Malignant mesothelioma (MM) is a rare disease, linked to asbestos exposure in more than 80% of the cases. The latency period can last up to thirty years and estimated median survival is 9–12 months. The worldwide incidence of mesothelioma is slowly rising, with approximately 94 000 new cases per year. The most affected areas are parts of Europe, Australia and the USA.1 The rise in the MM incidence has been noticed in the Slovene population as well. The Slovenian national registry follows the data on MM since 1961. The incidence in 2014 was 37 new cases per year in a population of approximately 2 million.2
Several preclinical studies have identified matrix metalloproteinases (MMPs) as modulators of the tumour microenvironment and having an important role in carcinogenesis.3 MMPs are calcium-dependent, zinc-containing endopeptidases, with three common domains containing the propeptide, catalytic and haemopexin-like C-terminal domain.4 They are involved in tissue remodelling by interfering with the cell-cell and cell-extracellular matrix interactions. Studies have shown that MMPs, particularly MMP-2 and MMP-9, play a role in tumour angiogenesis, invasion and metastasis.5 The studies performed thus far show that MMPs and their inhibitory molecules, tissue inhibitors of metalloproteinases (TIMPs), have an important role in proliferation and progression of MM and some other, more frequent malignancies, such as colon and breast cancer. Different MMP genes (
Many studies investigated the role of
The opposite effect was observed in T-cell acute lymphoblastic leukaemia (T-ALL), where
The data from the literature, linking
Patients with histologically confirmed pleural or peritoneal mesothelioma diagnosed and treated between 2007 and 2016 were included in this retrospective study. Patients were diagnosed mostly at the University Clinic Golnik and at the Department of Thoracic Surgery of the University Medical Centre Ljubljana. Patients were treated and followed-up at the Institute of Oncology Ljubljana, Slovenia.
Most patients included in the study were also participating in previous studies on pharmacogenomics of MM treatment, conducted at the Institute of Oncology Ljubljana, Slovenia. Some of the patients were also included in the clinical trial AGILI (Trial registration ID: NCT01281800).10
Clinical characteristics at diagnosis were obtained from medical records or assessed during clinical interview. Regarding asbestos exposure, patients were divided in two groups: patients with no known asbestos exposure and patients with known occupational or environmental exposure.
The control group consisted of 161 unrelated healthy Slovenian blood donors, aged 49 to 65.
The study was approved by the Slovenian National Medical Ethics Committee and was carried out according to the Declaration of Helsinki.
Genomic DNA was extracted from frozen whole-blood samples collected at the inclusion in any of the above mentioned studies using the Qiagen FlexiGene Kit (Qiagen, Hilden, Germany) in accordance with the manufacturer’s instructions.
Ten different polymorphisms in three
The genotyping of all the SNPs was carried out using a fluorescence-based competitive allele-specific assay (KASPar), according to the manufacturer’s instructions (LGC Genomics, UK).
For all investigated polymorphisms, 15% of samples were genotyped in duplicates. Genotyping quality control criteria included 100% duplicate call rate and 90% SNP-wise call rate.
Continuous and categorical variables were described using median and range (25%-75%) and frequencies, respectively. Deviation from the Hardy-Weinberg equilibrium (HWE) was assessed using the standard chi-square test. The additive and dominant genetic models were used in statistical analyses. The associations of genetic polymorphisms with MM risk were examined by logistic regression to calculate odds ratios (ORs) and their 95% confidence intervals (CIs).
All statistical analyses were carried out by IBM SPSS Statistics, version 21.0 (IBM Corporation, Armonk, NY, USA). Haplotypes were reconstructed and analysed using Thesias software, version 3.1. The most frequent haplotype was used as the reference. All statistical tests were two sided and the level of significance was set to P = 0.05. Due to the exploratory nature of the study, no adjustments for multiple comparisons were used.
In total, we included 236 patients with MM and 161 healthy blood donors as a control group. Clinical characteristics of patients are summarized in Table 1. Among controls, 125 (77.6%) were male and 36 (22.4%) were female. Median age was 55 (52–58.5) years. There were no significant differences between cases and controls regarding gender (P = 0.375), however, controls were significantly younger than MM patients (P < 0.001).
Patients’ characteristics (N = 236) Numbers in square brackets denote the number of patients with missing data. ECOG = Eastern Cooperative Oncology Group
Characteristic
N (%)
Male
174 (73.7)
Female
62 (26.3)
Median (25%-75%)
66 (58-72)
I
18 (7.6)
II
60 (25.4)
III
70 (29.7)
IV
67 (28.4)
Peritoneal
20 (8.5)
Not determined
1 (0.4)
Epitheloid
169 (71.6)
Biphasic
27 (11.4)
Sarcomatoid
26 (11.0)
Not characterized
14 (5.9)
0
15 (6.4)
1
114 (48.3)
2
92 (39.0)
3
15 (6.4)
No
206 (87.3)
Yes
30 (12.7)
Not exposed
61 (26.5) [6]
Exposed
169 (73.5)
No
123 (57.7)
Yes
106 (46.3)
Variant allele frequencies for investigated SNPs are presented in Table 2. The distributions of all the investigated SNPs in the control group were in agreement with the Hardy-Weinberg equilibrium.
