Malignant pleural mesothelioma (MPM) 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 from 9–12 months. The worldwide incidence of mesothelioma is approximately 94,000 cases per year. The incidence of mesothelioma is rising worldwide, with the most affected areas being Europe, Australia, and the USA [
Over the last decade, the standard treatment of mesothelioma has not changed. It relies on surgery, chemotherapy, and radiation-based approaches [
Recent studies have identified matrix metalloproteinases (MMPs) as modulators of the tumor microenvironment with an important role in carcinogenesis [
Common genetic polymorphisms that may influence MMP expression levels (as well as cancer risk) have been reported in all genes coding for the abovementioned MMPs. Genetic polymorphisms in
Patients with histologically proven pleural or peritoneal mesothelioma diagnosed and treated between 2007 and 2015 were included in this retrospective study. Patients were diagnosed mostly at the University Clinic of Golnik and University Clinical Center Ljubljana, Department of Thoracic Surgery. Most of the patients were treated and followed up at the Institute of Oncology, Ljubljana.
Most patients included in the study were also participating in previous studies on pharmacogenomics of MPM treatment at the Institute of Oncology, Ljubljana. Some of the patients were included in a parallel clinical trial AGILI (Trial registration ID
The study was approved by the Slovenian Ethics Committee for Research in Medicine and was carried out according to the Declaration of Helsinki.
Considering the retrospective nature of the study, time to progression (TTP) was chosen as an end point as well as overall survival (OS). TTP was defined as time from diagnosis to progression, and OS was defined as time from diagnosis to death of any cause. The patients that did not progress or die at the time of analysis were censored at the time of the last follow-up. Progression was assessed radiologically, using at least a chest X-ray; however, the majority of patients had either a CT scan or a PET/CT scan.
Genomic DNA was extracted from whole-blood frozen samples collected at the inclusion in any of the abovementioned studies using the Qiagen FlexiGene Kit (Qiagen, Hilden, Germany) in accordance with the manufacturer’s instructions.
Putatively functional SNPs with minor allele frequency of at least 5% in European population were selected for analysis: all nonsynonymous SNPs and SNPs in 3
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 95% 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 model was used in statistical analyses. The influence of genetic polymorphism on TTP and OS was examined by Cox regression to calculate hazard ratios (HRs) and their 95% confidence intervals (CIs). Clinical variables used for adjustment in multivariable survival analysis were selected from clinical variables at diagnosis using stepwise forward conditional selection.
All statistical analyses were carried out by Statistical Package for the Social Sciences (SPSS) for Windows, version 21.0 (IBM Corporation, Armonk, NY, USA). Haplotypes were reconstructed and analyzed using THESIAS software. The most frequent haplotype was used as the reference. All statistical tests were two-sided. To reduce the chance of false positive results, multiple testing analysis by false discovery rate from the Genetic Type I error calculator was used to select the threshold for
In total, we included 199 patients with MPM. Clinical characteristics of the study group are summarized in Table
Patients’ characteristics (
Characteristic |
| |
---|---|---|
Gender | Male | 151 (75.9) |
Female | 48 (24.1) | |
|
||
Age | Median (25%–75%) | 66 (58–72) |
|
||
Stage | I | 13 (6.5) |
II | 53 (26.6) | |
III | 61 (30.7) | |
IV | 54 (27.1) | |
Peritoneal | 18 (9.0) | |
|
||
Histological type | Epithelioid | 143 (71.9) |
Biphasic | 25 (12.6) | |
Sarcomatoid | 21 (10.6) | |
Not characterized | 10 (5.0) | |
|
||
ECOG performance status | 0 | 10 (5.0) |
1 | 95 (47.7) | |
2 | 84 (42.2) | |
3 | 10 (5.0) | |
|
||
C-reactive protein | Median (25%–75%) | 23 (10–68.3) [29] |
|
||
Asbestos exposure | Not exposed | 43 (22.3) [6] |
Exposed | 150 (77.7) | |
|
||
Smoking | Nonsmokers | 95 (49.0) [5] |
Smokers | 99 (51.0) | |
|
||
Type of chemotherapy | Gemcitabine/cisplatin | 123 (61.8) |
Pemetrexed/cisplatin | 48 (24.1) | |
Other | 11 (5.5) | |
None | 17 (8.6) | |
|
||
Response rate | CR | 7 (4.1) [27] |
PR | 57 (33.1) | |
SD | 86 (50.0) | |
PD | 22 (12.8) | |
|
||
Time to progression | Median (25%–75%) | 7.67 (5.27–13.80) |
|
||
Overall survival | Median (25%–75%) | 16.30 (9.07–26.80) |
|
||
Follow-up | Median (25%–75%) | 69.67 (22.00–81.53) |
Numbers in square brackets denote the number of patients with missing data. CR: complete response; ECOG: Eastern Cooperative Oncology Group; PD: progressive disease; PR: partial response; SD: stable disease.
