• LOH;
  • meningioma;
  • 1p36;
  • SNP;
  • SSCP


  1. Top of page
  2. Abstract
  3. Material and methods
  4. Results
  5. Discussion
  6. References
  7. Supporting Information

Mapping loss of heterozygosity (LOH) regions in the genomes of tumor tissues is a practical approach for identifying genes whose loss is related to tumorigenesis. Conventional LOH analyses using microsatellite or single nucleotide polymorphism (SNP) markers require the simultaneous examination of tumor- and matched normal-DNA. Here, we improved the previously developed SNP-based LOH assay using single strand conformation polymorphism (SSCP) analysis, so that LOH in tumor samples heavily contaminated with normal DNA can now be precisely estimated, even when matched normal DNA is not available. We demonstrate the reliability of the improved SSCP-based LOH detection method, called the LOH estimation by quantitative SSCP analysis using averaged control (LOQUS-AC), by comparing the results with those of the previous “LOH estimated by quantitative SSCP assay” (LOQUS) method. Using the LOQUS-AC assay, LOH was detected at a high consistency (98.1%) with the previous LOQUS method. We then applied this new method to characterize LOH profiles in 130 meningiomas, using 68 SNPs (i.e., a mean inter-SNP interval of 441 kbp) that are evenly distributed throughout chromosome 1p36. Benign, atypical and anaplastic meningiomas exhibited 1p36 LOH at frequencies of 48.39, 84.62 and 100.00%, respectively, using LOQUS-AC. Subsequently, we detected a candidate common LOH region on 1p36.11 that might harbor tumor suppressor genes related to malignant progression of meningioma. © 2007 Wiley-Liss, Inc.

Finding genetic alterations in tumor tissues is a basic approach to elucidate the mechanism of tumor formation or progression. Among the methods available, loss of heterozygosity (LOH) analysis is widely used for various tumor types, including meningioma, a common form of brain tumor arising from meningothelial cells. The majority (80–90%) of meningiomas have a benign character and are classified as World Health Organization grade I. The remaining meningiomas, however, which are categorized as grade II or III, are more aggressive and have a higher recurrence rate than grade I tumors.1–3 An LOH on 22q, which leads to the inactivation of the NF2 tumor suppressor gene located on 22q12.2, is detected in 40–70% of meningiomas.4, 5 This genetic alteration is an early event in the pathogenesis of meningiomas; mutations and/or deletions of this gene are frequently observed, even in grade I tumors.6, 7 On the other hand, the progression of meningiomas is thought to involve a multi-step process with the cumulative acquisition of genetic alterations.8 Little is known, however, about the actual genes associated with malignant progression. The investigation of LOH has revealed some chromosomal regions that are rarely affected in grade I meningiomas, but are frequently deleted in grade II or III meningiomas.9–11 Among them, chromosome 1p is considered to be one of the most probable regions in which a deletion is associated with the malignant progression of meningiomas and correlates with increased morbidity.12, 13 It has also been suggested that a putative area on chromosome 1p harbors tumor suppressor genes, which are yet to be identified; therefore, more detailed mapping of LOH regions is important to clarify the mechanism of meningioma progression.14–16

In a previous study, we established a new LOH-detection method, named LOQUS (LOH Estimation by Quantitative single-strand conformation polymorphism [SSCP] analysis), that can detect LOH at the single nucleotide polymorphism (SNP) level using a conventional capillary sequencer.17 The remarkable advantages of this system are (i) high sensitivity for LOH detection, which allows for the examination of highly heterogeneous tumor samples (e.g., samples contaminated with up to 80% noncancer cells), and (ii) flexibility of experimental design (i.e., optional high-density analyses can be performed simply by adding SNPs from public databases or other sources).

One of the limitations of LOQUS analysis is that it requires paired DNAs of tumor and normal tissues from the same individual. In the present study, we modified the LOQUS method and established an improved LOH detection system that does not require matched nontumor DNA. In this new method, LOH is evaluated based on the distribution of the signal ratio of the two alleles of heterozygotes, which are predetermined using a limited number of unrelated normal individuals. In addition, this method also has the advantage of performing higher throughput analysis than that described for LOQUS.

We analyzed the LOH for 68 SNP markers on chromosome 1p36 (average inter-SNP distance of 441 kbp) in 130 meningiomas and eventually identified a narrowed region of LOH hot spots at 1p36.11 that might harbor tumor suppressor genes associated with meningiomas.

