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Mutagenesis Advance Access originally published online on August 16, 2005
Mutagenesis 2005 20(5):365-373; doi:10.1093/mutage/gei052
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© The Author 2005. Published by Oxford University Press on behalf of the UK Environmental Mutagen Society. All rights reserved. For permissions, please email: journals.permissions@oupjournals.org

Screening of TP53 mutations by DHPLC and sequencing in brain tumours from patients with an occupational exposure to pesticides or organic solvents

V. Loyant*, A. Jaffré1, J. Breton2, I. Baldi1, A. Vital3, F. Chapon4, S. Dutoit, Y. Lecluse, H. Loiseau5, P. Lebailly and P. Gauduchon

Groupe Régional d'Etudes sur le Cancer, Université de Caen Basse-Normandie, Centre François Baclesse, Avenue du Général Harris, BP5026, 14076 Caen Cedex 05, France, 1Laboratoire Santé Travail Environnement, Institut de Santé Publique, d'Epidémiologie et de Développement, Université Victor Segalen Bordeaux 2, 146 rue Léo Saignat 33076 Bordeaux Cedex, France, 2Molecular Epidemiology Unit, Leeds Institute for Genetics, Health and Therapeutics, Faculty of Medicine and Health, University of Leeds, Clarendon Way, Leeds LS2 9JT, UK, 3Laboratoire d'anatomopathologie and 4Service de neurochirurgie, Hôpital Pellegrin, Place Amélie Raba-Léon 33 000 Bordeaux, France and 5Laboratoire de neuropathologie, Centre Hospitalier Universitaire, Avenue de la Côte de Nacre, 14033 Caen Cedex, France


   Abstract
Top
 Abstract
Introduction
 Materials and methods
 Results
 Discussion
 References
 
The aetiology of brain tumours remains unclear. Occupational exposures to pesticides and organic solvents are suspected risk factors. The case–control study CEREPHY (221 cases, 442 controls) carried in the Departement de la Gironde in France revealed a significantly increased risk of brain tumours for subjects most exposed to pesticides. In some cancers, TP53 mutations could reflect exposure to specific carcinogens. These mutations are present in ~30% of astrocytic brain tumours. In a pilot study, we explored the hypothesis that pesticide or solvent exposure could raise the frequency of TP53 mutations in brain tumour cells. We investigated TP53 mutations in exons 2–11 by denaturing high performance liquid chromatography (DHPLC) and sequencing, and p53 accumulation by immunohistochemistry in brain tumour of the 30 patients from CEREPHY study with a history of occupational exposure to pesticides (n = 21) and/or organic solvents (n = 14) for whom tumoral tissue was available. Included cases concerned 27% of CEREPHY cases exposed to pesticides and, based on the cumulative index of occupational exposure, they were more exposed to pesticides. There were 12 gliomas, 6 meningiomas, 7 neurinomas, 2 central nervous system lymphomas and 3 tumours of other histological types. We detected TP53 mutations in three tumours, which is similar to the expected number (3.3) calculated from 46 published studies referenced in the IARC TP53 mutations database, taking into account histological types. Considering TP53 mutations previously detected in the laboratory by DHPLC and the frequency of TP53 polymorphisms detected in this sample (similar to published data), the TP53 mutations rate is probably not underestimated. These preliminary results, even if it was on a limited number of tumours, are not in favour of the role of pesticide or organic solvent exposure in the occurrence of TP53 mutations in brain tumours.


   Introduction
Top
 Abstract
 Introduction
Materials and methods
 Results
 Discussion
 References
 
Brain cancers are still often disabling and lethal despite considerable advances in their treatment. In industrialized countries, incidence rates standardized on world population are 5.85/100000 for males and 4.06/100000 for females (1Go). The incidence of brain tumours increased over the past decades (2Go). In France, brain tumours would account for 2.1% of cancer deaths (3168 deaths in 2000) and the estimated number of incident cases was 5299 in 2000 (http://www.invs.sante.fr) (3Go).

