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1 International Agency for Research on Cancer, Lyon, France; 2 Cancer Registry, Canton of Zurich, Zurich, Switzerland; 3 Department of Neurosurgery, College of Medicine, Little Rock, Arkansas; and 4 Departments of Neurosurgery, Radiology, and Pathology, University Hospital Zurich, Zurich, Switzerland
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ABSTRACT |
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 Top ABSTRACT INTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONREFERENCES |
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A:T mutations at CpG sites were more frequent in secondary than primary glioblastomas (56% versus 30%; P = 0.0208). This suggests that the acquisition of TP53 mutations in these glioblastoma subtypes occurs through different mechanisms. |
INTRODUCTION |
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TopABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONREFERENCES |
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From a clinical and biological point of view, a distinction between primary and secondary glioblastoma is important. Primary (de novo) glioblastomas manifest rapidly, without evidence of less malignant precursor lesions, after a short clinical history. Secondary glioblastomas develop more slowly by progression from low-grade [World Health Organization (WHO) grade II] or anaplastic astrocytoma (WHO grade III; ref. 2 ). These glioblastoma subtypes affect patients at different ages and through different genetic pathways (2 , 3) . However, no data are available on the relative frequency of these glioblastoma subtypes at a population level.
Oncogenes (EGFR, PDGF and its receptors) and tumor suppressor genes (p16INK4a, p14ARF, PTEN, RB1, and TP53) are involved in the evolution of glioblastomas. Frequent loss of heterozygosity (LOH) at 1p, 10p, 10q, 19q, and 22q suggests the participation of additional tumor suppressor genes (2 , 4, 5, 6) . Whereas older age was shown to be predictive of poorer prognosis in several studies, the definition of genetic alterations predictive of response to therapy has been inconclusive, at least in part because of the usually small number of cases investigated (2 , 7) .
The present study is the first to examine key genetic alterations in glioblastomas and their impact on survival rates in a large population-based series of cases. It is based on 715 inhabitants of the Canton of Zurich, Switzerland who developed a glioblastoma during the period 1980 to 1994. We assessed the incidence of glioblastoma subtypes, survival rates, and key genetic alterations in this defined population.
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MATERIALS AND METHODS |
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TopABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONREFERENCES |
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1.16 million) during the 15-year period 1980 through 1994 (8)
. The incidence date was fixed as the date of the pathology report for patients who underwent surgery or the date of clinical diagnosis otherwise (including autopsied cases). Clinical diagnoses were based on CT or MRI. Survival time was computed as the time between the incidence date and the date of death, date of last contact if lost from follow-up evaluation, or December 31, 1999. Follow-up evaluation was complete for 99% of the cases with the mean follow-up time of 7.2 ± 7.6 months. Death certificates were collected at the Cantonal Cancer Registry. The mean age of patients was 61.3 ± 14.0 years. The age distribution of patients was as follows: <39 years, 6.9%; 40 through 49 years, 12.5%; 50 through 59 years, 21.1%; 60 through 69 years, 29.9%; 70 through 79 years, 22.1%; and >80 years, 7.6%.
Histology Review.
The 715 glioblastomas included 8 giant-cell glioblastomas and 5 gliosarcomas. The majority of cases (571 cases, 80%) were histologically confirmed following surgical intervention (385 cases, 54%) or at autopsy (186 cases, 26%). The remaining 144 cases (20%) were clinically diagnosed only by CT or MRI, typically based on the presence of an irregularly shaped lesion of contrast enhancement with a central area of necrosis and perifocal edema (2)
. The original histologic specimens of 549 of 571 (96%) histologically diagnosed cases were reevaluated by two neuropathologists (P-L.D.P., P.K.) according to the new WHO classification of tumors of the nervous system (2)
.
Glioblastoma Subtypes.
The following criteria were used to distinguish between glioblastoma subtypes: Tumors were considered primary (de novo) when the glioblastoma diagnosis was made at the first biopsy, without clinical or histopathologic evidence of a less malignant precursor lesion. The diagnosis of secondary glioblastoma was made only in cases with histopathologic evidence of preceding low-grade or anaplastic glioma.
Treatment.
Approximately half of the patients (384 of 715; 54%) with glioblastomas underwent partial or complete surgical resection, usually at the Department of Neurosurgery, University Hospital, Zurich. The mean age of patients who underwent partial or complete surgical resection was significantly younger (56.1 ± 12.7 years) than those who did not undergo surgery (67.5 ± 12.8 years; P < 0.0001). Survival rates of patients who underwent partial or complete surgical resection were significantly longer (median, 7.9 ± 0.5 months) than those who did not undergo surgery (2.5 ± 0.1 months; P < 0.001). Information on radiotherapy was available for 494 cases (69%); of these, 307 (62%) received radiotherapy, usually with 2-Gy fractions and a total dose of 60 Gy. The mean age of patients who received radiotherapy was 54.6 ± 11.4 years, significantly younger than those who did not receive radiotherapy (68.4 ± 12.7 years; P < 0.0001). The survival rate of patients who received radiotherapy was significantly longer (median, 10 ± 1.2 months) than those who did not receive radiotherapy (2.0 ± 0.3 months; P < 0.001).