Material and methods

  1. Top of page
  2. Abstract
  3. Material and methods
  4. Results
  5. Discussion
  6. References
  7. Supporting Information

Samples and DNA preparation

Meningioma samples were obtained from patients during surgery at Kyushu University Hospital. A part of the tumor tissue was saved for histopathologic examination, the rest was snap-frozen in liquid nitrogen and stored at −80°C. Tumors were histologically diagnosed by qualified neuropathologists (S.O.S. and T.I.) and graded according to WHO criteria.1 A total of 130 tumor tissue samples were collected from 122 patients with meningiomas, including 8 anaplastic meningiomas, 27 atypical meningiomas and 95 benign meningiomas (see Table I for details). Multiple samples obtained from different surgeries of the same patients were included if the histologic diagnosis of the recurrent tumor was different from that of the primary tumor. Of these samples, 30 were also used for LOH analysis, using microsatellite markers. Tumor DNA was isolated from the frozen blocks using a QIAamp DNA Mini Tissue Kit (Qiagen, Valencia, CA). Normal DNA was isolated from blood samples using a QIAamp DNA Blood Kit (Qiagen). The present study was approved by the Ethics Committee of Kyushu University.

Table I. LOH with Tumor Grade and Histologic Subtype
WHO grade and histologic subtypeLOH no./Total no.LOH (%)
Grade I45/9348.39
Grade II22/2684.62
Grade III8/8100.00

Single nucleotide polymorphism

We chose 96 SNPs on the distal portion of chromosome 1p (from the telomeric end to 1p35.3) from the public database, International Hapmap Project ( SNPs with allele frequencies greater than 40% in the Japanese population were chosen from the database. The genomic sequences, including the chosen SNPs, were downloaded from NCBI (, and the repetitive sequences were masked by use of Repeatmasker ( Polymerase chain reaction (PCR) primer-pairs for all SNPs were designed for nonredundant regions, using Primer3 software,18 to obtain a product of 80–120 bp and a standardized primer melting temperature (Tm) of 60°C. Oligonucleotide primer pairs (custom synthesized at SIGMA Genosys, Hokkaido, Japan) were made to carry either a 5′-ATT or 5′-GTT for postlabeling purposes, as described previously.19

Polymerase chain reaction

PCR was performed in a total volume of 5 μl containing 25 ng of template DNA, 0.25 μM of each primer, 0.2 mM of each nucleotide, 0.125 U of AmpliTaq® DNA polymerase (Applied Biosystems, Foster City, CA), 27.5 ng of TaqStart™ antibody (Clontech Laboratories, Palo Alto, CA), 2 mM MgCl2, 10 mM Tris-HCl, pH 8.3, 50 mM KCl and 5% DMSO. The thermal cycle profile was 1 min at 94°C for initial heating, followed by 40 cycles of 30 sec at 94°C, 30 sec at 60°C and 1 min at 72°C.

PLACE-SSCP and data analysis

Post-PCR labeling was performed, followed by removal of the residual fluorescent nucleotides by gel filtration, as described previously.20 After post-PCR labeling, 2 μl/well of the product was added to the prepared loading plate containing 28 μl/well of a premix solution (27.75 μl/well of 0.5 mM EDTA and 0.25 μl/well of homemade single-strand size marker). The samples were heated at 90°C for 3 min. Electrophoresis was performed at 27°C under SSCP conditions using a 36 cm capillary in the ABI Prism® 3100 Genetic Analyzer (Applied Biosystems). The samples were loaded by electrokinetic injection at 2 kV for 10 sec and separated at 15 kV for 30 min at 27°C, using the sieving matrix of 10% linear polydimethylacrylamide in 2 × TME (60 mM Tris, 70 mM MES and 2 mM Na2EDTA), as described previously.21 Output data were converted to ASCII format and then imported to Quantitative Interpretation of SSCP in Capillary Array (QUISCA) software for analysis.22

Microsatellite analysis

Tumor and nontumor DNA was evaluated by a PCR-based LOH assay using 26 microsatellite markers located on chromosome 1p, as shown in Supplemental Table S1. PCR and fluorescence labeling were performed according to the method described previously.23 Capillary electrophoresis was performed with a 3730 Prism Genetic Analyzer (Applied Biosystems). Alleles were identified and peak heights were measured using GeneMapper software (Applied Biosystems, Version 3.0). Allelic status was assessed by the criteria established in a previous study.23


  1. Top of page
  2. Abstract
  3. Material and methods
  4. Results
  5. Discussion
  6. References
  7. Supporting Information

Microsatellite analysis on entire chromosome 1p

To examine the overall LOH status on chromosome 1p in meningiomas, we first performed the LOH analysis using 26 microsatellite markers distributed throughout the entire short arm of this chromosome. For this analysis, we used a subset30 of the tumor samples obtained from patients whose normal DNA samples were available. As shown in Figure 1, LOH was detected most frequently on 1p36, which is in agreement with several previous studies.14, 24 We then attempted to narrow down the region by a SNP-based LOH assay.

thumbnail image

Figure 1. LOH profiles of chromosome 1p in 30 meningioma samples. Microsatellite markers and case numbers with WHO grade of the tumor samples are shown on the left and at the top, respectively. Twenty-three grade I, 6 grade II and 1 grade III meningiomas were examined. The samples were arranged in the order (from high to low) of their LOH rates, which were determined by the observed LOH loci of the total informative loci. Black box, LOH; white box, retention of heterozygosity; gray box, not informative (homozygous or not determined).

