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Cancer Genes and Genomics

Comprehensive Profiling of 8p11-12 Amplification in Breast Cancer

Véronique Gelsi-Boyer, Béatrice Orsetti, Nathalie Cervera, Pascal Finetti, Fabrice Sircoulomb, Carole Rougé, Laurence Lasorsa, Anne Letessier, Christophe Ginestier, Florence Monville, Séverine Esteyriès, José Adélaïde, Benjamin Esterni, Catherine Henry, Stephen P. Ethier, Frédéric Bibeau, Marie-Joëlle Mozziconacci, Emmanuelle Charafe-Jauffret, Jocelyne Jacquemier, François Bertucci, Daniel Birnbaum, Charles Theillet and Max Chaffanet
Véronique Gelsi-Boyer
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Béatrice Orsetti
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Nathalie Cervera
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Pascal Finetti
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Fabrice Sircoulomb
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Carole Rougé
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Laurence Lasorsa
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Anne Letessier
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Christophe Ginestier
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Florence Monville
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Séverine Esteyriès
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José Adélaïde
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Benjamin Esterni
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Catherine Henry
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Stephen P. Ethier
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Frédéric Bibeau
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Marie-Joëlle Mozziconacci
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Emmanuelle Charafe-Jauffret
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Jocelyne Jacquemier
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François Bertucci
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Daniel Birnbaum
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Charles Theillet
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DOI: 10.1158/1541-7786.MCR-05-0128 Published December 2005
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Abstract

In human carcinomas, especially breast cancer, chromosome arm 8p is frequently involved in complex chromosomal rearrangements that combine amplification at 8p11-12, break in the 8p12-21 region, and loss of 8p21-ter. Several studies have identified putative oncogenes in the 8p11-12 amplicon. However, discrepancies and the lack of knowledge on the structure of this amplification lead us to think that the actual identity of the oncogenes is not definitively established. We present here a comprehensive study combining genomic, expression, and chromosome break analyses of the 8p11-12 region in breast cell lines and primary breast tumors. We show the existence of four amplicons at 8p11-12 using array comparative genomic hybridization. Gene expression analysis of 123 samples using DNA microarrays identified 14 genes significantly overexpressed in relation to amplification. Using fluorescence in situ hybridization analysis on tissue microarrays, we show the existence of a cluster of breakpoints spanning a region just telomeric to and associated with the amplification. Finally, we show that 8p11-12 amplification has a pejorative effect on survival in breast cancer. (Mol Cancer Res 2005;3(12):655–67)

Keywords:
  • breast cancer
  • aCGH
  • DNA microarrays
  • tissue microarrays
  • FISH
  • DNA amplification
  • chromosome 8
  • 8p12

Introduction

The short arm of chromosome 8 is a frequent target of genetic alterations in a wide variety of human cancers (1, 2). In breast cancer, the 8p12-21 region often displays complex combinations of chromosomal breaks, losses, and DNA amplification (3-11).8,9 Loss-of-heterozygosity studies have identified at least two regions of loss (7, 11), whereas recurrent chromosome breaks are found in 6% of breast cancers at the NRG1 locus (12, 13). Amplification of 8p11-12 occurs in 10% to 15% of breast cancers (14-17) and is often visible cytogenetically as homogeneously staining region (9, 18-20). The frequency of 8p11-12 alterations contrasts with our limited knowledge of the genes involved, although several candidates have been suggested. No oncogene from the 8p11-12 amplification unit (amplicon) has been identified with certainty. The role of the FGFR1 gene, which codes for a tyrosine kinase receptor, has been evoked (17), but normal levels of FGFR1 expression in some amplified tumors have suggested that it may not be the actual or sole oncogene involved (21).

Due to its importance in breast cancer, several recent studies have aimed at a better definition of the 8p11-12 amplification. Ray et al. characterized the 8p11-12 amplicon in three breast tumor cell lines (21). Several potential oncogenes other than FGFR1 were suggested. Reyal et al. analyzed transcriptome data of 130 invasive breast carcinomas using an approach based on the calculation, for each gene, of the correlation between its expression profile and that of its neighbors (22). A list of candidate oncogenes has been established, including some proposed previously (21). However, this approach may have excluded isolated candidate genes and did not inform clearly on the structure of the amplicon. The most extensive study of 8p amplification to date has been reported by Garcia et al. (23). These authors studied 80 breast and ovarian tumors and cell lines by using both high-resolution array comparative genomic hybridization (aCGH) and gene expression analyses. They defined a 1-Mb region of common amplification. This region excluded most previously proposed candidate genes, including FGFR1, and contained four potential oncogenes, FLJ14299, SPFH domain family, member 2, related to stomatin, a component of lipid rafts (SPFH2/C8orf2), BRF2, and RAB11FIP1, which showed good correlation between amplification and overexpression. A novel amplicon resulting from NRG1 rearrangements and associated with poor prognosis was recently described (24). This small amplicon is included in the 1-Mb minimal amplicon defined by Garcia et al. (23) and contains two previously proposed candidate genes (22, 23). The four studies provided very valuable information. However, the structure of the amplification can be refined further, especially with regard to its centromeric part and its association with breaks and to the number and identity of potential oncogenes it contains.

We report here a detailed genomic analysis of the 8p11-12 region in a series of breast cell lines and primary breast tumors. Using aCGH, we show that the 8p11-12 amplification can be divided in four amplicons. Correlation analysis between amplification and gene expression identified several candidate oncogenes. Using fluorescence in situ hybridization (FISH) on primary breast tumors organized in tissue microarrays, we identified a cluster of breakpoints just upstream of the amplification. Finally, we show the clinical significance of 8p12 amplicons in breast cancers.

Results

aCGH Profiles Showed Multiphasic DNA Amplification at 8p12 Associated to Loss of Distal 8p

We studied genomic alterations at 8p in 37 breast cell lines and 62 primary breast tumors by using a custom-made BAC array that included a near tiling-path coverage from centromere (43.2 Mb) to 8p21 (26.1 Mb). Examples of profiles are shown in Fig. 1, and complete results for every sample analyzed are shown in Supplementary Fig. S1.