TP53 Mutations.
DNA was extracted from paraffin sections as reported previously (9)
. Prescreening for mutations in exons 4 through 8 of the TP53 gene by PCR–single-strand conformational polymorphism analysis was carried out as described previously (9)
. Primers for exon 4 were 5'-ACTGCTCTTTTCACCCATCTAC-3' (sense) and 5'-TCATGGAAGCCAGCCCCTCAG-3' (antisense). Samples that showed mobility shifts in single-strand conformational polymorphism analysis were further analyzed by direct DNA sequencing on an automated sequencing system (ABI PRISM 3100 Genetic Analyzer; Applied Biosystems, Foster City, CA) using an ABI PRISM BigDye Terminator version 1.1 Cycle Sequencing Ready Reaction Kit (Applied Biosystems).
EGFR Amplification.
To detect EGFR amplification, differential PCR was performed as described previously (10)
using the cystic fibrosis (CF) sequence as a reference. After PCR (26 to 30 cycles), PCR products were separated on 8% acrylamide gels using a Bio-Rad electrophoresis system (Bio-Rad, Hercules, CA). Gels were stained with ethidium bromide and digitalized using the Digital Science 1D analysis system (Kodak Digital Science, New Haven, CT). Quantitative analysis of the signal intensity was performed with the PhosphorImager 445 SI and the ImageQuant software (Molecular Dynamics, Urbana, IL). The mean EGFR to CF ratio of normal control DNA (peripheral blood of healthy adult donors) was 1.11 ± 0.05 (mean ± SD). The value of 2.36 (2x mean ± 3x SD) was regarded as the threshold for evidence of EGFR amplification (10)
.
Differential PCR for p16INK4a Homozygous Deletion.
To assess p16INK4a homozygous deletion, differential PCR was carried out using a primer set located in exon 1
of the p16INK4a gene and a ß-actin sequence as a reference as reported previously (11)
. Briefly, DNA was amplified with 30 cycles of PCR, and the PCR products were separated on 7% acrylamide gels. Gels were photographed using a DC120 Zoom Digital Camera (Kodak, Rochester, NY), and densitometry of the PCR fragments was performed as described previously. Samples in which the p16INK4a to ß-actin ratio was 
0.20 were considered as having homozygous deletion (11)
.
PTEN Mutations.
Prescreening for mutations in exons 1 through 9 of the PTEN gene by PCR–single-strand conformational polymorphism analysis was carried out as described previously (10)
. Samples that showed mobility shifts in single-strand conformational polymorphism analysis were further analyzed by direct DNA sequencing on an automated sequencing system as described previously (10)
.
Quantitative Microsatellite Analyses for LOH on Chromosome 10q.
Quantitative microsatellite analysis was carried out using two microsatellite markers on chromosome 10q (12)
. The microsatellite markers are located within the commonly deleted regions of 10q23 (D10S536) and 10q25 (D10S1683). PCR reactions were performed in a total volume of 12.5 µL with 2x TaqMan Universal PCR Master Mix, 0.4 µmol/L of each primer, 60 nmol/L probe [21-bp oligomer complementary to the microsatellite CA repeat: 5',6-carboxyfluorescein (FAM)-TGT GTG TGT GTG TGT GTG TGT-3' 6-carboxy-tetramethylrhodamine], and 10 ng DNA, with cycling parameters as reported previously (12)
. Primers, probe, and the TaqMan master mix were purchased from Proligo Primers and Probes (Paris, France), and PCR was carried out for each individual DNA in triplicate on a 96-well optical plate with an ABI 7900HT instrument (Applied Biosystems). The amplification of a reference pool of six reference loci served to normalize for differences in the amount of total input DNA as described previously (12)
. To calculate the average 
Ct [CT (normal)], DNA was isolated from 10 formalin-fixed, paraffin-embedded normal tissues. The Ct, Ct [Ct (microsatellite) – Ct (reference pool)], Ct [Ct (tumor) – Ct (normal)] values, the relative copy number (2–Ct), and the tolerance interval (TI) with a confidence of 95% determined from the pooled SD of normal DNA for both microsatellite loci were calculated as reported previously (12)
. On the basis of this TI, copy numbers <1.42 were considered to represent losses, whereas those >2.81 were considered to be gains.
Statistical Analyses.
The mean annual incidence rates per 100,000 population by sex were age-adjusted to the World Standard Population, the European Population, and to the United States standard of 2000 (13)
and were calculated using 5-year age groups. Ninety-five percent confidence intervals (CIs) were calculated after the logarithm transformation. Student’s t test was carried out to compare the mean age of patient groups. The log-rank test was carried out to assess univariate comparisons in survival rates. Multivariate Cox’s regression was carried out to identify predictive factors of survival of glioblastoma patients. Logistic regression analysis was carried out to assess associations between different genetic alterations.