The aetiology of brain tumours remains unclear. The only established risk factors are ionizing radiations and hereditary syndromes (2Go). Glioblastomas in patients who had been exposed to N-nitroso compounds during their job are recognized as occupational diseases in France. Among potential risk factors, occupational exposures have been investigated mainly through case–control studies. Elevated risks have been described for the occupation in petrochemical, rubber, textile and chemical industries, and for electrical or laboratory workers, farmers and healthcare (4GoGoGoGoGoGoGo–11Go). A meta-analysis based on 33 epidemiologic studies published between 1981 and 1996 reported a significant positive association between brain cancer and farming [OR = 1.3, 95% CI = (1.09–1.56)] (12Go). Among studies targeting specific exposures, some revealed elevated risk for electromagnetic field (13Go,14Go), pesticide (15Go), lead (16Go,17Go), organic solvent (17Go,18Go), N-nitroso compound (19Go), rubber (20Go) and vinyl chloride exposures (21Go).

According to experimental data, some pesticides and organic solvents are considered potential chemical mutagens. In some cancers, TP53 mutation pattern could reflect an exposure (22Go,23Go). There is very little information concerning TP53 mutational spectrum for exposure to organic solvents or pesticides. Vinyl chloride that has been found as a degradation product of chloroethylene solvents (trichloroethylene and perchloroethylene) (24Go) could be linked to TP53 mutations in angiosarcoma of the liver in occupationally exposed workers (25Go). Hoyer (26Go) described a significant association between exposure to dieldrin, an organochlorine and breast tumours with TP53 mutation that was not found for breast tumours without TP53 mutations. This observation is an indirect argument in favour of the implication of pesticides in the occurrence of TP53 mutation in breast cancer. To our knowledge, there is little information concerning the mutation patterns on genes other than TP53 for specific pesticides. Interestingly, it has been described that hprt mutations in malathion-treated cells arose preferentially at G:C basepair, which is consistent with reports that malathion alkylates guanine nucleotides (27Go).

TP53 gene mutations were found in ~30% of astrocytic tumours, the most frequent brain tumours (28Go), and could be an important event in the initiation, promotion or progression during brain carcinogenesis. Compared with the TP53 mutational spectrum in all types of cancers, the TP53 mutational spectrum in brain tumours is characterized by an increased mutational frequency at codon 273 (Figure 1) and by an increased transition rate at CpG sites (29Go). To our knowledge, the TP53 mutational spectrum has not yet been studied in relation with exposures in brain tumours.



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  		Fig. 1.. Mutational spectrum of TP53 gene in primary brain tumours (biopsy or surgery) according to the R9 version of the IARC TP53 mutation database (29Go).

 
In a first attempt to investigate the hypothesis that pesticides or organic solvents could increase TP53 mutation rate thus contributing to brain carcinogenesis, we took advantage of a case–control study (CEREPHY) on occupational and environmental risk factors of brain tumours carried in the Departement de la Gironde in France. This pilot study consisted in assessing TP53 mutation frequency and accumulation of the p53 protein in all the 30 brain tumours of individuals enrolled in the case–control study with known exposure to pesticides and/or to organic solvents from whom tumoral tissue was available.


   Materials and methods
Top
 Abstract
 Introduction
 Materials and methods
Results
 Discussion
 References
 
Study subjects
The case–control study (CEREPHY) on occupational and environmental risk factors of brain tumours included all newly diagnosed cases of brain tumours occurring between May 1, 1999 and April 30, 2001 in adults aged 16 years and above, and living in Gironde (Southwestern France) at the time of diagnosis. The name of the study ‘CEREPHY’ results from the association of parts of two French words, ‘CEREbral’ that refers to brain and ‘produit PHYtosanitaire’, which is a word used in France to refer to pesticides. The term CEREPHY was chosen because the main theme of this epidemiological study was to examine the role of pesticide exposure in the occurrence of brain tumours. The exclusion criteria were pituitary tumours, tumours occurring in AIDS patients, relapsing tumours, metastases, tumours detected by chance and asymptomatic tumours. Diagnoses were confirmed by two kinds of expertise: whenever a histological diagnosis was available, slides were systematically re-examined by a pathologist not involved in the first diagnosis. For cases without histological diagnosis, a diagnosis based on clinical and radiological criteria was made and re-examined by a neurosurgeon and a radiologist. All tumours were classified on the basis of the WHO classification of tumours of the central nervous system (CNS). Ninety-four of the 315 cases of brain tumours identified during the study period in Gironde were not included for the following reasons: 14 refused to participate and the 80 others were too ill or deceased and could not be interviewed with the assistance of a next of kin. For each case, two controls, individually matched by sex and age and living in the Departement de la Gironde during the inclusion period, were selected from electoral rolls. The final study group comprised the 221 cases and 442 individually matched population controls.

