Only about one in four people diagnosed with acute myelogenous leukemia (AML) survives five years after the initial diagnosis. To improve this survival rate, researchers at the University of Texas at San Antonio (UTSA) and MD Anderson Cancer Center at the University of Texas have created an online atlas to identify and classify protein signatures present in the diagnosis of AML.
The new protein classifications will help researchers and doctors recommend better treatment and personalized medicine for patients suffering from this aggressive cancer that occurs in the blood and bone marrow. Innovative research was published in the latest issue of Biomedical engineering of nature.
Researcher Amina Qutub, an associate professor in the Department of Biomedical Engineering at UTSA (who joined UTSA in 2018 at Rice University), and oncologist Steven M. Kornblau, a professor and clinician at the Department of Leukemia at the MD Anderson Cancer Center, examined the genetic, epigenetic and environmental diversity that occurs in cancer cells due to AML. Analyzing proteomic screens of 205 biopsies from patients obtained at the MD Anderson Cancer Center, first author Chenyue Wendy Hu (then a graduate student at Qutub Lab, now at Uber Technologies), Kornblau and Qutub developed a new computational method called MetaGalaxy to categorize the signatures of proteins in 154 different patterns based on their cellular functions and pathways.
By addressing this challenge through the unique lens of developing a quantitative map for each leukemia patient from protein expression in blood and bone marrow rather than the standard lens of qualitative metrics and genetic risks alone, Qutub, Kornblau and his research collaborators will be able to more accurately categorize patients into risk groups and better predict treatment outcomes.
To better understand AML's proteomics (protein system) tags and share the results of their work with other researchers, UTSA biomedical engineering professor and his team, including Hu, and students Andrew Ligeralde (now at the University of California, Berkeley)) and Allie Raybon (UTSA's Department of Biomedical Engineering) have built a Web portal known as Atlas of Proteomic Leukemia. Designed by the Qutub and Kornblau teams with information from clinical contributors around the world, the online portal offers oncologists and cancer scientists the tools they need to investigate patterns of AML protein expression from one patient to another. It also provides researchers around the world with clues to new research on leukemia and new computational tools.
As many genetic mutations can not be targeted, the proteomic identification and target identification process used in this study will accelerate the identification of therapeutic targets. It also drives researchers much closer to developing customized patient combination therapies based on their unique signatures of proteins.
"Acute myelogenous leukemia presents itself as a cancer so heterogeneous that it is often described as not one but a collection of diseases," said Qutub. "To decipher the clues found in blood and bone marrow proteins in patients with leukemia, we developed a new computational analysis – MetaGalaxy – that identifies the molecular markers of leukemia, which are analogous to the way constellations guide the navigation of stars. provide a map for protein changes for leukemia. All of the predictions are being tested experimentally through drug testing and can be programmed into cells through the synthetic manipulation of proteins.The next step is to bring this work to the clinic and impact patient care is to test whether these signatures lead to aggressive growth or resistance to chemotherapy seen in patients with leukemia.At the same time, to quickly accelerate leukemia research and advance the search for treatments, we provide the brands in an online compendium where fellow researchers and oncologists around the world can build from the resource, tools and discoveries, LeukemiaAtlas.org ".
Materials provided by University of Texas at San Antonio. Note: Content can be edited by style and size.