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RESULTS |
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TopABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONREFERENCES |
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Survival of Glioblastoma Patients.
The median survival time of all of the glioblastoma patients after glioblastoma diagnosis was 4.9 months. Observed survival rates of glioblastoma patients were 42.4% at 6 months, 17.7% at 1 year, 3.3% at 2 years, and 1.2% at 3 years.
Age and Sex.
Univariate and multivariate analyses showed that old age is a significant predictive factor for poor survival of glioblastoma patients (Fig. 1)
. Younger patients (<50 years) showed significantly longer survival (median, 8.8 months) than older patients (>50 years; median, 4.1 months; P < 0.001). Among patients >50 years, age was predictive of observed survival rates (Fig. 1)
. The male to female ratio of all of the glioblastoma patients was 1.28.
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Primary glioblastomas developed in older patients (mean, 62 years), and secondary glioblastomas developed in middle-aged individuals (Figs. 2A
and 3
). Primary glioblastomas developed more frequently in male cases, and secondary glioblastomas were more frequently found in female cases (Fig. 3)
. Log-rank test showed that patients with primary glioblastomas had significantly shorter survival than those with secondary glioblastoma (Fig. 4)
, but age-adjusted multivariate analysis showed no significant difference.
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. In secondary glioblastomas, TP53 mutations and LOH 10q were frequent (65% and 63%), whereas the other alterations were infrequent (4 to 19%; Fig. 3
). Univariate analysis showed that absence of TP53 mutations and presence of LOH 10q were predictive of shorter survival of patients (Fig. 4)
. However, after age-adjustment (multivariate Cox’s regression analysis), only the presence of LOH 10q was associated with shorter patient survival (P = 0.067). Patients with glioblastoma carrying a TP53 codon 175 mutation showed shorter survival (median, 4.5 months) than those carrying the other mutation (7.8 months), but the difference was not statistically significant (P = 0.17).
Copresence of Genetic Alterations.
For 240 glioblastomas, data were available on TP53 mutations, EGFR amplification, p16INK4a homozygous deletion, PTEN mutations, and LOH 10q. The most frequent combinations were LOH 10q and EGFR amplification (25.8%), LOH 10q and TP53 mutations (23.7%), and LOH 10q and p16INK4a homozygous deletion (23.3%), followed by p16INK4a homozygous deletion and EGFR amplification (17.0%) and LOH 10q and PTEN mutations (16.2%), whereas other combinations of genetic alterations were infrequent (Fig. 5A)
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. In contrast, TP53 mutations, p16INK4a deletion, EGFR amplification, and PTEN mutations showed inverse associations with each other (Fig. 5A and B)
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Type and Distribution of TP53 Mutations and Polymorphisms.
One hundred seventy TP53 mutations were observed in 126 of 402 glioblastomas analyzed (31%). Double mutations were found in 26 cases; three mutations were found in 7 cases; and four mutations were found in 1 case. Of 170 mutations, 145 (85.3%) were missense mutations leading to amino acid change, 5 (2.9%) were nonsense mutations, 10 (5.9%) were deletions leading to stop codons, 1 (0.6%) was insertion leading to a stop codon, 5 (2.9%) were in-frame deletions, 1 (0.6%) was in-frame insertion, and 3 (1.8%) were splicing mutations. Fifty-three percent of deletions and insertions were located in codons 150 through 167.
In secondary glioblastomas, 57% of point mutations were in codons 248 and 273, whereas in primary glioblastomas, point mutations were more equally distributed through exons (17% in codons 248 and 273; P < 0.001; Fig. 6
). G:CA:T mutations at CpG sites were significantly more frequent in secondary glioblastomas (56%) than in primary glioblastomas (30%).
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Type and Distribution of PTEN Mutations.
Seventy-eight PTEN mutations were observed in 77 glioblastomas (23.5%). Of these, 33.3% were missense mutations leading to amino acid change and preferentially located in exons 1 to 6 (i.e., in the region homologous to tensin, auxilin, and dual-specificity phosphatases; Fig. 6
). Nonsense mutations (12.8%) and deletions or insertions leading to stop codons (32.1%) were located more equally distributed throughout the exons (Fig. 6)
. The others included splicing mutations (11.5%), in-frame deletions (7.7%), and point mutations in 5'-untranslated region (2.6%).