The 30 patients studied were representative of cases from the case–control study who had been occupationally exposed to pesticides or organic solvents and occasionally to other chemicals (nitrosamides/nitrosamines, petrochemicals, lead) during their life and for whom tumoral tissue was available (Figure 2).



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  		Fig. 2.. Design of the identification of individuals to be included in the present study.

 
Exposure information
All subjects included in the CEREPHY study were interviewed directly by an investigator. The questionnaire included occupational information, including job and environmental calendars, medical and lifestyle information. Considering occupational exposure to pesticides, organic solvents, nitrosamides/nitrosamines, petrochemicals and lead, an industrial hygienist checked the consistency between job calendar and exposure statement. Furthermore, for each job, likelihood, frequency and intensity of exposure to pesticides were determined. For each subject, a cumulative index of occupational exposure to pesticides was calculated as the sum of indices calculated for the different calendar period. Each calendar period index was made as the product of the period duration by the likelihood, the frequency and the intensity of occupational exposure.

DNA extraction and amplification
Genomic DNA was extracted from ~5 to 10 mg of each of the 30 tumour samples stored at –80°C, using the Dneasy tissue Kit column (Qiagen SA, Courtaboeuf, France) with the protocol recommended.

For exons 2–9, the PCR amplification preceding denaturing high performance liquid chromatography (DHPLC) was carried out in a final reaction mixture volume of 25 µl containing 2 mM MgCl2, 2.5 µl of GeneAmp 10x PCR buffer II (Applied Biosystems, Courtaboeuf, France), 200 nM each deoxynucleotide triphosphate, 400 nM of forward and reverse primers, 0.5 U AmpliTaq Gold DNA polymerase (Applied Biosystems) and ~100 ng DNA. The primer sequences used to amplify exons 2–9 of TP53 gene are described in Table I. The reaction mixture was subjected to a touch-down PCR amplification using a DNA thermocycler (Eppendorf©): after 10 min at 95°C, the mixture was subjected to 27 cycles consisting of 20 s at 94°C, 20 s at 63°C, a decrease of 0.5°C at each cycle, and 45 s at 72°C followed by 20 cycles consisting of 20 s at 94°C, 20 s at 50°C and 45 s at 72°C. An elongation step of 7 min at 72°C was added at the end of the PCR. The same PCR conditions were used for the PCR amplification preceding sequencing except that the final volume was 50 µl. For exons 10 and 11, we used previously described primers and conditions (Table I) (30Go).


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  		Table I.. Primers used for PCR amplification of TP53 exons and DHPLC temperature conditions

 

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  		Table II.. DHPLC gradient conditions

 
DHPLC
After amplification, half of the PCR products were mixed with an equal volume of normal PCR product amplified from DNA coming from a healthy subject and previously sequenced to verify the absence of mutation or polymorphism. The PCR product mixture was subjected to heteroduplex and homoduplex formation as described previously (31Go). DHPLC analysis was carried out on the Helix system (Varian, Les Ulis, France). For exons 5–8, initial column temperatures were determined as described previously (31Go). For exons 2–4 and 9, initial column temperatures were determined by the DHPLC Melt Program (http://insertion.stanford.edu/melt.html), and the experimental curve of retention time from a sample previously sequenced containing neither polymorphism nor mutation. Because we had no control sample containing mutation or polymorphism for these exons, we began to screen our samples with temperatures and gradients previously determined until we detected a sample presenting an abnormal profile. If sequencing revealed that this abnormality was a mutation or a polymorphism, we used this sample as a positive control (see below). All samples already screened in a run without a positive control were screened again. The temperatures and gradients used are described in Tables I and II. To check for the quality of each DHPLC run, we injected, at the beginning and at the end of our sample series, a negative control (PCR product obtained from DNA of a blood sample previously sequenced and containing neither mutation nor polymorphism on the TP53 gene segment studied) and a positive control (PCR product obtained from DNA of an oesophageal tumour sample bearing an alteration on the TP53 gene segment detected by sequencing). We checked that an abnormal profile was obtained for the positive control compared with the negative control profile. Whenever possible, we used a positive control containing a mutation giving a profile that differs slightly from the negative control because this type of mutation requires more specific conditions (column quality and column temperature) to be detected (32Go).