Download figure to PowerPoint

Selection of SNP markers

We first chose 96 SNP markers, distributed over the distal portion of chromosome 1p (from the telomeric end to 1p35.3), to cover the entire 1p36, as described in the Materials and Methods. PCR reactions on nontumor DNA from 8 individuals were performed for each sequence-tagged site containing a SNP. Subsequently, PCR products were divided and used for sequencing and PLACE-SSCP analyses, to confirm the SNPs and to select SNPs suitable for precise quantitative analysis of alleles by SSCP. A total of 68 SNPs were used for subsequent LOQUS analyses (see Supplemental Table S2 for details).

Averaged control method

In the LOQUS assay, paired DNAs of tumor and normal samples are repeatedly analyzed by PLACE-SSCP to assess the variability of the allele signal ratio. LOH was statistically determined based on the distribution of the ratios of normal samples. Unfortunately, this method has the disadvantage of not being able to test tumor samples when the matched normal DNA is unavailable. Therefore, we exploited the possibility of detecting LOH using the signal ratio of alleles in heterozygous samples from multiple individuals as a control, instead of using matched nontumor DNA from the same patient. Here, we addressed the surgical tumor tissues including normal cells at the detective level so that LOH of tumors without matched normal DNA could be distinguished from homozygosity.

To test the possibility mentioned above, we first assessed the variability of the peak height ratios of alleles of all examined SNPs in many heterozygotes. We picked up 55 meningioma samples in which the corresponding nontumor DNAs were available. PLACE-SSCP analyses of all 68 SNPs were then performed using these samples. These 55 tumor DNAs were separately arranged to 2 μl plates and nontumor DNA samples from 24 different individuals were also included for the analysis by adding to each plate. We then determined the following values for all SNPs.

Rij(N): The peak-height ratio of alleles (fast to slow) of ith SNP in jth heterozygous nontumor sample.

Rik(T): The peak-height ratio of the alleles (fast to slow) of ith SNP in kth heterozygous tumor sample.

Ai(N): The average of Rij(N).

Vik(T): min [Rik(T)/Ai(N), Ai(N)/Rik(T)].

Some values were not determined because the individuals were homozygous for the particular SNPs. However, 5–19 (average 11.6) individuals were heterozygous for the SNPs examined. As a negative control, we replaced the data of tumor DNAs above to those of nontumor DNAs obtained from the same patients and performed the same analyses, then Rik(C) and Vik(C), which are the control data of Rik(T) and Vik(T) respectively, were calculated.

As shown in Figure 2a, the distribution of Vik(T) (1701 determinations) revealed a bimodal pattern, presumably representing a group of SNPs in a LOH region and another group representing those in a ROH region. Consistent with this interpretation, the distribution of the second group closely resembled that of Vik(C) (Fig. 2b). We named this procedure the LOH estimation by quantitative SSCP analysis using averaged control: LOQUS-AC.

thumbnail image

Figure 2. Distribution of Vik(T) showed bimodal pattern. Ai(N) was determined as the mean of Rij(N) in all heterozygous samples for each SNP marker (68 SNPs). Vik(T) (a.) and Vik(C) (b.), which were defined by min [Rik(T)/Ai(N), Ai(N)/Rik(T)] and min [Rik(C)/Ai(N), Ai(N)/Rik(C)], respectively, were then calculated. Columns indicate the frequencies of observed Vik(T) or Vik(C) within the bins of width 0.05.

Download figure to PowerPoint

In conclusion, the signal ratio of alleles in heterozygous samples from multiple individuals were used as an alternative control in the LOQUS assay, and based on the bimodal distribution pattern above, the appropriate threshold value of LOH was estimated to be between 0.65 and 0.85.

One would expect that the results analyzed by LOQUS-AC using the most appropriate threshold value, should be consistent with the conventional LOQUS method. Therefore, to infer the most appropriate threshold value of LOH, we tested an LOH estimation on 1701 loci analyzed above, based on a variable threshold value from 0.65 to 0.85. We also performed the conventional LOQUS assay using the data of paired DNAs within the same dataset. Subsequently, the total concordance rate, defined as the fraction of the loci showing the consistent determinations (LOH or ROH) in both assays, was calculated for each threshold value tested. In addition, specificity and sensitivity were also calculated, assuming that the LOQUS method provides an accurate answer. As shown in Figure 3, the maximum concordance rate of 98.1% was reached at the threshold value of 0.78, where the specificity is almost 100% (99.9%) and there is only a slight loss in the sensitivity (97.0%; 97.6% at maximum). Accordingly, we inferred that 0.78 should be the appropriate threshold value for detecting LOH by LOQUS-AC.

thumbnail image

Figure 3. Consistency of LOH determination between LOQUS-AC and LOQUS. The x-axis shows the tested threshold value of LOH determination in LOQUS-AC, and the y-axis shows the sensitivity (rhombus), specificity (quadrate) and total concordance rate (triangle) of LOH determination by a comparison with the conventional LOQUS method.