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DISCUSSION |
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TopABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONREFERENCES |
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Despite progress in surgery and radiotherapy and chemotherapy of brain tumors, the overall survival of patients with glioblastoma remains extremely poor. In the present population-based study, only 17.7% survived >1 year, 3.3% lived 2 years, and only 1.2% of patients were still alive 3 years after diagnosis. Similarly, a population-based study in Canada showed that after exclusion of neoplasms with a significant oligodendroglial component, only 15 of 689 glioblastoma patients (2.2%) diagnosed during 1975 to 1991 survived for 3 years (15) . Clinical trials of patients with malignant glioma show a better outcome because they usually combine glioblastomas and anaplastic astrocytomas. A recent meta-analysis showed that 40% of patients with malignant glioma treated with radiotherapy and 46% treated with radiotherapy plus chemotherapy survived >1 year (1) . However, clinical trials have a strong bias toward the recruitment of patients with higher preoperative Karnofsky performance score and of younger age (1) . In this population-based study, 30% of patients were >70 years (see Materials and Methods). They typically have a low Karnofsky performance score and would not be eligible for a therapy trial, and they are less likely to be treated using surgery and radiotherapy (see Materials and Methods). This is the main reason for the low survival rates in the present population-based study when compared with results of clinical trials and underlines that even in a country with unrestricted access to a sophisticated health care system, the prognosis of older patients with glioblastoma is still depressingly poor.
Several therapy trials and hospital-based studies have shown that younger glioblastoma patients (<50 years) have a better prognosis than older patients (7
, 16, 17, 18)
. The present study clearly showed that at the population level, age also was the most significant prognostic factor in univariate and multivariate analyses. Furthermore, this effect persisted through all of the age groups in a linear fashion, which allows calculation of the mean and median survival time from the date of glioblastoma diagnosis (Fig. 1)
.
Glioblastomas can be subdivided into primary and secondary neoplasms, which affect patients at different ages and through different genetic pathways (2
, 3)
. We show here that at the population-based level, secondary glioblastomas are a rare disease, amounting to only 5% of all of the glioblastomas. This is consistent with the finding of Dropcho et al. (19)
, who observed that 19 of 392 (5%) patients with glioblastomas at the University of Alabama had histologically proven previous low-grade gliomas. However, in the population-based series of the California Cancer Registry, the number of newly diagnosed cases of low-grade and anaplastic astrocytomas was 6% and 24% of incident glioblastoma cases (20)
. Similarly, in the present population-based study, the incidence rate of low-grade and anaplastic gliomas is approximately two or three times higher than that of secondary glioblastoma (21)
. The higher frequency of precursor lesions may be explained at least in part by the fact that a fraction of patients with low-grade or anaplastic astrocytoma die before progression to glioblastoma occurs. However, some cases with rapid progression from low-grade or anaplastic astrocytoma may have been misclassified as primary glioblastoma. Even considering this possibility, on a population-based level, secondary glioblastomas constitute a rare disease when compared with primary glioblastoma.
Univariate analysis revealed that patients with secondary glioblastoma survived significantly longer than those with primary glioblastoma, but this is likely because of the younger age of patients with secondary glioblastomas rather than a reflection of different biological behavior because the difference became nonsignificant in an age-adjusted multivariate analysis. We observed that secondary glioblastomas develop more frequently in women (male to female ratio, 0.65) than primary glioblastomas (1.33). This corroborates a previous finding that glioblastomas with TP53 mutations (a genetic hallmark of secondary glioblastomas) were more common in women (22) . This is surprising because in hospital-based studies (2 , 23) and in this population-based study, the incidence of low-grade or anaplastic gliomas in male patients was similar to or higher than in female patients (21) . The possibility exists that gliomas progress more frequently or more rapidly to glioblastoma in female patients.
The present study is one of the largest genetic analyses in glioblastomas and the first carried out on a population. Although not all of the archival samples (in particular, autopsy cases) were suitable for PCR amplification, we were able to assess key genetic alterations in up to 71% of histologically diagnosed cases. The TP53 gene encodes a protein that plays important roles in several cellular processes, including the cell cycle, response to DNA damage, apoptosis, cell differentiation, and neovascularization (24)
. Data on the predictive value of TP53 mutations in glioblastomas are contradictory. Although some hospital-based studies showed no association between TP53 status and outcome of glioblastoma patients (17
, 18)
, Schmidt et al. (25)
analyzed 97 glioblastoma cases and found that the presence of TP53 mutations was a favorable prognostic factor. In the present population-based study, univariate analysis revealed that the presence of TP53 mutations was predictive of longer survival (Fig. 4)
. However, age-adjusted multivariate analysis revealed no difference in survival between patients with and without TP53 mutations. It has been reported that low-grade astrocytomas with a TP53 mutation at codon 175 showed a significantly worse prognosis than morphologically similar tumors with mutations at other sites (26)
. In the present study, there was a tendency that patients with glioblastoma carrying a TP53 codon 175 mutation had shorter survival times than those carrying other mutations, but the difference was not statistically significant.