FIGURE 1.
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FIGURE 1.

Genomic profiling of 8p11-12 amplification in breast cancers. A. Compilation of interpreted 8p11-12 aCGH profiles in breast cell lines and primary tumors exhibiting gains in this region. Regions were considered to be gained or lost when at least two consecutive BAC clones presented a log2 ratio > 0.25 (gain) and less than −0.25 (loss). Each square represents one BAC clone: green, loss; red, gain; open square normal, no square no data available. Clones are ordered by chromosomal position from telomere to centromere according to the May 2004 University of California at Santa Cruz freeze. Only samples presenting gains are shown. Samples are numbered as in Supplementary Table S1: breast cancer cell lines: 3, BT474; 4, BT483; 6, CAMA1; 8, HCC38; 9, HCC1187; 12, HCC1500; 13, HCC1569; 15, HCC1954; 16, HCC2218; 17, Hs578T; 19, MDA-MB-134; 21, MDA-MB-175; 24, MDA-MB-415; 28, S68; 29, SK-BR-3; 30, SUM44; 31, SUM52; 32, SUM149; 33, SUM185; primary tumors: 3, MA4420; 6, MA4814; 8, MA5103; 10, MA5357; 11, MA5633; 12, MA5731; 13, MA6137; 14, MA6165; 15, MA6795; 17, MA7371; 18, MA7499; 19, MA7641; 20, MA7767; 21, MA7809; 23, MA8189; 25, MA8404; 26, MA8406; 28, MA8525; 29, MA9377; 31, MA11934; 34, VA4380; 43, VA6052; 48, VA6190; 49, VA6204; 50, VA6219; 51, VA6270; 54, VA6582; 57, VA6660; 60, VA7106. Bold lines and numbers at the bottom of the Mb scale indicate regions shown as blowups in B. B. Detailed genomic profiles of four subregions of amplification at 8p11-12. The aCGH profiles of tumors or cell lines showing gains in the considered interval were plotted. Subregion 1, 35.52-38.44 Mb; subregion 2, 37.59-40.10 Mb; subregion 3, 38.65-41.35 Mb; subregion 4, 40.88-42.58 Mb. Y axis, log2 ratios; X axis, midpoint Mb position of each clone covering the subregion. The threshold used to define amplicons was log2 ratio > 0.75. Horizontal bars at the bottom of the plots, the region encompassed in the amplicon.

Samples were not analyzed at random; several of them were preselected based on either amplification or chromosomal rearrangement at 8p observed by either FISH or Southern blotting. As a result, chromosome 8p alterations were frequent in our series with 87.1% of the tumors and 100% of the cell lines showing either gains or losses. Tumors and cell lines showed similar aCGH profiles. Losses were prevalent from telomere to 8p12 and gains in the 8p12-11 region. Transitions between gains and losses were concentrated in a region located at the 8p12-8p21 boundary. Individual aCGH profiles showed wavy patterns, suggesting the existence of several peaks of amplification within this region of gain. Compilation of gains and losses data from all samples further supported this idea (Supplementary Fig. S2A). Alignment of the regions of gains showed three recurrent interruptions and four subregions of amplification (Fig. 1A). The latter were designated amplicons A1 to A4, from telomere to centromere.

The boundaries of the amplified subregions were positioned in the immediate nonamplified neighbor BAC clones. In addition, to ascertain that the subregion selected corresponded strictly to an amplification common to several tumor samples, we determined its core by using a stringent cutoff and considering only BAC clones whose log2 ratio exceeded 0.75 (Fig. 1B). Amplicons and their cores were then characterized. Locations, BAC and gene contents, and sizes and cores of the amplicons are detailed in Fig. 2 and Table 1. Although we defined amplicon A1 as a single core, aCGH profiles indicated the existence of two subpeaks, a main one centered ∼37.3 Mb and a second at 37.8 Mb, which we designated A1′ (Fig. 1B). Profiles of the other amplicons did not show clear-cut subpeaks. According to National Center for Biotechnology Information Build 35 of the Human Genome Sequence, amplicons A1 to A4 contained 17, 25, 8, and 10 genes or part of genes, respectively (Table 1; Fig. 2B and C). The four amplicons showed separate cores but overlapped at their extremities: A1/A2, A2/A3, and A3/A4 overlaps included 11, 2, and 3 genes, respectively (Table 1; Fig. 2B and C). The amplicons could be observed independently in some samples (Fig. 1A). Thus, DNA amplification at 8p11-12 presented a complex structure, suggesting multiple causal elements.

FIGURE 2.
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FIGURE 2.

Genetic map of 8p11-12 and outline of alterations found in breast cancer. A. Mb scale of the region and corresponding cytogenetic banding. B. Genes mapping in the interval of interest. C. Boundaries (lines) and cores (enlarged lines) of the four amplicons. D. Intervals with identified chromosomal breaks. Cell lines in which they have been characterized are indicated. Boxes, intervals in which breaks have been determined in primary tumors by FISH on tissue microarray. Blue boxes, number of primary tumors presenting breaks in the BPC2 region (defined by opened box). BPC1 region spanning NRG1 was reported previously (12, 13). E. Numbers in boxes, frequency of amplification observed in a given interval in tumors by FISH on tissue microarray. F. BAC clones used as FISH probes on either metaphases or tissue microarray. Pools of BAC clones used as probes in FISH on tissue microarray and regions covered are indicated as P1 to P6 (for more details, see Supplementary Table S4). Map and gene names were taken from the Build 35 from National Center for Biotechnology Information.

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Table 1.

