Clinical Cancer Research The Future of Cancer Research: Science and Patient Impact
HOME HELP FEEDBACK SUBSCRIPTIONS ARCHIVE SEARCH TABLE OF CONTENTS
Cancer Research Clinical Cancer Research
Cancer Epidemiology Biomarkers & Prevention Molecular Cancer Therapeutics
Molecular Cancer Research Cancer Prevention Research
Cancer Prevention Journals Portal Cancer Reviews Online
Annual Meeting Education Book Meeting Abstracts Online
Clinical Cancer Research 13, 4777-4785, August 15, 2007. doi: 10.1158/1078-0432.CCR-07-0456
© 2007 American Association for Cancer Research
This Article
Right arrow Abstract Freely available
Right arrow Full Text (PDF)
Right arrow Alert me when this article is cited
Right arrow Alert me if a correction is posted
Services
Right arrow Similar articles in this journal
Right arrow Similar articles in PubMed
Right arrow Alert me to new issues of the journal
Right arrow Download to citation manager
Right arrow reprints & permissions
Citing Articles
Right arrow Citing Articles via HighWire
Right arrow Citing Articles via Google Scholar
Google Scholar
Right arrow Articles by Ross, C. W.
Right arrow Articles by Malek, S. N.
Right arrow Search for Related Content
PubMed
Right arrow PubMed Citation
Right arrow Articles by Ross, C. W.
Right arrow Articles by Malek, S. N.

Human Cancer Biology

Comprehensive Analysis of Copy Number and Allele Status Identifies Multiple Chromosome Defects Underlying Follicular Lymphoma Pathogenesis

Charles W. Ross2, Peter D. Ouillette1, Chris M. Saddler1, Kerby A. Shedden3 and Sami N. Malek1

Authors' Affiliations: 1 Division of Hematology and Oncology, Department of Internal Medicine, Departments of 2 Pathology, and 3 Statistics, University of Michigan, Ann Arbor, Michigan

Requests for reprints: Sami N. Malek, Division of Hematology and Oncology, Department of Internal Medicine, 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
Top
 Abstract
Materials and Methods
 Results
 Discussion
 References
 
Purpose: Follicular lymphoma (FL) constitutes the second most common non-Hodgkin's lymphoma in the Western world. The clinical course is variable and only in part explained by known tumor-intrinsic or -extrinsic factors. FL carries the hallmark chromosomal translocation t(14;18), deregulating the expression of Bcl-2, but this is not sufficient to explain either FL biology or clinical behavior.

Experimental Design: We have employed high-density genomic profiling technology using the Affymetrix 50K-XbaI oligonucleotide single nucleotide polymorphism–chip platform to interrogate the genomes of 58 fluorescence-activated cell–sorted (FACS) FL specimens for chromosomal copy number changes and 46 specimens for loss of heterozygosity (LOH).

Results: We report (a) previously unknown high-frequency copy-neutral LOH (uniparental disomy) in FL on chromosomes 1p (~50%) and 6p (~30%); (b) that del6q is complex, as reported, with at least two regions of minimal common loss at 6q13-15 and 6q23-24, and that in addition, ~8% of FL specimens contain a homozygous deletion at 6q23.3-24.1 that spans the negative NF{kappa}B regulator A20 and the p53 apoptosis effector PERP; (c) that combined analysis of chromosome 17p for LOH, copy number, and p53 mutations shows that most p53 mutations in FL do not involve del17p. Finally, we map high-frequency LOH with and without copy loss on chromosomes 9p, 10q, and 16p and genomic gains on 2p15-16 and 8q24.22-24.3.

Conclusions: This comprehensive description of the pathologic anatomy of the FL genome uncovers novel genetic lesions and should aid with identification of genes relevant to FL biology and clinical behavior.

Follicular lymphoma (FL) is the most common indolent B cell lymphoma and remains incurable with current therapies. FL has a varied clinical course. Genetically, FL is characterized by the hallmark balanced chromosomal translocation t(14;18), leading to deregulated expression of Bcl-2 (1, 2). Translocation(14;18) is found in about 85% of FL cases, thus predicting the existence of additional tumor-intrinsic and -extrinsic factors that are important in FL biology and clinical behavior (3).

The importance of tumor-extrinsic factors (infiltrating immune cells) on FL biology and outcome was recently shown using array-based expression analysis and tissue array–based immunohistochemistry (infiltrating macrophage content; refs. 4–6).

Tumor-intrinsic factors, including genetic markers, for FL biology and outcome have been less well defined, in large part due to an incomplete view of the pathologic anatomy of the FL genome (7, 8). Unlike other hematologic neoplasms, like acute myelogenous leukemia or chronic lymphocytic leukemia (CLL; refs. 9, 10), where genomic information is prominently used for patient risk stratification, genome-based prognostication is not yet available for FL patients.

Genomic changes in FL have been difficult to study comprehensively because FL cells do not grow well ex vivo. Nonetheless, over the years, recurrent abnormalities have been described using either conventional karyotyping or comparative genomic hybridization (CGH; refs. 7, 8, 11–15): del6q, del1p32-36, +7, +12, +X and der(18)t(14;18), as well as others. Essentially, nothing is known about gene mutations or gene deregulations as part of or secondary to these changes.

Because cancer is fundamentally a genetic disease, the discovery of genes mutated in various forms of cancer has advanced our understanding of the specific pathogenetic mechanisms that operate in various cancer cell types (16). Many cancers are heterogeneous and represent multiple biologically and clinically distinct subtypes. For most cancer types, sporadic information on recurrent genetic changes has accumulated, but a genome-wide, high-resolution, comprehensive view of all copy number changes or loss of heterozygosity (LOH) is emerging for just a few (17–20).

Given the recent development of high-density technologies to measure genome-wide changes in gene or genome copy number or allele identities in DNA extracted from tumor cells, we reasoned that it would prove promising to interrogate the FL genomes of a large number of samples using single nucleotide polymorphism (SNP) chip technology (21). SNP chip technology has the advantage of allowing for simultaneous LOH detection and copy number estimation, permitting the detection of copy-neutral LOH (22, 23).

