Genetic Signatures Define Leukemia Risk Categories

Investigators at St. Jude Children's Research Hospital (Memphis, TN, USA) analyzed 130 pediatric and 20 adult AML diagnostic bone marrow or peripheral blood samples using a microarray in order to identify unique genetic signatures for each risk category.

They reported in the June 29, 2004, online edition of Blood that analysis of the genetic signatures by supervised learning algorithms gave overall classification accuracy of greater than 93%. The expression signatures generated from the pediatric samples accurately classified adult de novo AMLs with the same genetic lesions. Furthermore, using a combined pediatric dataset of 130 AMLs and 137 acute lymphoblastic leukemias, the investigators identified an expression signature for cases with chimeric fusion genes irrespective of the type of white blood cell from which the leukemia arose.

Senior author Dr. James Downing, chairman of the department of pathology at St. Jude Children's Research Hospital, said, "The gene expression signatures will also give us insights into the causes of each subtype of AML, which is an important step toward developing new and more effective treatments. Our ability to make such fine distinctions among the various subtypes of AML based on gene expression signatures is much like developing a dictionary. In this case, one gene expression signature defines a person as having a specific subtype of AML, while a person with another signature has a different type of AML. This study will also contribute to our understanding of the various underlying causes of AML. In other words, it will help take a lot of the educated guesswork out of managing AML.”




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