Description of Boundaries, BAC Clone Coverage, and Gene Content for A1 to A4 Amplicons, Respectively

Gene Expression Profiling Revealed Overexpression of 8p11-12 Genes

Total RNA from 34 cell lines, 89 tumors, and 4 normal breast RNA pools were hybridized to whole-genome oligonucleotide DNA microarrays. After filtering, we focused our analysis on 261 genes mapped to chromosome 8p, of which 67 are located in 8p11-12. For each sample, gene expression levels were centered on the average levels obtained with the four normal breast samples. Expression profiling data were classified by hierarchical clustering (Fig. 3A). In data sets, genes (rows) were ordered according to their chromosomal location, whereas samples (columns) were classified according to similarity of their expression profiles. Expression data were color-coded: red for overexpression and green for underexpression compared with normal breast samples. Expression profiles displayed contiguous red clusters containing 67 genes of the 8p11-12 region from telomere-NRG1 to centromere.

FIGURE 3.
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FIGURE 3.

Gene expression analysis of the 8p region and correlation with amplification. A total of 34 breast cancer cell lines, 89 primary tumors (123 samples), and 4 normal breast tissue RNA pools were hybridized to whole-genome Affymetrix U133 Plus 2.0 human oligoarrays. Genes located in 8p were filtered and their expression patterns were studied. Expression levels were centered on the average level obtained with normal breast RNA. Expression profiles were studied by hierarchical clustering. A. Zoom showing expression patterns of the 67 genes located between NRG1 and the centromere (8p11-12). Each row represents a gene; each column represents a sample. Genes are ordered according to their Mb position (http://genome.ucsc.edu/). Log2-transformed expression level of each gene in a single sample is relative to its abundance across normal breast sample and is depicted according to the color scale (bottom). The dendrogram of samples (above matrix) represents overall similarities in gene expression profiles. B. Correlation transcriptome map of 8p11-12 between NRG1 and the centromere in 123 breast samples. The TCS evaluates the correlation between the expression profile of each gene and those of its neighbors. The diagram shows the TCS for each gene: dot, a gene; orange line, significant threshold (equal to 0.33) for the TCS; a gene with a score exceeding the threshold is significantly correlated with its neighbors. C. Discriminating score of the 11 genes identified by supervised analysis as significantly differentially expressed between samples with amplification and samples without amplification within each of the four amplicons (A1, A2, A3, or A4). A total of 42 samples (25 cell lines and 17 tumors) common to aCGH and RNA expression experiments were analyzed: 29 samples did not present any amplification and 13 exhibited A1, A2, A3, and/or A4 amplification. Bars, genes whose expression correlates with the amplification of one amplicon. Results were color-coded according to which amplicon correlated with increased expression: green, A1; blue, A2; purple, A3; yellow, A4. The significance thresholds producing <0.1 false positive are 0.65, 0.62, and 0.77, respectively. D. Mann-Whitney test of the same data set as discriminating score. Color codes are as in discriminating score. E. Chromosomal location and limits of the four amplicons (A1-A4 from NRG1 to the centromere) as defined by aCGH. Genes significant in both discriminating score and Mann-Whitney tests are indicated in color. Loci with asterisks are not listed in Genome Browser but can be accessed in Entrez Gene.

Based on a published method (22), we defined a “transcriptome correlation map” of the 8p11-12 region that shows the degree of coexpression of each gene with its neighbor genes. With a stringent significance threshold (1/10.000), 16 of the 67 genes (SPFH2, BRF2, RAB11FIP1, EIF4EBP1, ASH2L, LSM1, BAG4, DDH domain containing 2 (DDHD2), HTPAP, Wolf-Hirschhorn syndrome candidate 1-like 1 (WHSC1L1), AP3M2, IKBKB, POLB, VDAC3, SLC20A2, and LOC114926) displayed expression profile significantly correlated with the expression of neighbor genes. Fig. 3B shows the diagram of transcriptome correlation scores (TCS) measured for each probe set, organized according to chromosomal location. The distribution of the correlated genes was bimodal with a first peak at 37.7 to 38.3 Mb and a second peak at 42.1 to 42.5 Mb. Correlated gene expression could be due to coamplification. Therefore, we compared the transcriptome correlation map to the location of the four amplicons defined by aCGH (Fig. 3E). Genes whose expression correlated with neighbors included seven genes from A1 (SPFH2, BRF2, RAB11FIP1, EIF4EBP1, ASH2L, LSM1, and BAG4) and nine genes from A2 (BRF2, RAB11FIP1, EIF4EBP1, ASH2L, LSM1, BAG4, DDHD2, phosphatidic acid phosphatase type 2 domain containing 1B (HTPAP/PPAPDC1B), and WHSC1L1). Six were common to both amplicons A1 and A2. Whereas A3 did not contain any correlated gene, A4 included AP3M2 and IKBKB. Other genes with significant TCS were located centromeric to A4 (POLB, VDAC3, SLC20A2, and LOC114926).

Correlation between Gene Expression and Amplification Identified 14 Candidate Genes

To identify genes whose expression levels were significantly modified in relation to DNA copy number changes, a total of 42 samples (25 cell lines and 17 tumors) common to aCGH and RNA expression experiments were analyzed (Supplementary Table S1). Among them, 29 samples did not present amplification at any of the four amplicons and 13 exhibited A1, A2, A3, and/or A4 amplification. Samples presenting <33% of BAC clones with a log2 ratio exceeding 0.75 within the amplicon were not considered as amplified.

We applied two statistical tests (discriminating score and Mann-Whitney) to identify genes whose pattern of overexpression correlated with DNA amplification (Fig. 3C and D). Of the 67 8p11-12 genes, 24 were selected by either one or both methods. Fourteen were selected by both tests and considered as the best candidates. FLJ14299, SPFH2, proline synthetase cotranscribed homologue (PROSC), BRF2, and RAB11FIP1 correlated with A1 amplification, whereas LSM1, DDHD2, HTPAP, WHSC1L1, FGFR1, and TM2 domain containing 2 (BLP1/TM2D2) correlated with A2. The only gene correlating with A3 was GOLGA7, and two genes, MYST3 and AP2M3, correlated with A4 (Fig. 3E).