In this study, we describe an unbiased, high-density, whole-genome view of LOH and copy number changes in FL. These data may serve as a reference for the detection of FL-associated gene mutations and development of genomics-based clinical assays in the future. Using highly purified FL preparations and paired T cell–derived DNA, we were able to detect novel FL-associated genetic changes, including formerly unknown high-frequency copy-neutral LOH at 1p and 6p, and have established an overview of the pathologic FL genome.


   Materials and Methods
Top
 Abstract
 Materials and Methods
Results
 Discussion
 References
 
Source material and Internal Review Board-Medicine approval. Source material for this study was cryopreserved cell suspensions of variable viability representing low grade FL from 58 adult patients. The 58 samples had been collected between 1990 and 2005 and processed by the clinical flow cytometry laboratory at the University of Michigan. Patient specimen sources included 52 lymph node biopsies, 4 bone marrow aspirates, and 2 peripheral blood samples. Patients ranged in age from 35 to 79 years (median age 55 years), with a male-to-female ratio of 1:1.

Subclassification of the FL by the WHO criteria was verified by a hematopathologist (C.W.R.) using histopathologic, cytologic, and immunophenotypic features (24, 25). Thirty-two of the specimens were classified as FL, grade 1, and the remainder were grade 2. The research protocol was approved by the University of Michigan Medical Center Institutional Review Board (2005-0338).

Flow cytometry. Aliquots of cryopreserved, postdiagnostic FL cells were washed and recovered by centrifugation and stained with phycoerythrin-conjugated anti-CD20, FITC-conjugated anti-CD3, and APC-conjugated anti-CD45 (eBioscience). Propidium iodide was added after the final washing to a concentration of 1 µg/mL to discriminate dead cells, and viable CD45+/CD20+/CD3– and CD45+/CD20–/CD3+ cells were sorted on a high-speed FACS Aria (Becton Dickinson) flow cytometer.

Preparation of sample DNA and hybridization to Affymetrix 50k-XbaI-mapping arrays. Sorted CD20+ or CD3+ cells were digested overnight in 100 mmol/L Tris (pH, 8.0), 50 mmol/L EDTA, 50 mmol/L NaCl, 0.5% SDS, and 100 µg/mL of proteinase K (Invitrogen) at 56°C. DNA was extracted using phenol-chloroform and precipitated using ammonium acetate, ethanol, and glycogen. About 250 µg of DNA was digested for 10 h at 37°C, and the samples were subsequently processed according to the manufacturer's (Affymetrix) instructions. Hybridization of labeled DNA fragments to the 50k-XbaI-mapping arrays was done in an Affymetrix Hybridization Oven 640 for 16 h at 48°C with rotation at 60 rpm. Washing and staining was done on an Affymetrix Fluidics Station 450. Scanning was done using an Affymetrix Scanner 3000 7G with autoloader. Data files were archived and transferred using CAB (windows cabinet) files.

Selected technical characteristics of the 50k-XbaI SNP chips used in this study are a total combined number of ~58,000 SNPs, a median intermarker distance of about 16 kb, a mean intermarker distance of about 47 kb, and an average heterozygosity of 0.29; therefore, on average, about 16,800 SNPs per individual FL genome will be informative for LOH analysis, resulting in an effective median and mean inter-SNP distance for LOH searches of about 50 and 140 kb, respectively.

Genomic DNA sequencing. Primers to amplify exons and adjacent intronic sequences of human p53, IRF4, Blimp1, ID4, and p73 and primers to amplify selected genomic regions containing informative SNPs were designed using the primer 3 program.4 Primer sequences can be found in Supplementary Table S3. PCR products were generated using DNA templates from Qiagen Repli-g kit-amplified, fluorescence-activated cell–sorted (FACS) CD20+ or CD3+ cells. Amplifications were done using Taq polymerase. PCR amplicons were prepared for direct sequencing with internal nested sequencing primers using the exonuclease/shrimp alkaline phosphatase method (USB).

Data analysis. SNP chip data outputs from the Affymetrix Chromosome Copy Number Tool software were used to perform LOH analysis. dChipSNP, a freely available software package (26), was used to visualize copy number changes by analyzing Affymetrix.CEL files and GDAS software output data. LOH display was done using a software program developed for these studies in our laboratory (LOH tool). The LOH tool is a Java-based genome browser that displays LOH for entire chromosomes across multiple patient samples simultaneously. An executive copy of this software and instructions for use are available on disc by obtaining an academic license from the University of Michigan. In total, 58 patient samples (out of a total of 78 screened samples) could be analyzed for copy changes (with sufficient CD20+ cell-derived DNA available) and 46 for LOH (with sufficient paired CD3+ T cell DNA available) for this study. The remaining samples did not yield sufficient DNA from either CD20+ cells, CD3+ cells, or both for this analysis.

Mutation Surveyor (SoftGenetics LLC) software was used to compare experimental DNA sequences from FL samples against GenBank-derived cDNA sequences or genomic sequences, complemented by visual inspection of sequence chromatograms.

Quantitative real-time PCR analysis of genomic copy number changes. Primers and TaqMan-based probes for Q-PCR applications were purchased from Applied Biosystems (Primers-on-demand). Primer/probe mixtures included Hs00751717_s1 (PERP, chr.6q), Hs00250581_s1 (BCL11A, chr.2p), Hs01851142_s1 (RAG2, chr.11), Hs01112790_s1 (NHLRC1, chr.6p), Hs01937396_s1 (ZCCHC5, chr. X), Hs00369747_s1 (ACTRT2, chr.1p), Hs00272432_s1 (RSC1A1, chr.1p), and Hs00252427_s1 (C8orf17, chr.8q). Triplicate amplification reactions included primers/probes, TaqMan 2x Universal PCR Master Mix, No AmpErase UNG, and 10 ng of unamplified genomic template DNA extracted from CD20+-sorted cells in a 20-µL reaction volume. Reactions were done on an ABI 7900HT machine. The ability of the assay to discriminate one from two genomic allele copies was confirmed using the X chromosome probe set in most reactions and comparing Ct values with the gender of individual cases. Standardization of relative copy number estimates for genomic regions of interest was done using the {Delta}CT method with the Ct values for the RAG2 locus as reference.


