Genomic variation by whole-genome SNP mapping arrays predicts time-to-event outcome in patients with chronic lymphocytic leukemia: a comparison of CLL and HapMap genotypes.

Genomic abnormalities, such as deletions in 11q22 or 17p13, are associated with poorer prognosis in patients with chronic lymphocytic leukemia (CLL). We hypothesized that unknown regions of copy number variation (CNV) affect clinical outcome and can be detected by array-based single-nucleotide polymorphism (SNP) genotyping. We compared SNP genotypes from 168 untreated patients with CLL with genotypes from 73 white HapMap controls. We identified 322 regions of recurrent CNV, 82 of which occurred significantly more often in CLL than in HapMap (CLL-specific CNV), including regions typically aberrant in CLL: deletions in 6q21, 11q22, 13q14, and 17p13 and trisomy 12. In univariate analyses, 35 of total and 11 of CLL-specific CNVs were associated with unfavorable time-to-event outcomes, including gains or losses in chromosomes 2p, 4p, 4q, 6p, 6q, 7q, 11p, 11q, and 17p. In multivariate analyses, six CNVs (ie, CLL-specific variations in 11p15.1-15.4 or 6q27) predicted time-to-treatment or overall survival independently of established markers of prognosis. Moreover, genotypic complexity (ie, the number of independent CNVs per patient) significantly predicted prognosis, with a median time-to-treatment of 64 months versus 23 months in patients with zero to one versus two or more CNVs, respectively (P = 3.3 × 10(-8)). In summary, a comparison of SNP genotypes from patients with CLL with HapMap controls allowed us to identify known and unknown recurrent CNVs and to determine regions and rates of CNV that predict poorer prognosis in patients with CLL.