Download figure to PowerPoint

To further support this threshold value, we estimated the sample-to-sample variability of the allele signal ratio using the data set of Rij(N) and Ai(N) above. We determined the overall variability of Rij(N) (734 determinations) by calculating Vij(N), which is Rij(N)/Ai(N), and the variability of Vij(N) can be approximated by the normal distribution, judged by the Shapiro-Wilk W test using JMP software (SAS Institute, Cary, NC; Version 5.0.1J, 2002. Available at: (Supplementary Fig. 1).25 The mean and SD of Vij(N) were 1.000 and 0.072, respectively, comparable to the value of run-to-run variability of the peak-height ratios for normal samples in the previous study.17 The data set of another 24-individuals for all SNPs showed that the mean and SD of Vij(N) were highly reproducible. Accordingly, when we adopt three times the standard deviation as the threshold for determining the LOH, the threshold value becomes 0.784 (1–3 × 0.072), which is close to the inferred threshold value of Vij(T) for the LOH determination earlier. We thus conclude that a Vik(T) of less than 0.78 (∼3 times the SD from the mean) can be regarded as an LOH at a confidence level of 99.7% (according to the probability density of the Gaussian distribution). We adopted this criterion as an indication of LOH in the LOQUS-AC assay described later.

LOQUS-AC assay of meningioma tissue samples

To detect the critical LOH region on 1p in meningiomas, we analyzed LOH of the 68 SNPs on 1p36 in 130 meningiomas. PCR, subsequent post-PCR labeling, and electrophoresis for each SNP were performed with two 96-well microtiter plates, both of which contained 24 normal DNA samples. Figure 4 shows the summary of the assay. For example, Figure 4a reveals a complete 1p36 loss as the frequent pattern of benign meningiomas, which is in agreement with the results from the microsatellite analysis (see Fig. 1). The LOH on 1p36.12-35.3 in an atypical meningioma (M-160) and terminal LOH on 1p36.33-36.32 in a benign meningioma (M-50a) are shown in Figures 4b4c, respectively.

thumbnail image

Figure 4. Examples of LOQUS-AC assay of meningioma tissue samples. For each figure, cytogenetic position is shown on the right and a plot of Vik(T) on the left. In the middle, electrophoresis peaks (top for blood and bottom for tumor) with corresponding SNP ID and Vik(T) values (boxed in black for LOH and white for retention of heterozygosity) are shown. The vertical dotted line in each panel indicates the threshold value for LOH detection (0.78). (a) LOQUS-AC assay showing complete loss of 1p36 in a benign meningioma (M001). (b) LOQUS-AC assay of an atypical meningioma (M160) tissue, revealing LOH at 1p36.12-35.3. (c) LOQUS-AC assay of a benign meningioma (M50a) tissue indicating distal LOH at 1p36.33-36.21.

Download figure to PowerPoint

When tumor tissues are heavily contaminated with normal cells, the accuracy of detecting LOH is often reduced. Not surprisingly, we found 3 such tumor samples (M-007, M-035 and M-145) in the present study. In these samples, the majority of the Vik(T) values were near 0.78, the threshold value of LOH detection in the present method, but none were in the range of 0.9–1.0, where most of the Vik(T) of the SNPs in retention of heterozygosity (ROH) regions are clustered (Supplemental Fig. 2). We thus excluded these three samples from the following data analyses.

LOH profiles of 1p36 in meningiomas

The LOH profiles of the 127 meningiomas studied here are summarized in Figure 5. The tumor frequencies with LOH in 1p36 were 48.39% (45/93 cases) for Grade I, 84.62% (22/26 cases) for Grade II and 100.00% (8/8 cases) for Grade III, suggesting the progressive nature of LOH, in accordance with the grade of malignancy (See Table I for detail). These results were consistent with previous reports about genetic alterations of meningiomas.8, 26, 27 We then estimated the correlation between the LOH fraction and the grade of tumor malignancy. Statistical analysis showed significant differences between Grade I and Grade II (p = 0.001; Fisher's exact test), as well as Grade I and Grade III (p = 0.004; Fisher's exact test), but there was no significant difference between Grade II and Grade III (p = 0.322; Fisher's exact test), suggesting that 1p36 LOH is associated with the malignancy progression from benign meningiomas to atypical and/or anaplastic meningiomas. The LOH fractions were also compared among the histologic subtypes of Grade I meningiomas and there were no significant differences.

thumbnail image

Figure 5. LOH profiles in 130 meningiomas. The results of 95 grade I meningiomas, 27 grade II meningiomas and 8 grade III meningiomas are presented. Samples were arranged according to their LOH ratio (the ratio of number of LOH markers to that of informative markers). SNP markers are shown on the left. Case numbers and WHO grade of tumors are shown at the top. Black box, LOH; white box, retention; gray box, not informative (homozygous individual or not determined).