   Results
Top
 Abstract
 Materials and Methods
 Results
Discussion
 References
 
The 50K-SNP chip assay can detect single copy gains or losses. We initially tested the ability of the 50K-SNP chip assay to detect single copy gains and losses in a cohort of CLL patients for which clinical information was available. Using data for the X chromosome for 76 CLL patients, we showed 100% sensitivity and specificity to identify males and females (one versus two copies of the X chromosome; data not shown).

Next, we proceeded to analyze a collection of FACS-sorted FL specimens. We reasoned that FACS sorting of cells would result in very highly pure FL cells and would allow for the detection of homozygous losses and single copy gains.

In Fig. 1A , we have displayed data using the X chromosome analysis (LOH analysis, left; copy number analysis, right).


Figure 1
View larger version (53K):
[in this window]
[in a new window]

  		Fig. 1. The SNP chip assay can detect single copy differences in the FL genome. Copy number estimates for each SNP position were calculated using dChipSNP and displayed for all SNP positions for all patients for the indicated chromosomes. Blue, copy losses; red, copy gains. The physical position of SNPs is not linear along the displayed portions of the chromosome. A, chromosome X. Left, LOH analysis; right, copy number analysis. Text files generated through the use of the Affymetrix program Chromosome Copy Number Tool for all patients were imported into the LOH tool, and all individual positions of LOH between CD3+ cell-derived DNA and paired tumor CD20+ cell-derived DNA graphed as a blue tick mark across the length of the chromosomes. A, right, black asterisk, female patients; red asterisk, male patients. Red arrow, patients with discordant results between gender and copy number analysis. Black arrow, patients with LOH. The estimated copy numbers for all SNP positions for FL 2 are displayed along the entire chromosome below the X chromosome display; red line, 2N state. B, copy number analysis for SNP rs10487741 in the T cell receptor {gamma} variable region locus. Top, TRGV locus schematically depicted. The estimated copy numbers for all SNP positions for FL 25 are depicted below the display; red line, 2N state. C, copy number display of SNP positions in the {lambda} light-chain locus on chromosome 22. Top, Ig-{lambda}-locus is schematically depicted. Black arrows, cases exhibiting locus deletions. The estimated copy numbers for all SNP positions for FL 51 are depicted below the display; red line, 2N state.

 
Female patients (asterisks) were identified as 2N, and female patients with a loss of one X chromosome, as detected by LOH (black double arrows), were identified as 1N. Only 4:56 (7%, red single arrows) of informative samples were not, demonstrating the expected X chromosome copy number, but instead showed 2N and 3N estimates. Analysis of X chromosome copy number estimates for the paired normal T cell DNA in three of the four cases gave expected results (no. 41 lacked T cell data), supporting true copy gains in the tumor cells as described (11).

We next proceeded to test the assay's ability to detect amplifications using data from the analysis of the T cell receptor {gamma} variable region (TRGV) on chromosome 7 for all samples (Fig. 1B). SNP rs10487741 is embedded in the TRGV region and is expected to be deleted in T cells as part of T cell antigen receptor rearrangements that occur during T cell ontogeny. In Fig. 1B, we show copy number estimates at TRGV and a schema depicting the physical boundaries of the TRGV locus relative to the position of the informative SNPs of interest. As predicted, copy number estimates for SNP rs10487741 uniformly showed relative gains in CD20+ FL cells (strong red signal) as compared with the {alpha}/ß TCR-positive and TRGV-rearranged CD3+ T cells that were used as the copy number comparator for this analysis.

As a final semiquantitative assessment to show the ability of the assay to detect mono- and biallelic deletions, we analyzed the {lambda} light-chain locus on chromosome 22. In Fig. 1C, we have displayed a screenshot of copy number estimates for all samples for the IgV-{lambda} locus and flanking SNP positions. Above the screenshot is a schema depicting the physical boundaries of this locus relative to the copy number estimates. As expected, multiple samples (black arrows) showed visible deletions (blue) of various lengths at this locus, presumably reflecting the mono- or biallelic genomic losses following IgV-{lambda} rearrangements.

In summary, these data in aggregate and Q-PCR data presented in Supplementary Table S2 provide confidence that single-copy losses or gains can be detected at high apparent sensitivities and specificities using the assay conditions employed in this study.

Detection of high-frequency copy-neutral LOH at chromosome 1p in FL. Having confirmed that we could reliably detect copy number changes and LOH in these samples, we proceeded to scan the FL genome for novel changes.

Through comparison of LOH and copy number estimates, we detected a very high frequency of copy-neutral LOH on chromosome 1p (see Fig. 2, red arrows ). Additionally, LOH with copy loss was detected at 1p (see Fig. 2, black arrows). Combined, the frequency of these lesions was 23:46 (50%), the second most frequent genetic lesion ever described in FL. Confirmatory allele copy number measurements by Q-PCR on randomly selected cases using primers/probes embedded in 1p (within ACTRT2), within RAG2 (a reference gene present in two copies in all FL genomes) and on chromosome X (see Materials and Methods and Supplementary Table S2), combined with sequence analysis of informative SNPs in tumor and paired normal DNA (PCR-based LOH analysis, Supplementary Table S1), confirmed uniparental disomy in these cases.


Figure 2
View larger version (76K):
[in this window]
[in a new window]

  		Fig. 2. Detection of high-frequency copy-neutral LOH on chromosome 1p36 in FL. A, LOH display for chromosome 1p. Vertical solid lines, 10-Mb intervals. Roman numerals and arrows, subtypes of the 1p36 region. The approximate positions of the genes p73 and CASP9 are indicated. B, copy number display for chromosome 1. The estimated copy numbers for all SNP positions for FL 60 are depicted below the chromosome 1 display; red line, 2N state. Red arrows, FL patients with copy-neutral LOH on chromosome 1p; black arrows, LOH with copy loss.