Chromosome Breaks Are Associated with 8p Amplification

Typical aCGH profiles showed sharp transitions at the telomeric end of the amplified region. In most cases, these transitions lead from gain at 8p11-12 to loss of 8p21-ter and were comprised in an interval between 35 and 37 Mb (Supplementary Figs. S1 and S2A). In some cases, illustrated by the SUM52 profile (Supplementary Fig. S2B), transitions were found at 32 Mb, colocalizing with a breakpoint cluster identified in the NRG1 locus (12, 13). We wondered whether the sharp transitions at 35 to 37 Mb were associated with chromosomal breaks. We used dual-color FISH analysis with probes covering the region between NRG1 (not included) and FGFR1 (Fig. 2F; Supplementary Table S4) in a series of 12 cell lines (Set 1, Supplementary Table S1) selected based on either the existence of transition in their aCGH profile or 8p11-21 rearrangement detected previously by mbanding FISH (25).

Results are shown in Fig. 4 and summarized in Supplementary Table S5. Eight cell lines (MDA-MB-134, BT-20, SUM44, HCC-1500, CAMA-1, BT-483, S68, and SUM225) showed breakpoints (Fig. 4B and C) in a 4-Mb interval delimited by BAC clones RP11-91P13 and RP11-265K5, which spanned the telomeric region of UNC5D to the 3′ end of FGFR1. Breakpoints involved UNC5D (35.5 Mb) in SUM44, a region comprising six genes (MGC33309, ADRB3, EIF4EP, ASH2L, STAR, and LSM1; 37.7-38.1 Mb) in S68, and a region comprising BAG4, DDHD2, HTPAP, and WHSC1L1 (38.1-38.3 Mb) in SUM225 (Fig. 2D).

FIGURE 4.
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FIGURE 4.

FISH characterization of breakpoints in 8p12 region. A. Localization of BPC2 on chromosome 8. B and C. Dual-color FISH analysis of cell lines using combinations of BAC probes. BPC2 affects chromosome 8 derivatives present in SUM44 (B) and BT-20, CAMA-1, MDA-MB-134, and S68 cell lines (C). Metaphase chromosomes of SUM44 were successively hybridized with RP11-595O22 and RP11-3P9 BAC clones (red) spanning UNC5D, combined with a centromeric probe (green). RP11-595O22 hybridizes solely to normal chromosome 8 (left), whereas red signals from RP11-3P9 are observed on both, normal, and der(8) chromosomes (right), indicating that the breakpoint is located in an interval delimited by RP11-595O22 and RP11-3P9 within the large intron 1 of UNC5D. To detect breakpoints of derivative chromosome 8 in BT-20, CAMA-1, MDA-MB-134, and S68, BAC clones located between NRG1 and FGFR1 (green) were used in combination with RP11-350N15 (red; this clone contains sequence including FGFR1 and is the most proximal BAC used). The top and bottom of FISH images correspond to results obtained with BAC clones located in the proximal and distal regions of the corresponding breakpoints, respectively. All breaks lead to the lack of 8p12-pter chromosome. D. FISH analysis of sections of tumors included in tissue microarrays. Different probe combinations were used to refine 8p12 amplification and/or breaks occurring in the region between UNC5D and FGFR1 (34.84-38.65 Mb). Three types of patterns are illustrated: (1) tumors without break [right; FISH result obtained with P2 (green) + P5 (red) probe combination], (2) tumors with amplification [middle; FISH result obtained with P2 (green) + P5 (red) probe combination], and (3) tumors with break associated with amplification of the proximal region [left; FISH result obtained with P1 (green) + P2 (red) probe combination]. Schematic representation of signals for interpretation of results is shown below.

In agreement with aCGH profiles, chromosomal breaks defined by FISH were associated to the loss of 8p telomeric portions and concomitant amplification of sequences immediately centromeric to these breakpoints. Gain or amplification was achieved by either multiplication of chromosome derivatives (BT-483, CAMA-1, HCC-1500, SUM44, and SUM225) or homogeneously staining region formation (MDA-MB-134 and S68; Fig. 4B and C). The data indicate the existence of two breakpoint clusters at 8p12-21 in breast cancer, one at NRG1 (designated BPC1) and a second more proximal (designated BPC2).

To better define BPC2, we studied primary tumors arrayed in TMA1 by FISH. We screened the region between UNC5D and FGFR1 (34.84-38.65 Mb) using BAC pools as probes (Fig. 2G; Supplementary Table S4). Chromosomal break and/or DNA amplification were determined by the split-signal FISH approach. Intact copies of the region were seen as a pair of adjacent green and red signals, whereas a break resulted in split signals. A break associated with amplification was seen as an increased number of red signals without green signal colocalization (Fig. 4D). Of 161 interpretable results, 31 (19%) tumors showed either a break and/or an amplification in the UNC5D-FGFR1 region. We studied TMA2 with two BAC combinations (P1 + P2 and P2 + P3) to refine the presence of alterations in UNC5D and UNC5D-FKSG2 genomic region, respectively. Breaks in the UNC5D-FGFR1 region occurred always in combination with amplification at 8p11-12 (six tumors with both break and amplification), whereas amplification was observed without break in eight tumors (Fig. 4D, middle and left; Supplementary Table S6).