Download figure to PowerPoint

We also attempted to narrow down the common LOH regions that might harbor tumor suppressor genes related with the meningioma progression on 1p36. In total, 75 tumors with LOH were assembled (Fig. 6), and among them, all of the Grade III and the majority of Grade II meningiomas showed complete LOH of 1p36. We also noted that a small fraction of meningiomas showed a partial terminal LOH (M-050a and M-050b), interstitial LOH (M-003a and M-160), and complex LOH pattern (two or more discontinuous LOH, as observed for M-048, M-152 and M-049). Furthermore, based on the overlapping continuous LOH region in M-048, M-049, M-152 and M-160, the region that spans 2.02 Mbp, from rs6671571 to rs9438620, might be a novel candidate locus, which harbors tumor suppressor genes associated with meningiomas. The genes located in these regions and their possible involvement in meningioma progression are discussed later.

thumbnail image

Figure 6. Summary of 1p36 LOH regions in meningioma samples. The tumor samples with LOH are shown. Gray columns indicate LOH regions containing at least two continuous LOH markers with any number of noninformative markers and with boundaries defined in each direction by one retention marker. Black boxes indicate isolated LOH markers. Identified common LOH region was showed on the right. SNP markers are shown on the left. Case numbers are indicated at the top.

Download figure to PowerPoint


  1. Top of page
  2. Abstract
  3. Material and methods
  4. Results
  5. Discussion
  6. References
  7. Supporting Information

In the present study, we improved the LOQUS assay that we previously proposed for LOH-detection17 by developing a new approach called LOQUS-AC, which has the advantage of detecting LOH in tumor samples for which matched normal DNA samples are unavailable. The present method is also more efficient because of less repetition in the measurement, compared with the previous method. Conventional LOH analysis using microsatellite markers always requires paired DNA from the same patient because of the fact that the polymorphism could show many genotype patterns in individuals because they are multi-allelic. The recently reported strategy of microsatellite analysis based on real-time quantitative PCR, called Quantitative Microsatellite Analysis, also allows for LOH detection without using paired nontumor DNA, but this method requires tumor tissue containing at least 70% cancerous cells.28

On the other hand, normally only a single pattern of a heterozygous genotype can exist on SNPs; theoretically, this means LOH analyses using SNPs could be performed as long as at least one control DNA sample displaying the heterozygous genotype was available. We evaluated the sample-to-sample variability of the peak-height ratio of SNP alleles (Rh) in heterozygous individuals with high reproducibility. This result indicates that DNAs from unspecified individuals can be used as a control for the estimation of Rh. We also compared the LOH status using both methods and demonstrated that the consistency rate of LOH determination was 98.1%, demonstrating the high reliability of this new method.

Recently, several approaches were established to study LOH using SNPs. Among them, SNP-mass spectrometry-genotyping technology has been applied to detect LOH at high-resolution.29 In this study, a rapid source of high-throughput method was provided and thus a high-resolution investigation of LOH for given chromosomal regions was carried out. However, this method detects LOH by comparing the genotype of tumor DNA to that of the matched normal DNA and therefore requires the examination of both DNAs simultaneously. In addition, LOH can be detected precisely only when the population of normal cell contamination is less than 10%. On the other hand, current generations of SNP arrays provide high-density markers, making it possible to estimate LOH regions with extremely high resolution. In some of these methods, LOH can be inferred by the probability of the appearance of consecutive homozygous genotypes.30, 31 In recent studies, hidden Markov model-based interpretation of the data obtained from SNP array or SNP-beads, allowed for an accurate LOH detection for most of the examined SNP markers. Compared with their previous study using paired nontumor DNA as control,30 a significant loss in tolerance of normal DNA contamination was observed for this method which requires samples of tumor cell lines or tumor tissues that are almost free of normal DNA, an unrealistic event in the field of clinical testing.32, 33 In contrast to these past methods, our current method can be applied to samples without paired nontumor DNAs and also maintains tolerance of tumor DNA that is highly contaminated with normal DNA. We thus suggest our method would be appropriate for clinical application because clinically obtained tumor samples should include nontumoral cells to some extent, derived from blood or connective tissues, and because paired normal DNAs may not be obtained from some patients because of various clinical issues. It is true that LOH is not detectable by this method in the tumor tissues containing very little amount of normal cells because their LOH is hardly distinguishable from homozygosity, but such cases are extremely rare in surgically obtained samples.

Allelic loss of 1p, one of the most frequent chromosomal abnormalities in meningioma, is predominant in atypical and anaplastic histologic types, and is therefore recognized as a progression-associated genetic aberration in meningioma.8, 34 Several studies have succeeded in narrowing down the critical regions on 1p that relate to tumorigenesis of meningiomas.12–14, 35, 36 Several candidate genes on 1p have been discussed with regard to their relationship with meningioma tumorigenesis or progression, including TP73, CDKN2C (encoding p18INK4c), RAD54L and ALPL.37–40 The roles of these genes, however, are still controversial.