 
Attempting further subclassification using anatomic criteria, we could identify a small telomeric lesion of about 8.5 Mb in length that was part of all lesions (1p type I) and a second type of lesion of about 25 Mb in length (1p type II). Both lesions are fully contained in cytoband 1p36, deletion of which confers poor outcome in patients with neuroblastoma (27).

Chromosome 1p lesions of types I and II harbor the p73 locus, and we proceeded to sequence all coding exons of p73 in 16 FLs. We did not detect mutations, and due to the lack of fresh FL tissue, we were not able to measure the influence of the LOH/copy loss at p73 on p73 expression.

Finally, 1p LOH was the only genetic lesion significantly overrepresented in FL grade 2, as compared with grade 1 lesions (log odds ratio, 1.37; 95% confidence interval, 0.28-2.46) and co-occurred with copy-neutral LOH at 6p (log odds ratio, 1.9; 95% confidence interval, 0.6-3.1).

Detection of novel high-frequency copy-neutral LOH at chromosome 6p in FL. Focusing our attention on chromosome 6p, we detected novel high-frequency LOH in 14:46 (30%) of cases at 6p that was copy neutral in all but two cases (Fig. 3A ). Combined Q-PCR analyses and genomic SNP sequencing confirmed these findings (Supplementary Tables S1 and S2).


Figure 3
View larger version (76K):
[in this window]
[in a new window]

  		Fig. 3. Detection of high-frequency copy-neutral LOH on chromosome 6p in FL and high-resolution mapping of del6q in FL. A, LOH display for chromosome 6. Vertical solid lines, 10-Mb intervals. Vertical red lines, minimal deleted regions. B, copy number display for chromosome 6. The approximate positions of various genes are indicated. The estimated copy numbers for all SNP positions for FL 26 are depicted below the chromosome 6 display; red line, 2N state. Red arrows, FL patients with copy-neutral LOH; black arrows, samples with LOH and copy loss. Red dotted lines, boundaries of minimally deleted regions (MDR1 and MDR2). C, copy number estimates for a subregion on chromosome 6q23.3-24.1. Each row represents one patient. Arrows, patients with homozygous deletions. The approximate positions of two genes, A20 and PERP, are indicated. The estimated copy numbers for all SNP positions for FL 62 are depicted below the chromosome 6 display; red line, 2N state.

 
Scanning of genes located in these areas with relevance to B cell or cancer physiology identified IRF4 and ID4 as potential candidates for this abnormality, but sequence analysis of all coding exons failed to identify mutations in these genes.

High-density mapping of del(6q) and identification of A20 and PERP as possible del(6q) candidate genes. Loss of material from chromosome 6q has been described in non-Hodgkin lymphoma (NHL), and a number of nonoverlapping minimally deleted regions have been proposed by various investigators over the years (28–30). Various del6q have been associated with negative prognosis in NHL and FL; nothing is known about specific gene aberrations on 6q in FL (15, 31).

We analyzed chromosome 6q by LOH and copy number analysis in all FL samples and detected a total of 22:58 (38%) positive samples (see Fig. 3A and B).

We readily detected at least two nonoverlapping regions of loss at frequencies of 16:58 (28%) at 6q13-15 (MDR1: physical boundaries, 73.69-88.07 Mb) and 13:58 (22%) at 6q23.2-24.2 (MDR2: physical boundaries, 132.45-138.31 Mb). Additional large, recurrent, contiguous regions of loss both between MDR1 and MDR2 and telomeric to MDR2 could be identified, supporting prior reports that multiple genes of importance may reside on 6q.

Scanning the regions of loss for copy estimates indicative of biallelic deletions revealed five cases with presumed homozygous deletion at 6q23.3-24.1 within MDR2 (Fig. 3C). Mean copy number estimates for these cases were 0.34 ± 0.2 (mean ± SD). In comparison, average copy number estimates for the entire FL cohort for all of chromosomes 1, 2, 4, 15, 19, and 20 were 2.01 ± 0.19, respectively. Delineation of a minimal homozygously deleted region uncovered two genes, A20, a well-studied NF{kappa}B regulator (32), and PERP, a p53 apoptosis effector (33).

Confirmatory copy number Q-PCR analysis using primers/probe with PERP confirmed progressively fewer copy number estimates in reference cases, candidate monoallelic deleted cases, and candidate homozygously deleted cases (Supplementary Table S2).

Sequencing of all coding exons for both genes, A20 and PERP, in ~50 FL cases failed to uncover mutations, but expression studies were hampered by the lack of access to fresh FL tissue.

Blimp1, found mutated or underexpressed in subsets of diffuse large B cell lymphoma (34, 35) and located outside of MDR1 or MDR2 in FL, was not found to be mutated in our FL cohort.

Detection of genetic changes in FL on chromosomes 16p, 9p, and 10q. Completing the genome-wide survey for LOH and copy number changes, we identified three additional regions of interest: chromosome 16p LOH (Supplementary Fig. S1) in 12:46 (26%) of cases (mostly copy neutral), chromosome 9p LOH (Supplementary Fig. S2) in 9:46 (20%) of cases (copy neutral or with copy loss) spanning the CDKN2A and CDKN2B gene loci, and chromosome 10q LOH and copy loss (Supplementary Fig. S2), in which the PTEN locus was included in 7:46 (15%) of cases.

FL-associated 10q lesions co-occurred with 6q-MDR2 lesions (log odds ratio, 2.4, 95% confidence interval, 0.7-4.1).

Most p53 mutations in FL are not associated with structural changes at 17p. CLL patients with del17p by fluorescence in situ hybridization have a very poor prognosis, with an average survival of about 2.5 years (9). Given the importance of this cytogenetic abnormality in CLL, we proceeded to analyze the 17p regions in our FL cohort.

In Fig. 4A , we have displayed LOH calls on 17p. Three patients showed LOH of about 7 to 18 Mb length at this chromosomal position, a frequency of 3:58, or about 5%. Unlike the situation in CLL, where del17p invariably deletes one p53 allele, one of the three FL cases (case 65) did not involve the p53 locus. In Fig. 4B, we display matching copy number data and, in Fig. 4C, a p53 mutation analysis.


