Abstract
Abstract 1773
Risk stratification in chronic lymphocytic leukemia (CLL) is highly desirable and should comprise not only evaluation of clinical features but also molecular prognostic markers. Currently such molecular markers include loss of 17p13, 11q22, 13q14, 6q22, and gain of chromosome 12 as assessed by fluorescence in situ hybridization (FISH) and mutation status of the variable region of the IGH gene (IGHV) by sequencing. In recent years, genome-wide scanning technologies such as array-comparative genomic hybridization (array-CGH) have revealed novel and refined known copy number alterations (CNAs) in the CLL genome. In order to evaluate the potential of array-CGH in prognostication in mature B-cell neoplasms, including CLL, and implement array-CGH in a clinical diagnostic laboratory, a targeted oligonucleotide-based microarray was custom designed to represent genomic regions exhibiting gain/loss in these lymphoid neoplasms. The 4 × 44K formatted array included 2 × 17,348 probes for the 80 selected genomic regions (average resolution of 34kbp), and recommended controls including a 1Mbp genome backbone. DNA extracted from two CLL datasets were submitted to array-CGH using an equimixture of commercially available male/female DNA as a reference. CNAs were detected using Genomics Workbench Lite (Agilent Technologies, Inc.) with the ADM2 algorithm. Analytical sensitivity was assessed by cell line DNA dilution and by FISH (116 specimens) and was 30–40% and 20–25%, respectively. Recurrent CNAs in previously untreated patients, greater than 1.5Mbp in size, were analyzed for association with time to first treatment (TTFT) and overall survival (OS) by the log rank test. Association with IGHV mutation status was tested using the Fisher's two-sided exact test. In both datasets for untreated specimens, unmutated IGHV negatively correlated with both TTFT and OS significantly (p < 0.05). Gain of chromosome 12 was detected in 11–12% of untreated specimens in both datasets and as expected did not associate with outcome. Loss of 13q14 as a sole abnormality (excluding copy number changes arising at known sites of normal variation) was associated with an overall favorable outcome, but specimens with loss of both loci (MIR15A/16-1 and RB1) versus one locus (MIR15A/16-1) did not display significantly different outcomes. As expected loss of 17p13 associated with shorter TTFT and OS, and was observed at higher levels in treated specimens. A similar result was observed for 11q22 loss but not in the second dataset, perhaps due to the relatively short follow-up time. Importantly, four additional copy number changes (gain of 2p, 3q, and 8q, and loss of 8p) were found to associate with shorter TTFT and/or OS, and also occurred at higher frequency in treated specimens. Notably, all but one specimen exhibiting two of these CNAs, were Rai Stage 0-II. After multiple comparisons correction, gain of 2p and 3q, and loss of 8p remained significantly associated with an unfavorable outcome. Gain of 2p25.3-p15 was observed exclusively in unmutated IGHV specimens. Loss of 18p and gain of 17q24 were not considered further for testing due to low frequency or lower frequency in treated specimens (data not shown). Uniquely, these data demonstrate in low-intermediate risk CLL cohorts the prognostic value of genomic gain/loss at multiple sites and support implementation of array-CGH into a clinical setting for risk stratification in CLL where genomic gain or loss of multiple clinically relevant genomic regions can be assessed simultaneously.
Dataset 1 Untreated n = 81 TTFT p-value OS p-value Treated n = 38 Dataset 2 n = 169 TTFT p-value OS p-value Treated n = 28 Median TTFT 87.6 mo 24.1 mo Median OS 117.7 mo 37.2 mo Rai Stage 0 25 77 I-II 42 48 III-IV 5 1 na 9 43 Unmutated IGHV 46% (n=80) 0.0003 0.0004 38% (n=163) 0.002 0.044 13q14 loss (sole abnormality) 52.5% 0.038‡ 0.087‡ 33.7% 0.144‡ 0.008‡ MIR15A/16-1, RB1 27.5% 0.77 0.337 11.2% 0.011 1 MIR15A/16-1 25.0% 22.5% 11q22 loss (ATM) 12.3% 0.125 0.009 23.7% 8.3% 0.393 0.977 14.3% 17p13 loss (TP53) 2.5% 0.010 0.012 15.8% 4.7% 0.006 <.0001 10.7% 2p25.3-p15 gain 6.2% 0.002 <.0001 10.5% 3.0% 0.702 0.025 10.7% 8q24 gain 2.5% 0.238 0.014 7.9% 4.1% 0.564 0.007 0.0% 3q26-q27 gain 2.5% <.0001 <.0001 5.3% 3.0% 0.850 <.0001 7.1% 8p23-p21 loss 2.5% 0.002 0.016 10.5% 1.2% 1 <.0001 7.1% Unless otherwise noted, all values associated with shorter times ‡ Associated with longer time na not available
Disclosures:
Houldsworth: Cancer Genetics, Inc.: Employment. Guttapalli:Cancer Genetics, Inc.: Employment. Ma:Cancer Genetics, Inc.: Employment. Chen:Cancer Genetics, Inc.: Employment. Patil:Cancer Genetics, Inc.: Consultancy.
Integrated proteogenomic analysis of metastatic thoracic tumors identifies APOBEC mutagenesis and copy number alterations as drivers of proteogenomic tumor evolution and heterogeneity
