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[Cancer Research 65, 11335-11344, December 15, 2005]
© 2005 American Association for Cancer Research

Molecular Biology, Pathobiology and Genetics

Gene Expression Profiles Associated with Treatment Response in Oligodendrogliomas

Pim J. French1, Sigrid M.A. Swagemakers2,5, Jord H.A. Nagel4, Mathilde C.M. Kouwenhoven1, Eric Brouwer1, Peter van der Spek2, Theo M. Luider1, Johan M. Kros3, Martin J. van den Bent1 and Peter A. Sillevis Smitt1

Departments of 1 Neurology, 2 Bioinformatics, 3 Pathology, 4 Medical Oncology, and 5 Cell Biology and Genetics, Cancer Genomics Center, Erasmus Medical Center, Rotterdam, the Netherlands

Requests for reprints: Pim J. French, Department Neurology, Josephine Nefkens Institute, Erasmus Medical Center, Room Be462a, P.O. Box 1738, 3000 DR Rotterdam, the Netherlands. Phone: 31-10-408-8333; Fax: 31-10-408-8365; E-mail: p.french{at}erasmusmc.nl.


   Abstract
Top
 Abstract
Introduction
 Materials and Methods
 Results
 Discussion
 References
 
Oligodendrogliomas are a specific subtype of brain tumor of which the majority responds favorably to chemotherapy. In this study, we made use of expression profiling to identify chemosensitive oligodendroglial tumors. Correlation of expression profiles to loss of heterozygosity on 1p and 19q, common chromosomal aberrations associated with response to treatment, identified 376, 64, and 60 differentially expressed probe sets associated with loss of 1p, 19q or 1p, and 19q, respectively. Correlation of expression profiles to the tumors' response to treatment identified 16 differentially expressed probe sets. Because transcripts associated with chemotherapeutic response were identified independent of common chromosomal aberrations, expression profiling may be used as an alternative approach to the tumors' 1p status to identify chemosensitive oligodendroglial tumors. Finally, we correlated expression profiles to survival of the patient after diagnosis and identified 103 differentially expressed probe sets. The observation that many genes are differentially expressed between long and short survivors indicates that the genetic background of the tumor is an important factor in determining the prognosis of the patient. Furthermore, these transcripts can help identify patient subgroups that are associated with favorable prognosis. Our study is the first to correlate gene expression with chromosomal aberrations and clinical performance (response to treatment and survival) in oligodendrogliomas. The differentially expressed transcripts can help identify patient subgroups with good prognosis and those that will benefit from chemotherapeutic treatments. (Cancer Res 2005; 65(24): 11335-44)


   Introduction
Top
 Abstract
 Introduction
Materials and Methods
 Results
 Discussion
 References
 
Diffuse gliomas are the most common primary central nervous system tumors in adults (1, 2), and it is estimated that ~18,000 new patients per annum are diagnosed with a primary brain tumor in the United States (CBTRUS 2004-2005 statistical report; http://www.cbtrus.org). The worldwide standard for grading and classification of these tumors is at present the WHO classification (3). Based on their histologic appearance, gliomas can be divided into astrocytic tumors, pure oligodendroglial tumors, and mixed oligoastrocytic tumors. The oligodendrogliomas comprise ~20% of all gliomas and, compared with most other gliomas, have a relatively long average survival time (5-12 years) after diagnosis (4, 5). Two malignancy grades are recognized in oligodendrocytic tumors: grade 2 (low grade) and grade 3 (anaplastic; ref. 6).

One of the striking differences between oligodendroglial tumors and other glioma subtypes is their sensitivity to chemotherapy. The majority of oligodendrogliomas respond favorably to chemotherapy with alkylating agents [either temozolomide or PCV, a combination therapy of procarbazine, 1-(2-chloroethyl)-3-cyclohexyl-L-nitrosourea, and vincristine], whereas other gliomas are often chemoresistant (7, 8). The more favorable clinical behavior of oligodendroglial tumors renders it therefore important to correctly identify this subtype of gliomas. Unfortunately, histologic classification and grading of gliomas has a significant subjective component. However, malignant gliomas can also be classified according to their gene expression profile (9), and such classification can aid in identification of glioma subtype (for review, see ref. 10). Nevertheless, even within the histologically defined subset of oligodendroglial tumors, there are large variations in prognosis (e.g., see ref. 11) and treatment response. It is therefore of importance not only to identify oligodendrogliomas but also to identify those oligodendroglial tumors that are likely to benefit from chemotherapeutic treatments.

