Scientists discover a new way to predict healthy people at risk of developing AML



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July 10, 2018

An international team of leukemia researchers has discovered how to predict healthy individuals at risk of developing acute myeloid leukemia (AML), an aggressive and often fatal blood cancer.

The findings, published today in Nature, illuminate the "black box of leukemia" and answer the question of where, when and how the disease begins, says Dr. John Dick, Senior Researcher at the Princess Margaret Cancer Center at the University "We have been able to identify people from the general population who have traces of mutations in the blood that represent the first steps in the way that normal blood cells start to become more and more abnormal and expose them to the risk of We can trace these traces up to 10 years before the AML actually develops, "says Dr. Dick. "This window of time gives us the first opportunity to think about how to prevent AML."

Dr. Dick is also a Professor in the Department of Molecular Genetics at the University of Toronto, Canada Research Chair in Stem Cell Biology and co-director of the Translational Research Initiative on Acute Leukemia. 39, Ontario Institute for Cancer Research

. Dr. Sagi Abelson, a postdoctoral fellow at the Dick Lab, says, "AML is a devastating disease diagnosed too late, with a 90% mortality rate after the age of 65. Our results show that it is possible to identify individuals with the ultimate goal is to identify these individuals and to study how we can target mutated blood cells well before the start of the disease. "

The study builds on Dr. Dick's discovery in 2014 that a pre-leukemic stem cell could be found among all the leukemic cells present in the blood sample taken during the first diagnosis of LMA, the eukemic stem cell is still functioning normally but it has taken the first step in generating a cell pathway that has become increasingly abnormal causing AML ( Nature, 12 February 2014), and continues its quest to follow each step "Our 2014 study predicted that people with early mutations in their blood stem cells, long before the disease appears and makes them sick, should be able to be detected in cells blood strains, the general population by testing a blood sample for the presence of the mutation, "says Dr. Dick.

Co-Principal Investigator Dr. Liran Shlush, Former Member Dick's lab, and now Senior Scientist at the Israel Weizmann Institute led the approach of using data from a large European study on the health and lifestyle of the population that has followed 550,000 people over 20 years to determine correlations to cancer.

The leukemia team extracted data from more than 100 participants who developed the LMA six to ten years after joining the study, plus data from a cohort of overweight patients. equal age of more than 400 who have not developed the disease.

Dr. Dick says, "We wanted to know if there was a difference between these two groups in the genetics of their" normal "blood samples taken during rooting. To find out, we developed a sequencing tool for genes that captures the most common genes in AML and sequenced all 500 blood samples. "

The answer was" yes. "The seeds of the blood system began to spot mutations years before a diagnosis of AML was made, which allowed the team to predict with In addition, the team used advanced computation technology to obtain information obtained from blood tests routinely collected for more than 15 years in Israel and housed in a database. mbadive data from 3.4 million electronic health records

The study deepened our understanding of the distinction between AML and a common feature of aging called ARCH-l clonal hematopoiesis related to the disease. age – by which blood stem cells acquire mutations and become a little more proliferative.For the vast majority of people, it is simply a completely benign characteristic of aging. [19659003] "Every AML patient has an ARCH, but everyone with ARCH does not have AML," says Dr. Dick

. /www.uhn.ca/corporate/News/PressReleases/Pages/Leukemia_researchers_discover_genetic_screening_tool_to_predict_healthy_people_at_risk_for_developing_AML.aspx

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