Sequencing
For exons 2–9, DNA samples presenting an abnormal signal in DHPLC were amplified using the same PCR conditions as those described above. PCR products were then purified on S300 column (Amersham Pharmacia). Sequencing of the two strands was performed using the ABI Prism Big Dye Terminator Ready Reaction Cycle Sequencing kit (Applied Biosystems) on an ABI Prism 377 sequencer (Applied Biosystems): the mixture contained 3 µl primers forward or reverse (Tables I and II), 2 µl Big Dye and 5 µl PCR products. For exons 10 and 11, all DNA samples were sequenced directly using the same conditions as those described above and primer described in Table I, except that sample 109 was not sequenced for exon 10.

Immunohistochemistry
Expression of p53 protein was investigated with the monoclonal antibody DO-7 (Dako, Trappes, France). Paraffin-embedded tissue slides were immunostained with an avidin-biotin peroxidase method using a VENTANA ES 320 automat (Strasbourg, France) and the VentanaTM enhanced DAB detection Kit (Strasbourg, France) with the protocol recommended. Before immunostaining, deparaffinized 3 µm sections were placed in a citrate buffer (pH 7) for antigen retrieval and heated in a pressure cooker for 3 min. p53 protein expression was determined by incubating the tissue sections with the monoclonal antibody DO-7 diluted 1:100 for 20 min at 37°C. This antibody recognizes both wild-type and mutant forms of the p53 protein. Following incubation, the sections were counterstained with haematoxylin for 4 min at 37°C.

Immunostaining was classified into the following four groups according to both intensity and extent: (–) no staining present; (+) positive staining detected in <25% of cells; (++) mild positive staining in a range of 25–75% of cells; (+++) strong positive staining in a range of 25–75% of cells; (++++) strong positive immunostaining in >75% of cells.

Calculation of the expected number of mutations
In our sample, the expected number of mutations was calculated from 46 published studies included in the IARC TP53 mutations database (29Go) (Table III). First of all, all publications concerning brain tumours referenced in the IARC TP53 mutation database were listed. We then retained all relevant articles (n = 46) by excluding those concerning histological types not included in our study (gliosarcomas, PNETs, etc.), paediatric tumours, mutations studied from cell lines, reports of single cases and tumours from patients with known genetic syndrome or prior radiation exposure. The number of mutations and samples studied from each article (only primary tumours of histological types of interest in adults) were determined giving a mutational frequency for each histological type. In order to limit the number of duplicates, the number of mutations identified in each article was compared with the number of mutations referenced in the IARC TP53 mutation database. The mutational frequencies were then multiplied by the number of tumours in our sample giving the expected number of mutations (n = 3.3).


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  		Table III.. Calculation of the expected number of mutations

 
Statistical analysis
To compare characteristics of CEREPHY patients included or not included in the p53 study, the Chi-square and the Fisher's exact tests were used for categorical variables and the bilateral Student's t-test for continuous variables. A P-value below 0.05 was considered statistically significant.


   Results
Top
 Abstract
 Introduction
 Materials and methods
 Results
Discussion
 References
 
Among the 221 patients included in the CEREPHY study, 193 patients (87%) had undergone surgery. Ninety-five of these 193 patients had been occupationally exposed to pesticides and/or organic solvents during their life (Figure 2). At least one tumour sample was available for 30 (32%) of these 95 patients: 16 were exposed to pesticides, 9 to organic solvents and 5 to both pesticides and organic solvents. All these 30 patients were included in the present study. Compared with the other 191 CEREPHY cases, patients included in our analysis were more frequently males (67 versus 39% for non-included cases; P = 0.005) and had a significantly lower educational level (90 versus 68% for non-included cases; P = 0.01). Even if histological type distribution did not differ significantly (P = 0.18), cases included were more frequently neurinomas (23 versus 14%), less frequently meningiomas (20 versus 32%) and astrocytic gliomas other than glioblastomas (3 versus 12%) compared with non-included cases.