In oligodendroglial tumors, there is a strong correlation between chromosomal aberrations and response to treatment. For example, a common genomic aberration is a combined loss of the short arm of chromosome 1 (1p) and the long arm of chromosome 19 (19q; refs. 5, 12–16). Loss of heterozygosity (LOH) on both chromosomal arms is correlated with a favorable response to chemotherapy. A response to chemotherapy is observed in 80% to 90% of oligodendrogliomas with 1p LOH and in 25% to 30% without 1p LOH (12, 15, 16). Other chromosomal aberrations observed at lower frequency include LOH on 10q and amplification of 7p11 (17). These aberrations are correlated with poor prognosis and are negatively correlated with LOH on 1p and 19q. This correlation between response to treatment and chromosomal aberrations can therefore help identify chemosensitive oligodendroglial tumors. However, predicting the tumors' response to treatment by its chromosomal status also incorrectly classifies a significant percentage of tumors.

Expression profiling can be an alternative approach to identify oligodendroglial tumors that will benefit from chemotherapeutic treatment. Although expression profiling has been done on oligodendroglial tumors (9, 11, 18, 19), mRNA expression has thus far not been correlated to treatment response. We therefore performed expression profiling on oligodendroglial tumors and correlated the results to response to treatment, survival after diagnosis, and common chromosomal aberrations. The transcripts identified by our study can help identify patients with a high likelihood to respond to treatment and patient subgroups with favorable prognosis.


   Materials and Methods
Top
 Abstract
 Introduction
 Materials and Methods
Results
 Discussion
 References
 
Tumor samples. Patients were chosen with (anaplastic) oligodendroglioma or mixed oligoastrocytoma with enhancing disease at the time of chemotherapy. Patients were treated in a single institution (Erasmus Medical Center) in clinical trials evaluating the efficacy of temozolomide or PCV. Only patients with an evaluable for response to chemotherapy were included in this study. Treatment response was evaluated by magnetic resonance imaging and scored according to McDonald's criteria (20). Tumor size was defined as the product of the two largest perpendicular tumor diameters. Complete response (CR) was defined as disappearance of all contrast-enhancing tumors on two subsequent scans at least 1 month apart, with the patient being off steroids and neurologically stable or improved. Partial response (PR) was defined as ≥50% reduction in tumor area on two subsequent scans at least 1 month apart, with the patient being steroids stable or decreased and neurologically stable or improved. Progressive disease (PD) was defined as ≥25% increase in tumor area, new tumor on magnetic resonance imaging or neurologic deterioration, and steroids stable or increased. All other situations were considered stable disease (SD). Samples were collected immediately after surgical resection, snap frozen, and stored at –80°C in the Erasmus Medical Center brain tumor tissue bank. Samples were visually inspected on 10-µm H&E-stained frozen sections by the neuropathologist (J.M.K.). Samples with <80% tumor were omitted from this study. Tissue adjacent to the inspected sections was subsequently used for nucleic acid isolation. Using these criteria, 28 oligodendroglial tumors were selected (Table 1). Four additional tumor samples with insufficient RNA quantity for array analysis were selected for confirmation of differentially expressed genes using quantitative PCR.


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  		Table 1. Summary of patient data, histologic diagnosis, and response to chemotherapy of samples used in this study

 
Nucleic acid isolation. Tissues were homogenized using a polytron, following which RNA and genomic DNA were extracted using Trizol (Invitrogen, Breda, the Netherlands) according to the manufacturer's instructions. Total RNA, present in the aqueous phase after extraction, was precipitated in isopropanol, redissolved in diethyl-pyrocarbonate-treated water, and further purified on RNeasy mini columns (Qiagen, Venlo, the Netherlands). Genomic DNA present in the organic phase was precipitated using ethanol, washed in 0.1 mol/L Na citrate/10% ethanol, and dissolved in 8 mmol/L NaOH, whereafter the pH was adjusted to 8.4 using 1 mol/L HEPES (free acid).

cDNA synthesis and array hybridization. RNA quality was assessed on agarose gel and Bioanalyser (Agilent, Palo Alto, CA). cDNA synthesis and cRNA labeling was done using the alternative protocol for one-cycle cDNA synthesis. Biotin-labeled cRNA was generated using the ENZO Highyield RNA transcript labeling kit (ENZO Life Sciences, Inc., Farmingdale, NY). Affymetrix (Santa Clara, CA) HG U133-plus2 microarrays were hybridized overnight with 15 µg biotin-labeled cRNA; 54,675 probe sets (a probe set is a set of oligonucleotide probes that examines the expression of a single transcript) are spotted on these arrays, allowing expression profiling of virtually all human transcripts. Multiple probe sets may be directed against the same transcript. Microarrays were then washed using fluidics stations according to standard Affymetrix protocols.

