Malignant mesothelioma (MM) is a rare and aggressive tumour of the serosal membranes with poor prognosis. It is mainly localized to the pleura, but could also arise in the peritoneum, pericardium and tunica vaginalis.1-3 MM is more commonly found in men than in women. It occurs mainly in adults, 75% of patients are older than 65 years.4 The majority of MM cases could be attributed to occupational or environmental exposure to asbestos.3,5-7 The global incidence is expected to continue to increase due to a long latency period, which could range from 15 to 60 years.8 Although the association between asbestos exposure and occurrence of MM is well established, the mechanism of carcinogenesis is not fully explained.9,10 Nevertheless, some studies reported genotoxic effects of asbestos.11-13 It has been suggested that the DNA damage may be caused by the direct influence of asbestos fibres that interfere with mitosis or by the indirect effect caused by the release of reactive oxygen species (ROS) and reactive nitrogen species (RNS) from macrophages. It is well established, that oxidative stress triggers DNA repair mechanisms, however, their role in the development of MM has not been fully studied yet.12,13 It has been suggested that the genetic variability of proteins involved in DNA repair mechanisms affects the risk of MM. In particular, excision repair cross-complementing group 1 (ERCC1) and X-ray repair cross-complementing protein 1 (XRCC1) may be involved and genes coding for these proteins are known to be polymorphic.14,15
ERCC1 is a protein involved in the repair of DNA by nucleotide excision repair (NER). Together with the Xeroderma pigmentosum F it forms an endonuclease, which also participates in homologous recombination and base excision repair (BER).16 The ERCC1 protein plays crucial role in NER, so some studies suggested that
XRCC1 is an important protein involved in BER and the repair of DNA single-strand breaks (SSBR). It does not have enzymatic activity, but acts as a scaffolding protein that interacts with repair enzymes.24 The
So far only two studies investigated the influence of the genetic variability of proteins involved in DNA repair mechanisms on the development of MM. The first study investigated the influence of
According to our knowledge and available literature the influence of the
The aim of this study was to investigate whether functional polymorphisms in
A retrospective case-control study included 237 patients with pleural or peritoneal MM treated at the Institute of Oncology Ljubljana between November 2001 and October 2016, along with 193 controls who worked and were occupationally exposed to asbestos in the asbestos cement factory of Salonit Anhovo, Slovenia. The controls were evaluated at the State Board for the Recognition of Occupational Asbestos Diseases between January 1999 and December 2003 and did not have any asbestos-related disease.
The study was approved by the Slovenian Ethics Committee for Research in Medicine and was carried out according to the Declaration of Helsinki.
Patients with pleural MM were diagnosed by ultrasound-guided biopsy or thoracoscopy and patients with peritoneal MM were diagnosed by laparoscopy. The diagnosis was confirmed by a histopathological examination by an experienced pathologist.5
The asbestos exposure was determined by semiquantative method. For all controls and some patients with MM, the data on cumulative asbestos exposure in fibres/cm3-years were available. On the basis of this data, the subjects were divided into three groups: low (< 11 fibers/cm3-years), medium (11–20 fibres/cm3-years) and high (> 20 fibres/cm3-years) asbestos exposure. For those patients with MM where cumulative asbestos exposure data were not available, a precise work history was obtained and their asbestos exposure was deduced from comparison to a group of subjects with known cumulative asbestos exposure at a given working place. Also in this case the exposure was divided into three groups: low, medium and high asbestos exposure. A personal interview with each of the subjects was performed to obtain the data on smoking using a standardized questionnaire.5,29
DNA of the MM patients and some controls without asbestos-related diseases was available from our previous studies.5 DNA from the rest of the controls was isolated from capillary blood collected on Whatman FTA cards during this study using MagMaxTM DNA Multi-Sample Kit (Applied Biosystems, Foster City, California, USA). Competitive allele-specific and real-time polymerase chain reaction (PCR) based KASP and TaqMan assays were used for the analysis of
Standard descriptive statistics were first performed. To determine the differences in age between the cases and controls the non-parametric Mann-Whitney (U) test was performed.
The dominant genetic models were used for all the comparisons. To analyse the association between genotypes, cumulative asbestos exposure, and standard confounders (age, gender) and MM,
univariate logistic regression was first used, followed by multivariate logistic regression modelling. The interactions were calculated by logistic regression models using dummy variables.