Amplification Has Effect on Survival

To determine the incidence of 8p11-12 amplicons in breast cancer, we studied their occurrence by FISH on TMA1 using BAC pools covering A1 to A3 regions as probes (P4-P6 pools in Fig. 2). Amplification at 8p was found in 13.2%, 9.4%, and 11.4% of the tumors for amplicon A1 to A3, respectively (Table 2; Supplementary Table S6; Supplementary Fig. S3). We next assessed the effect of 8p amplification on disease features and outcome. The presence of amplification at any of three amplicons (A1-A3) was correlated to histoclinical features (Table 2; Fig. 5). It was not possible to study amplification at A1 and A3 separately because the number of samples included in these classes was too small. A correlation was observed with histologic grade and Ki-67 proliferation index. No correlation was found with the other tested factors, including age, histologic type, size of the tumor, vascular or lymph node invasion, type of treatment, estrogen receptor, ERBB2, FGFR1, progesterone receptor, or p53 protein expression. Five-year metastasis-free survival was significantly different between tumors without amplification and tumors with amplification at any of the three amplicons tested (P = 2.96 × 10−3; Fig. 5). Metastasis-free survival was also different (P = 1.59 × 10−5, log-rank test) between tumors without amplification and tumors with amplification detected by the P5 probe. This suggests that amplification could be involved in pejorative disease evolution. Similar analysis was done for overall survival and disease-free survival (Supplementary Figs. S4A and S4B, respectively). Whereas for overall survival there was a trend for 8p11-12 amplification status and clinical outcome association (P = 0.236 and 0.0591), only disease-free survival was different between tumors without amplification and tumors with amplification at any of the three amplicons tested (P = 2.29 × 10−2) as well as between tumors without amplification and tumors with amplification detected by the P5 probe (P = 8.15 × 10−3, log-rank test).

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Table 2.

Correlations between 8p11-12 Amplification Determined by FISH and Histoclinical Features

FIGURE 5.
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FIGURE 5.

8p11-12 amplification and disease outcome. Kaplan-Meier curves illustrating metastasis-free survival (MFS) of 319 patients according to 8p11-12 amplification detected at amplicon A1 to A3 by FISH on TMA1 with P4 to P6 pool probes, respectively (see map of Fig. 2). P is calculated using the log-rank test. Metastasis-free survival is different between patients with and without 8p11-12 amplification (at any of the three tested amplicons; P = 2.96 × 10−3; orange curves) as well as between patients with and without A2 amplification (P = 1.59 × 10−5; blue curves).

Discussion

Chromosome 8 is affected by frequent and complex alterations in many cancers (1, 2). What occurs on the short arm and specifically in region p11-21 is part of this genomic “turbulence” (26). We have here characterized in detail 8p11-12 alterations in breast cancer using a combination of aCGH, gene expression profiling, and FISH analyses. Genomic alterations consisted of amplification and chromosome breaks, which overall were found in ∼10% of breast tumors. We identified four amplicons and two breakpoint clusters.

Amplicons and Potential Oncogenes

Genomic profiles obtained by aCGH showed four subregions of amplification at 8p11-12. Expression analysis by DNA microarrays was coherent with the genomic profiles. Concordance between high-level amplification and increased gene expression has been shown by previous analyses (27, 28). However, TCS analysis was not useful either to understand the structural complexity of amplicons or to determine the best candidate oncogenes.

In subregion A1, genes with strong expression correlated with amplification were FLJ14233 (which codes for a protein containing zing finger motifs), SPFH2, PROSC, BRF2 (encoding a RNA polymerase III transcription initiation factor), and RAB11FIP1 (a regulator of RAB GTPases). In contrast, GPR124, which encodes a G protein-coupled receptor, could be a tumor suppressor gene (29). A1 comprised the 1-Mb minimal amplicon defined by Garcia et al. (23), with FLJ14299, SPFH2, BRF2, and RAB11FIP1 as candidate oncogenes, and the amplicon defined by Prentice et al. (24), which contains FLJ14299 and SPFH2.

Selected genes in A2 code for WHSC1L1 and signaling regulators DDHD2, BLP1, and PPAPDC1P. These proteins may play a role in cell proliferation and survival and could act as oncogenes (30, 31). However, their function is often not well characterized and their role will have to be further shown. DDHD2 and HTPAP phospholipid enzymes may act in the same metabolic pathways. LSM1/CaSM is a potential oncogene (32). Recent data have suggested that FGFR1 is not the driving oncogene of the 8p11-12 amplicon (21, 23). Its role in the A2 amplicon is indeed debated, because it is not always overexpressed when amplified and not always contained in the amplification (21). However, even if FGFR1 is not the sole or actual selected driver gene of an amplification unit, it might be useful to systematically measure FGFR1 gene amplification and FGFR1 protein overexpression. Because it is a kinase and a transmembrane protein, FGFR1 could be used for targeted therapy with either anti-kinases or antibodies. Anti-FGFR1 kinase drug PD185070 does not inhibit the proliferation of amplified SUM cell lines (21). However, in our hands, anti-FGFR1 kinase SU5402 inhibits the growth of other amplified cell lines, which may have come to depend on FGFR1 for proliferation.10 Breast tumor patients with FGFR1 protein overexpression might be one day benefit from anti-FGFR1 targeted therapy. The TACC1 gene did not meet criteria for being a potential oncogene, which is in agreement with our previous studies (33).

Subregion A3 is framed by two down-regulated genes, indoleamine-pyrrole 2,3-dioxygenase (INDO) and secreted frizzled-related protein 1 (SFRP1). SFRP1, a regulator of the WNT pathway, is a potential TSG in breast cancer (7, 17, 34, 35). The role of INDO is less clear. Amplification containing multiple amplicons may be formed by different mechanisms, one of which could be the selective elimination of TSG, such as SFRP1. Subregion A4 was associated to MYST3 and AP3M2. MYST3 encodes a histone acetyltransferase that becomes oncogenic in a subset of acute myeloid leukemias following chromosomal translocation (36). Golgi adaptor AP3M2 and golgin GOLGA7 may be both involved in vesicular transport.

Thus, the 8p amplification contains many potentially relevant genes. For most of them, the function is poorly defined and a potential role in cancer has not been documented. Some of these genes may be neutral passengers without any role in oncogenesis (37). Alternatively, the reason to find many genes in a complex amplification unit could be that not a single one but only the combined effect of several loci provides a selective advantage to the cancer cell. Different genes of the amplification may even participate in the same pathway or cell process. Most of the proteins encoded by the 8p candidate oncogenes can be grouped into two categories. SPFH2, RAB11FIP1, DDHD2, PPAPDC1B, TM2D2, GOLGA7, and AP3M2 might all be involved in vesicular protein transport and membrane trafficking between the Golgi apparatus and the cell surface. This process might be associated with chlathrin-coated pits and increased in the tumor cells, perhaps as a consequence of hypoxia. The RAB25 gene, which is related to the RAB11 family and regulates exocyst function, is amplified in about half breast cancers (38). The second category includes transcription modulators FLJ14299/ZNF703, BRF2, WHSC1L1, and MYST3.