Microsatellite analysis. Microsatellites were amplified by PCR on 10 ng genomic DNA using forward and reversed primers and a fluorescently labeled M13 (–21) primer. Primers and cycling conditions are stated in Supplementary Table 1. PCR products were precipitated, denatured in formamide and run on an ABI 3100 genetic analyzer (Applied Biosystems, Foster City, CA). Samples were analyzed using Genescan 3.7 software (Applied Biosystems) and scored by two independent researchers. Because nonneoplastic tissues were not available for most of the tumor samples, allelic losses were statistically determined as described (21). Allelic loss was assumed when the tumor sample had a homozygous allele pattern for all microsatellites within the locus (P < 0.05 for each locus).

Fluorescence in situ hybridization. 1p/19q status of samples with noninformative microsatellite analysis was determined using fluorescence in situ hybridization (FISH) as previously described (22). Locus-specific probes for 1p36 (D1S32), centromere 1 (pUC1.77), 19q13.4 (Bac clone 426G3), and 19p13 (Bac clones 957I1, 153P24, and 959O6) were labeled with either biotin-16-dUTP, digoxigenin-16-dUTP (Roche Diagnostics, Mannheim, Germany), or Spectrum Orange (Vysis, Downers Grove, IL) as previously described (23). Probes were detected using FITC-labeled sheep-anti-digoxigenin (Roche Diagnostics) and/or CY3-labeled avidin (Brunschwig Chemie, Amsterdam, the Netherlands). Nuclei were counterstained with 4',6-diamidino-2-phenylindole. Sixty nonoverlapping nuclei were enumerated per hybridization. Ratios were calculated as the number of signals of the marker divided by the number of signals of the reference. Ratio < 0.80 was considered allelic loss.

Semiquantitative reverse transcription-PCR. Semiquantitative reverse transcription-PCR (RT-PCR) was done using SYBR Green PCR master mix (Applied Biosystems) according to the manufacturer's instructions. Expression levels were evaluated relative to hypoxanthine phosphoribosyltransferase and porphobilinogen deaminase controls. Intronspanning primers were designed against 16 genes (Supplementary Table 2). All primers had an amplification efficiency of >80% (determined by serial dilution) and generated a single amplification product at a temperature above 77°C (determined by melting point analysis). Cycling was done on an ABI7700 sequence detection system (Applied Biosystems); cycling conditions are stated in Supplementary Table 2.

Amplification of epidermal growth factor receptor (EFGR) was determined by semiquantitative PCR using identical conditions as described above. Genomic DNA (20 ng) was used for each reaction. The amount of product amplified using genomic EGFR primers was compared with the amount of product amplified using primers on different chromosomes lying within the F3 and FGFR3 loci. Statistical analysis was done using the Mann-Whitney U test (http://eatworms.swmed.edu/~leon/stats/utest.cgi); values are mean ± SE.

Data analysis. Arrays were omitted from the analysis when the number of present calls was <35% and when the 5'/3' ratio of glyceraldehyde-3-phosphate dehydrogenase controls was >3. Probe sets that were absent (according to Affymetrix MAS5.0 software) in at least 33 of the 34 microarrays were omitted from further analysis. Raw intensities of the remaining probe sets (36,875) of each chip were log 2 transformed and normalized using quantile normalization. For each probe set, the geometric mean of the hybridization intensities of all samples was calculated. The level of expression of each probe set was determined relative to this geometric mean and log 2 transformed. The geometric mean of the hybridization signal of all samples was used to ascribe equal weight to gene expression levels. Unsupervised clustering was done using Omniviz version 3.6.0 (Omniviz, Maynard, MA) software. Probe sets whose expression levels differed >2-fold from the geometric mean in at least one sample were selected for the unsupervised clustering analysis. Similarities between samples are plotted using Omniviz software as Pearson's correlations.

Differentially expressed genes were identified using statistical analysis of microarrays (SAM analysis; ref. 24). Such supervised analysis correlates gene expression with an external variable. SAM calculates a score for each probe set on the basis of the change in expression relative to the SD of all measurements. Unless otherwise indicated, analyses were done using stringent statistical variables with a false discovery rate (FDR) of <1 probe set. Differentially expressed probe sets were imported into Spotfire DecisionSite (Spotfire, Somerville, MA) to perform principle components analysis (PCA) and hierarchical clustering. Data were log 2 transformed followed by calculation of the z score for each probe set. PCA structures a data set using as few variables as possible and is a mathematical way to reduce data dimensionality. PCA summarizes the most important variance in a data set as principle components. For more information on the use of PCA in microarray analysis, see ref. 25 and references therein. Hierarchical clustering groups data based on their similarities in gene expression profiles. Weighed average was used to perform most clustering analysis, in which the distance between two clusters is defined as the average of distances between all pairs of objects. Unlike clustering based on unweighed averages, the weighed average ascribes equal weight to the two branches of the dendrogram that are about to be fused. Ward's hierarchical clustering method forms groups in a manner that minimizes the loss associated with each grouping. At each step in this analysis, the two clusters whose fusion results in minimum increase in information loss are combined.