The patients’ and controls’ characteristics are shown in Table 1. There was no statistical difference in gender (p = 0.089) and smoking (p = 0.699) between the two groups. Groups differed significantly by age (p < 0.001) and cumulative asbestos exposure (p < 0.001). The median age was 66.0 years for patients and 56.2 years for controls. In univariate logistic regression analysis age, gender and smoking did not affect the risk of MM. The results showed that medium and high level of asbestos exposure increased the risk of MM 4-fold (odds ratio [OR] = 4.23; 95% confidence interval [CI] = 2.44–7.36; p < 0.001) in comparison to a low level of asbestos exposure (Table 1).
Characteristics of malignant mesothelioma (MM) patients, controls and the influence of these characteristics on MM risk
MM | patients (n = 237) | Controls (n = 193) | Test | OR (95% CI) | p | |
---|---|---|---|---|---|---|
Male n (%) | 175 (73.8%) | 128 (66.3%) | χ2 = 2.889 | 0.70 | 0.089 | |
Female n (%) | 62 (26.2%) | 65 (33.7%) | (0.46–1.06) | |||
Years; median (25–75%) | 66 (58–72) | 56.2 (49.3–65.0) | U = 32583 | 1.08 (0.46–1.06) | < 0.001 | |
Low | 36 (44.4%) | 149 (77.2%) | χ2 = 31.933 | |||
Medium | 24 (29.6%) | 15 (7.8%) | ||||
High | 21 (25.9%) | 29 (15.0%) | ||||
Low | 36 (44.4%) | 149 (77.2%) | χ2 = 27.916 | 4.233 | ||
Medium and high | 45 (55.6) | 44 (22.8%) | (2.44–7.36) | |||
No | 122 (53.0%) | 106 (54.9%) | χ2 = 0.149 | 1.08 | 0.699 | |
Yes | 108 (47.0%) | 87 (45.1%) | (0.74–1.58) |
1 data available for 81 MM patients, 2 data missing for 7 MM patients, 3 medium and high exposure in comparison to low exposure
The frequency distribution of the studied genetic polymorphisms is shown in Table 2. Minor allele frequencies were 39.9% for
The influence of polymorphisms on MM risk
Polymorphism | Genotype | MM patients | Controls | Unadjusted risk | Adjusted risk by gender and age | |||
---|---|---|---|---|---|---|---|---|
N (%) | N (%) | OR (95% CI) | p | OR (95% CI) | p | |||
TT | 97 (41.8)1 | 64 (35.8)2 | ||||||
TC | 94 (40.5) | 87 (48.6) | 0.78 | 0.69 | ||||
CC | 41 (17.7) | 28 (15.6) | (0.52–1.16) | 0.213 | (0.45–1.06) | 0.091 | ||
GG | 142 (59.9) | 84 (47.7)3 | ||||||
GT | 77 (32.5) | 75 (42.6) | 0.61 | 0.52 | ||||
TT | 18 (7.6) | 17 (9.7) | (0.41–0.91) | (0.34–0.80) | ||||
CC | 196 (86.0)4 | 171 (90.0)5 | 1.47 | 1.12 | ||||
CT | 32 (14.0) | 19 (10.0) | (0.80–2.69) | 0.211 | (0.58–2.16) | 0.728 | ||
CC | 90 (38.0) | 74 (42.8)6 | ||||||
CT | 125 (52.7) | 79 (45.7) | 1.22 | 1.03 | ||||
TT | 22 (9.3) | 20 (11.6) | (0.82–1.82) | 0.327 | (0.67–1.59) | 0.890 |
For determining MM risk, carriers of at least one polymorphic allele were compared to non-carriers
1missing data for 5 patients; 2missing data for 14 patients; 3missing data for 17 patients, 4missing data for 9 patients, 5missing data for 3 patients, 6missing data for 20 patients
In further logistic regression modelling the interactions between
The influence of interactions between investigated genetic polymorphisms on MM risk
Gene 1 | Gene 2 | Interaction | |||||
---|---|---|---|---|---|---|---|
0.78 | 0.61 | 1.971 | |||||
TC + CC vs. TT | (0.52–1.16) | 0.213 | GT + TT vs. GG | (0.41–0.91) | 0.014 | (0.42–9.17) | 0.75 |
0.78 | 1.47 | 1.302 | |||||
TC + CC vs. TT | (0.52–1.16) | 0.213 | CT vs. CC | (0.80–2.69) | 0.211 | (0.37–4.52) | 0.680 |
0.78 | 1.22 | 0.793 | |||||
TC + CC vs. TT | (0.52–1.16) | 0.213 | CT + TT vs. CC | (0.82–1.82) | 0.327 | (0.34–1.86) | 0.592 |
0.61 | 1.47 | 1.494 | |||||
GT + TT vs. GG | (0.41–0.91) | 0.014 | CT vs. CC | (0.80–2.69) | 0.211 | (0.42–5.21) | 0.537 |
0.61 | 1.22 | 0.655 | |||||
GT + TT vs. GG | (0.41–0.91) | 0.014 | CT + TT vs. CC | (0.82–1.82) | 0.327 | (0.29–1.47) | 0.302 |
1.47 | 1.22 | 2.416 | |||||
CT vs. CC | (0.80–2.69) | 0.211 | CT + TT vs. CC | (0.82–1.82) | 0.327 | (0.66–8.80) | 0.182 |
