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Molecular Biology, Pathobiology, and Genetics |
1 Department of Internal Medicine, Division of Hematology and Oncology and 2 Department of Statistics, University of Michigan, Ann Arbor, Michigan
Requests for reprints: Sami N. Malek, Department of Internal Medicine, Division of Hematology and Oncology, University of Michigan, 1500 E. Medical Center Drive, Ann Arbor, MI 48109-0936. Phone: 734-763-2194; Fax: 734-647-9654; E-mail: smalek{at}med.umich.edu.
| Abstract |
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50.2 to 50.5 Mb physical position; (c) LATS2 RNA levels are
2.6-fold to 2.8-fold lower in cases with del13q14 type I that do not delete Rb, as opposed to del13q14 type II or all other CLL cases; (d) PHLPP RNA is absent in
50% of CLL cases with del13q14; and (e)
15% of CLL cases display marked reductions in miR15a/miR16 expression that are often but not invariably associated with bi-allelic miR15a/miR16 loss. These data should aid future investigations into biological differences imparted on CLL by different del13q14 subtypes. [Cancer Res 2008;68(4):1012–21] | Introduction |
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Fluorescence in situ hybridization (FISH) has identified various chromosomal changes, including del13q14, in
80% of patients with CLL, and the presence of specific chromosomal abnormalities has proved to be a prognostic indicator for disease progression and survival (6).
Loss of chromosomal material, including the genomic marker D13S319 on chromosome 13 (known as the deletion 13q14), occurs in
50% of all CLL cases and multiple other cancers (7, 8). Efforts by multiple groups have identified candidate genes within an
1 Mb stretch on chromosome 13 that have each been implicated in CLL del13q14 biology; nonetheless, mutations in these genes have not been identified and questions remain as to the validity of reducing the biology of del13q14 to a minimal deleted region or a single-gene mutation/expression event (8–19). Analysis of del13q14 is further complicated by an evolving understanding of resident gene structure and the discovery of complex noncoding RNAs (20).
Given the absence of mutations in genes within del13q14, haploinsufficiency has been proposed as a mechanism of action (21). However, independent experimental verification for such a mechanism has not yet been reported.
More recently, discovery of the deletion or reduced expression of two microRNAs miR15a and miR16 as part of del13q14 has been suggested as a unifying principle underlying del13q14 pathogenesis (22). Searches for miR15a/miR16 targets have identified Bcl-2 mRNA, and data have been presented in heterologous cell lines that suggest Bcl-2 mRNA regulation by these miRs (23).
Nonetheless, the general favorable outlook for patients with del13q14 remains difficult to reconcile with the postulated consequences of miR-locus deregulation/deletion, as patients with CLL and high Bcl-2 levels tend to have more aggressive disease (24).
Given the frequent occurrence of del13q14 in multiple cancers and given some of the abovementioned uncertainties surrounding its biology, we decided to analyze this lesion using high-resolution genomic mapping efforts.
Herein, we report the results of a large CLL profiling study with focused analysis of deletion 13q14 using 50k Affymetrix SNP microarrays (25) resulting in the identification of subtypes of del13q14 based on anatomic and functional criteria. Furthermore, we report that
15% of CLL cases display marked reductions in miR15a/miR16 expression that are often but not invariably associated with bi-allelic miR15a/miR16 loss (26).
SNP array data were integrated with expression data and led to the discovery of differential expression of LATS2 in del13q14 subtypes. Finally, expression of PHLPP was lower and often undetectable in del13q14 CLL cases as opposed to other FISH-based genomic CLL subgroups (27).
| Materials and Methods |
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Cell Isolation
Cell purification. Peripheral blood mononuclear cells from CLL patients were isolated by Ficoll-Paque gradient centrifugation (GE Healthcare), aliquoted into FCS with 10% DMSO, and cryopreserved in liquid nitrogen.
Flow cytometry. Cryopreserved CLL cells were washed and stained with phycoerythrin-conjugated anti-CD19 and FITC-conjugated anti-CD3 antibodies (eBioscience). Propidium iodide was added to a concentration of 1 µg/mL, and viable CD19+ and CD3+ single-positive cells were sorted on a high-speed FACSAria (Becton Dickinson) sorter.