   Results
Top
 Abstract
 Introduction
 Materials and Methods
 Results
Discussion
 References
 
Samples. Patient data, histologic diagnosis, chromosomal aberrations, and response to chemotherapy are summarized in Table 1. In total, we performed expression analysis on 28 oligodendrogliomas (two low-grade and 26 anaplastic oligodendrogliomas) and six control brain samples (four samples from whole cortex and two from white matter only). We identified 14 of 28 samples (50%) with loss of most/all of the short arm of chromosome 1 (sample 18 had a predicted loss distal to 1p33) and 16 of 28 (57%) samples with loss of 19q. Most tumors showed combined loss or retention of 1p and 19q. Only three tumors showed loss of 19q without loss of 1p, and one showed LOH on 1p35.2 without loss of 19q. EGFR amplification and LOH on 10q was identified in 4 of 28 (14%) oligodendroglial tumors, three of which showed combined EGFR amplification and 10q LOH.

When comparing the response rate (CR + PR versus PD + SD) to loss of the telomeric end of chromosome 1, a response to chemotherapy was observed in 12 of 14 (86%) samples with 1p35.2 LOH and 6 of 14 (43%) without loss of 1p35.2. Similar results were obtained when comparing the response rate to LOH on 19q or to combined LOH on 1p and 19q (Table 1). All four tumors in which the EGFR genomic region was amplified had retained both copies of 1p and 19q and showed no response to chemotherapy (progressive disease for all). Three of four tumors with 10q LOH showed no response to treatment.

Unsupervised clustering. Unsupervised clustering identifies a number of subgroups (summarized in Fig. 1). A first subgroup consists mainly of control samples but also includes low-grade tumor samples. Because the amount of tumor present in all samples was high (determined by visual inspection of sections before the sample used for expression profiling), this close homology to control brain tissue is likely to reflect an intrinsic property of low-grade oligodendroglial tumors. The low-grade oligodendroglioma samples have a higher homology to samples from the whole cortex than to samples from the white matter. Group II consists of tumor samples that have LOH on 1p and 19q and has a relatively good prognosis. All but one sample respond favorably to chemotherapy, and most (4 of 6) patients with CR are found in this group. Patients in this group also have a relatively long survival both after diagnosis (15.3 ± 3.6 years) and after surgical resection of the tumor (4.8 ± 1.5 years). Group III has the worst prognosis. None of the tumors respond to chemotherapy, and the average time of survival after diagnosis was short (1.9 ± 0.2 years) as was the average time after surgical resection (1.5 ± 0.3 years). All tumors of this subgroup have retained both copies of 1p and 19q and are characterized by an amplification of the EGFR locus. The samples between groups II and III have a more mixed appearance; there is some degree of correlation with both groups I and III. Many samples with PR and all samples with SD are found in this group. Survival after diagnosis and surgical resection is intermediate between groups II and III: 8.3 ± 1.5 and 2.3 ± 0.3 years, respectively.



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  		Figure 1. Correlation plot of all samples. Samples are plotted against each other to determine the degree of similarity based on expressed genes. Red, high similarity; blue, low similarity (scale bar). Bottom, graphic representation of histologic and patient data. Tissue, origin of sample. {05-1886fx01c}, control cortex; {05-1886fx02c}, control white matter; {05-1886fx03c}, low-grade oligodendroglioma; {05-1886fx04c}, anaplastic oligodendroglioma. 1p, 19q, 10q LOH: {05-1886fx01c}, no LOH; {05-1886fx04c}, LOH. EGFR ampl, amplification of the EFGR chromosomal locus. {05-1886fx01c}, no amplification; {05-1886fx04c}, amplification. Response, response to chemotherapy. {05-1886fx01c}, complete response; {05-1886fx02c}, partial response; {05-1886fx03c}, stable disease; {05-1886fx04c}, progressive disease. Surv tot, survival (years) from time of diagnosis. {05-1886fx01c} >10, {05-1886fx02c} 7-10, {05-1886fx03c} 3-7, {05-1886fx04c} <3. A, patient alive at time of analysis.

 
Supervised clustering: tumor versus controls. We first performed supervised clustering to identify genes that are differentially expressed between control and tumors tissue. SAM analysis identified 1,881 differentially expressed probe sets (~1,413 genes). The strongest down-regulated transcripts in oligodendrogliomas include those that encode proteins expressed in mature oligodendrocytes: myelin-associated oligodendrocyte basic protein, myelin oligodendrocyte glycoprotein (MOG), myelin-associated glycoprotein, claudin 11, and myelin basic protein. These transcripts are expressed (± SD) at 0.052 ± 0.021 (four probe sets), 0.10 ± 0.013 (four probe sets), 0.086 (one probe set), 0.30 ± 0.25 (two probe sets), and 0.21 ± 0.17 (seven probe sets) levels of control brain mRNA, respectively. This down-regulation was observed in each sample. The strong down-regulation in low-grade samples confirms the hypothesis that their homology to control brain tissue (see Fig. 1) is a result of the genes expressed by the tumor. The down-regulation of MOG was confirmed using RT-PCR (Table 2).