In the present study, we successfully applied the improved LOQUS method, LOQUS-AC, to detect the allelic status of chromosome 1p36 in various stages of meningiomas at a higher resolution compared with previous reports.12–14 We finally defined a candidate common LOH region which might associate with meningioma. This region, located at 1p36.11, was considerably narrowed down when compared with a 19.3- Mbp candidate locus, R2, located at 1p36.21-p34.1 by Buckley et al.16 Genes located at this region are shown in Supplemental Table S3. Among them, interesting candidate genes include RUNX3 and EXTL1. RUNX3 is frequently deleted or transcriptionally silenced in various types of cancer.41–44EXTL1 is a member of the human tumor suppressor EXT gene family.45 Further analyses are needed to identify tumor suppressor genes from these candidate genes. Finally, LOQUS-AC might also be applicable to detect LOH in other tumor types.


  1. Top of page
  2. Abstract
  3. Material and methods
  4. Results
  5. Discussion
  6. References
  7. Supporting Information
  • 1
    Kleihues P,Cavenee WK. World Health Organization classification of tumors. Tumors of the nervous system. Lyon: IARC Press, 2000; 2939.
  • 2
    Perry A,Stafford SL,Scheithauer BW,Suman VJ,Lohse CM. Meningioma grading: an analysis of histologic parameters. Am J Surg Pathol 1997; 21: 145565.
  • 3
    Lamszus K. Meningioma pathology, genetics, and biology. J Neuropathol Exp Neurol 2004; 63: 27586.
  • 4
    Seizinger BR,de la Monte S,Atkins L,Gusella JF,Martuza RL. Molecular genetic approach to human meningioma: loss of genes on chromosome 22. Proc Natl Acad Sci USA 1987; 84: 541923.
  • 5
    Dumanski JP,Carlbom E,Collins VP,Nordenskjold M. Deletion mapping of a locus on human chromosome 22 involved in the oncogenesis of meningioma. Proc Natl Acad Sci USA 1987; 84: 92759.
  • 6
    Ruttledge MH,Sarrazin J,Rangaratnam S,Phelan CM,Twist E,Merel P,Delattre O,Thomas G,Nordenskjöld M,Collins VP,Dumanski JP,Rouleau GA. Evidence for the complete inactivation of the NF2 gene in the majority of sporadic meningiomas. Nat Genet 1994; 6: 1804.
  • 7
    Wellenreuther R,Kraus JA,Lenartz D,Menon AG,Schramm J,Louis DN,Ramesh V,Gusella JF,Wiestler OD,von Deimling A. Analysis of the neurofibromatosis 2 gene reveals molecular variants of meningioma. Am J Pathol 1995; 146: 82732.
  • 8
    Weber RG,Boström J,Wolter M,Baudis M,Collins VP,Reifenberger G,Lichter P. Analysis of genomic alterations in benign, atypical, and anaplastic meningiomas: toward a genetic model of meningioma progression. Proc Natl Acad Sci USA 1997; 94: 1471924.
  • 9
    Rempel SA,Schwechheimer K,Davis RL,Cavenee WK,Rosenblum ML. Loss of heterozygosity for loci on chromosome 10 is associated with morphologically malignant meningioma progression. Cancer Res 1993; 53: 238692.
  • 10
    Lindblom A,Ruttledge M,Collins VP,Nordenskjöld M,Dumanski JP. Chromosomal deletions in anaplastic meningiomas suggest multiple regions outside chromosome 22 as important in tumor progression. Int J Cancer 1994; 56: 3547.
  • 11
    Simon M,von Deimling A,Larson JJ,Wellenreuther R,Kaskel P,Waha A,Warnick RE,Tew JM,Menon AG. Allelic losses on chromosomes 14, 10, and 1 in atypical and malignant meningiomas: a genetic model of meningioma progression. Cancer Res 1995; 55: 4696701.
  • 12
    Sulman EP,Dumanski JP,White PS,Zhao H,Maris JM,Mathiesen T,Bruder C,Cnaan A,Brodeur GM. Identification of a consistent region of allelic loss on 1p32 in meningiomas: correlation with increased morbidity. Cancer Res 1998; 58: 322630.
  • 13
    Ishino S,Hashimoto N,Fushiki S,Date K,Mori T,Fujimoto M,Nakagawa Y,Ueda S,Abe T,Inazawa J. Loss of material from chromosome arm 1p during malignant progression of meningioma revealed by fluorescent in situ hybridization. Cancer 1998; 83: 3606.
  • 14
    Bello MJ,de Campos JM,Vaguero J,Kusak ME,Sarasa JL,Rev JA. High-resolution analysis of chromosome arm 1p alterations in meningioma. Cancer Genet Cytogenet 2000; 120: 306.
  • 15