It is of interest to note that the type and distribution of TP53 mutations differed between glioblastoma subtypes. In secondary glioblastomas, 57% of mutations were located in the two hotspot codons, 248 and 273 (Fig. 6)
. In primary glioblastomas, mutations were more equally distributed through exons, only 17% occurring in codons 248 and 273 (Fig. 6)
. Furthermore, G:CA:T transitions at CpG sites were significantly more frequent in secondary than in primary glioblastomas. The best-characterized mechanism of G:CA:T transitions at CpG sites is deamination of 5-methylcytosine, which is clustered at CpG sites, resulting in substitution of 5-methylcytosine by thymine. This occurs spontaneously or is factor mediated (e.g., through the action of oxygen radicals or by nitric oxide produced by nitric oxide synthase in conditions of chronic inflammation; ref. 27
). Alternatively, our previous observation of a significant correlation between TP53 mutations and promoter methylation of the O6-methylguanine-DNA methyltransferase (MGMT) gene in low-grade astrocytomas and secondary glioblastomas suggests the possible involvement of endogenous or exogenous DNA alkylation at the O6-position of guanine (28)
. In any case, G:CA:T mutations at CpG sites, particularly in hotspot codons 248 and 273, seem to be an early event directly associated with malignant transformation in the pathway to secondary glioblastomas, whereas the less specific pattern of TP53 mutations in primary glioblastomas may, in a majority of cases, constitute secondary events reflecting increased genomic instability during tumor progression.
Epidermal growth factor receptor (EGFR) is a transmembrane receptor that binds to extracellular ligands such as epidermal growth factor and transforming growth factor and transduces a mitotic signal (29)
. EGFR amplification has been identified as a genetic hallmark of glioblastomas (2)
. The predictive value of EGFR amplification has been unclear. In previous studies (<40 cases), EGFR amplification was associated with poorer survival of glioblastoma patients (30
, 31)
. One study of 97 patients showed a lack of predictive value of EGFR amplification (25)
; similarly, a meta-analysis of seven previous studies (total, 395 glioblastoma cases) did not detect a significant predictive value of EGFR amplification (32)
. Shinojima et al. (33)
reported that EGFR amplification was a significant unfavorable predictor for overall survival in glioblastoma patients and that the EGFR gene status was a more significant prognostic factor in younger patients (<60 years). Other studies reported that EGFR amplification was a predictor of longer survival only in older glioblastoma patients (18
, 34)
. Simmons et al. (17)
reported that EGFR overexpression was associated with poorer survival of glioblastoma patients younger than the median age and that EGFR overexpression was negatively associated with survival in cases without the TP53 mutation. The present population-based study indicates that the presence of EGFR amplification does not affect survival of glioblastoma patients at any age. The striking finding of EGFR amplification in the present study is the unusual age distribution. EGFR amplification closely reflects the age distribution of primary glioblastomas and was not detected in any glioblastomas of patients <35 years (Fig. 2B)
.
The p16INK4a gene binds to cyclin-dependent kinase 4 and inhibits the cyclin-dependent kinase 4–cyclin D1 complex (35 , 36) . This complex phosphorylates the RB1 protein, thereby inducing release of the E2F transcription factor that activates genes involved in the late G1 and S phases (35 , 36) . In glioblastomas, disruption of the p16INK4a gene occurs through homozygous deletion (2) . Findings regarding the predictive value of p16INK4a homozygous deletion have been inconsistent. In an analysis of 46 cases, Kamiryo et al. (37) reported that homozygous p16INK4a deletion was a significantly unfavorable criterion for survival of glioblastoma patients. Another study showed that homozygous p16INK4a deletion was associated with shorter survival only in a subgroup of glioblastoma patients >50 years of age (38) . In the present population-based study, univariate and multivariate analyses failed to show any predictive value of homozygous p16INK4a deletion. We did observe a significant association between EGFR amplification and p16INK4a deletion, in agreement with the findings of previous hospital-based studies based on a small numbers of cases (39 , 40) .
PTEN gene locates on chromosome 10q23 and encodes a protein that plays important roles in the regulation of cell proliferation, apoptosis, and tumor invasion (41 , 42) . PTEN mutations have been reported in 15 to 40% of glioblastomas (42 , 43) . PTEN homozygous deletions may occur, but they are rare in glioblastomas (<2%; ref. 44 ). Promoter methylation may be alternative mechanisms of loss of PTEN expression, but the significance of PTEN methylation in the evolution of glioblastomas remains to be clarified (45) . In several previous studies, PTEN mutations were not associated with prognosis of glioblastoma patients (18 , 25 , 46) , and this was confirmed in the present population-based study. Interestingly, most missense mutations were located in exons 1 to 6, the region homologous to tensin, auxilin, and dual-specificity phosphatases, whereas nonsense mutations and deletions/insertions leading to stop codons and protein truncation were located more equally throughout the gene. This suggests that cells with PTEN truncation at any site or PTEN missense mutations in the region homologous to tensin/auxilin and dual-specificity phosphatases acquire transformed phenotype.
LOH 10 is the most frequent genetic alteration in glioblastomas and occurs in 60 to 80% of cases (47, 48, 49, 50) . Many glioblastomas seem to have lost one entire copy of chromosome 10. LOH occurs most frequently at three common loci (i.e., 10p14-p15, 10q23–24, and 10q25-pter), suggesting the presence of several tumor suppressor genes (47, 48, 49 , 51) . We show here that LOH 10q is the most frequent genetic alteration in the pathways to primary and secondary glioblastomas. LOH 10q has been found to be associated with reduced survival of glioblastoma patients in previous studies (25 , 52 , 53) , and this was confirmed at the population level. The presence of LOH 10q was the only genetic alteration associated with shorter survival.