Figure 4
View larger version (50K):
[in this window]
[in a new window]

  		Fig. 4. Comparative analysis of chromosome 17p LOH, copy number estimates, and p53 mutation analysis. A, LOH display for chromosome 17p. Vertical solid lines, 10-Mb intervals. Vertical arrow, location of the p53 gene at 17p13.1. B, copy number display for chromosome 17p. Vertical arrow, location of the p53 gene at 17p13.1. The estimated copy numbers for all SNP positions for FL 67 are shown below the chromosome 17p display; red line, 2N state. C, p53 mutation analysis for exons 5 to 9. Column 1, sample numbers. Column 2, nucleotide and amino acid residue for that position in the cDNA NM_000546 or genomic DNA (same result); column 3, nucleotide and amino acid residue for that position in FACS-sorted CD20+ cells. Red, p53 mutations without 17p LOH or copy loss; green, 17p LOH and copy loss without p53 mutations; purple, 17p LOH without p53 mutations; black, 17p LOH and copy loss with p53 mutations; blue, 17p copy loss and p53 mutation data not available.

 
It is commonly assumed that the del17p indicates that p53 is mutated on the retained allele. We decided to test this relationship directly and found 6:58 (10%) patients with mutations in p53 (exons 5-9), including 4 patients with missense mutations and 2 patients with frameshifts.

Interestingly, del17p did not predict for mutated p53, as only 1:6 cases (FL 67) had both a del17p involving the p53 gene and a p53 mutation on the retained allele. Most p53 mutations occurred without notable chromosomal alterations at 17p.

Finally, p53 mutations co-occurred with 6q-MDR2 lesions, 8q24 gains, and 16p LOH (log odds ratios, 2.3, 2.3, and 2.0; 95% confidence intervals, 0.5-4.2, 0.5-4.2 and 0.2-3.8, respectively).

The non-Hodgkin's lymphoma-associated amplification on chromosome 2p15-16 invariably includes BCL11A and REL. Hodgkin's lymphoma and NHL, including FL, are known to harbor a genomic amplification on chromosome 2p15-16 in 10% to 40% of samples (36, 37). In Fig. 5A and B , we display copy number estimates for chromosome 2p15-16 for all 58 samples. As can be seen, 9:58 (16%) of samples showed an amplification of varying length, and a minimally amplified region could be derived spanning ~600 kb (physical position, 60.5-61.1 Mb on chr.2). These copy gains were confirmed by Q-PCR with primers/probe for BCL11A (Supplementary Table S2). Interestingly, even this relatively small consensus region contained both BCL11A and REL, providing support to the hypothesis that both genes may play a pathogenetic role in FL (38).


Figure 5
View larger version (77K):
[in this window]
[in a new window]

  		Fig. 5. The lymphoma-associated amplification on chromosome 2p15-16 invariably includes BCL11A and REL. A, genomic copy number display for parts of chromosome 2. The physical positions of BCL11A and REL are indicated. Arrows, samples with amplifications. The estimated copy numbers for all SNP positions for FL 53 are displayed below the chromosome 2 display; red line, 2N state. B, genomic copy number display for a subregion of chromosome 2p15-16, with a schema of the BCL11A and REL loci in relation to individual SNP positions.

 
Delineation of a minimal region of amplification on chromosome 8q. A genome-wide review of copy number data showed frequent low-level amplifications of all or parts of chromosome 8 in 10:58 (17%) of the specimens (see Fig. 6 ). Further analysis narrowed a region of minimal amplification to 8q24.22-8q24.23 (physical boundaries 134.43-telomere at ~144 Mb), thereby excluding the Myc locus, which has previously been suspected as being the primary target of 8q amplifications. These copy gains were confirmed by Q-PCR with primers/probe for C8orf17 (Supplementary Table S2). Scanning of 8q24.22-8q24.23 identified a minimum of four genes that have previously been implicated in tumor biology, including the potassium channel KCNK9 (39), the NF{kappa}B-activating protein NIBP (40), the protein tyrosine kinase PTK2/FAK (41), and the protein tyrosine phosphatase PTP4A3 (42).


Figure 6
View larger version (106K):
[in this window]
[in a new window]

  		Fig. 6. Identification of a minimally amplified region on chromosome 8q24.22-23 in FL that excludes Myc. The boundaries of a minimal amplified region on chromosome 8q24.22-24.3 are indicated. The estimated copy numbers for all SNP positions for FL 67 are displayed below the chromosome 8 display; red line, 2N state.

 
Amplifications of der(18)t(14;18) do not involve Bcl-2. The genetic hallmark lesion of FL is the translocation t(14;18), juxtaposing the Bcl-2 gene and the immunoglobulin heavy-chain locus enhancer elements. Fine mapping of the breakpoints showed that the part of chromosome 18 that did not contain Bcl-2 was present in three copies as der(18)t(14;18) (11), as previously reported (43), whereas the remainder of this chromosome was disomic (Supplementary Fig. S3A and B). Trisomy 18 (black arrows) was detected as well.

This analysis suggests (a) that chromosome 18 may harbor an additional, amplified gene with relevance in FL biology located on der(18)t(14;18) other than Bcl-2; and (b) that a significant fraction of additional FL cases harbor trisomy 18, suggesting a mechanism to explain increased Bcl-2 expression independent of t(14;18) (43).


   Discussion
Top
 Abstract
 Materials and Methods
 Results
 Discussion
References
 
In this study we are presenting high-density genomic profiling data, including LOH and copy number changes, for a series of FL specimens. These data have implications for basic as well as clinical research in FL, are novel in nature, and have not been reported for this important malignancy.

We have described novel, high-frequency regions of LOH and copy loss as well as copy-neutral LOH (uniparental disomy) on multiple chromosomes in the FL genome. Copy-neutral LOH is not detectable using either conventional cytogenetics or array-CGH and, therefore, has not been previously described in FL.

The occurrence of alterations at 1p36 in about half of all FL may be of clinical significance because a similar region has been shown to confer poor prognosis for children with neuroblastoma (27). It certainly makes analysis of the impact of this lesion on FL outcome a research priority.