Genotype frequencies of investigated SNPs and their predicted functions are presented in Table
Genotype frequencies of investigated polymorphisms.
Gene | SNP | Genotype |
|
Predicted function |
|
---|---|---|---|---|---|
|
rs243865 | c.-1306C>T | CC | 130 (65.3) | May influence binding of transcription factors, may alter chromatin states |
CT | 66 (33.2) | ||||
TT | 3 (1.5) | ||||
rs243849 | c.999C>T, p.Asp333= | CC | 140 (70.4) | May influence splicing | |
CT | 51 (25.6) | ||||
TT | 8 (4.0) | ||||
rs7201 | c. |
AA | 67 (33.7) | Differential miRNA binding may alter regulatory motifs and tissue-specific gene expression | |
AC | 96 (48.2) | ||||
CC | 36 (18.1) | ||||
|
|||||
|
rs17576 | c.836A>G, p.Gln279Arg | AA | 80 (40.6) [2] | Nonsynonymous may change protein function or structure, may influence splicing |
AG | 98 (49.7) | ||||
GG | 19 (9.6) | ||||
rs2250889 | c.1721C>G, p.Arg574Pro | CC | 181 (91.0) | Nonsynonymous may influence splicing | |
CG | 18 (9.0) | ||||
GG | 0 (0.0) | ||||
rs17577 | c.2003G>A, p.Arg668Gln | GG | 141 (71.6) [2] | Nonsynonymous may influence splicing | |
GA | 53 (26.9) | ||||
AA | 3 (1.5) | ||||
rs20544 | c. |
CC | 37 (18.7) [1] | Differential miRNA binding may alter regulatory motifs and tissue-specific gene expression | |
CT | 101 (51.0) | ||||
TT | 60 (30.3) | ||||
|
|||||
|
rs1042703 | c.22T>C, p.Pro8Ser | TT | 130 (67.0) [5] | Nonsynonymous |
TC | 53 (27.3) | ||||
CC | 11 (5.7) | ||||
rs1042704 | c.817G>A, p.Asp273Asn | GG | 135 (67.8) | Nonsynonymous may influence splicing | |
GA | 54 (27.1) | ||||
AA | 10 (5.0) | ||||
rs743257 | c. |
CC | 50 (25.1) | Differential miRNA binding may alter chromatin states and regulatory motifs | |
CT | 86 (43.2) | ||||
TT | 63 (31.7) |
Numbers in square brackets denote the number of patients with missing data.