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  		Table 2. Confirmation of a subset of differentially expressed genes identified by expression profiling

 
It has been reported that PDGFR{alpha} is often highly expressed in oligodendrogliomas (26). However, this gene was not present in the set of tumor-associated genes identified by our screen. Closer inspection reveals that although PDGFR{alpha} is on average up-regulated 4.1-fold, the high variation of up-regulation (4.1 ± 4.7) indicates that this transcript is not a reliable marker for the amount of tumor present in the sample. In fact, we failed to observe any up-regulation in 10 of 28 samples. The select up-regulation of PDGFR{alpha} in a subset of samples was confirmed using RT-PCR.

Supervised clustering on chromosomal aberrations. Supervised clustering was done to identify genes associated with specific chromosomal losses. For this, we compared expression profiles of samples with (a) 1p LOH (n = 9) versus no loss (n = 9), (b) 19q LOH (n = 11) versus no loss (n = 7), and (c) combined 1p and 19q LOH (n = 6) with no loss on either arm (n = 6). SAM analysis identified 376, 64, and 60 probe sets as being differentially expressed following loss of 1p, 19q or 1p and 19q, respectively. Probe sets are listed in Supplementary Table 3. Interestingly, many of the identified probe sets are located on the lost chromosomal arm(s): 136 of 376 (36.1%) probe sets are located on 1p, 25 of 64 (39.1%) on 19q, and 49 of 60 (82%) on 1p or 19q. Of the differentially expressed genes located on the lost chromosomal arm(s), the ratio (± SD) loss versus no loss is 0.53 ± 0.22 (1p), 0.54 ± 0.07 (19q), and 0.53 ± 0.09 (1p and 19q), indicating that loss of one allele reduces expression levels by ~50%. In fact, all but two of the differentially expressed probe sets that are located on the lost chromosomal(s) are down-regulated. This correlation between chromosomal loss and expression level therefore suggests that these genes have an allele number–dependent expression level. Furthermore, the differentially expressed genes can be identified across the entire chromosomal arms and suggests that the entire arms have been lost.

PCA and hierarchical clustering of genes associated with LOH on 1p and 19q are depicted in Fig. 2. All anaplastic oligodendrogliomas with combined loss/retention of 1p and 19q were correctly distributed by the first principal component axis, PCA1. This correct distribution includes seven samples (two samples that have retained both 1p and 19q copies and five samples with LOH on 1p and 19q) that were omitted from the clustering analysis. Further confirmation of a subset of differentially expressed genes by RT-PCR is shown in Table 2 (including four additional oligodendroglial tumors).



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  		Figure 2. PCA and hierarchical clustering of 60 probe sets differentially expressed between oligodendrogliomas with combined 1p and 19q LOH and those that have retained both 1p and 19q arms. A, samples are separated on their 1p and 19q chromosomal status by PCA1, whereas PCA2 separates control brain from anaplastic oligodendrogliomas. 1p and 19q status: {05-1886fx01c}, no LOH on 1p and 19q; {05-1886fx04c}, LOH on 1p and 19q; and {05-1886fx05c}, LOH on either 1p or 19q. B, hierarchical clustering shows relative expression levels of individual genes (columns) plotted against individual tumor samples (rows). For clarity, control brain samples were omitted from the clustering analysis. Gene expression levels: red, high expression (+2); green, low expression (–2) on a log 2 scale. Dendrograms, hierarchical clustering (Euclidian distance) of samples (top) and genes (left). The 1p and 19q status in indicated below the hierarchical clustering: {05-1886fx01c}, no LOH; {05-1886fx04c}, LOH. As can be seen, hierarchical clustering clearly identifies two main subgroups associated with 1p/19q LOH.

 
Genes associated with chemosensitivity. We next performed supervised clustering to identify genes that are associated with response to chemotherapy. For this analysis, we compared mRNA expression levels between tumors that show a response to chemotherapy (CR + PR) and those that do not (SD + PD). Such comparison using SAM (FDR < 1 gene) identified 16 differentially expressed probe sets that are listed in the Supplementary Table 3. One hundred sixty differentially expressed probe sets (137 genes) were identified using less stringent statistical analysis (FDR = 4.9%), of which 31 (27 genes) are located on chromosomes 1p or 19q (19%). Confirmation of differentially expressed genes was done using RT-PCR on IQGAP, MAN1C1, TRIM56, and AQP1 transcripts (Table 2).

