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Research Highlight | May 09, 2023

Investigators explore how acute myeloid leukemia (AML) therapies can be tailored to individuals

While there has been an emergence of new acute myeloid leukemia (AML) therapies into the clinic that target different cancer cell vulnerabilities, it is still difficult to predict which therapy would be best suited for each patient.

To address this, a team of researchers at Princess Margaret Cancer Centre, led by senior scientist and TFRI New Frontiers Program Project Grant leader Dr. John Dick, developed an approach that can help predict a cancer’s response to therapy in a biologically intuitive way. Their study, published in Nature Medicine, reveals a potential way to tailor acute myeloid leukemia (AML) therapies to individual patients.

“In our approach, we considered the identity of all the leukemic cells present in a particular patient and asked how each type of leukemia cell compares to a normal blood hierarchy. In this way, we created a description of each patient’s cellular hierarchy,” says Andy Zeng, an MD/PhD candidate in Dr. Dick’s lab and first author of the study. “This personalized description of the leukemic hierarchy, which comprises different cancer cells that are present in different proportions, represents a type of ‘fingerprint’ that we can use to compare to any clinical property including how an individual’s cancer will respond to therapy.”

In the study, the team characterized the personalized cellular hierarchies of more than 1,000 AML patient samples using genomic sequencing data from leukemic cell types that ranged from stem cells to mature cells. Gene expression was used to estimate the abundance of each cell type within a patient’s hierarchy.

They found that these personalized hierarchies could be grouped together, resulting in four main classes, where each class varies in how they respond to experimental drugs. They also identified a panel of seven genes that can be used to classify patient hierarchies and then predict how each particular AML sample will respond to over 100 experimental drugs. 

“These new insights address a long-standing clinical challenge in AML—one that has prevented us from predicting survival outcomes and relapse following chemotherapy. By looking at the cell hierarchies in these cancers, we can now identify which drugs can best target them. These insights are now enabling us to explore how therapies can be tailored to individuals, so that the right patient gets the right treatment when they need it the most. We think this approach we developed for AML might be applicable to many other types of cancer” says Dr. Dick.

The work was supported by TFRI and other funders.

Adapted from a UHN press release.