The results of TTP analysis are shown in Table
The influence of
Gene | Genotype | Time to progression | HR (95% CI) |
|
Overall survival | HR (95% CI) |
|
---|---|---|---|---|---|---|---|
Median (25%–75%) | Median (25%–75%) | ||||||
|
|||||||
rs243865 | CC | 8.83 (6.43–15.03) | Ref. | 17.43 (10.60–27.27) | Ref. | ||
CT | 10.17 (6.00–16.33) | 0.88 (0.63–1.22) | 0.437 | 17.47 (9.47–31.17) | 0.96 (0.68–1.36) | 0.826 | |
TT | 14.97 (8.20–44.57) | 0.54 (0.17–1.75) | 0.305 | 30.00 (22.03–30.00) | 0.44 (0.11–1.81) | 0.255 | |
CT + TT | 10.20 (6.27–16.33) | 0.85 (0.61–1.18) | 0.334 | 18.07 (9.63–31.17) | 0.92 (0.66–1.30) | 0.653 | |
rs243849 | CC | 9.87 (6.13–16.67) | Ref. | 19.10 (9.83–28.13) | Ref. | ||
CT | 8.67 (6.67–14.30) | 1.30 (0.91–1.86) | 0.144 | 16.23 (10.80–29.03) | 1.26 (0.86–1.85) | 0.227 | |
TT | 7.33 (3.27–11.80) |
|
|
17.63 (7.33–36.73) | 1.18 (0.51–2.72) | 0.698 | |
CT + TT | 8.67 (6.60–14.30) | 1.38 (0.98–1.94) | 0.064 | 16.63 (10.80–30.27) | 1.25 (0.87–1.80) | 0.225 | |
rs7201 | AA | 9.27 (6.37–16.93) | Ref. | 16.23 (10.63–28.03) | Ref. | ||
AC | 10.00 (6.73–15.03) | 0.87 (0.61–1.24) | 0.441 | 19.30 (10.80–30.00) | 0.89 (0.62–1.29) | 0.547 | |
CC | 8.00 (5.50–12.63) | 1.15 (0.73–1.80) | 0.551 | 14.20 (9.23–26.17) | 1.20 (0.74–1.95) | 0.467 | |
AC + CC | 9.80 (6.43–14.57) | 0.93 (0.67–1.30) | 0.684 | 18.07 (9.63–29.03) | 0.96 (0.67–1.36) | 0.803 | |
|
|||||||
|
|||||||
rs17576 | AA | 9.27 (6.13–13.53) | Ref. | 13.57 (9.83–23.90) | Ref. | ||
AG | 10.73 (6.80–18.47) | 0.84 (0.60–1.17) | 0.303 | 21.20 (12.17–32.53) | 0.72 (0.50–1.03) | 0.070 | |
GG | 8.50 (6.00–16.67) | 1.17 (0.69–1.98) | 0.558 | 16.63 (8.27–26.60) | 0.96 (0.54–1.68) | 0.881 | |
AG + GG | 10.00 (6.67–16.90) | 0.89 (0.65–1.23) | 0.478 | 19.30 (11.33–31.17) | 0.76 (0.54–1.06) | 0.106 | |
rs2250889 | CC | 10.03 (6.73–16.67) | Ref. | 19.10 (11.33–30.00) | Ref. | ||
CG | 6.07 (4.07–7.90) |
|
|
9.23 (4.53–14.20) |
|
|
|
rs17577 | GG | 10.00 (6.60–16.33) | Ref. | 18.07 (10.60–28.30) | Ref. | ||
GA | 8.33 (5.50–14.57) | 1.20 (0.84–1.72) | 0.319 | 17.63 (9.47–32.87) | 0.82 (0.56–1.20) | 0.311 | |
AA | 8.83 (8.00–19.43) | 1.02 (0.32–3.25) | 0.977 | 13.50 (9.97–25.93) | 1.58 (0.49–5.04) | 0.444 | |
GA + AA | 8.50 (5.53–14.57) | 1.19 (0.84–1.68) | 0.339 | 17.63 (9.63–32.53) | 0.85 (0.59–1.24) | 0.403 | |
rs20544 | CC | 7.53 (5.53–11.53) | Ref. | 13.50 (8.13–21.20) | Ref. | ||
CT | 10.93 (7.37–19.97) |
|
|
20.67 (11.33–32.53) |
|
|
|
TT | 9.40 (6.27–14.30) | 0.67 (0.43–1.03) | 0.069 | 15.40 (10.80–25.67) | 0.70 (0.44–1.11) | 0.132 | |
CT + TT | 10.13 (6.73–16.20) |
|
|
19.30 (10.80–31.17) |
|
|
|
|
|||||||
|
|||||||
rs1042703 | TT | 9.27 (6.67–16.33) | Ref. | 17.50 (9.97–29.13) | Ref. | ||
TC | 10.17 (6.27–14.53) | 1.36 (0.94–1.96) | 0.100 | 19.30 (9.47–29.03) | 1.25 (0.87–1.81) | 0.229 | |
CC | 8.70 (5.13–16.20) |
|
|
