Therapy-related acute myeloid leukemia (t-AML) is a rare but devastating complication of priorchemotherapy. That only a subset of patients treated for cancer develops t-AML suggests that theseindividuals may be genetically predisposed to t-AML. Alkylator-induced t-AML accounts for approximately75% of all cases of t-AML, and is characterized by antecedent myelodysplasia and the characteristicrecurrent loss of the long arm or chromosome 5 and/or chromosome 7. The long-term objective of thisproject is to identify genetic susceptibilities to t-AML that can be clinically translated into biomarkers for risk,or that can be used to guide therapy at the time of initial cancer diagnosis to minimize the subsequent riskof alkylator-induced t-AML. In particular, we hypothesize that genetic variation that alters the function ofcore stress response pathways may thereby alter cancer susceptibility. Indeed, several studies haveidentified genetic variants that are associated with t-AML; these studies, however, were uniformly small,reliant upon pre-existing knowledge, and limited to testing only a few plausible candidate genes. In a pilotstudy, we demonstrated that a genome-wide association study (GWAS) is a feasible strategy to identifygenetic risk factors for t-AML, and we identified both single nucleotide polymorphisms (SNPs) and copynumber variants associated with t-AML susceptibility. Here, we propose to build upon these results byundertaking a very high density GWAS to identify the complement of inherited genetic variation associatedwith t-AML using the Affymetrix Genome-Wide Human SNP Array 6.0. For these studies, we haveamassed an unprecedented cohort of about 300 well-characterized samples from patients with t-AML,including the University of Chicago series of t-AML patients maintained in Core A of this program project.The objectives of this project will be pursued through four specific aims.
In Aim 1, we will undertake aGWAS to identify polymorphic and copy number variation associated with t-AML as compared to bothcancer-free healthy control and individuals matched to cases for primary cancer, but who do not have t-AML.
In Aim 2, we will undertake a novel bioinformatic analysis of these data to identify the most likelygenes and pathways implicated in the pathogenesis of t-AML.
In Aim 3, we will undertake a series offunctional studies to clarify the role of the associated polymorphisms identified in Aims 1 and 2 on theetiology of t-AML.
In Aim 4, we will determine whether genetic variants found to be associated with t-AMLare also associated with de novo AML. Project 2 of this application is the genome-wide analysis of copynumber changes (somatically acquired mutations in t-AML). Together, these two projects provide anunmatched opportunity to study the genetics of t-AML. Because t-AML is a unique model for the geneenvironmentinteractions that may drive virtually all cancer, these studies may shed significant light on thegenetic contribution not only towards t-AML, but to a variety of common human cancers as well.
Showing the most recent 10 out of 221 publications
