As cancer cell analysis became more detailed and comprehensive, researchers learned just how many mutations and other genetic disruptions many cancer cells have. The promise of precision therapy is to target specific cancer-causing mechanisms, but it is often difficult to determine them amongst many co-occurring mutations. Before better therapies are feasible, therefore, it’s vital to identify exactly which mutations drive cancer initiation and, in cases of recurrence, which provided therapy resistance.
In a paper in Science Translational Medicine, researchers led by Fumihiko Ishiskawa, M.D., Ph.D., of the Riken Center for Integrative Medical Sciences (Japan) and including JAX Professor present how they used two powerful new research methods, and (PDX), to investigate the mutational landscape of acute myeloid leukemia (AML). They obtained samples from 27 human patients for the study, and leveraged mice developed to host patient cells (the xenografts in PDX) and assess their ability to initiate cancer in vivo. They were able to determine the differences between different cells, even within the same patient samples, using single cell sequencing protocols.
A hallmark of the AML in these patients was the presence of a mutation known as FLT3-ITD in addition to mutations in other genes associated with AML. The research team determined that, in the absence of FLT3-ITD, the other mutations did not drive cancer initiation. In addition, using an inhibitor of the FLT3 pathway they had previously identified (RK-20449), they were able to significantly reduce cancer initiation in the mice. In the cases that either had or gained resistance to the inhibitor therapy, they observed increased expression of genes that promote cell survival. The team therefore hypothesized that a combined therapy of ABT-199, a compound that blocks anti-cell death signaling, plus RK20449 would be more effective still. Indeed, the combination therapy completely eliminated AML cells in vivo in nine out of 12 previously resistant samples.
The authors conclude, “By functionally connecting genomic information with in vivo fate and behavior of patient-derived cells at the level of single cells through a PDX model, we could identify therapeutic targets with improved precision to promote more effective drug discovery in genetically complex human malignancies.”