Array Data Analysis
Affymetrix data files were generated from SNP chips posthybridization via scanners at the University of Michigan Microarray Core Facility and imported into the Affymetrix GCOS and GDAS software suites. dChip used native Affymetrix .CEL files and text formatted .CHP files from GDAS to generate copy number heatmap displays (29).
The loss of heterozygosity (LOH) tool was used to display SNPs with LOH between paired tumor samples and buccal DNA (30).
Genomic Southern Blotting
Cryopreserved peripheral blood mononuclear cells derived from CLL patients were washed and then treated with anti-human CD3 (Miltenyi Biotec 130-050-101) and anti-human CD14 microbeads (Miltenyi Biotec 130-050-201) per manufacturer's recommendations. Cell suspensions were run through Miltenyi MACS separation LS columns (130-042-401) to negatively enrich for CD19+ B cells. This resulted in >95% CD19+-positive cells.
Genomic DNA was prepared using digestion of cell pellets with proteinase K at 20 µg/mL in 100 mmol/L Tris, 50 mmol/L EDTA, 50 mmol/L NaCl, and 1% SDS at 56°C. DNA was digested and prepared for Southern analysis using standard protocols.
Probes for genomic Southern analysis were generated using PCR, subcloned into TOPO-TA cloning vectors (Invitrogen) and gel purified. Probes were labeled with
-32P-dCTP using the RadPrime DNA labeling system kit (Invitrogen).
Genomic probes used were composed of
1.0 to 1.5 kb of DNA corresponding to genomic sequence (green asterisks, probes 1–8; see Fig. 2C) including rs9316482 (probe 1), the miR16/15a locus (probe 2), rs9316484 (probe 3), DLEU7-Ex2 (probe 4), DLEU7-Ex1 (probe 5), physical position 50.382 (probe 6), rs768015 (probe 7), and rs2408291 (probe 8).
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Determination of Immunoglobulin Heavy Chain Variable Gene Mutation Status
Determination of immunoglobulin heavy chain variable gene (IgVH) mutation status was done as described (31).
Determination of Percentage of ZAP-70–Positive Cells Using Multivariable Fluorescence-Activated Cell Sorting Analysis
Determination of percentage of ZAP-70–positive cells using multivariable fluorescence-activated cell sorting (FACS) analysis was done as described (31).
Fluorescence In situ Hybridization
FISH was performed for all patient samples at the Mayo Clinic as a routine clinical test with the following published chromosomal target regions: 6 cen (D6Z1), 6q23.3 (c-myb locus), 11 cen (D11Z1), 11q13 (CCND1-XT), 11q22.3 (ATM), 12 cen (D12Z3), 12q15 (MDM2), 13q14 (D13S319), 13q34 (LAMP1), 14q32 (IGH-XT), 17 cen (D17Z1), 17p13.1 (p53).
Preparation of Sample DNA for Hybridization to Affymetrix 50k-XbaI Mapping Arrays and Assay Characteristics
A novel oligonucleotide platform, the 50k SNP chip, was introduced in 2004 by Affymetrix. Selected technical characteristics of the 50k SNP chips are a total combined number of
58,000 SNPs, a median intermarker distance of
16 kb, a mean intermarker distance of 47 kb, and average heterozygosity of 0.29.
A 50k SNP chip-based analysis using DNA purified from FACS-sorted CD19+ or CD3+ cells or buccal swabs was done as described (31).
Preparation of CLL-Derived Amplified RNA for Hybridization to Affymetrix Human 133 2.0 Plus Arrays
Twenty CD19+ selected CLL samples were sorted to purity using a high-speed FACSAria (Becton Dickinson) sorter, and RNA was extracted using the Trizol reagent. RNA was further purified using the RNeasy kit (Qiagen). Total RNA (50 ng) was amplified using Ovation RNA Amplification System (NuGen, Inc.), labeled with the FL-Ovation cDNA Biotin module (NuGen, Inc.), and hybridized to the Human 133 2.0 Plus GeneChip (Affymetrix) following the manufacturer's recommended protocols.
Affymetrix GeneChip data were analyzed as follows. Raw probe-level data were converted to expression measures using the Robust Multiarray Average method, which is implemented in the Affymetrix package of BioConductor (32). Briefly, the raw perfect match probes are first quartile normalized to remove any nonbiological variability. The normalized probe data are then converted to an expression measure (log scale) for each gene on each chip using a robust modeling strategy.