    Sulman EP,White PS,Brodeur GM. Genomic annotation of the meningioma tumor suppressor locus on chromosome 1p34. Oncogene 2004; 23: 101420.
  • 16
    Buckley PG,Jarbo C,Menzel U,Mathiesen T,Scott C,Gregory SG,Langford CF,Dumanski JP. Comprehensive DNA copy number profiling of meningioma using a chromosome 1 tiling path microarray identifies novel candidate tumor suppressor loci. Cancer Res 2005; 65: 265361.
  • 17
    Hata N,Yoshimoto K,Yokoyama N,Mizoguchi M,Shono T,Guan Y,Tahira T,Kukita Y,Higasa K,Nagata S,Iwaki T,Sasaki T, et al. Allelic losses of chromosome 10 in glioma tissues detected by quantitative single-strand conformation polymorphism analysis. Clin Chem 2006; 52: 3708.
  • 18
    Rozen S,Skaletsky H. Primer3 on the WWW for general users and for biologist programmers. Methods Mol Biol 2000; 132: 36586.
  • 19
    Inazuka M,Wenz HM,Sakabe M,Tahira T,Hayashi K. A streamlined mutation detection system: multicolor post-PCR fluorescence labeling and single-strand conformational polymorphism analysis by capillary electrophoresis. Genome Res 1997; 7: 1094103.
  • 20
    Kukita Y,Higasa K,Baba S,Nakamura M,Manago S,Suzuki A,Tahira T,Hayashi K. A single-strand conformation polymorphism method for the large-scale analysis of mutations/polymorphisms using capillary array electrophoresis. Electrophoresis 2002; 23: 225966.
  • 21
    Baba S,Kukita Y,Higasa K,Tahira T,Hayashi K. Single-stranded conformational polymorphism analysis using automated capillary array electrophoresis apparatuses. Biotechniques 2003; 34: 74650.
  • 22
    Higasa K,Kukita Y,Baba S,Hayashi K. Software for machine-independent quantitative interpretation of SSCP in capillary array electrophoresis (QUISCA). Biotechniques 2002; 33: 13428.
  • 23
    Yoshimoto K,Iwaki T,Inamura T,Fukui M,Tahira T,Hayashi K. Multiplexed analysis of post-PCR fluorescence-labeled microsatellite alleles and statistical evaluation of their imbalance in brain tumors. Jpn J Cancer Res 2002; 93: 28490.
  • 24
    Murakami M,Hashimoto N,Takahashi Y,Hosokawa Y,Inazawa J,Mineura K. A consistent region of deletion on 1p36 in meningiomas: identification and relation to malignant progression. Cancer Genet Cytogenet 2003; 140: 99106.
  • 25
    Boehm D,Herold S,Kuechler A,Liehr T,Laccone F. Rapid detection of subtelomeric deletion/duplication by novel real-time quantitative PCR using SYBR-green dye. Hum Mutat 2004; 23: 36878.
  • 26
    Arslantas A,Artan S,Oner U,Durmaz R,Muslumanoglu H,Atasoy MA,Basaran N,Tel E. Comparative genomic hybridization analysis of genomic alterations in benign, atypical and anaplastic meningiomas. Acta Neurol Belg 2002; 102: 5362.
  • 27
    Muller P,Henn W,Niedermayer I,Ketter R,Feiden W,Steudel WI,Zang KD,Steilen-Gimbel H. Deletion of chromosome 1p and loss of expression of alkaline phosphatase indicate progression of meningiomas. Clin Cancer Res 1999; 5: 356977.
  • 28
    Nigro JM,Takahashi MA,Ginzinger DG,Law M,Passe S,Jenkins RB,Aldape K. Detection of 1p and 19q loss in oligodendroglioma by quantitative microsatellite analysis, a real-time quantitative polymerase chain reaction assay. Am J Pathol 2001; 158: 125362.
  • 29
    Tai AL,Mak W,Ng PK,Chua DT,Ng MY,Fu L,Chu KK,Fang Y,Qiang SY,Chen M,Zhang M,Sham PC, et al. High-throughput loss-of-heterozygosity study of chromosome 3p in lung cancer using single-nucleotide polymorphism markers. Cancer Res 2006; 66: 41338.
  • 30
    Huang J,Wei W,Zhang J,Liu G,Bignell GR,Stratton MR,Futreal PA,Wooster R,Jones KW,Shapero MH. Whole genome DNA copy number changes identified by high density oligonucleotide arrays. Hum Genomics 2004; 1: 28799.
  • 31
    Wong KK,Tsang YT,Shen J,Cheng RS,Chang YM,Man TK,Lau CC Allelic imbalance analysis by high-density single-nucleotide polymorphic allele (SNP) array with whole genome amplified DNA. Nucleic Acids Res 2004; 32: e69.
  • 32
    Beroukhim R,Lin M,Park Y,Hao K,Zhao X,Garraway LA,Fox EA,Hochberg EP,Mellinghoff IK,Hofer MD,Descazeaud A,Rubin MA, et al. Inferring loss-of-heterozygosity from unpaired tumors using high-density oligonucleotide SNP arrays. PLoS Comput Biol 2006; 2: e41.
  • 33