12.70 (7.07–20.60) |
|
|
|
TC + CC | 10.17 (6.03–14.97) |
|
|
17.63 (8.30–28.30) | 1.36 (0.97–1.92) | 0.076 | |
rs1042704 | GG | 9.80 (6.73–14.90) | Ref. | 17.50 (10.80–31.17) | Ref. | ||
GA | 8.30 (5.70–16.20) | 1.05 (0.74–1.49) | 0.780 | 17.47 (9.10–24.23) | 1.40 (0.98–2.00) | 0.068 | |
AA | 7.87 (6.00–16.90) | 0.90 (0.45–1.82) | 0.777 | 20.27 (13.57–25.93) | 1.22 (0.59–2.53) | 0.598 | |
GA + AA | 8.30 (5.93–16.90) | 1.03 (0.74–1.42) | 0.881 | 18.07 (9.63–24.57) | 1.37 (0.97–1.92) | 0.072 | |
rs743257 | CC | 9.87 (7.07–14.07) | Ref. | 13.50 (9.97–27.27) | Ref. | ||
CT | 9.40 (5.97–19.43) | 1.08 (0.72–1.64) | 0.700 | 15.40 (6.80–28.13) | 0.98 (0.65–1.49) | 0.931 | |
TT | 9.70 (6.60–14.53) | 1.15 (0.75–1.76) | 0.535 | 20.17 (12.53–31.17) | 0.87 (0.56–1.36) | 0.544 | |
CT + TT | 9.43 (6.07–16.33) | 1.11 (0.76–1.63) | 0.588 | 19.30 (9.83–30.27) | 0.93 (0.63–1.37) | 0.722 |
On the other hand, carriers of at least one polymorphic
A nominally significant association with shorter TTP was observed in carriers of polymorphic
The results of OS analysis are shown in Table
The influence of
Again, carriers of at least one polymorphic
Carriers of two polymorphic alleles
As two SNPs in
The influence of
Haplotype | Estimated frequency | TTP HR (95% CI) |
|
OS HR (95% CI) |
|
---|---|---|---|---|---|
ACGT | 0.560 | Reference | Reference | ||
GCGC | 0.214 | 0.98 (0.74–1.29) | 0.877 | 0.97 (0.73–1.30) | 0.853 |
GCAC | 0.129 | 1.13 (0.81–1.58) | 0.460 | 0.96 (0.68–1.37) | 0.830 |
ACGC | 0.053 | 1.33 (0.81–2.18) | 0.261 | 1.85 (1.12–3.05) |
|
AGGC | 0.024 | 2.14 (1.03–4.44) |
|
2.07 (1.02–4.22) |
|
AGAC | 0.020 | 2.93 (1.30–6.60) |
|
3.38 (1.33–8.54) |
|
The SNPs are ordered from the 5
This study investigated the influence of
One of the previous studies in
In addition to the abovementioned role of MMP9 in local tumor progression and metastasis, it also has a tumor-suppressing function of producing endogenous angiogenesis inhibitors, promoting inflammatory antitumour activity and inducing apoptosis [
In our study, we have also investigated
The cited studies that investigated the role of our selected SNPs included a limited number of patients and were not setup as genome-wide association studies (GWAS). However, an Italian-based GWAS study that included 407 patients and 389 controls found that
Our study brings novel interesting findings; however, it has a few limitations, due to the low size number and the fact that we did not perform a GWAS and/or a replication study. As MPM is very rare, the results should be validated in an independent population in the future.
In conclusion, we believe that selected
The authors declare that there is no conflict of interest regarding the publication of this paper.
This work was financially supported by the Slovenian Research Agency (Grant nos. L3-3648, P1-0170, and L3-8203).