We compared pesticide exposure in exposed patients included and non-included in the present study (Table IV). The 21 included patients were slightly more exposed to pesticides with a mean cumulative index of occupational exposure of 34.8 versus 25.1 for the non-included patients (P = 0.39). Thirty eight percent of patients included in this study had a cumulative index of occupational pesticide exposure in the fourth quartile against 22% of the non-included ones (P = 0.16). Moreover, 33% of included patients had sprayed or mixed pesticides against 10% of the non-included ones (P = 0.03). Pesticide exposure was mainly due to tasks devoted to agricultural activities like application of pesticides (vineyard treatment) and to other tasks such as grape harvesting. Moreover two patients, a carpenter (case 333) and a joiner (case 84), had been exposed to wood treatment pesticides. Distributions of other chemical exposures among subjects exposed to pesticides or organic solvents included or not in this study are given in Table IV. For cases exposed to pesticides, nitrosamine or nitrosamide exposure was the main co-exposure (33% of cases) and for cases exposed to organic solvents, it was petrochemical exposure (43% of cases).


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  		Table IV.. Comparison of characteristics of patients included or not included, exposed to pesticides or/and to organic solvents

 
Individual information about sex, age at the diagnosis, occupational exposure to pesticides and organic solvents are given in Table V. There were 12 gliomas, 7 neurinomas, 6 meningiomas, 2 CNS lymphomas, 1 ganglioglioma, 1 haemangioblastoma and 1 choroid plexus papilloma.


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  		Table V.. Characteristics of patients of CEREPHY included in the present study and p53 accumulation, TP53 mutations and TP53 polymorphisms detected

 
Using the DO-7 antibody that recognizes normal and abnormal p53 proteins, 17 tumours (57%) with a positive immunostaining were detected and among them, 11 were astrocytic gliomas. The intensity of staining and the percentage of stained cells were heterogeneous (Figure 3, Table V). An immunohistochemistry score (described in Materials and methods section) was used to classify the positive tumours. Three tumours presented >75% of stained cells, 4 tumours presented between 25 and 75% of highly stained cells, 3 tumours presented between 25 and 75% of slightly stained cells and 7 tumours presented <25% of stained cells. Six out of the seven tumours with a high immunohistochemistry score (+++ or ++++) were glioblastomas. Neurinomas were all negative except one which presented a low staining. Three meningiomas (42%) presented a positive rather low immunostaining and two of these were atypical or anaplastic meningiomas.



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  		Fig. 3.. (A) No stained cells. (B) <25% of stained cells. (C) 25–75% of poorly stained cells. (D) 25–75% of highly stained cells. (E) 75% of stained cells. Magnification 40x.

 
Three tumours out of the 30 bore a mutation in TP53: 1 transversion and 2 transitions at non-CpG sites (Table V), located on codons 132 (missense), 271 (nonsense) and 280 (missense). Mutations were detected in a glioblastoma (case 256) and in the two CNS lymphoma (cases 45 and 75) cases. Overall two tumours presented both TP53 mutation and p53 accumulation, and one tumour presented only a TP53 mutation that was a nonsense mutation. Fifteen tumours (50%) presented only a positive immunostaining and 12 tumours (40%) presented neither TP53 mutation nor p53 accumulation.

Occupational exposures of the three cases presenting a mutation greatly differ from each other. Patient 45 was a 28-year-old male who had been exposed to organic solvents and petrochemicals. He had worked as a mechanic in aeronautics in the army for 8 years and thereafter as an informatics technician for 2 years (Figure 4). Patient 75 was a 73-year-old female who had worked in a farm for 48 years (Figure 4). Her cumulative index of occupational exposure to pesticides was 96. Patient 256 was a 69-year-old female who had worked as a saleswoman for 9 years and who had harvested grapes once in 2 days (Figure 4). Her cumulative index of occupational exposure to pesticides was 1. Interestingly, she had been living in rural areas for 18 years.



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  		Fig. 4.. Occupational history of patients having a tumour presenting a TP53 gene mutation.

 
Nine different polymorphisms in TP53 gene were detected in 17 patients (57%). Three polymorphisms were located on coding regions (codons 36, 72 and 213), but only the polymorphism on codon 72 led to an amino acid exchange (Arg > Pro). Heterozygote polymorphisms on codon 72 and nucleotide 11827 were found together in 11 patients and one patient had both homozygote polymorphisms (72Pro and 11827c variants). Three patients had only the heterozygous polymorphism at the 11827 nucleotide. The most frequently estimated allelic frequencies found in our sample are 28.3% for variant 11827c (intron 2), 21.7% for variant 72Pro (exon 4), 15% for variant 11951ins16bp (intron 3), 5% for variant 11992a (intron 3) and variant 14181t-14201g (intron 7).


