the development of personalized therapies beyond AML for other cancer types, he added.

“This study opens new opportunities in the field of personalized medicine,” Cutillas said. “We expect that this work will eventually lead to treatments tailored to the patient’s tumor, so that less time and money is wasted with treatments that are not expected to work, saving funding for the [National Health Service] and benefiting patients with better treatments.”

Reference

Cascado P, Wilkes EH, Miraki-Moud F, et al. Proteomic and genomic integration identifies kinase and differentiation determinants of kinase inhibitor sensitivity in leukemia cells. Leukemia. Accepted article preview 12 December 2017; doi: 10.1038/leu.2017.349