Acute Myeloid Leukemia Data Set Now Includes Pediatric, Adolescent, and Young Adult Data
A 2018 report by Dr. Jeffrey Tyner and colleagues, titled “Functional Genomic Landscape of Acute Myeloid Leukemia,” published in Nature, described the availability of the “largest functional genomic data set of primary tumor biopsies to date.”
That study featured 672 primary specimens from 562 Acute Myeloid Leukemia (AML) patients, including extensive clinical information, genomic and transcriptomic analyses, and drug sensitivity study findings. The data set was particularly unique in that it integrates multi-omic information from tumor samples with functional analyses on how cells respond to drugs.
This week, researchers from Oregon Health & Science University’s (OHSU’s) Knight Cancer Institute shared new data that significantly expands the original data set. Data sharing was supported by NCI’s Childhood Cancer Data Initiative (CCDI).
The new data set includes pediatric and adolescent and young adult (AYA) leukemia samples from OHSU’s Knight Cancer Institute that were not included in the original BeatAML cohort study by Tyner and colleagues. This data set includes genomic, clinical, and drug response data, offering important functional context for developing therapies.
According to Dr. Shannon McWeeney, an investigator in the OHSU study, “The multi-omic nature of this data set is particularly important for informing precision medicine, as the different data dimensions can be integrated in unique ways to help us optimize the tailoring of therapeutic strategies for the patients who are most likely to have a beneficial response.”
Dr. Subhashini Jagu, a CBIIT Health Science Administrator and CCDI Data Platform Working Group member, noted that “Data sets with detailed molecular characterizations and ex vivo drug screening, such as the OHSU cohort, are vital for understanding the underlying mechanisms of disease and to find new ways to disrupt those mechanisms to more effectively treat cancers such as AML.”
Dr. Jagu added, “Because childhood cancers are a very diverse group of malignancies, there’s a great need for pediatric data if we’re to make an impact on treating disease in pediatric patients.”
For more information on the data from the original study, see the blog, “Beat AML 1.0: A Functional Genomic Data Integration,” by Dr. Tyner.