PCA based on the 16 genes associated with chemotherapeutic response identifies three main subgroups (Fig. 3): samples with no response to chemotherapy (SD and PD, red), samples with response to treatment (CR and PR, green), and control samples (gray). Similarly, hierarchical clustering also separates the majority of oligodendrogliomas with response to chemotherapy from those that show no or little response to treatment (Fig. 3). Similar results were obtained when clustering was done on 160 differentially expressed probe sets identified using FDR = 4.9%. Most oligodendroglial tumors were correctly distributed on their response to treatment by PCA1: PCA1 > 0 in 14 of 18 samples that respond to treatment, whereas PCA1 < 0 in 10 of 10 samples with no response to treatment. Only 4 of 28 samples were therefore incorrectly classified based on expression of genes associated with chemosensitivity. In comparison, 8 of 28 samples are incorrectly classified when predicting response to treatment based on the 1p chromosomal status: 6 of 14 tumors without LOH on 1p show response to treatment and 2 of 14 with LOH on 1p do not respond to treatment.



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  		Figure 3. PCA and hierarchical clustering based on 16 probe sets differentially expressed between chemosensitive (CR + PR) and chemoresistant (SD + PD) oligodendrogliomas. A, samples are separated on their response to chemotherapy by PCA1, whereas PCA2 separates control brain from anaplastic oligodendrogliomas. B, hierarchical clustering based on 16 differentially expressed probe sets. Relative expression levels of individual genes (columns) are plotted against individual tumor samples (rows). Gene expression levels: red, high expression (+1.8); green, low expression (–1.8). Dendrograms, hierarchical clustering of samples (top) and genes (left) using Wards method. Hierarchical clustering separates tumors that fully respond to chemotherapy (CR) from tumors that do not respond (SD + PD). Furthermore, hierarchical clustering also clearly separates tumors with poor prognosis (subgroup III in Fig. 1) from other oligodendroglial tumors. Responses in oligodendroglial tumors: {05-1886fx01c}, CR; {05-1886fx02c}, PR; {05-1886fx03c}, SD; {05-1886fx04c}, PD; {05-1886fx06g}, control brain. 1p chromosomal status is depicted as {05-1886fx01c}, no loss of 1p and {05-1886fx04c}, 1p LOH.

 
Genes associated with survival. We next performed supervised clustering to identify genes associated with overall survival after diagnosis. For this analysis, we compared expression profiles of tumors from patients with the shortest survival time (2.0 ± 0.3 years, n = 7) with those with the longest survival time (17.6 ± 4.4 years, n = 8) after diagnosis. SAM analysis identified 103 probe sets (92 genes; see Supplementary Data) associated with patient survival. Thirty (29%) of these probe sets are located on either 1p or 19q chromosomal arms. PCA of survival-associated genes identifies three main clusters of samples: oligodendroglial tumors with short survival, oligodendroglial tumors with long survival, and control samples. Low-grade samples cluster between control and tumor samples. Similar subgroups were identified by hierarchical clustering using these probe sets (Fig. 4). It is interesting to note that the subgroups identified by hierarchical clustering are virtually identical to the subgroups that were identified by unsupervised clustering (Fig. 1). Most oligodendroglial tumors were correctly distributed on survival after diagnosis by PCA1: PCA1 > 0 in 12 of 14 samples with favorable prognosis (i.e., survival time > 7 years after diagnosis), whereas PCA1 < 0 in 8 of 11 samples with relatively short survival after diagnosis (i.e., <7 years).



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  		Figure 4. PCA hierarchical clustering based on 103 probe sets associated with survival after diagnosis. A, PCA identifies three main clusters of samples: oligodendroglial tumors with short survival, oligodendroglial tumors with long survival, and control samples. Two low-grade samples (38 and 42; survival, <10 years; {05-1886fx02c}) cluster between control and tumor samples. PCA analysis separates short versus long survivors on the PCA1, whereas control and tumor samples are separated by PCA2. B, hierarchical clustering based on 103 differentially expressed probe sets. Relative expression levels of individual genes (columns) are plotted against individual tumor samples (rows). Gene expression levels: red, high expression (+2); green, low expression (–2). Dendrograms, hierarchical clustering (Euclidian distance) of samples (top) and genes (left). Interestingly, the subgroups identified by hierarchical clustering are virtually identical to the subgroups that were identified by unsupervised clustering (Fig. 1). Survival after diagnosis is depicted as {05-1886fx01c}, >10 years of survival; {05-1886fx02c}, <10 years of survival; {05-1886fx03c}, <7 years of survival; {05-1886fx04c}, <4 years of survival; {square}, patient still alive; or {05-1886fx06g}, control brain.