Several previous studies focused on genetic alterations and their impact on survival of glioblastoma patients. However, most of these were based on small case numbers and usually on a single cancer-related gene. To obtain better understanding of effect of copresence of different genetic alterations, we carried out analyses of several key genetic alterations in a large number of glioblastomas. Our population-based study shows that LOH 10q was typically copresented with any of the other genetic alterations (Fig. 5)
. In contrast, TP53 mutations, p16INK4a deletion, EGFR amplification, and PTEN mutations showed inverse associations with each other, except for a positive correlation between p16INK4a deletion and EGFR amplification (Fig. 5)
. This suggests that LOH 10q plus at least one other genetic alteration may be operative in the development of a majority of glioblastomas. LOH 10q25-qter distal to the PTEN seems to be associated with acquisition of the glioblastoma phenotype (54)
, suggesting that a tumor suppressor gene in this region may be crucial in the development of glioblastomas. Candidate genes include DMBT1 (52
, 55)
and FGFR2 (52)
. Identification and validation of such a gene would be an important advancement in our understanding of the pathogenesis of glioblastomas and in devising new strategies for the management of this most malignant brain tumor.
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ACKNOWLEDGMENTS |
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FOOTNOTES |
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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.
Requests for reprints: Hiroko Ohgaki, International Agency for Research on Cancer, 150 cours Albert Thomas, 69372 Lyon Cedex 08, France. Phone: 33-472-73-85-34; Fax: 33-472-73-85-64; E-mail: ohgaki{at}iarc.fr
Received 4/27/04. Revised 6/18/04. Accepted 7/19/04.
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 T. Wakabayashi, T. Kayama, R. Nishikawa, H. Takahashi, T. Yoshimine, N. Hashimoto, T. Aoki, K. Kurisu, A. Natsume, M. Ogura, et al. A Multicenter Phase I Trial of Interferon-{beta} and Temozolomide Combination Therapy for High-grade Gliomas (INTEGRA Study) Jpn. J. Clin. Oncol., October 1, 2008; 38(10): 715 - 718. [Abstract] [Full Text] [PDF]
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 L. W Buie and J. Valgus Bevacizumab: A Treatment Option for Recurrent Glioblastoma Multiforme Ann. Pharmacother., October 1, 2008; 42(10): 1486 - 1490. [Abstract] [Full Text] [PDF]
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 D. W. Parsons, S. Jones, X. Zhang, J. C.-H. Lin, R. J. Leary, P. Angenendt, P. Mankoo, H. Carter, I-M. Siu, G. L. Gallia, et al. An Integrated Genomic Analysis of Human Glioblastoma Multiforme Science, September 26, 2008; 321(5897): 1807 - 1812. [Abstract] [Full Text] [PDF]
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 A. Idbaih, F. Ducray, M. Sierra Del Rio, K. Hoang-Xuan, and J.-Y. Delattre Therapeutic Application of Noncytotoxic Molecular Targeted Therapy in Gliomas: Growth Factor Receptors and Angiogenesis Inhibitors Oncologist, September 1, 2008; 13(9): 978 - 992. [Abstract] [Full Text] [PDF]
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 W. P. Mason and J. G. Cairncross Invited Article: The expanding impact of molecular biology on the diagnosis and treatment of gliomas Neurology, July 29, 2008; 71(5): 365 - 373. [Abstract] [Full Text] [PDF]
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S. P. Reddy, R. Britto, K. Vinnakota, H. Aparna, H. K. Sreepathi, B. Thota, A. Kumari, B.M. Shilpa, M. Vrinda, S. Umesh, et al. Novel Glioblastoma Markers with Diagnostic and Prognostic Value Identified through Transcriptome Analysis Clin. Cancer Res., May 15, 2008; 14(10): 2978 - 2987. [Abstract] [Full Text] [PDF]
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C.-H. Kwon, D. Zhao, J. Chen, S. Alcantara, Y. Li, D. K. Burns, R. P. Mason, E. Y.-H. P. Lee, H. Wu, and L. F. Parada Pten Haploinsufficiency Accelerates Formation of High-Grade Astrocytomas Cancer Res., May 1, 2008; 68(9): 3286 - 3294. [Abstract] [Full Text] [PDF]
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Y. Li, F. Guessous, S. Kwon, M. Kumar, O. Ibidapo, L. Fuller, E. Johnson, B. Lal, I. Hussaini, Y. Bao, et al. PTEN Has Tumor-Promoting Properties in the Setting of Gain-of-Function p53 Mutations Cancer Res., March 15, 2008; 68(6): 1723 - 1731. [Abstract] [Full Text] [PDF]