Chromosome 6p LOH spans the IRF4 locus. This may be significant to FL pathogenesis because others have recently shown that the transcriptional regulator IRF4 is necessary for B cell germinal center exit (44).

Deletion 6q has been reported to confer negative prognostic impact on patients with NHL, but a critical gene has not been identified in any of the studied regions.

Analysis of a novel homozygously deleted region at 6q23.3-24.1 identifies A20 and PERP as two novel genes of potential interest in FL biology.

A20 is a negative regulator of NF{kappa}B and Toll-like receptor signaling (32). Studies in multiple cellular and murine systems suggest that reduction in A20 function results in sustained NF{kappa}B signaling, a molecular feature of many NHL subtypes (45). A20 knock-out animals develop a lethal inflammatory syndrome and die shortly after birth, precluding possible observation of tumor proneness (46).

PERP, a gene induced by p53, executes part of the p53 apoptosis program. Radiation-induced apoptosis in thymocytes or neuronal cells is impaired in PERP–/– mice (47). Down-regulation of PERP has been implicated in the poor outcome of patients with various cancers (48, 49). Both genes are attractive targets for future studies on well-preserved FL tissue.

The data presented on the well-known amplification on chromosome 2p15-16 show that BCL11A and REL are always coamplified. BCL11A is a Krueppel zinc finger transcription factor essential for pre–B cell development, with restricted expression in tissues; it should be investigated further for the role it assumes in malignant B cell physiology (9, 50).

The analysis of a minimally amplified region on chromosome 8q24 excludes Myc as the critically relevant gene and suggests a short list of genes that all have proven roles in cancer cell properties or cell proliferation.

Combined analysis of chromosome arm 17p for LOH, copy loss, and p53 mutations shows that most p53 mutations in FL are not associated with chromosomal alterations at 17p, and that the development of clinically useful tests based on genomic profiling should include p53 sequence analysis.

In summary, this large genomic profiling study extends knowledge about the FL genome and suggests basic and clinical research implications. The high-resolution mapping data highlight novel chromosomal regions of potential importance to FL biology and candidate genes worthy of further analysis. The clinical importance of these findings awaits testing of various genetic FL subgroups for prognostic power.


   Footnotes
 
Grant support: Leukemia and Lymphoma Society of America Special Fellow Award and a Leukemia Research Foundation New Investigator Award. This research is supported (in part) by the NIH through the University of Michigan's Cancer Center Support Grant (5 P30 CA46592).

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.

Note: Supplementary data for this article are available at Clinical Cancer Research Online (http://clincancerres.aacrjournals.org/).

C.W. Ross and P.D. Ouillette contributed equally to this work.

4 http://frodo.wi.mit.edu/cgi-bin/primer3/primer3_www.cgi Back

Received 2/21/07; revised 4/23/07; accepted 5/18/07.


