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1 Marseilles Cancer Institute, Department of Molecular Oncology, UMR599 Institut National de la Sante et de la Recherche Medicale and Institut Paoli-Calmettes; 2 Department of Biostatistics, UMR599 and Institut Paoli-Calmettes; 3 Department of BioPathology, Institut Paoli-Calmettes, Marseilles, France; 4 EMI229 Institut National de la Sante et de la Recherche Medicale and 5 Department of Pathology, CRLC Val d'Aurelle-Paul Lamarque, Montpellier, France; 6 Laboratory of Cytogenetics, Centre Hospitalier Universitaire of Rennes, Rennes, France; and 7 Karmanos Institute, Detroit, Michigan
Requests for reprints: Daniel Birnbaum, UMR599 Institut National de la Sante et de la Recherche Medicale, 27 Bd. Leï Roure, 13009 Marseilles, France. Phone: 33-4-91-75-84-07; Fax: 33-4-91-26-03-64. E-mail: birnbaum{at}marseille.inserm.fr
| Abstract |
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| Introduction |
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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 |
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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.
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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).
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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 x 103; Fig. 5). Metastasis-free survival was also different (P = 1.59 x 105, 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 x 102) as well as between tumors without amplification and tumors with amplification detected by the P5 probe (P = 8.15 x 103, log-rank test).
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| Discussion |
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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 |
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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
2 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.
| Acknowledgements |
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| Notes |
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The costs of publication of this article were defrayed in part by the payment of page charges. This article must therefore be hereby marked advertisement in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.
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/).
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. ![]()
Received 8/ 8/05; revised 10/26/05; accepted 11/14/05.
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