For differential expression analysis relating to 13q14 deletion status, we first removed the bottom 25% of probe sets in terms of overall variability. After this filtering step, 41,007 probe sets remained. We then used two-way ANOVA to identify differentially expressed genes, while accounting for the two-batch design of our expression array experiment. The ANOVA model included main effects for both the deletion status and the experimental batch, with the log-scale gene expression measurements as the dependent variable. The deletion effect on gene expression is isolated in the standardized coefficient estimate (the ratio of the deletion effect estimate to its SE). The standardized deletion effect estimates were then analyzed using a false discovery rate at a cutoff of 10% (33).
It was determined that a standardized deletion effect exceeding 3.3 in magnitude corresponded to a 10% or lower false discovery rate. There were 198 probe sets meeting this criterion. These probe sets are listed in Supplementary Table S7 and sorted by the magnitude of their 13q14 deletion coefficient estimate from the ANOVA.
Expression array data were deposited in the GEO repository (34, 35) with the accession number GSE9250 (GSM234840–GSM234859) and can be accessed at the NCBI Web site.3
Measurement of Gene Expression Using Quantitative PCR
RNA was prepared from 2 to 4 x 106 FACS-sorted CD19+ cells from 165 CLL cases using the Trizol reagent and resuspended in 100 µL DEPC-treated water. Complementary DNA (20 µL) was made from
50 ng of RNA using the Superscript III first strand synthesis kit (Invitrogen) and random priming.
Complementary DNA for microRNA reverse transcriptase quantitative PCR (Q-PCR) was made from
5 ng of RNA using the TaqMan microRNA reverse transcription kit (Applied Biosystems) and RNA-specific primers.
Primers and TaqMan-based probes were purchased from Applied Biosystems (primers-on-demand). Primer/probe mixtures included LATS2 (Hs00324396_m1), PHLPP (Hs01597866_m1), LPIN1 (Hs00299515_m1), DFNA5 (Hs00189346_m1), SERPINE2 (Hs00299953_m1), ARHGAP20 (Hs00826991_m1), cytochrome B5 (Hs00157217_m1), AQP3 (Hs00185020_m1), SLA2 (Hs00260078_m1), GAPD (Hu GAPD), PGK1 (Hu PGK1), miR16 (Tmol/L 391), miR15a (RT 389), RNU43 (TM 1095), and RNU49 (TM 1005).
Duplicate amplification reactions included primers/probes, TaqMan 2x Universal PCR Master Mix, No AmpErase UNG, and 1 µL of cDNA in a 20-µL reaction volume. Reactions were done on an ABI 7900HT machine. Normalization of relative copy number estimates for RNA species of interest was done with the Ct values for GAPD or PGK1 as reference (Ct mean gene of interest – Ct mean GAPD or PGK1). Comparisons between CLL subgroups were performed though subtractions of means of normalized Ct values.
Similar efficacies of amplification of target genes using primers for LATS2, PHLPP, GAPD and PGK1 or miR16, and RNU49 were verified using 2-fold serial dilutions of cDNA made from cell line–derived RNA over a range of 256-fold dilutions. Data were analyzed using least square regression analysis.
Statistical analysis was done using two-sample t statistics. PCR cycle times x were converted to abundance units via the transform x
1,500 x 2–x. These values were subsequently transformed to logarithmic abundance units via the transform x
log(x + 1)/log(2). The resulting values were approximately symmetrically distributed.
Duplicate amplification reactions for microRNAs included primers/probes, TaqMan 2x Universal PCR Master Mix, No AmpErase UNG, and 1.35 µL of cDNA in a 20-µL reaction volume. Normalization of relative copy number estimates for RNA species of interest was done with the Ct values for the RNU43 or RNU49 as reference (Ct mean gene of interest – Ct mean RNU43 or RNU49). Comparisons between CLL subgroups were performed through subtractions of means of normalized Ct values.
| Results |
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Combined high-resolution LOH and copy number analysis of del13q14 in CLL. 50k SNP array data from 171 patients were analyzed for LOH and subchromosomal copy loss on chromosome 13. Comparative analysis of SNP array–derived detection of del13q14 using copy number analysis compared with clinical FISH results showed strong agreement between both methods: FISH detected 91 of 171 (53%) overall del13q14 incidence and 77 of 171 cases (45%) with >25% of cells involved. SNP arrays detected 82 of 171 del13q14 incidence (48%). SNP arrays detected 74 of 77 (96%) of all CLL cases which were >25% FISH positive and 82 of 91 (90%) of all CLL cases which were FISH positive.
