Chronic lymphocytic leukemia (CLL) is the most common leukemia in the Western Hemisphere. Although it has been viewed as an indolent disease of older adults, its clinical course is heterogeneous and difficult to predict. The median survival is 9 years, but may be as short as 1 to 2 years. Traditional prognostic factors are insufficient to account for its clinical heterogeneity. Recent studies have identified promising new prognostic markers. Cytogenetic studies using FISH have shown that most cases contain non-random abnormalities. Sequence analysis has shown that patients whose CLL cells contain somatic mutations in their Ig variable region genes survive longer than patients whose cells lack mutations. Gene expression profiling microarray studies have identified genes that are differentially expressed in CLL subtypes, and may have prognostic significance. We hypothesize that a clinically useful assay to determine the prognosis of CLL patients can best be constructed by combining molecular signatures derived from RNA (gene expression profiling) and DNA (molecular cytogenetics). Because gene expression microarrays have limited dynamic range and are unlikely to be usable in a routine clinical setting, we propose using semi- quantitative real-time PCR on microfluidics cards (MF-QRT-PCR) to develop a clinical assay for RNA biomarker signatures. Because FISH is labor-intensive and can only be used to study a limited number of cytogenetic abnormalities, we propose using single nucleotide polymorphism (SNP) DNA mapping arrays to perform chromosome copy number analysis to develop a clinical assay for DNA biomarker signatures. Thus, we propose a study with the following Specific Aims: (1) To validate candidate biomarkers of prognosis, previously identified by gene expression profiling, in untreated CLL patients using MF-QRT-PCR, to determine how well they correlate with clinical prognostic indicators at presentation, and to combine them into an RNA-based multivariate (MV) model of prognosis; (2) To validate prospectively the RNA-based model of prognosis on an independent test set; (3) To collect DNA copy-number profiles of untreated patients using SNP DNA mapping arrays in order to confirm previously identified markers, to determine how well they correlate with clinical prognostic indicators at the time of presentation, and to combine them into a DNA-based MV model of prognosis; (4) To validate prospectively the DNA-based model of prognosis on an independent test set; (5) To determine whether a model that combines RNA and DNA markers produces a better predictor of prognosis than either model alone. Relevance: CLL is the most common leukemia in the U.S. Its clinical course is difficult to predict. Some patients live for many years without treatment; others succumb quickly. We are attempting to devise a new clinical test, based on new discoveries in molecular medicine, to help doctors identify patients who may need aggressive therapy early in their disease course. ? ? ?