   References
Top
 Abstract
 Materials and Methods
 Results
 Discussion
 References
 

  1. Lipford E, Wright JJ, Urba W, et al. Refinement of lymphoma cytogenetics by the chromosome 18q21 major breakpoint region. Blood 1987;70:1816–23.[Abstract/Free Full Text]
  2. Negrini M, Silini E, Kozak C, et al. Molecular analysis of mbcl-2: structure and expression of the murine gene homologous to the human gene involved in follicular lymphoma. Cell 1987;49:455–63.[CrossRef][Medline]
  3. Bende RJ, Smit LA, van Noesel CJ. Molecular pathways in follicular lymphoma. Leukemia 2007;21:18–29.[CrossRef][Medline]
  4. Farinha P, Masoudi H, Skinnider BF, et al. Analysis of multiple biomarkers shows that lymphoma-associated macrophage (LAM) content is an independent predictor of survival in follicular lymphoma (FL). Blood 2005;106:2169–74.[Abstract/Free Full Text]
  5. Dave SS, Wright G, Tan B, et al. Prediction of survival in follicular lymphoma based on molecular features of tumor-infiltrating immune cells. N Engl J Med 2004;351:2159–69.[Abstract/Free Full Text]
  6. Lee AM, Clear AJ, Calaminici M, et al. Number of CD4+ cells and location of forkhead box protein P3-positive cells in diagnostic follicular lymphoma tissue microarrays correlates with outcome. J Clin Oncol 2006;24:5052–9.[Abstract/Free Full Text]
  7. Tilly H, Rossi A, Stamatoullas A, et al. Prognostic value of chromosomal abnormalities in follicular lymphoma. Blood 1994;84:1043–9.[Abstract/Free Full Text]
  8. Viardot A, Moller P, Hogel J, et al. Clinicopathologic correlations of genomic gains and losses in follicular lymphoma. J Clin Oncol 2002;20:4523–30.[Abstract/Free Full Text]
  9. Dohner H, Stilgenbauer S, Benner A, et al. Genomic aberrations and survival in chronic lymphocytic leukemia. N Engl J Med 2000;343:1910–6.[Abstract/Free Full Text]
  10. Grimwade D, Walker H, Oliver F, et al. The importance of diagnostic cytogenetics on outcome in AML: analysis of 1,612 patients entered into the MRC AML 10 trial. The Medical Research Council Adult and Children's Leukaemia Working Parties. Blood 1998;92:2322–33.[Abstract/Free Full Text]
  11. Hoglund M, Sehn L, Connors JM, et al. Identification of cytogenetic subgroups and karyotypic pathways of clonal evolution in follicular lymphomas. Genes Chromosomes Cancer 2004;39:195–204.[CrossRef][Medline]
  12. Horsman DE, Connors JM, Pantzar T, Gascoyne RD. Analysis of secondary chromosomal alterations in 165 cases of follicular lymphoma with t(14;18). Genes Chromosomes Cancer 2001;30:375–82.[CrossRef][Medline]
  13. Avet-Loiseau H, Vigier M, Moreau A, et al. Comparative genomic hybridization detects genomic abnormalities in 80% of follicular lymphomas. Br J Haematol 1997;97:119–22.[CrossRef][Medline]
  14. Bentz M, Werner CA, Dohner H, et al. High incidence of chromosomal imbalances and gene amplifications in the classical follicular variant of follicle center lymphoma. Blood 1996;88:1437–44.[Abstract/Free Full Text]
  15. Yunis JJ, Frizzera G, Oken MM, McKenna J, Theologides A, Arnesen M. Multiple recurrent genomic defects in follicular lymphoma. A possible model for cancer. N Engl J Med 1987;316:79–84.[Abstract]
  16. Vogelstein B, Kinzler KW. Cancer genes and the pathways they control. Nat Med 2004;10:789–99.[CrossRef][Medline]
  17. Walker BA, Leone PE, Jenner MW, et al. Integration of global SNP-based mapping and expression arrays reveals key regions, mechanisms, and genes important in the pathogenesis of multiple myeloma. Blood 2006;108:1733–43.[Abstract/Free Full Text]
  18. Lieberfarb ME, Lin M, Lechpammer M, et al. Genome-wide loss of heterozygosity analysis from laser capture microdissected prostate cancer using single nucleotide polymorphic allele (SNP) arrays and a novel bioinformatics platform dChipSNP. Cancer Res 2003;63:4781–5.[Abstract/Free Full Text]
  19. Irving JA, Bloodworth L, Bown NP, Case MC, Hogarth LA, Hall AG. Loss of heterozygosity in childhood acute lymphoblastic leukemia detected by genome-wide microarray single nucleotide polymorphism analysis. Cancer Res 2005;65:3053–8.[Abstract/Free Full Text]
  20. Zhao X, Li C, Paez JG, et al. An integrated view of copy number and allelic alterations in the cancer genome using single nucleotide polymorphism arrays. Cancer Res 2004;64:3060–71.[Abstract/Free Full Text]
  21. Dutt A, Beroukhim R. Single nucleotide polymorphism array analysis of cancer. Curr Opin Oncol 2007;19:43–9.[Medline]
  22. LaFramboise T, Weir BA, Zhao X, et al. Allele-specific amplification in cancer revealed by SNP array analysis. PLoS Comput Biol 2005;1:e65.[CrossRef][Medline]
  23. Di X, Matsuzaki H, Webster TA, et al. Dynamic model based algorithms for screening and genotyping over 100 K SNPs on oligonucleotide microarrays. Bioinformatics 2005;21:1958–63.[Abstract/Free Full Text]
  24. Tworek JA, Singleton TP, Schnitzer B, Hsi ED, Ross CW. Flow cytometric and immunohistochemical analysis of small lymphocytic lymphoma, mantle cell lymphoma, and plasmacytoid small lymphocytic lymphoma. Am J Clin Pathol 1998;110:582–9.
  25. Nathwani B, Harris NL, Weisenburger D. Follicular lymphoma. In: Jaffe E, Harris NL, Stein H, Vardiman JW, editors. Pathology and genetics of tumours of haematopoietic and lymphoid tissues. Lyon: IARC Press; 2001. p. 162–7.
  26. Lin M, Wei LJ, Sellers WR, Lieberfarb M, Wong WH, Li C. dChipSNP: significance curve and clustering of SNP-array–based loss-of-heterozygosity data. Bioinformatics 2004;20:1233–40.[Abstract/Free Full Text]
  27. Attiyeh EF, London WB, Mosse YP, et al. Chromosome 1p and 11q deletions and outcome in neuroblastoma. N Engl J Med 2005;353:2243–53.[Abstract/Free Full Text]
  28. Henderson LJ, Okamoto I, Lestou VS, et al. Delineation of a minimal region of deletion at 6q16.3 in follicular lymphoma and construction of a bacterial artificial chromosome contig spanning a 6-megabase region of 6q16–21. Genes Chromosomes Cancer 2004;40:60–5.[CrossRef][Medline]
  29. Offit K, Parsa NZ, Gaidano G, et al. 6q deletions define distinct clinico-pathologic subsets of non-Hodgkin's lymphoma. Blood 1993;82:2157–62.[Abstract/Free Full Text]
  30. Gaidano G, Hauptschein RS, Parsa NZ, et al. Deletions involving two distinct regions of 6q in B-cell non-Hodgkin lymphoma. Blood 1992;80:1781–7.[Abstract/Free Full Text]
  31. Offit K, Jhanwar SC, Ladanyi M, Filippa DA, Chaganti RS. Cytogenetic analysis of 434 consecutively ascertained specimens of non-Hodgkin's lymphoma: correlations between recurrent aberrations, histology, and exposure to cytotoxic treatment. Genes Chromosomes Cancer 1991;3:189–201.[Medline]
  32. Liu YC, Penninger J, Karin M. Immunity by ubiquitylation: a reversible process of modification. Nat Rev Immunol 2005;5:941–52.[CrossRef][Medline]
  33. Attardi LD, Reczek EE, Cosmas C, et al. PERP, an apoptosis-associated target of p53, is a novel member of the PMP-22/gas3 family. Genes Dev 2000;14:704–18.[Abstract/Free Full Text]
  34. Pasqualucci L, Compagno M, Houldsworth J, et al. Inactivation of the PRDM1/BLIMP1 gene in diffuse large B cell lymphoma. J Exp Med 2006;203:311–7.[Abstract/Free Full Text]
  35. Tam W, Gomez M, Chadburn A, Lee JW, Chan WC, Knowles DM. Mutational analysis of PRDM1 indicates a tumor-suppressor role in diffuse large B-cell lymphomas. Blood 2006;107:4090–100.[Abstract/Free Full Text]
  36. Houldsworth J, Mathew S, Rao PH, et al. REL proto-oncogene is frequently amplified in extranodal diffuse large cell lymphoma. Blood 1996;87:25–9.[Abstract/Free Full Text]
  37. Martin-Subero,JI, Gesk S, Harder L, et al. Recurrent involvement of the REL and BCL11A loci in classical Hodgkin lymphoma. Blood 2002;99:1474–7.[Abstract/Free Full Text]
  38. Gilmore TD, Kalaitzidis D, Liang MC, Starczynowski DT. The c-Rel transcription factor and B-cell proliferation: a deal with the devil. Oncogene 2004;23:2275–86.[CrossRef][Medline]
  39. Pei L, Wiser O, Slavin A, et al. Oncogenic potential of TASK3 (Kcnk9) depends on K+ channel function. Proc Natl Acad Sci U S A 2003;100:7803–7.[Abstract/Free Full Text]
  40. Hu WH., Pendergast JS, Mo XM, et al. NIBP, a novel NIK and IKK(ß)-binding protein that enhances NF-({kappa})B activation. J Biol Chem 2005;280:29233–41.[Abstract/Free Full Text]
  41. McLean GW, Carragher NO, Avizienyte E, Evans J, Brunton VG, Frame MC. The role of focal-adhesion kinase in cancer—a new therapeutic opportunity. Nat Rev Cancer 2005;5:505–15.[CrossRef][Medline]
  42. Stephens BJ, Han H, Gokhale V, Von Hoff DD. PRL phosphatases as potential molecular targets in cancer. Mol Cancer Ther 2005;4:1653–61.[Abstract/Free Full Text]
  43. Galteland E, Sivertsen EA, Svendsrud DH, et al. Translocation t(14;18) and gain of chromosome 18/BCL2: effects on BCL2 expression and apoptosis in B-cell non-Hodgkin's lymphomas. Leukemia 2005;19:2313–23.[CrossRef][Medline]
  44. Klein U, Casola S, Cattoretti G, et al. Transcription factor IRF4 controls plasma cell differentiation and class-switch recombination. Nat Immunol 2006;7:773–82.[CrossRef][Medline]
  45. Jost PJ, Ruland J. Aberrant NF-{{kappa}}B signaling in lymphoma: mechanisms, consequences and therapeutic implications. Blood 2006;7:2700–7.
  46. Lee EG, Boone DL, Chai S, et al. Failure to regulate TNF-induced NF-{kappa}B and cell death responses in A20-deficient mice. Science 2000;289:2350–4.
  47. Ihrie RA, Reczek E, Horner JS, et al. Perp is a mediator of p53-dependent apoptosis in diverse cell types. Curr Biol 2003;13:1985–90.
  48. Luthra R, Luthra MG, Izzo J, et al. Biomarkers of response to preoperative chemoradiation in esophageal cancers. Semin Oncol 2006;3 Suppl 11:2–5.[Medline]
  49. Paraoan L, Gray D, Hiscott P, Ebrahimi B, Damato B, Grierson I. Expression of p53-induced apoptosis effector PERP in primary uveal melanomas: downregulation is associated with aggressive type. Exp Eye Res 2006;83:911–9.[CrossRef][Medline]
  50. Satterwhite E, Sonoki T, Willis TG et al. The BCL11 gene family: involvement of BCL11A in lymphoid malignancies. Blood 2001;98:3413–20.[Abstract/Free Full Text]



