Submitted July 5, 2007
Accepted March 23, 2008
Genomic complexity identifies patients with aggressive chronic lymphocytic leukemia
Lisa Kujawski, Peter Ouillette, Harry Erba, Chris Saddler, Andrzej Jakubowiak, Mark Kaminski, Kerby Shedden, and Sami N Malek*
Department of Internal Medicine, Division of Hematology and Oncology, University of Michigan, Ann Arbor, United States
Department of Statistics, University of Michigan, Ann Arbor, United States
* Corresponding author; email: smalek{at}med.umich.edu.
Chronic lymphocytic leukemia (CLL) has a variable clinical course. Presence of specific genomic aberrations has been shown to impact survival outcomes and can help categorize CLL into clinically distinct subtypes.
We studied 178 CLL patients that are enrolled in a prospective study at the University of Michigan, of which 139 and 39 were previously untreated and treated, respectively. We obtained unbiased, high-density, genome-wide measurements of sub-chromosomal copy number changes in highly purified DNA from sorted CD19+ cells and buccal cells using the Affymetrix XbaI 50K SNP-array platform. Genomic complexity scores were derived and correlated with the surrogate clinical endpoints time to first therapy (TTFT) and time to subsequent therapy (TTST): measures of disease aggressiveness and/or therapy efficaciousness.
In univariate analysis, progressively increasing complexity scores in previously untreated CLL patients identified patients with short TTFT at high significance levels. Similarly, TTST was significantly shorter in pre-treated patients with high as opposed to low genomic complexity.
In multivariate analysis, genomic complexity emerged as an independent risk factor for short TTFT and TTST. Finally, algorithmic sub-chromosomal complexity determination was developed, facilitating automation and future routine clinical application of CLL whole-genome analysis.