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P. C. Huszthy, D. Goplen, F. Thorsen, H. Immervoll, J. Wang, A. Gutermann, H. Miletic, and R. Bjerkvig Oncolytic Herpes Simplex Virus Type-1 Therapy in a Highly Infiltrative Animal Model of Human Glioblastoma Clin. Cancer Res., March 1, 2008; 14(5): 1571 - 1580. [Abstract] [Full Text] [PDF]
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G. Filippini, C. Falcone, A. Boiardi, G. Broggi, M. G. Bruzzone, D. Caldiroli, R. Farina, M. Farinotti, L. Fariselli, G. Finocchiaro, et al. Prognostic factors for survival in 676 consecutive patients with newly diagnosed primary glioblastoma Neuro-oncol, February 1, 2008; 10(1): 79 - 87. [Abstract] [Full Text] [PDF]
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D. Kuga, M. Mizoguchi, Y. Guan, N. Hata, K. Yoshimoto, T. Shono, S. O. Suzuki, Y. Kukita, T. Tahira, S. Nagata, et al. Prevalence of copy-number neutral LOH in glioblastomas revealed by genomewide analysis of laser-microdissected tissues Neuro-oncol, January 1, 2008; 10(6): 995 - 1003. [Abstract] [Full Text] [PDF]
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H. Aoki, T. Yokoyama, K. Fujiwara, A. M. Tari, R. Sawaya, D. Suki, K. R. Hess, K. D. Aldape, S. Kondo, R. Kumar, et al. Phosphorylated Pak1 Level in the Cytoplasm Correlates with Shorter Survival Time in Patients with Glioblastoma Clin. Cancer Res., November 15, 2007; 13(22): 6603 - 6609. [Abstract] [Full Text] [PDF]
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 F. B. Furnari, T. Fenton, R. M. Bachoo, A. Mukasa, J. M. Stommel, A. Stegh, W. C. Hahn, K. L. Ligon, D. N. Louis, C. Brennan, et al. Malignant astrocytic glioma: genetics, biology, and paths to treatment Genes & Dev., November 1, 2007; 21(21): 2683 - 2710. [Abstract] [Full Text] [PDF]
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D. Krex, B. Klink, C. Hartmann, A. von Deimling, T. Pietsch, M. Simon, M. Sabel, J. P. Steinbach, O. Heese, G. Reifenberger, et al. Long-term survival with glioblastoma multiforme Brain, October 1, 2007; 130(10): 2596 - 2606. [Abstract] [Full Text] [PDF]
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 J. B. Axelsen, J. Lotem, L. Sachs, and E. Domany Genes overexpressed in different human solid cancers exhibit different tissue-specific expression profiles PNAS, August 7, 2007; 104(32): 13122 - 13127. [Abstract] [Full Text] [PDF]
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 H. Aoki, Y. Takada, S. Kondo, R. Sawaya, B. B. Aggarwal, and Y. Kondo Evidence That Curcumin Suppresses the Growth of Malignant Gliomas in Vitro and in Vivo through Induction of Autophagy: Role of Akt and Extracellular Signal-Regulated Kinase Signaling Pathways Mol. Pharmacol., July 1, 2007; 72(1): 29 - 39. [Abstract] [Full Text] [PDF]
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D. K. Sandsmark, H. Zhang, B. Hegedus, C. L. Pelletier, J. D. Weber, and D. H. Gutmann Nucleophosmin Mediates Mammalian Target of Rapamycin-Dependent Actin Cytoskeleton Dynamics and Proliferation in Neurofibromin-Deficient Astrocytes Cancer Res., May 15, 2007; 67(10): 4790 - 4799. [Abstract] [Full Text] [PDF]
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H. Ohgaki and P. Kleihues Genetic Pathways to Primary and Secondary Glioblastoma Am. J. Pathol., May 1, 2007; 170(5): 1445 - 1453. [Abstract] [Full Text] [PDF]
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M. Eoli, F. Menghi, M. G. Bruzzone, T. De Simone, L. Valletta, B. Pollo, L. Bissola, A. Silvani, D. Bianchessi, L. D'Incerti, et al. Methylation of O6-Methylguanine DNA Methyltransferase and Loss of Heterozygosity on 19q and/or 17p Are Overlapping Features of Secondary Glioblastomas with Prolonged Survival Clin. Cancer Res., May 1, 2007; 13(9): 2606 - 2613. [Abstract] [Full Text] [PDF]
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M. Nakamura, K. Shimada, E. Ishida, T. Higuchi, H. Nakase, T. Sakaki, and N. Konishi Molecular pathogenesis of pediatric astrocytic tumors Neuro-oncol, April 1, 2007; 9(2): 113 - 123. [Abstract] [Full Text] [PDF]
