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Monday, April 22, 2019

Researchers Develop Protein Atlas to Accelerate AML Personalized Medicine

Only about one in four people diagnosed with acute myelogenous leukemia (AML) survive 5 years after the initial diagnosis. To improve that survival rate, researchers at The University of Texas at San Antonio (UTSA) and the University of Texas MD Anderson Cancer Center created an online atlas to identify and classify protein signatures present at AML diagnosis.

The new protein classifications will help researchers and clinicians recommend better treatment and personalized medicine for patients suffering from this aggressive cancer (Nat Biomed Eng 2019; doi:10.1038/s41551-019-0387-2).

Researcher Amina Qutub, PhD, Associate Professor in the UTSA Department of Biomedical Engineering (who joined UTSA in 2018 from Rice University), and Steven M. Kornblau, MD, Professor and practicing clinician in the Department of Leukemia at MD Anderson Cancer Center, examined the genetic, epigenetic, and environmental diversity that occurs in cancerous cells due to AML. Analyzing proteomic screens of 205 patient biopsies obtained at MD Anderson Cancer Center, the researchers developed a new computational method called MetaGalaxy to categorize the protein signatures into 154 different patterns based on their cellular functions and pathways.

By approaching this challenge through the unique lens of developing a quantitative map for each leukemia patient from protein expression in their blood and bone marrow, rather than the standard lens of qualitative metrics and genetic risks alone, the research collaborators will be able to more precisely categorize patients into risk groups and better predict their treatment outcomes.

To better understand the AML hallmarks at the proteomic level and to share the results of their work with other researchers, the Qutub and her team built a web portal known as the Leukemia Proteome Atlas. Designed with input from clinical collaborators worldwide, the online portal gives oncologists and cancer scientists the tools they need to investigate AML protein expression patterns from one patient to the next. It also provides investigators around the world with leads for new leukemia research and new computational tools.

Since many genetic mutations cannot be targeted, the proteomic profiling and target identification process used in this research study will accelerate the identification of therapeutic targets. It also propels researchers much closer to the development of personalized combination therapies for patients based on their unique protein signatures.

"Acute myelogenous leukemia presents as a cancer so heterogeneous that it is often described as not one, but a collection of diseases," noted Qutub. "To decipher the clues found in proteins from blood and bone marrow of leukemia patients, we developed a new computer analysis—MetaGalaxy—that identifies molecular hallmarks of leukemia. These hallmarks are analogous to the way constellations guide navigation of the stars: they provide a map to protein changes for leukemia. Our 'hallmark' predictions are being experimentally tested through drug screens and can be 'programmed' into cells through synthetic manipulation of proteins.

"A next step to bring this work to the clinic and impact patient care is testing whether these signatures lead to the aggressive growth or resistance to chemotherapy observed in leukemia patients. At the same time, to rapidly accelerate research in leukemia and advance the hunt for treatments, we provide the hallmarks in an online compendium where fellow researchers and oncologists worldwide can build from the resource, tools and findings, LeukemiaAtlas.org."