Variant allele characteristics, frequencies and agreement with HWE HWE = Hardy-Weinberg equilibrium; SNP = single nucleotide polymorphism
Gene
SNP
SNP characteristics
Variant allele frequency
PHWE
rs243865
c.-1306C>T
0.24
0.165
rs243849
c.999C>T, p.Asp333=
0.14
0.798
rs7201
c.∗260A>C
0.41
0.441
rs17576
c.836AG, p.Gln279Arg
0.36
0.785
rs2250889
c.836A>G, p.Gln279Arg
0.05
0.535
rs17577
c.2003G>A, p.Arg668Gln
0.15
0.096
rs20544
c.∗C>T
0.44
0.445
rs1042703
c.22T>C, p.Pro8Ser
0.26
0.164
rs1042704
c.817G>A, p.Asp273Asn
0.20
0.830
rs743257
c.∗3C>T
0.50
0.519
Duplicate call rate was 100% for all SNPs. With the exception of one SNP that had a call rate of 92%, all SNPs had a call rate above 97%.
Genotype frequencies for cases and controls are presented in Table 3. Carriers of at least one polymorphic
The association of investigated SNPs with risk for malignant mesothelioma Numbers in square brackets denote the number of patients with missing data. Significant values are printed in bold. CI = confidence interval; OR = odds ratio; SNP = single nucleotide polymorphism
SNP
Genotype
Controls N (%)
Cases N (%)
OR (95% CI)
P
Cases exposed to asbestos N (%)
OR (95% CI)
P
CC
90 (55.9)
155 (65.7)
Ref.
118 (69.8)
Ref.
CT
65 (40.4)
77 (32.6)
0.69 (0.45-1.05)
0.081
48 (28.4)
0.56 (0.35-0.89)
TT
6 (3.7)
4 (1.7)
0.39 (0.11-1.41)
0.150
3 (1.8)
0.38 (0.09-1.57)
0.181
CT+TT
71 (44.1)
81 (34.3)
0.66 (0.44-1.00)
51 (30.2)
0.55 (0.35-0.86)
CC
108 (75.0) [17]
163 (71.5) [8]
Ref.
116 (71.2) [6]
Ref.
CT
33 (22.9)
57 (25.0)
1.14 (0.70-1.87)
0.592
42 (25.8)
1.18 (0.70-2.00)
0.527
TT
3 (2.1)
8 (3.5)
1.77 (0.46-6.81)
0.408
5 (3.1)
1.55 (0.36-6.65)
0.554
CT+TT
36 (25.0)
65 (28.5)
1.20 (0.74-1.92)
0.459
47 (28.8)
1.22 (0.73-2.02)
0.451
AA
56 (35.9) [5]
78 (33.5) [3]
Ref.
63 (37.5) [1]
Ref.
AC
71 (45.5)
114 (48.9)
1.15 (0.73-1.81)
0.539
78 (46.4)
0.98 (0.60-1.58)
0.923
CC
29 (18.6)
41 (17.6)
1.02 (0.56-1.82)
0.960
27 (16.1)
0.83 (0.44-1.56)
0.560
AC+CC
100 (64.1)
155 (66.5)
1.11 (0.73-1.70)
0.622
105 (62.5)
0.93 (0.59-1.47)
0.765
AA
64 (40.3) [2]
100 (42.9) [3]
Ref.
74 (44.3) [2]
Ref.
AG
75 (47.2)
114 (48.9)
0.97 (0.63-1.49)
0.900
79 (47.3)
0.91 (0.57-1.44)
0.691
GG
20 (12.6)
19 (8.2)
0.61 (0.30-1.23)
0.165
14 (8.4)
0.61 (0.28-1.30)
0.196
AG+GG
95 (59.8)
133 (57.1)
0.90 (0.59-1.35)
0.599
93 (55.7)
0.85 (0.55-1.31)
0.458
GG
146 (90.7)
212 (90.2) [1]
Ref.
152 (89.9)
Ref.
GA
15 (9.3)
23 (9.8)
1.06 (0.53-2.09)
0.876
17 (10.1)
1.09 (0.52-2.26)
0.820
GG
113 (70.2)
169 (72.8) [4]
Ref.
119 (71.3) [2]
Ref.