In Fig. 1
, we display horizontally LOH data (A) for all patients for chromosome 13 together with heatmap displays of paired copy number estimates (B). This analysis identified four cases (red arrows) with extensive LOH on chromosome 13 but copy loss restricted to a small area at
D13S319 (
49.6 Mb physical position) and one case without any LOH-associated copy loss (uniparental disomy).
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Identification of multiple distinct anatomic subtypes of del13q14 in CLL. Inspection of chromosomal copy number displays for del13q14 at higher resolution led to the characterization of del13q14 subtypes based on anatomic criteria (Fig. 2A–C ). In Fig. 2A, we have displayed from left to right all profiled CLL cases according to del13q14 lesion length. In Fig. 2B, we display a "zoomed-in" view of the epicenter of these deletions centered on the clinically important genomic FISH probe D13S319. In Fig. 2C, we display genomic copy number estimates [red vertical lines flanked by copy number estimates (0, 1, or 2 copies)] based on comparative genomic Southern blotting.
This anatomic clustering allowed us to propose the following schema for del13q14 lesions.
(a) Type I lesions (60% of all del13q14 lesions) do not include Rb and almost always terminate in a genomic region at
50.2 to 50.5 Mb that we, here, term the major 13q14 telomeric breakpoint cluster (M13q14TBC; Fig. 2C). Within the group of 13q14 type I deletions, one can further identify a majority subset of cases (del13q14 type Ia) with breaks in close proximity to rs9316482 and, therefore, close to the miR16/15a locus.
Southern analysis on selected del13q14 type Ia cases (Fig. 2C) confirmed that chromosomal breaks occur within a tight genomic region (between 49.45 and 49.55 Mb). Breakpoint analysis further identified cases with bi-allelic loss of the miR cluster (physical position at
49.52 Mb), as well as cases with one retained miR cluster copy (Fig. 2C). In addition, type Ia lesions were identified in multiple CLL cases coexisting on the second chromosome with larger 13q14 deletions.
(b) Type II lesions (40% of all del13q14 lesions) include Rb and, in many cases, extend many Mb past Rb toward the centromere. A subset of type II lesions at the telomeric end terminate in the M13q14TBC.
This analysis reliably identified only 2 of 171 CLL cases with deletions shorter than del13q14 type Ia lesions, implying that removal of
0.8 Mb of chromosomal material from
49.5 to
50.5 Mb is required for the biology of del13q14 type Ia lesions (10, 12, 15, 16, 18, 19, 36).
Finally, we note that the clustering of breaks could result in fusion genes in a small subset of CLL cases involving either (a) DLEU2 or either DLEU7 or GUCY1B2 or (b) RFP2/DLEU5 and FLJ11712.
Clinical characteristics associated with del13q14 subtypes. Of the 171 CLL cases analyzed, 134 were from patients that were untreated at enrollment. Of these 134 patients, 14% had a del13q14 type II, 34% had a del13q14 type I, and 52% lacked a del13q14. The ratio of del13q14 type II to del13q14 type I deletions was 19:46 (0.41). ZAP-70 was positive in 32%, 30%, and 54% of the patients with del13q14 type II, del13q14 type I, or no del13q14, respectively. IgVH genes were unmutated in 32%, 37%, and 46% of patients with del13q14 type II, del13q14 type I, or no del13q14, respectively (Supplementary Tables S2 and S3A,B; Table 1 ).
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2 test; ref. 37) compared with patients with either del13q14 type I or no del13q14 (mean Rai stage of 1.42, 0.91, and 0.78, respectively). Overall survival data were not mature enough for correlative analysis. Thirty-seven patients were pretreated at enrollment. Of these 37 patients, 32% had a del13q14 type II, 14% had a del13q14 type I, and 54% lacked a del13q14. The ratio of del13q14 type II to del13q14 type I deletions was 12:5 (2.4; Supplementary Tables S3A,B and S4; Table 1). Interestingly, compared with previously untreated patients, del13q14 type II lesions were significantly enriched and del13q14 type I lesions significantly depleted in the previously treated group of patients (P = 0.001).