Rather than a single gene, a functional module could be selected in the 8p amplification. The structure of the amplification may thus be slightly different from one tumor to another at the edges of each subregion (e.g., may or may not include FGFR1) depending on whether the module is complete or not. A search for the absolute driver of the 8p11-12 amplification may be elusive, but targeting a single protein might prove efficient. Rather than aiming at determining which of the amplified genes is the best candidate driver, further functional studies could aim at selecting what would be the best therapeutic target and to which molecular subtype targeting should be applied. Our list of genes and that of other studies (21-24) are good starting points (see Supplementary Table S7).

Chromosome Breaks and Potential Tumor Suppressors

Two regions of recurrent breaks were identified on 8p: BPC1, located in the NRG1 locus (13), and BCP2, centromeric to NRG1. In tumors, BPC2 corresponded to a 2-Mb region from UNC5D to FGFR1. In agreement with recent data (24), we found that breaks in NRG1 can occur independently of amplification, but the two types of alterations are often linked. BPC2 is located just telomeric to amplicon A1. Breaks at BPC2 always occurred in combination with amplification at 8p11-12. Amplifications were sometimes found in the absence of break at BPC2. Concomitant break and amplification are likely to result from the same “break-fusion-bridge” mechanism (39). Amplification is likely to be the main oncogenic determinant, but some regions may be more frequently affected by breaks than others, because they are susceptible to breakage and/or are selected because concomitant alteration provides an additional advantage. The existence of breakpoints at 8p12 associated to loss-of-heterozygosity suggests that this chromosomal region is highly prone to breakage (11). The discovery of homozygous deletions at D8S87, within intron 1 of the UNC5D gene, in prostate cancer gives additional support to this idea (40, 41). Some of the BPC2 breaks target the UNC5D gene itself. This gene, which is expressed in the normal mammary gland (42), codes for a netrin receptor (see ref. 43 for review) and could be a tumor suppressor (44). The clustering of breakpoints suggests that the 8p12 region is sensitive to breakages and could play a general role in oncogenesis via inactivation of one or several potential TSG. Both genomic profiles and FISH analysis showed that regions distal to breakpoints were lost. Loss of 8p21-ter sequences with several other potential TSG (e.g., DBC2; ref. 45) is also likely to be important for oncogenesis.

In conclusion, we have defined the structure of the 8p11-12 amplification, which consists of four amplicons associated with telomeric breaks. The amplicons include 14 candidate oncogenes and have clinical significance in breast cancers.

Materials and Methods

Breast Cell Lines

A total of 47 breast cell lines were studied (Set 1, Supplementary Table S1): BrCa-MZ-01 (46), BT-20, BT-474, BT-483, CAL51, CAMA-1, EFM19, HCC38, HCC202, HCC1187, HCC1395, HCC1428, HCC1500, HCC1569, HCC1937, HCC1954, HCC2218, HME1, Hs578T, MCF-7 Rich, MCF-7, MCF-10A, MDA-MB-134, MDA-MB-157, MDA-MB-175, MDA-MB-231, MDA-MB-361, MDA-MB-415, MDA-MB-435, MDA-MB-436, MDA-MB-453, SK-BR-3, SK-BR-7, T-47D, UACC-812, ZR-75-1, ZR-75-30 (American Type Culture Collection, Manassas, VA), 184B5, SUM44, SUM52, SUM149, SUM159, SUM185, SUM190, SUM206, and SUM225 (47)11 and S68, a newly established breast tumor cell line (a kind gift of V. Catros, Rennes, France). All cell lines are derived from carcinomas, except MCF-10A, which is derived from atypical ductal hyperplasia, and HME1 and 184B5, which originate from normal mammary gland. The cells were grown using the recommended culture conditions.

Primary Tumors

A total of 134 primary breast carcinomas were analyzed using aCGH, DNA microarrays, and/or FISH methods (Sets 2 and 3, Supplementary Table S1). Of 62 primary breast carcinomas studied by aCGH, 31 were collected at the Institut Paoli-Calmettes (Marseilles, France) and 31 at the Centre Val d'Aurelle (Montpellier, France; Sets 2 and 3, Supplementary Table S1). Among these, 19 were selected based on FGFR1 gene amplification status established by Southern blot (12 amplified and 7 nonamplified) as positive controls of amplification (12), 6 were selected based on NRG1 break (13), and 12 for alterations in the UNC5D-FGFR1 region observed by FISH in this study. Profiled breast samples included 123 samples (34 cell lines and 89 cancer tissue samples collected at Institut Paoli-Calmettes) and 11 normal breast tissue samples pooled in 4 RNA samples (1 sample from 4 women from Val d'Aurelle and 3 commercial pools of 1, 2, and 4 normal breast RNA, respectively; Clontech, Palo Alto, CA). Samples for tissue microarrays were in two series: TMA1 comprised 547 nonmetastatic invasive carcinomas described previously (Supplementary Table S2; ref. 48). TMA2 contained 23 cases selected for 8p alterations, including 14 cases of 31 altered in the UNC5D-FGFR1 region and 9 cases with a documented NRG1 breakpoint (13).

Genomic Arrays and aCGH Conditions

Custom-made genomic arrays were constructed as described previously (49). For 8p, 184 genomic clones (BAC and PAC) were selected, resulting in an average density of 1 clone/240 kb and an increased density of 1 clone/140 kb in the 8p11-12 region. Most clones were from CHORI12 (Oakland, CA), with a subset of 72 genomic clones selected to enrich the 8p11.1-21.3 region, from CTB and CTD libraries obtained from Research Genetics (Huntsville, AL). Clones were ordered according to the May 2004 release of the human draft sequences.13 Detailed information is compiled in Supplementary Table S3. Probe labeling was done as described previously (49). Hybridization and further processing of the arrays were done using a HS4800 hybridization station (Tecan, Lyon, France). Comprehensive survey of genomic imbalances at 8p was done for 37 breast cell lines and 62 primary breast tumors. Log2 thresholds for gains and losses were set at 0.25 and −0.25 as described previously (49).