 

   Discussion
Top
 Abstract
 Introduction
 Materials and Methods
 Results
 Discussion
References
 
We have used oligonucleotide arrays to identify genes associated with response to treatment, patient survival, and common chromosomal aberrations in 28 oligodendroglial tumors. Our study identified 16 probe sets/genes that are associated with treatment response and 103 probe sets associated with patient survival. We also identified 376 probe sets associated with LOH on 1p, 64 probe sets associated with LOH on 19q, and 60 probe sets associated with LOH on both 1p and 19q. Although other studies have identified subgroups of oligodendroglial tumors associated with tumor grade (18), prognosis (11), and LOH on 1p (19), our study is the first to directly and comprehensively correlate gene expression with response to treatment, survival, and chromosomal aberrations in oligodendroglial tumors.

Chromosomal aberrations and response to treatment. Our results confirm the previously identified correlation of LOH on 1p and 19q with favorable response to chemotherapy (12, 15, 16); 11 of 13 (85%) of oligodendrogliomas with combined LOH on 1p and 19q showed response to chemotherapy, whereas this response was observed in only 4 of 11 (36%) tumors that have retained both chromosomal arms. Our results also confirm the observation that 1p and 19q are often codeleted in oligodendroglial tumors: 13 of 14 samples with LOH on 1p also showed LOH on 19q. It is interesting to note that deletion of the 1p and 19q arms is sometimes the only genomic aberration observed in oligodendroglioma (17, 27), suggesting that an as yet to be identified tumor suppressor gene resides on either chromosomal arm. Chromosomal aberrations that are associated with poor prognosis and negatively correlated with response to treatment include LOH on 10q (12, 15, 28, 29) and EGFR amplification (28, 29). Indeed, samples used in this study with these aberrations also had poor prognosis and most had no response to treatment. Similar to reported (28), LOH on 10q and EGFR amplifications are observed at relatively low frequency (14% for both in this study) and negatively correlated with LOH on 1p and 19q (for review, see refs. 30, 31).

Genes associated with chromosomal aberrations. This study identified 376, 64, and 60 probe sets associated with LOH on 1p, 19q, and 1p and 19q, respectively. Of these probe sets, 136 of 376 (36%), 25 of 64 (39%), and 49 of 60 (82%) are located on the deleted chromosomal arm(s). Because the average expression level for these genes is ~50% following allelic loss, it suggests these genes have an allele number dependent expression level. The predictive value of the probe sets associated with 1p and 19q LOH was tested on 10 additional samples; all but one were clustered according to the chromosomal aberration(s) identified by LOH-PCR and/or FISH. Our data therefore indicate that probe sets associated with LOH on 1p and/or 19q can predict losses on these chromosomal arms in anaplastic oligodendrogliomas and suggests that expression profiling can be used to identify large chromosomal deletions in cancer. Correlation between genomic aberrations and gene expression has been confirmed in other studies, including glioblastomas (32).

In a separate study, Mukasa et al. also identified genes associated LOH on 1p in oligodendroglial tumors (19). Interestingly, of the 212 differentially expressed transcripts identified, 31 were also associated with 1p LOH in this study with a similar ratio of expression between loss/retention of 1p. Twenty-eight of the commonly identified transcripts are down-regulated ~50% following LOH on 1p, and 25 are located on 1p. Although several of the transcripts identified by us have been confirmed in an independent study, the observation that not more common transcripts were identified may be explained by differences in tumor grade between the two studies. Mukasa et al. (19) used a combination of low-grade samples (7 of 11), anaplastic oligodendrogliomas (3 of 11), and one (1 of 11) oligoastrocytoma, whereas our study made use of only anaplastic oligodendrogliomas. Other studies have shown that many genes are differentially expressed between these two WHO grades (18). This illustrates the need for subclassification on tumor grade before identification of chromosomal aberration. Nevertheless, because the chromosomal aberrations in oligodendroglial tumors are strongly correlated with favorable response to treatment, genes associated with chromosomal aberrations can help identify oligodendroglial tumors that respond favorably to chemotherapy.