   Discussion
Top
 Abstract
 Introduction
 Materials and methods
 Results
 Discussion
References
 
To investigate the hypothesis that pesticides or organic solvents could increase TP53 mutation rate thus contributing to brain carcinogenesis, we took advantage of a case–control study (CEREPHY) on occupational and environmental risk factors of brain tumours carried in the Departement de la Gironde in France. Three mutations were detected among the 30 tumours studied, which is similar to the expected number (3.3 tumours). However, only 1 of the 11 glioblastomas reported here contained a TP53 mutation, that is much less than expected (9% against 27% expected). On the other hand, the two other mutations have been found in the two CNS lymphomas of the study, that is much higher than expected from the database (100% against 13% expected), even if TP53 mutations have been rarely studied in CNS lymphoma.

The CEREPHY study showed only a marginally elevated risk of brain tumours in individuals occupationally exposed to pesticides which became significant in the most exposed individuals (fourth quartile of cumulative index of occupational exposure to pesticides) [OR = 2.58, 95% CI = (1.30–6.00)], particularly for gliomas [OR = 3.21, 95% CI = (1.13–9.11)] (D. Provost, A. Cantagrel, P. Lebailly, A. Jaffré, V. Loyant, H. Loiseau, A. Vital, P. Brochard and I. Baldi, manuscript in preparation). Even if included cases concerned 27% of all CEREPHY cases exposed to pesticides, they were on average more exposed to pesticides (36% of them in the fourth quartile of the cumulative index of occupational exposure versus 22% for the non-included patients exposed to pesticides). Mutations were detected in tumoral tissue of patients with various types and duration of exposure: one patient highly exposed to pesticides, one patient marginally exposed to pesticides and one patient exposed to organic solvents and petrochemicals. This observation does not favour the association between TP53 mutations and pesticide exposure.

According to literature, DHPLC is a very sensitive mutation screening technique when conditions (primers, temperatures and gradients) are well defined (33Go). A critical analysis of the mutation detection method suggests that we probably did not underestimate TP53 mutation rate. With temperatures and gradient conditions chosen for DHPLC, we have previously shown that we are able to detect the four most frequent mutations occurring in brain tumours according to the IARC TP53 mutations database (31Go). Those mutations are located on codons 273, 248, 175 and 282, and represent respectively 17.9, 8.1, 6.8 and 3.1% of mutations in brain tumours present in the R9 version of the IARC TP53 mutations database. Moreover, 40 other alterations on different nucleotides of TP53 (mutations or polymorphisms) have been detected with DHPLC in our laboratory (31Go). Some of them have been detected by others in brain tumours. Exchange of DNA presenting TP53 mutations or polymorphisms with another research group screening TP53 by DHPLC (Groupe d'Etudes des Tumeurs Urologiques of Hôpital Henri Mondor, Creteil, France) permitted us to detect a relatively large panel of mutations in our laboratory. We detected alterations located at known polymorphic sites on TP53 gene. Unfortunately, these alterations could not be firmly identified as polymorphism, since non-tumoral DNA was not available. For the most frequent putative polymorphisms that we detected, calculated allelic frequencies were in the range of those described in the literature for Caucasian healthy subjects. For proline variant of codon 72, it was 21.7% in our study versus 25–40% (34GoGo–36Go). For variant 11951ins16bp (intron 3), it was 15% versus 10–20% (37Go). For variant 11827c (intron 2), it was 28.3% versus 28% (38Go). Moreover, we detected a base substitution on nucleotide 11992 in intron 3 which was considered to be a polymorphism because we detected it for three patients.

In brain tumours, contamination of tumoral tissue by normal tissue artificially decreases the proportion of mutated cells, which could lead to false TP53 mutation negative samples. It has been described that DHPLC could detect mutation from 3.25% to 20% of mutated alleles (39Go–40Go) which is similar to our observations (data not shown). Because we did not know the percentage of mutated cells in the tissue studied, we decided to use immunohistochemistry. Indeed some TP53 mutations induce stabilization of the p53 protein that become detectable by immunohistochemistry. Among tumours with mutations, two tumours with a TP53 mutation presented an immunostaining respectively for <25% of stained cells and for >75% of stained cells, and the third tumour with a TP53 mutation presented no stained cell (nonsense mutation). Six of the seven tumours with the highest immunohistochemistry score (+++ or ++++) had no mutation. Considering that p53 accumulation represents the presence of tumoral tissue, we have considered that if there were mutated cells in these samples, they would not be diluted and that mutations in exons studied would have been detected. In the 10 tumours with a low immunostaining (+ or ++) and no detected mutation, lack of detection of mutations could be due to dilution of mutated cells. Sequencing of immunostained cells isolated by microdissection could help us to answer this question.