Finally, of the 46 untreated patients with del13q14 type I, 14 cases displayed copy number estimates of <1 (range, 0.23–0.98; mean, 0.6), whereas 32 cases displayed estimates equal to or >1 (range, 1.0–1.41; mean, 1.17). The Rai stage at enrollment was not significantly different (P = 0.37) for these cases (mean Rai stage of 1.1 versus 0.8, respectively).
A subset of CLL cases display very low miR16/miR15a cluster expression. We proceeded to analyze the expression of miR16 and miR15a using Q-PCR in
95% of the 171 CLL cases studied (Supplementary Table S5). Measurements were normalized to expression of two unrelated microRNAs, RNU43 (on chromosome 22q13.1) and RNU49 (on chromosome 17p11.2). Expression of RNU49 and RNU43 was detected in all CLL cases at relatively uniform levels. The correlation coefficient (with 95% confidence interval) between measurements of RNU49 Ct mean versus RNU43 Ct mean was high at 0.61 (0.51–0.70).
The range of the normalized expression values for both miR16 and miR15a across this large cohort of CLL cases was wide: range
Ct miR16-RNU43 of 1.7 to –7.4, 10th percentile to 90th percentile of –0.3 to –5.8 (corresponding to a 45-fold expression difference) and range
Ct miR15-RNU43 of 9.4 to –2.2, 10th percentile to 90th percentile of –5.7 to 0.0 (corresponding to a 52-fold expression difference).
We proceeded to compare relative expression levels of miR16 and miR15a in two mutually exclusive CLL subgroups: cases with and without del13q14 by FISH. Mean expression values of both miRs were modestly lower (miR16 = 1.2-fold/1.7-fold and miR15a = 1.4-fold/2-fold for RNU49/RNU43 normalization, respectively) in the del13q14 subgroup as opposed to non-del13q14 CLL cases.
Subsequently, we ranked all CLL cases according to chromosomal copy number estimates for a
0.4 Mb chromosomal region between rs9316484 (centromeric to the miR16/15a locus) and rs3118650 (telomeric to the miR16/15a locus). We calculated mean normalized expression values for miR16 and miR15a for the 22 (13%) CLL cases with more extensive chromosomal loss (range, 0.23–0.98; mean, 0.6) and the remaining 141 (87%) CLL cases with less extensive or no loss (range, 1.0–2.32; mean, 1.64).
Mean normalized expression values of both miR16 and miR15a were substantially lower (miR16 = 4.3-fold/3-fold and miR15a = 6.5-fold/4.9-fold for RNU49/RNU43 normalization, respectively) in the subgroup with more extensive del13q14 as opposed to the group with less extensive or no del13q14.
Upon removal of these 22 CLL cases (13%) with extensive del13q14 chromosomal loss from analysis, the relative miR16/15a expression levels for the remaining 141 (87%) of cases (with del13q14 or without del13q14) were indistinguishable from all cases without del13q14.
Finally, we ranked all CLL cases by normalized miR16 or miR15a expression and analyzed the 41 (25%) cases with the lowest miR expression levels. This analysis disclosed 8 of 14 (miR15a/miR16) cases with no detectable alteration at 13q14 by either FISH or SNP array measurements, but low relative expression of the miR15a/miR16 genes, comparable in magnitude to CLL cases with extensive del13q14.
This combined data suggests that
15% of CLL cases indeed have very low miR16/miR15a levels and that the majority of CLL cases (
85%) display a range of expression of these miRs that seems independent of the genetic background.
MiR16/miR15a levels do not predict Bcl2 levels in CLL. Bcl-2 mRNA has been proposed as a physiologic target for miR15a and miR16 in CLL. We therefore measured and compared expression levels of Bcl-2 using immunoblotting in FACS-sorted, highly pure CLL cells derived from CLL cases with or without del13q14 by both FISH and SNP arrays (average copy number estimates of 0.42 versus 2.1) and low versus high relative miR16/miR15a expression (
Ct miR16-RNU43 = 0.1 versus –2.5, corresponding to a 6.1-fold expression difference and
Ct miR15-RNU43 = 5.5 versus 2.8, corresponding to a 6.5-fold expression difference).