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 A. Broniscer, S. J. Baker, A. N. West, M. M. Fraser, E. Proko, M. Kocak, J. Dalton, G. P. Zambetti, D. W. Ellison, L. E. Kun, et al. Clinical and Molecular Characteristics of Malignant Transformation of Low-Grade Glioma in Children J. Clin. Oncol., February 20, 2007; 25(6): 682 - 689. [Abstract] [Full Text] [PDF]
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 A. Semmler, M. Simon, S. Moskau, and M. Linnebank The Methionine Synthase Polymorphism c.2756A>G Alters Susceptibility to Glioblastoma Multiforme. Cancer Epidemiol. Biomarkers Prev., November 1, 2006; 15(11): 2314 - 2316. [Abstract] [Full Text] [PDF]
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Y. Kotliarov, M. E. Steed, N. Christopher, J. Walling, Q. Su, A. Center, J. Heiss, M. Rosenblum, T. Mikkelsen, J. C. Zenklusen, et al. High-resolution Global Genomic Survey of 178 Gliomas Reveals Novel Regions of Copy Number Alteration and Allelic Imbalances Cancer Res., October 1, 2006; 66(19): 9428 - 9436. [Abstract] [Full Text] [PDF]
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 R. S. Muraoka-Cook, L. S. Caskey, M. A. Sandahl, D. M. Hunter, C. Husted, K. E. Strunk, C. I. Sartor, W. A. Rearick Jr., W. McCall, M. K. Sgagias, et al. Heregulin-Dependent Delay in Mitotic Progression Requires HER4 and BRCA1. Mol. Cell. Biol., September 1, 2006; 26(17): 6412 - 6424. [Abstract] [Full Text] [PDF]
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C.-L. Tso, P. Shintaku, J. Chen, Q. Liu, J. Liu, Z. Chen, K. Yoshimoto, P. S. Mischel, T. F. Cloughesy, L. M. Liau, et al. Primary Glioblastomas Express Mesenchymal Stem-Like Properties Mol. Cancer Res., September 1, 2006; 4(9): 607 - 619. [Abstract] [Full Text] [PDF]
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Q. Wei, L. Clarke, D. K. Scheidenhelm, B. Qian, A. Tong, N. Sabha, Z. Karim, N. A. Bock, R. Reti, R. Swoboda, et al. High-grade glioma formation results from postnatal pten loss or mutant epidermal growth factor receptor expression in a transgenic mouse glioma model. Cancer Res., August 1, 2006; 66(15): 7429 - 7437. [Abstract] [Full Text] [PDF]
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J. A. McCubrey, M. M. LaHair, and R. A. Franklin OSU-03012 in the Treatment of Glioblastoma Mol. Pharmacol., August 1, 2006; 70(2): 437 - 439. [Abstract] [Full Text] [PDF]
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M. Wrensch, J. K. Wiencke, J. Wiemels, R. Miike, J. Patoka, M. Moghadassi, A. McMillan, K. T. Kelsey, K. Aldape, K. R. Lamborn, et al. Serum IgE, Tumor Epidermal Growth Factor Receptor Expression, and Inherited Polymorphisms Associated with Glioma Survival. Cancer Res., April 15, 2006; 66(8): 4531 - 4541. [Abstract] [Full Text] [PDF]
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D. A. Reardon, J. N. Rich, H. S. Friedman, and D. D. Bigner Recent Advances in the Treatment of Malignant Astrocytoma J. Clin. Oncol., March 10, 2006; 24(8): 1253 - 1265. [Abstract] [Full Text] [PDF]
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S. Ghosh and G. J. Duigou Decreased Replication Ability of E1-Deleted Adenoviruses Correlates with Increased Brain Tumor Malignancy Cancer Res., October 1, 2005; 65(19): 8936 - 8943. [Abstract] [Full Text] [PDF]
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J. K. Wiencke, K. Aldape, A. McMillan, J. Wiemels, M. Moghadassi, R. Miike, K. T. Kelsey, J. Patoka, J. Long, and M. Wrensch Molecular Features of Adult Glioma Associated with Patient Race/Ethnicity, Age, and a Polymorphism in O6-Methylguanine-DNA-Methyltransferase Cancer Epidemiol. Biomarkers Prev., July 1, 2005; 14(7): 1774 - 1783. [Abstract] [Full Text] [PDF]
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T.-Y. Chou, C.-H. Chiu, L.-H. Li, C.-Y. Hsiao, C.-Y. Tzen, K.-T. Chang, Y.-M. Chen, R.-P. Perng, S.-F. Tsai, and C.-M. Tsai Mutation in the Tyrosine Kinase Domain of Epidermal Growth Factor Receptor Is a Predictive and Prognostic Factor for Gefitinib Treatment in Patients with Non-Small Cell Lung Cancer Clin. Cancer Res., May 15, 2005; 11(10): 3750 - 3757. [Abstract] [Full Text] [PDF]
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 J. Rahnenfuhrer, N. Beerenwinkel, W. A. Schulz, C. Hartmann, A. von Deimling, B. Wullich, and T. Lengauer Estimating cancer survival and clinical outcome based on genetic tumor progression scores Bioinformatics, May 15, 2005; 21(10): 2438 - 2446. [Abstract] [Full Text] [PDF]
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