Purification of Nucleic Acids

Genomic DNA was isolated as described previously (14). Total RNA was extracted from frozen samples as described previously (14) and integrity was controlled by denaturing formaldehyde agarose gel electrophoresis and by microanalysis (Agilent Bioanalyzer, Palo Alto, CA).

RNA Expression Profiling of Chromosome 8 Using DNA Microarrays

Gene expression profiling was done with Affymetrix U133 Plus 2.0 human oligonucleotide microarrays as recommended by the supplier.14 Briefly, for each sample, synthesis of the first-strand cDNA was done from 3 μg total RNA by T7-oligo(dT) priming followed by second-strand cDNA synthesis. After purification of cDNA, an in vitro transcription combined with amplification of cRNA was used to generate the cRNA containing biotinylated pseudouridine, which was then purified, quantified, and chemically fragmented at 95°C for 35 minutes. Fragmented biotinylated cRNA was hybridized in 200 μL hybridization buffer at 45°C for 16 hours to microarrays contained >47,000 transcripts and variants, including 38,500 well-characterized human genes. Automated washes of microarrays and staining with streptavidin-phycoerythrin were done according to the manufacturer's instructions. Double signal amplification was done by biotinylated anti-streptavidin antibody with goat IgG blocking antibody. Scanning was done with Affymetrix GeneArray scanner and signals were quantified using Affymetrix GCOS software.

All hybridization images were inspected for artifacts. Expression data were then analyzed by the Robust Multichip Average method in R using Bioconductor and associated packages (50). Robust Multichip Average did the background adjustment, the quantile normalization, and finally the summarization of 11 oligonucleotides per gene. Filtering process removed from analysis the genes with low and poorly measured expression as defined by expression level inferior to 100 units in all samples. A second filter was then applied to exclude genes showing low expression variation across the samples as defined by Max-Min difference inferior to 100 units for genes with Min expression value superior to 100 and by Max-100 difference inferior to 100 units for genes with Min expression value inferior to 100. All data were then log2 transformed for display and analysis. Before analysis and for each sample, gene expression levels were centered on the average levels obtained with normal breast samples.

Oligonucleotide probe sets were mapped to the human genome according to the Build 35 from the National Center for Biotechnology Information Ensemble database and the University of California at Santa Cruz Genome Bioinformatics database Genome Browser.13 Of all probe sets represented on the microarrays, 1,423 were assigned to chromosome 8. After filtering of data, we retained for analysis 561 that focused on chromosome 8. Oligonucleotides assigned to 8p BAC arrays are listed in Supplementary Table S3 in agreement to the May 2004 human draft sequences (40).13,14 To eliminate the redundancy of probe sets representing the same gene present on microarrays, we selected for each gene the probe set that presented the highest correlation with the median profile obtained with all corresponding probe sets. Therefore, we retained 261 probe sets (genes) on 8p and 67 in the region contained between NRG1 and the centromere. Hierarchical clustering of expression data was done with the Cluster program (51) using Pearson correlation as similarity metric and centroid linkage clustering. Results were displayed using the TreeView program (51).

Identification of Deregulated Gene Sets

To evaluate the correlation between the expression profile of each gene and that of its neighbors, we used the same approach as Reyal et al. (22) focused on the 261 probe sets (genes) located on 8p. For each probe set (gene), we computed a TCS. This score is the average of the correlation coefficients across all samples between RNA expression levels of this gene and the RNA levels of each of the physically nearest 20 genes (10 centromeric genes and 10 telomeric genes). A significance threshold for TCS was obtained by permutation tests in using the 1,000th quantile of the random distribution (i.e., the value for which 1 of 1,000 probe sets in the random data sets was above this value). This significant threshold was equal to 0.33. A probe set with a score exceeding the threshold was considered as significantly correlated with its neighbors.

For each gene located on the 8p11-12 region, we also measured the frequency of RNA overexpression (ratio superior to 2) and underexpression (ratio inferior to 0.5) in the 123 samples (34 cell lines and 89 tumors) compared with the average expression in the 4 normal breast RNA samples.

Supervised analysis was applied to identify genes that discriminate between samples with and without DNA amplification within each of our defined amplicons (A1, A2, A3, or A4). The selection of samples was done based on the aCGH profiles. Samples presenting <33% of the BAC clones with a log2 ratio exceeding 0.75 in the studied amplicon were not considered as amplified. For each gene of the 8p11-12 region, we computed a discriminating score by comparing the expression levels between the subgroup of samples presenting gene amplification in one of the four amplicons and the subgroup of samples with gene amplification within one or more of the other three amplicons and samples without any amplification. Discriminating score (52) was defined as discriminating score = (M1 − M2) / (S1 + S2), where M1 and S1 represent mean and SD of expression levels of the gene in subgroup 1, respectively, and M2 and S2 in subgroup 2. Confidence levels were estimated by 2,000 iterative random permutations of samples as described previously (53) with a significance threshold producing <0.1 false positive. We applied the Mann-Whitney test to identify significant differences in expression associated to the occurrence of amplification at either of the defined amplicons (A1-A4). The nonparametric nature of this test seemed well adapted to the nonnormal distribution of microarray data and was therefore a good complement to the discriminating score approach.

Tissue Microarrays

Tissue microarrays were prepared as described (54). Sections (5 μm) of the resulting microarray block were made and used for FISH or immunohistochemistry analysis after transfer onto glass slides.