We detected many more tumours with a positive immunostaining (n = 17) compared with tumours containing a TP53 mutation (n = 3). This discrepancy has already been described in brain tumours (41GoGoGo–44Go). A possible explanation is that another mechanism than mutations could stabilize the p53 protein. The mdm2 protein, through binding p53 protein, shuttles p53 protein out of the nucleus, into the cytoplasm where it is degraded. An overexpression of proteins responsible for mdm2 expression decrease, such as p14ARF, would lead to p53 accumulation (45Go). Moreover, Chung et al. (46Go) reported an accumulation of p53 in reactive astrocytes of rat exposed to a transient brain hypoxia. It remains that TP53 mutations could also be located in the non-coding exon 1 or in intronic regions not studied here. However, mutations on regions not studied here represent <2% of all mutations described in brain tumours according to the TP53 mutations database (29Go). The discrepancy between immunostaining and TP53 mutation we observed (91% immunostaining without TP53 mutation and 0% TP53 mutation without immunostaining) for glioblastomas is comparable with the one observed by Gomori (92% immunostaining without TP53 mutation and 0% TP53 mutation without immunostaining, respectively) and von Eckardstein (79% immunostaining without TP53 mutation and 0% TP53 mutation without immunostaining) (47Go,48Go). However, it is more important than the discrepancy generally described (~33% immunostaining without TP53 mutations and 4% TP53 mutations without immunostaining). To date, we thought it is premature to say that this discrepancy could be linked to solvent or pesticide exposure, although we do not exclude it. In order to answer this question, it would be interesting to study TP53 mutations and p53 accumulation in tumours of patients not exposed to pesticides or solvents during their occupational life.

In conclusion, results of this pilot study, conducted on 30 incident cases occupationally exposed to pesticides or organic solvents, are not in favour of the role of pesticide or organic solvent exposures in the occurrence of TP53 mutations in brain tumours. However, this result must be considered with caution given the small sample size. Perspectives are to complete this pilot study with a screening of TP53 mutations in brain tumours from patients exposed to solvents and/or pesticides and included in a multicentric case–control study that began in the beginning of 2004 in four French Regions. We calculated that with a sample of 100 tumours from patients exposed to pesticides or solvents with a similar distribution of histological types than in the present study, the minimal significant increased mutation rate we could detect with {alpha} = 5%, and a statistical power of 80% would be 1.9 that would represent 21 mutations against 11 expected.


   Acknowledgments
 
We acknowledge Dorothée Provost from the Laboratoire Sante Travail Environnement, Bordeaux, Gilbert Roussel, Jean-Jacques Bauman and Dominique Vaur from the Laboratoire de Biologie Clinique, Centre F. Baclesse, CAEN, Ashraf Bakkar and Sixtina Gil Diez de Medina from the Centre de Recherches Chirurgicales, Groupe d'Etudes des Tumeurs Urologiques, Hopital Henri Mondor, Creteil, and Ahmed Abbas and Michel Henry-Amar from the Groupe Régional d'Etudes sur le Cancer, Centre F. Baclesse, CAEN for their technical advices and helpful comments. The authors are also grateful to the clinical collaborators for identifying patients and secretarial assistance in the neurosurgery department of the University Teaching Hospital, Bordeaux, to technicians of the sequencing department of the Pole de Recherche en Biologie Medicale et Epidemiologie (PRBME), Caen. We also would like to thank all the subjects who participated in the study. This study was supported by grants from Fondation de France, Ministère de l'Emploi et de la Solidarité, Association pour la Recherche sur le Cancer and Ligue Nationale contre le Cancer (Comites de la Gironde et du Calvados). V.L. is the recipient of a fellowship from the Ligue Nationale contre le Cancer (Comite du Calvados).


   Notes
 
* To whom correspondence should be addressed. Tel: +33 231 455 070; Fax: +33 231 455 172; Email: v.loyant{at}baclesse.fr


   References
Top
 Abstract
 Introduction
 Materials and methods
 Results
 Discussion
 References
 

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Received on September 22, 2004; revised on April 30, 2005; accepted on July 13, 2005.


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