A large genomic sequencing analysis of patients with T-ALL revealed a new landscape of mutations that may inform future treatment strategies.
It may soon be possible to engineer better mouse models to probe leukemia's aberrant biologic machinery thanks to an unprecedented genomic sequencing analysis of hundreds of patients with T-lineage acute lymphoblastic leukemia (T-ALL). The results of the analysis, which have been published in Nature Genetics, provide a detailed genomic landscape that will inform treatment strategies and aid efforts to develop drugs to target newly discovered mutations.
"We found a range of new mutations in genes not known to be drivers in T-ALL, as well as associations between genes and different subtypes of T-ALL, suggesting that co-mutation drives the disease,” said investigator Charles Mullighan, MD, from St. Jude Children's Research Hospital in Memphis, Tennessee. “Broadly, these results have important implications both for how we understand the disease develops as well as new approaches for therapy."
Dr. Mullighan said leukemias typically arise from multiple genetic changes that work together. Previous studies overall did not have the breadth of genomic data in enough patients to identify the constellations of mutations and their associations, he noted. The research also offers a broader lesson for genomic studies of cancers.
T-ALL is a form of leukemia in which the immune system's T cells acquire multiple mutations that freeze the cells in an immature stage, causing them to accumulate in the body. The researchers sequenced the genomes of 264 children and young adults with T-ALL. The analyses identified 106 driver genes and half of those mutated genes had not been previously identified in childhood T-ALL.
The study enabled the researchers to compare the frequencies of mutations among patients whose cancerous cells were sequenced at the same detailed level, explained Dr. Mullighan. In addition, all the patients had uniform treatment, allowing the researchers to draw meaningful associations between the genetics of their cancer and the response to different treatments.
The new genomic analysis confirmed that T-ALL was driven by mutations in known signaling pathways, including JAK-STAT, Ras, and PTEN-PI3K. However, the new analysis identified many more genetic mutations in those known pathways. The findings open the door to more targets for drugs to shut down the aberrant cells. Dr. Mullighan said this is good news because it suggests the number of the patients who are potentially amenable to targeted approaches may be much higher than previously suspected.
The multitude of new mutations uncovered in the current study can enable researchers to use genetic engineering to create mouse models that more accurately reflect human cancer, according to the researchers. Such models are invaluable for understanding the biologic machinery of T-ALL as well as for testing new drug strategies.
"For the clinician, a key message is that many patients have mutations in at least one pathway that is amenable to targeting with new agents, for example, agents that inhibit kinase signaling pathway," Dr. Mullighan told OncoTherapy Network.