FISH Analysis on Breast Tumor Cell Lines

To characterize breaks between NRG1 and FGFR1 loci, dual-color FISH analysis was done as described previously (12), on metaphase chromosomes from 12 cell lines (Set 1, Supplementary Table S1), using as probes a combination of labeled BAC clones. Fixation and preparation of metaphase spreads for FISH analysis were done on cytogenetic pellets of cultured cell lines as published (55). BAC clones selected to cover 8p12 are listed in Supplementary Table S4. BAC clones were checked for chimerism by FISH on normal metaphases chromosomes. After counterstaining with Vectashield containing 4′,6-diamidino-2-phenylindole (Vector, Burlingame, CA), images were processed as described previously (25).

FISH Analysis on Tissue Microarray

Dual-color FISH analysis was directly done on tumor samples arrayed in tissue microarray as published (13, 56). We used a combination of two differently labeled (biotinylated and revealed in green, FITC; digoxigenin-labeled and revealed in red, rhodamine) DNA from BAC pools P1 (34.8-35.4 Mb), P2 (35.8-36.6 Mb), P3 (36.6-37.0 Mb), P4 (37.6-38.0 Mb), P5 (38.1-38,6 Mb), and P6 (40.5-41 Mb; Supplementary Table S4). BAC positions were ascertained by metaphase FISH.

Break characterization was based on the split-signal FISH approach (25, 57). Tumor sections present on tissue microarray were first hybridized with biotinylated and digoxigenin-labeled BAC combinations P1 + P5 to determine the presence of alterations (breaks and/or amplification) in the [UNC5D-FGFR1] genomic region. P1 + P2, P2 + P5, and P2 + P3 were then used to refine the alterations in [UNC5D], [UNC5D-FGFR1], and [UNC5D-FKSG2] (UNC5D excluded from these intervals) genomic regions, respectively. Amplification generated in subregions A1 to A3 was studied by dual-color FISH using P4 to P6 probes, respectively. Counterstaining treatment and images were processed as described in the previous section. Areas enriched for tumor cells were identified by reference to near-adjacent sections stained with H&E, and fluorescence was scored on a minimum of 50 nuclei per tumor. Two observers (C. Ginestier and V. Gelsi-Boyer) read the tissue microarray independently.

Immunohistochemical Analysis

Immunohistochemistry was done and analyzed as described previously (48, 54). Results were evaluated under a light microscope by two pathologists (E. Charafe-Jauffret and J. Jacquemier).

Statistical Methods

Distributions of molecular markers and other categorical variables were compared using standard χ2 tests or Fisher exact test. Overall survival, disease-free survival, and metastasis-free survival intervals were calculated from the date of diagnosis. For overall survival, death was scored as an event; for disease-free survival, first locoregional recurrence or first metastasis was scored as an event; for metastasis-free survival, first distant metastasis was scored as an event. Patients without event were censored at the time of last follow-up for each survival measurement methods or at death for disease-free survival and metastasis-free survival. For graphical presentation, follow-up was truncated at 120 months. Survival curves were derived from Kaplan-Meier estimates and the curves were compared by log-rank tests.

Acknowledgments

We thank F. Birg, D. Maraninchi, and C. Mawas for encouragement and L. Ursule for help.

Footnotes

  • ↵http://amba.charite.de/~ksch/cghdatabase/index.htm.

  • ↵http://cgap.nci.nih.gov/Chromosomes/RecurrentAberrations.

  • ↵Gelsi-Boyer et al., unpublished observations.

  • ↵http://www.cancer.med.umich.edu/breast_cell/clines/clines.html.

  • ↵http://bacpac.chori.org/.

  • ↵http://genome.ucsc.edu/.

  • ↵http://www.Affymetrix.com.

  • Grant support: Institut National de la Sante et de la Recherche Medicale, Institut Paoli-Calmettes, Association pour la Recherche sur le Cancer (2002-2003), Ligue Nationale Contre le Cancer (Label 2003-2006), and Ministries of Health and Research (Cancéropôles PACA and GSO); Ligue Nationale Contre le Cancer fellowship (A. Letessier) and Ministry of Research fellowship (C. Ginestier, F. Monville, F. Sircoulomb, and S. Esteyriès).

  • 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: V. Gelsi-Boyer and B. Orsetti have equally contributed to this work.Supplementary data for this article are available at Molecular Cancer Research Online (http://mcr.aacrjournals.org/).

    • Accepted November 14, 2005.
    • Received August 8, 2005.
    • Revision received October 26, 2005.
  • American Association for Cancer Research

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Molecular Cancer Research: 3 (12)
December 2005
Volume 3, Issue 12
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Comprehensive Profiling of 8p11-12 Amplification in Breast Cancer
Véronique Gelsi-Boyer, Béatrice Orsetti, Nathalie Cervera, Pascal Finetti, Fabrice Sircoulomb, Carole Rougé, Laurence Lasorsa, Anne Letessier, Christophe Ginestier, Florence Monville, Séverine Esteyriès, José Adélaïde, Benjamin Esterni, Catherine Henry, Stephen P. Ethier, Frédéric Bibeau, Marie-Joëlle Mozziconacci, Emmanuelle Charafe-Jauffret, Jocelyne Jacquemier, François Bertucci, Daniel Birnbaum, Charles Theillet and Max Chaffanet
Mol Cancer Res December 1 2005 (3) (12) 655-667; DOI: 10.1158/1541-7786.MCR-05-0128

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Comprehensive Profiling of 8p11-12 Amplification in Breast Cancer
Véronique Gelsi-Boyer, Béatrice Orsetti, Nathalie Cervera, Pascal Finetti, Fabrice Sircoulomb, Carole Rougé, Laurence Lasorsa, Anne Letessier, Christophe Ginestier, Florence Monville, Séverine Esteyriès, José Adélaïde, Benjamin Esterni, Catherine Henry, Stephen P. Ethier, Frédéric Bibeau, Marie-Joëlle Mozziconacci, Emmanuelle Charafe-Jauffret, Jocelyne Jacquemier, François Bertucci, Daniel Birnbaum, Charles Theillet and Max Chaffanet
Mol Cancer Res December 1 2005 (3) (12) 655-667; DOI: 10.1158/1541-7786.MCR-05-0128
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Molecular Cancer Research
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