GA
47 (29.2)
60 (25.9)
0.85 (0.54-1.34)
0.490
45 (26.9)
0.91 (0.56-1.47)
0.699
AA
1 (0.6)
3 (1.3)
2.01 (0.21-19.53)
0.549
3 (1.8)
2.85 (0.29-27.79)
0.368
GA+AA
48 (29.8)
63 (27.2)
0.88 (0.56-1.37)
0.565
48 (28.7)
0.95 (0.59-1.53)
0.831
CC
33 (20.6) [1]
38 (16.3) [3]
Ref.
29 (17.4) [2]
Ref.
CT
74 (46.3)
121 (51.9)
1.42 (0.82-2.46)
0.210
82 (49.1)
1.26 (0.70-2.27)
0.441
TT
53 (33.1)
74 (31.8)
1.21 (0.68-2.18)
0.518
56 (33.5)
1.20 (0.64-2.25)
0.563
CT+TT
127 (79.4)
195 (83.7)
1.33 (0.79-2.24)
0.275
138 (82.6)
1.24 (0.71-2.15)
0.453
TT
90 (57.0) [3]
147 (63.4) [4]
Ref.
109 (65.7) [3]
Ref.
TC
54 (34.2)
67 (28.9)
0.76 (0.49-1.18)
0.225
44 (26.5)
0.67 (0.41-1.09)
0.110
CC
14 (8.9)
18 (7.8)
0.79 (0.37-1.66)
0.530
13 (7.8)
0.77 (0.34-1.71)
0.518
TC+CC
68 (43.0)
85 (36.6)
0.77 (0.51-1.16)
0.204
57 (34.3)
0.69 (0.44-1.08)
0.108
GG
103 (64.0)
160 (68.1) [1]
Ref.
113 (66.9)
Ref.
GA
51 (31.7)
64 (27.2)
0.81 (0.52-1.26)
0.346
47 (27.8)
0.84 (0.52-1.35)
0.475
AA
7 (4.3)
11 (4.7)
1.01 (0.38-2.69)
0.982
9 (5.3)
1.17 (0.42-3.26)
0.761
GA+AA
58 (36.0)
75 (31.9)
0.83 (0.55-1.27)
0.395
56 (33.1)
0.88 (0.56-1.39)
0.581
CC
40 (26.0) [7]
59 (25.1) [1]
Ref.
41 (24.4) [1]
Ref.
CT
73 (47.4)
104 (44.3)
0.97 (0.59-1.59)
0.892
76 (45.2)
1.02 (0.59-1.75)
0.955
TT
41 (26.6)
72 (30.6)
1.19 (0.68-2.07)
0.538
51 (30.4)
1.21 (0.67-2.21)
0.526
CT+TT
114 (74.0)
176 (74.9)
1.05 (0.66-1.67)
0.848
127 (75.6)
1.09 (0.66-1.80)
0.746
In haplotype analysis, no significant associations with MM risk were observed, even when asbestos exposure was taken into account (Table 4). Nevertheless, haplotypes that included the polymorphic
The association of haplotypes with frequencies above 5% for investigated genes with risk for malignant mesotjelioma in patients with asbestos exposure The single nucleotide polymorphisms are ordered from the 5’- to 3’-end as follows:
Gene
Haplotype
Estimated frequency
OR (95% CI)
P
CCA
0.377
Ref.
CCC
0.272
1.14 (0.77 - 1.68)
0.518
CTA
0.144
1.14 (0.70 - 1.85)
0.599
TCC
0.144
0.77 (0.48 - 1.25)
0.291
TCA
0.056
0.59 (0.26 - 1.38)
0.223
ACGT
0.572
Ref.
GCGC
0.204
0.86 (0.59 - 1.26)
0.440
GCAC
0.137
0.81 (0.52 - 1.26)
0.353
TGC
0.338
Ref.
TGT
0.267
1.39 (0.94 - 2.06)
0.103
CGT
0.125
0.85 (0.52 - 1.37)
0.494
TAT
0.110
1.23 (0.71 - 2.12)
0.461
CGC
0.080
1.33 (0.71 - 2.46)
0.371
This study investigated the influence of
Considering that lung cancer is the most common thoracic malignancy, these results can be parallel to a less common thoracic malignancy such as MM. However,
All of the above discussed publications present the
According to the db SNP and HapMap data on rs243865 frequency in genetically different populations, the C allele is more common in Caucasian populations. That can perhaps contribute to the different results in different studied populations.16
Nevertheless, all of the cited studies find that
Genome Wide Associated Study (GWAS) of 759 subjects in the Northern Italian population investigated 15 different SNPs in several genes, and one of them was
The
Our results suggest a combined effect of asbestos exposure and
Despite some limitations of our study, such as a small sample size and a control group that was not appropriately age balanced, low rate of patient asbestos exposure and lacking this data of the control group, our results reached statistical significance and showed that there could be a genetic predisposition of certain MMP SNPs for MM and that there is a potential gene-environment interaction between MMP SNPs and asbestos that is a major risk factor for MM.
In conclusion, our data suggests that