Genes associated with response to treatment. To our knowledge, our study is the first to correlate gene expression with response to chemotherapy in oligodendrogliomas. Correlation of expression profiles with chemosensitivity identified 16 probe sets/genes (FDR < 1 probe set) or 169 probe sets (FDR = 4.9%) that are associated with treatment response independent of chromosomal aberration or tumor grade. Twenty-four of 28 (86%) samples were correctly classified based on these 16 chemosensitivity-associated genes. The four (14%) incorrectly classified samples all were (partial) responders that were clustered among the nonresponding oligodendroglial tumors. Two of these four tumors had LOH on 1p and 19q, one with LOH on 19q, and one sample that retained both copies of 1p and 19q. In comparison, classification based on the tumors' 1p status, as currently used in the clinic, correctly classifies 20 of 28 (71%) samples. Of the eight samples misclassified based on the 1p status (29%), two were chemoresistant tumors with 1p LOH and six were chemosensitive without 1p LOH. In summary, of the tumors used in this study, prediction of treatment response based on expression of chemosensitivity-associated genes correctly classifies a higher percentage of tumors compared with classification based on the tumors' 1p status (15% versus 29%). Genes that are associated with response to treatment, therefore, may provide an alternative approach to identify chemosensitive oligodendroglial tumors. However, these genes will require validation in an independent study.

Many of the chemosensitivity-associated transcripts are involved in transcriptional regulation, interaction with the extracellular matrix, or affect cytoskeletal dynamics. For example, genes involved in regulation of transcription include (a) PAX8, a member of the paired box gene family of transcription factors (33); (b) Sp110, a protein that can function as an activator of transcription (34); (c) RENT1, a protein involved in mRNA nuclear export and nonsense-mediated mRNA decay (35); and (d) TNFSF13, a member of the tumor necrosis factor ligand family that activate transcription via e.g. nuclear factor-{kappa}B (NF-{kappa}B). TNFSF13 transgenic mice develop lymphoid tumors (36). Transcripts involved in the cellular interaction with the extracellular matrix include (a) MAN1C1, an {alpha}-mannosidase involved in the maturation of N-linked glycans (37); (b) CHSY1 (38) synthesizes chondroitin sulfate, a widely expressed glycosaminoglycan (39); and (c) LGALS9, a member of the tandem repeat type galectins that bind ß-galactoside. LGALS9 is expressed at high levels in distant metastasis of breast cancer (for review, see ref. 40). We also identified two chemosensitivity associated transcripts that are involved in regulation of cytoskeletal dynamics: (a) ARPC1B, involved in the branching of actin filaments and down-regulated in gastric cancers (41); and (b) IQGAP1, a scaffolding protein that interacts with components of the cytoskeleton. Overexpression of IQGAP1 enhances cell migration (42). Other genes expressed at high levels in chemoresistant oligodendrogliomas include (a) AQP1, a water channel often highly expressed in malignant gliomas (43) that plays a role in migration and neovascularization of tumors (44); (b) TRIM56, a member of the tripartite motif family; and (c) ARH, an adaptor protein that interacts with the low-density lipoprotein receptor (45). In summary, the genes identified in this study that are associated with chemosensitivity are involved in several discrete cellular processes, and these transcripts may help identify the molecular mechanisms that underlie chemosensitivity.

Genes associated with survival. Comparison of expression profiles to patient survival after diagnosis identified 103 differentially expressed probe sets. The observation that many genes are differentially expressed suggests that different molecular pathways are affected in the tumors of short and long survivors. The genetic background of the tumor, therefore, seems an important factor in determining the prognosis of the patient, although other factors also can contribute significantly to patient survival (e.g., tumor location). Therefore, genes that are differentially expressed between long and short survivors can help identify patient subgroups that are associated with favorable prognosis.

Functional analysis reveals that many transcripts up-regulated in short survivors are involved in the regulation of transcription. Examples include (a) BTEB1, a member of the SP1-like/KLF family of transcription regulators (46); (b) BCL10, an activator NF-{kappa}B (47); (c) DR1, a transcriptional repressor (48); (d) JUN, part of the activator protein transcription factor complex (49); (e) PTPN12 and (f) PTP4A2, members of the protein tyrosine phosphatase family that regulate processes, including cell growth, differentiation, mitotic cycle, and oncogenic transformation; (g) SFRS4, a member of the SR family of splicing factors (50); and (h) LMO4, a LIM domain-containing protein that may play a role as a transcriptional regulator (51). In contrast, transcripts encoding proteins involved in RNA translation are down-regulated in short survivors. They include five ribosomal proteins (RPL24, RPL3, PRL7, RPLP2, and RPS3; for review, see ref. 52) and proteins involved in post-transcriptional modification like CUGBP1 (53) and RBM4 (54).

In conclusion, our results indicate that expression profiling can identify transcripts associated with chromosomal aberrations, chemotherapeutic response, and survival after diagnosis. These transcripts can help identify patient subgroups with a high likelihood to respond to treatment and patient subgroups with favorable prognosis.


   Acknowledgments
 
The costs of publication of this article were defrayed in part by the payment of page charges. This article must therefore be hereby marked advertisement in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.


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

Received 5/31/05. Revised 8/ 3/05. Accepted 9/27/05.


   References
Top
 Abstract
 Introduction
 Materials and Methods
 Results
 Discussion
 References
 

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