As can be seen in Fig. 3A-C , Bcl-2 levels, once normalized to Actin levels, were similar in both groups of CLL cases, prompting our interest in other genes deregulated as a consequence of del13q14.
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In this group of 198 genes, we identified reduced expression of FLJ11712, KCNRG, RFP2, RFP2OS, and DLEU1, providing confidence that genes deleted through del13q14 type I displayed reduced relative expression under our assay conditions.
Multiple other genes emerged as candidate differentially expressed genes from this analysis. Measurements of expression of LATS2, DFNA5, PHLPP, LPIN1, SERPINE2, ARHGAP20, CYTB5, SLA2, and AQP3 by Q-PCR in cDNA derived from the 20 CLL samples used for array analysis confirmed differential expression of these genes (see Supplementary Table S8).
LATS2 showed substantial and significant underexpression in del13q14 cases as opposed to reference cases as detected by two probes and was one of the genes selected for further study (Supplementary Fig. S1).
Finally, PHLPP, a recently discovered phosphatase that dephosphorylates Ser473 in AKT was selected for study as differential AKT activity and/or expression in CLL has been described (3, 38).
LATS2 expression levels are lower in CLL with del13q14 type I as opposed to all other CLL types. LATS2 expression levels were measured in 165 CLL cases using Q-PCR, and data were normalized using either GAPD or PGK1 expression levels (Supplementary Table S9). Expression of GAPD and PGK1 was detected in all CLL cases at relatively uniform levels. The correlation coefficient (with 95% confidence interval) between measurements of GAPD Ct mean versus PGK1 Ct mean was high at 0.78 (0.72–0.84).
Analysis of LATS2 levels by subgroups showed 1.6-fold/1.7-fold (GAPD/PGK1 normalization) lower expression levels in CLL cases with del13q14 than in all cases without del13q14. Given that we had initially observed the differential expression of LATS2 in del13q14 type Ia lesions as opposed to non-del13q14 cases, we proceeded to analyze LATS2 expression in three distinct CLL groups: (a) CLL with del13q14 type I, (b) CLL with del13q14 type II, and (c) all other CLL cases.
Interestingly, this analysis uncovered that CLL cases with del13q14 type I showed reduced LATS2 expression relative to CLL cases with del13q14 type II (
2.6-fold/
2.8-fold of GAPD/PGK1 normalization, respectively) or no del13q14 (
2.6-fold/
2.6-fold of GAPD/PGK1 normalization, respectively;
Ct mean LATS2-GAPD of 9.8/8.4/8.4, respectively, and
Ct mean LATS2-PGK1 of 5.4/3.9/3.8, respectively; Fig. 4A and B
).
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PHLPP expression is low or undetectable in
50% of CLL cases with del13q14. Q-PCR–based measurements of PHLPP expression in the 20 CLL cases profiled using the expression arrays detected low/absent expression in 8 of 10 of the del13q14 cases versus 3 of 10 of the reference cases (Supplementary Table S8).
Subsequently, PHLPP expression levels were measured in 164 CLL cases using Q-PCR, and data were normalized using PGK1 expression levels. CLL cases with a
Ct (Ct mean PHLPP – Ct mean PGK1) of >9 (indicating very low relative levels) or cases with undetectable levels were grouped as low/absent PHLPP expression (Supplementary Table S10).
Correlative analysis of PHLPP expression by FISH categories discovered that
50% of CLL cases with del13q14 did not express PHLPP (Fig. 5
). The percentage of CLL cases that did not express PHLPP was 51% (isolated del13q14), 40% (normal FISH), 28% (complex FISH), 22% (isolated del11q or del17p), and 14% (isolated trisomy 12), respectively. Using a standard test of proportions, the difference between del13q14 and trisomy 12 cases for PHLPP expression was highly significant at P of 0.01, whereas a trend was observed for the comparison of del13q14 and complex FISH findings (P = 0.14).