This article has been cited by other articles:


Home page
 haematolHome page
S. Hartmann, J. I. Martin-Subero, S. Gesk, J. Husken, M. Giefing, I. Nagel, J. Riemke, A. Chott, W. Klapper, M. Parrens, et al.
Detection of genomic imbalances in microdissected Hodgkin and Reed-Sternberg cells of classical Hodgkin's lymphoma by array-based comparative genomic hybridization
Haematologica, September 1, 2008; 93(9): 1318 - 1326.
[Abstract] [Full Text] [PDF]

Home page
 BloodHome page
L. Kujawski, P. Ouillette, H. Erba, C. Saddler, A. Jakubowiak, M. Kaminski, K. Shedden, and S. N. Malek
Genomic complexity identifies patients with aggressive chronic lymphocytic leukemia
Blood, September 1, 2008; 112(5): 1993 - 2003.
[Abstract] [Full Text] [PDF]

Home page
 haematolHome page
N. A. Johnson and R. D. Gascoyne
Gene expression signatures in follicular lymphoma: are they ready for the clinic?
Haematologica, July 1, 2008; 93(7): 982 - 987.
[Full Text] [PDF]

Home page
 Cancer Res.Home page
P. Ouillette, H. Erba, L. Kujawski, M. Kaminski, K. Shedden, and S. N. Malek
Integrated Genomic Profiling of Chronic Lymphocytic Leukemia Identifies Subtypes of Deletion 13q14
Cancer Res., February 15, 2008; 68(4): 1012 - 1021.
[Abstract] [Full Text] [PDF]

Home page
 BloodHome page
C. Saddler, P. Ouillette, L. Kujawski, S. Shangary, M. Talpaz, M. Kaminski, H. Erba, K. Shedden, S. Wang, and S. N. Malek
Comprehensive biomarker and genomic analysis identifies p53 status as the major determinant of response to MDM2 inhibitors in chronic lymphocytic leukemia
Blood, February 1, 2008; 111(3): 1584 - 1593.
[Abstract] [Full Text] [PDF]

This Article
Right arrow Abstract Freely available
Right arrow Full Text (PDF)
Right arrow Alert me when this article is cited
Right arrow Alert me if a correction is posted
Services
Right arrow Similar articles in this journal
Right arrow Similar articles in PubMed
Right arrow Alert me to new issues of the journal
Right arrow Download to citation manager
Right arrow reprints & permissions
Citing Articles
Right arrow Citing Articles via HighWire
Right arrow Citing Articles via Google Scholar
Google Scholar
Right arrow Articles by Ross, C. W.
Right arrow Articles by Malek, S. N.
Right arrow Search for Related Content
PubMed
Right arrow PubMed Citation
Right arrow Articles by Ross, C. W.
Right arrow Articles by Malek, S. N.

HOME HELP FEEDBACK SUBSCRIPTIONS ARCHIVE SEARCH TABLE OF CONTENTS
Cancer Research Clinical Cancer Research
Cancer Epidemiology Biomarkers & Prevention Molecular Cancer Therapeutics
Molecular Cancer Research Cancer Prevention Research
Cancer Prevention Journals Portal Cancer Reviews Online
Annual Meeting Education Book Meeting Abstracts Online