    Peiffer DA,Le JM,Steemers FJ,Chang W,Jenniges T,Garcia F,Haden K,Li J,Shaw CA,Belmont J,Cheung SW,Shen RM, et al. High-resolution genomic profiling of chromosomal aberrations using Infinium whole-genome genotyping. Genome Res 2006; 16: 113648.
  • 34
    Bello MJ,de Campos JM,Kusak ME,Vaquero J,Sarasa JL,Pestana A,Rey JA. Allelic loss at 1p is associated with tumor progression of meningiomas. Genes Chromosomes Cancer 1994; 9: 2968.
  • 35
    Bostrom J,Muhlbauer A,Reifenberger G. Deletion mapping of the short arm of chromosome 1 identifies a common region of deletion distal to D1S496 in human meningiomas. Acta. Neuropathol 1997; 94: 47985.
  • 36
    Leuraud P,Marie Y,Robin E,Huguet S,He J,Mokhtari K,Cornu P,Hoang-Xuan K,Sanson M. Frequent loss of 1p32 region but no mutation of the p18 tumor suppressor gene in meningiomas. J Neurooncol 2000; 50: 20713.
  • 37
    Lomas J,Bello MJ,Arjona D,Gonzalez-Gomez P,Alonso ME,de Campos JM,Vaquero J,Ruiz-Barnes P,Sarasa JL,Casartelli C,Rey JA. Analysis of p73 gene in meningiomas with deletion at 1p. Cancer Genet Cytogenet 2001; 129: 8891.
  • 38
    Bostrom J,Meyer-Puttlitz B,Wolter M,Blaschke B,Weber RG,Lichter P,Ichimura K,Collins VP,Reifenberger G. Alterations of the tumor suppressor genes CDKN2A (p16(INK4a)), p14(ARF). CDKN2B (p15(INK4b)), and CDKN2C (p15(INK4c)) in atypical and anaplastic meningiomas. Am J Pathol 2001; 159: 6619.
  • 39
    Mendiola M,Bello MJ,Alonso J,Leone PE,Vaquero J,Sarasa JL,Kusak ME,De Campos JM,Pestana A,Ray JA. Search for mutations of the hRAD54 gene in sporadic meningiomas with deletion at 1p32. Mol Carcinog 1999; 24: 3004.
  • 40
    Niedermayer I,Feiden W,Henn W,Steilen-Gimbel H,Steudel WI,Zang KD. Loss of alkaline phosphatase activity in meningiomas: a rapid histochemical technique in indicating progression-associated deletion of a putative tumor suppressor gene on the distal part of the short arm of chromosome 1. J Neuropathol Exp Neurol 1997; 56: 87986.
  • 41
    Li QL,Ito K,Sakakura C,Fukamachi H,Inoue K,Chi XZ,Lee KY,Nomura S,Lee CW,Han SB,Kim HM,Kim WJ, et al. Causal relationship between the loss of RUNX3 expression and gastric cancer. Cell 2002; 109: 11324.
  • 42
    Ku JL,Kang SB,Shin YK,Kang HC,Hong SH,Kim IJ,Shin JH,Han IO,Park JG. Promoter hypermethylation downregulates RUNX3 gene expression in colorectal cancer cell lines. Oncogene 2004; 23: 673642.
  • 43
    Lau QC,Raja E,Salto-Tellez M,Liu Q,Ito K,Inoue M,Putti TC,Loh M,Ko TK,Huang C,Bhalla KN,Zhu T, et al. RUNX3 is frequently inactivated by dual mechanisms of protein mislocalization and promoter hypermethylation in breast cancer. Cancer Res 2006; 66: 651220.
  • 44
    Sato K,Tomizawa Y,Ijima H,Saito R,Ishizuka T,Nakajima T,Mori M. Epigenetic inactivation of the RUNX3 gene in lung cancer. Oncol Rep 2006; 15: 12935.
  • 45
    Kim BT,Kitagawa H,Tamura J,Saito T,Kusche-Gullberg M,Lindahl U,Sugahara K. Human tumor suppressor EXT gene family members EXTL1 and EXTL3 encode α 1,4-N-acetylglucosaminyltransferases that likely are involved in heparin sulfate/heparin biosynthesis. Proc Natl Acad Sci USA 2001; 98: 717681.

Supporting Information

  1. Top of page
  2. Abstract
  3. Material and methods
  4. Results
  5. Discussion
  6. References
  7. Supporting Information

This article contains supplementary material available via the Internet at .

ijc23297-Supplemental_figure_S1.tif142KSupporting Information file ijc23297-Supplemental_figure_S1.tif
ijc23297-Supplemental_figure_S2.tif143KSupporting Information file ijc23297-Supplemental_figure_S2.tif
ijc23297-SupplementalTableS1.doc41KSupporting Information file ijc23297-SupplementalTableS1.doc
ijc23297-SupplementalTableS2.doc33KSupporting Information file ijc23297-SupplementalTableS2.doc
ijc23297-SupplementalTableS3.xls18KSupporting Information file ijc23297-SupplementalTableS3.xls

Please note: Wiley Blackwell is not responsible for the content or functionality of any supporting information supplied by the authors. Any queries (other than missing content) should be directed to the corresponding author for the article.