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| Discussion |
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A significant strength of this study is the use of sorted CD19+ cells as substrates for all analyses, effectively eliminating confounding variables introduced by non–B cells.
SNP array analysis proved to be a highly sensitive and specific method for determining copy number losses at 13q14 in CLL based on comparison with FISH. Both methods, with few exceptions, detected the same cases.
Detailed anatomic analysis of del13q14 suggested to us the existence of distinct subtypes. Our initial suggestion for categorization classifies del13q14 lesions with Rb loss as type II (40% of del13q14 cases) and without such loss as type I (60% of del13q14 cases). Rb is a critical regulator of cell cycle progression and genomic stability, and loss of one or two alleles could differentially affect the biology of affected CLL cases (42, 43); further support for clustering del13q14 type I lesions as a separate group comes from expression analysis of LATS2, which we performed across this large CLL cohort.
LATS2 RNA levels were found to be low in CLL cases with del13q14 type I as opposed to type II cases or all other CLL cases without del13q14. Given that LATS2 has been implicated in cell cycle progression control, we surmise that Rb, LATS2, and possibly additional, unidentified regulators (in non-del13q14 cases) are regulating this process in different subsets of CLL (44, 45).
The mechanism of low LATS2 expression in CLL subtypes is not known; LATS2 lies outside of all 13q14 deletions. Possibilities include LATS2 promoter methylation, as described for other cancers, or an effect in trans of 13q14 resident genes on LATS2 expression (46, 47).
The discovery of differing LATS2 levels in CLL subtypes may also be of interest in the context of response to therapy or disease progression, as LATS2 has been shown to intersect with the Mdm2-p53 axis (48). This topic needs prospective analysis in well-defined CLL cohorts.
Further subdivision of del13q14 type I cases into type Ia and type Ib is suggested by the occurrence of deletions that appear of relatively uniform length (del13q14 type Ia) and that display centromeric breaks within the vicinity of the miR15a/miR16 cluster and telomeric breaks within a newly identified break cluster that we here term the major telomeric del13q14 breakpoint cluster. Bi-allelic del13q14 type Ia lesions were associated with marked reductions in miR15a/miR16 expression levels and may exert effects on affected CLL cases through yet-to-be identified miR15a/miR16 targets. In this context, it seems relevant that Bcl-2 levels were not correlated with miR15a/miR16 levels, providing a renewed impetus for searches for critical miR15a/miR16 targets (26).
Correlative analysis of surrogate clinical end points/variables by del13q14 subtype disclosed a higher Rai stage at study enrollment for del13q14 type II lesions, as opposed to del13q14 type I lesions. Furthermore, we detected a highly significant enrichment for del13q14 type II cases in previously treated as opposed to untreated CLL specimens. Whereas these data may portend that del13q14 type II is a marker for more aggressive CLL, only prospectively collected clinical data will allow for firm conclusions to be drawn regarding possible detrimental effects of del13q14 type II lesions on CLL outcome.
The novel discovery that
50% of all CLL cases with del13q14 do not express PHLPP is of interest. PHLPP dephosphorylates activated AKT and low or absent PHLPP expression may allow for sustained AKT signaling after proper cell surface stimuli (49).
In summary, anatomic and functional data suggest that multiple genes are deregulated as part of various deletions on chromosome 13, including genes with properties that warrant reduction in actively dividing cancer cells (Rb, LATS2) and genes with the potential for more specialized functions (miR15a/miR16, RFP2, PHLPP and others; ref. 50).
| Acknowledgments |
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The costs of publication of this article were defrayed in part by the payment of page charges. This article must therefore be hereby marked advertisement in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.
| Footnotes |
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3 ftp://ftp.ncbi.nih.gov/pub/geo/DATA/supplementary/series/ ![]()
Received 8/13/07. Revised 11/19/07. Accepted 12/ 6/07.
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V. Grubor, A. Krasnitz, J. E. Troge, J. L. Meth, B. Lakshmi, J. T. Kendall, B. Yamrom, G. Alex, D. Pai, N. Navin, et al. Novel genomic alterations and clonal evolution in chronic lymphocytic leukemia revealed by representational oligonucleotide microarray analysis (ROMA) Blood, February 5, 2009; 113(6): 1294 - 1303. [Abstract] [Full Text] [PDF] |
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