1 rs 11615 ERCC1 TC + CC vs. TT * rs3212986 ERCC1 GT + TT vs. GG; 2 rs 11615 ERCC1 TC + CC vs. TT * rs1799782 XRCC1 CT vs. CC; 3 rs 11615 ERCC1 TC + CC vs. TT * rs25487 XRCC1 CT + TT vs. CC; 4 rs3212986 ERCC1 GT + TT vs. GG * rs1799782 XRCC1 CT vs. CC; 5 rs3212986 ERCC1 GT + TT vs. GG * rs25487 XRCC1 CT + TT vs. CC; 6 rs1799782 XRCC1 CT vs. CC * rs25487 XRCC1 CT + TT vs. CC
Analysing the influence of interactions between the
The influence of interactions between the investigated polymorphisms and asbestos exposure on MM risk
Polymorphism | OR | 95% CI | p |
---|---|---|---|
1.93 | 0.61–6.10 | 0.262 | |
1.85 | 0.33–10.48 | 0.489 | |
2.80 | 0.89–8.79 | 0.078 |
Finally, we analysed the interaction between
The influence of interaction between
Asbestos exposure | OR for asbestos exposure inside category | |||||||||
---|---|---|---|---|---|---|---|---|---|---|
Low | Medium and high | |||||||||
MM (N) | Controls (N) | OR (95% CI) | p | MM (N) | Controls (N) | OR (95% CI) | p | OR (95% CI) | p | |
20 | 48 | 1 | Ref. | 14 | 16 | 2.10 (0.872.10 –5.10) | 0.101 | 2.10 (0.872.10 –5.10) | 0.101 | |
15 | 91 | 0.40 (0.190.40 –0.84) | 0.016 | 30 | 24 | 3.00 (1.423.00 –6.34) | 0.004 | 7.58 (3.537.58 –16.31) | < 0.001 | |
0.40 (0.19–0.84) | 0.016 | 1.43 (0.58–4.50) | 0.435 |
The relationship between MM and asbestos exposure was first described in 1960, but relatively little has been known about the mechanisms of carcinogenesis and the influence of genetic factors on the development of this malignant disease.30 In the current study we investigated the influence of
In this study, the majority of patients with MM were older than 58 years. This is consistent with the findings of previous studies showing that this tumour occurs primarily in the elderly, which could be contributed by the long latency period.3,4,8
Our study did not detect any association between smoking and the risk of MM, which is in agreement with the findings of some previous studies.31,32 On the contrary, a previous Slovenian study showed that smoking increased the risk of MM.3 The relation between smoking and the risk of MM development has to be further investigated.
An important finding of our study is that the medium and higher levels of asbestos exposure is associated with a 4-fold higher risk of developing
MM compared to low level of exposure. Although it is assumed that there is no threshold dose for developing MM,10 some studies have proven that the occurrence of MM is associated with the level of asbestos exposure at the beginning of employment and the length of exposure.33,34
A key finding of our study is that the carriers of at least one polymorphic
Other investigated polymorphisms did not have a statistically significant effect on the risk of MM. Our results differ from the previous two Italian studies, which found an increased risk for MM in the carriers of polymorphic allele
In this study, the interactions between studied polymorphisms did not have a statistically significant effect on the risk of MM. In contrast, the former Italian study indicated the effect of interactions between
According to our knowledge the influence of interactions between the studied polymorphisms and the asbestos exposure on the risk of MM have not been investigated so far. An important finding of our study is that the interaction between
A limitation of our study is that the information on smoking and asbestos exposure was not available for all subjects. Therefore some of the analyses were performed only on the subgroup of MM patients. The next drawback is that we failed to determine the genotype in some subjects due to the insufficient amount and the degraded DNA in samples isolated from Whatman FTA cards and contamination.
In conclusion, our study showed the protective effect of the