It is generally accepted that the risk of developing diseases and an individual’s response to the treatment may also depend on their genetic characteristics. In this study, we have focused on malignant mesothelioma (MM), which is a very aggressive cancer associated with the exposure to asbestos.1, 2, 3, 4 Most frequently it arises from pleura or peritoneum, but can also arise from other serous surfaces.5, 6
In Slovenia, the professional exposure to asbestos occurred mainly in asbestos cement industry, in construction, in manufacture of machinery and insulation materials, in maintenance of various means of transport, in textile industry and in other activities.7, 8, 9 Malignant mesothelioma is associated also with exposure to asbestos outside the workplace.5, 8, 9, 10 It is estimated that the incidence of MM will remain stable or will even increase in the near future due to the continuous presence of asbestos in buildings and to the long latent period after exposure to asbestos.11, 12 It is predicted that its incidence in the most industrialized countries will continue to increase until 2020,5 or even later.11
Due to an increasing incidence of MM and its poor prognosis, new prognostic and predictive biomarkers are needed.13 Symptoms of MM commonly occur only at late stages, therefore novel biomarkers for earlier diagnosis of MM and for establishing the response to treatment might be a promising opportunity for these patients.14 Several classes of potential biomarkers of MM have been studied so far, from serum peptides to genetic and epigenetic biomarkers, however with limited success. Among serum biomarkers, soluble peptides related to mesothelin (soluble mesothelin-related peptides, SMRP),15 fibulin-3,16 survivin13 have been studied, however none of them had sufficient predictive value as a standalone biomarker. It has been proposed, that biomarkers from two different molecular classes: protein and miRNA could be used in a combination to improve the biomarker sensitivity and specificity.14
Another approach was to investigate interin-dividual genetic variability in genes coding for key determinants of molecular pathogenesis of MM as potential biomarkers for prediction of the risk of MM as well as treatment response. Several studies have shown that polymorphisms in the genes involved in xenobiotic and oxidative metabolism or in DNA repair processes may play an important role in aetiology and pathogenesis of MM.17, 18, 19 The most commonly studied
Aquaporins (AQPs) are small transmembrane proteins, which facilitate an osmotically controlled passage of water. Recent research indicated a key role of AQPs in human carcinogenesis.25, 26, 27 All key processes in cancer cells depend on water in the tumour microenvironment, therefore an enhanced transmembrane transmission of water is stimulated in comparison to normal cells. Overexpression of AQPs in the cell lines of the vascular endothelium and tumour cell lines suggests that AQPs may be closely related to the development and progression of a tumour.28 In some cancers AQP1 expression was also shown to participate in metastatic processes.29 In
The expression of AQP1 in MM tumour cells has been suggested to be an independent prognostic factor favouring survival in MM patients: higher levels of an AQP1 expression only in tumour cells, but not in vascular cells, predicted a better survival.31 Higher levels of AQP1 expression were also associated with a better course of the disease in MM, but with worse course of the disease in some other tumours such as breast cancer, melanoma, urothelial and pharyngeal carcinoma.32, 33, 34, 35 AQP1 is of interest as a potential biomarker in MM patients as it was shown to be an independent prognostic factor11 with high levels of its expression correlating with an increased survival.29, 31, 36 AQP1 expression also correlated with improved survival rates in MM with epithelioid component in comparison to AQP1-poor MM.37 Furthermore, AQP1 is also a possible new target for MM treatment,5 and there are already AQP1 blockers available which could be used for therapy.38
Genetic polymorphisms were reported in
The aim of the present study was to investigate the influence of
The case-control study included patients treated for mostly MM of pleura or also peritoneum at the Institute of Oncology Ljubljana from 2007 to the end of 2016. Control group consisted of blood donors from the Institute of Transfusion Medicine in Ljubljana and were over 40 years old.
The diagnosis of MM was made by means of thoracoscopy or video-assisted thoracoscopic surgery (VATS) in patients with pleural MM and by means of laparoscopy or laparotomy in peritoneal MM. The diagnosis was confirmed histopathologically by an experienced pathologist [15].15
Demographic and clinical data (age, gender, smoking, possible other diseases) from patients with MM were obtained from the medical records of the Institute of Oncology Ljubljana.
The following clinical indicators were used to evaluate the efficacy of treatment: response to treatment according to the modified criteria RECIST (Response Evaluation Criteria in Solid Tumours),43 PFS and overall survival (OS). The toxicity of the treatment was assessed according to NCI criteria (National Cancer Institute Common Terminology Criteria for Adverse Events, version 4.0).44
The study was approved by the Republic of Slovenia National Medical Ethics Committee (41/02/09) and was carried out according to the Helsinki Declaration. All the subjects included in the study have signed the written informed consent.
DNA samples from 26 patients were isolated from peripheral venous blood with commercially available reagent sets (QIAamp DNA Mini Kit and Flexigene DNA Kit (Qiagen, Hilden, Germany)). For all other patients and controls DNA was already isolated from peripheral venous blood samples during the course of the previous studies.18, 45, 46, 47, 48
Based on the bioinformatics analysis, we selected the following SNPs:
All the polymorphisms were genotyped using competitive allele specific PCR (KASPar) according to the manufacturer’s instructions (LGC Genomics, UK).
All statistical analyses were performed using IBM SPSS Statistics version 21.0 (IBM Corporation, Armonk, NY, USA). With the usual descriptive statistics we first described the characteristics of each variable separately. In order to assess the causal relationship between MM and the individual variables, we first used a univariate logistic regression. Both additive and dominant models were used to assess the effect of the selected
In order to test the interactions between the selected
The clinical characteristics of MM patients are shown in Table 1. Among all 231 patients whose median (25%–75% range) age was 66 (58–73) years, men represented 73.6%. Epithelioid MM was present in 72.3% of patients. ECOG performance status 1 (48.1%) and 2 (39.0%) prevailed. Exposure to asbestos was confirmed in 73.8% of patients. Among all patients, 46.7% were smokers. In total 194 patients were treated with cisplatin based therapy.
Description of all malignant mesothelioma (MM) patients (N = 231) and MM patients treated with cisplatin based chemotherapy (N = 194)
All MM patients | MM patients cisplatin treated based with chemotherapy | ||
---|---|---|---|
Characteristic | Characteristic type | N (%) | N (%) |
Age | Median (25%–75%) | 66 (58–73) | 65 (58–71.3) |
Gender | Men | 170 (73.6) | 146 (75.3) |
Women | 61 (26.4) | 48 (24.7) | |
I | 18 (7.8) | 15 (7.7) | |
II | 57 (24.7) | 48 (24.7) | |
MM stage | III IV | 69 (29.9) 66 (28.6) | 62 (32.0) 50 (25.8) |
Peritoneal MM | 20 (8.7) | 18 (9.3) | |
Undefined | 1 (0.4) | 1 (0.5) | |
Epithelioid | 167 (72.3) | 147 (75.8) | |
Histological | Biphasic | 26 (11.3) | 21 (10.8) |
type | Sarcomatoid | 24 (10.4) | 21 (10.8) |
Undefined | 14 (6.0) | 5 (2.6) | |
0 | 15 (6.5) | 15 (7.7) | |
ECOG | 1 | 111 (48.1) | 100 (51.5) |
performance status | 2 | 90 (39.0) | 76 (39.2) |
3 | 15 (6.5) | 3 (1.5) | |
Exposure to | No | 59 (26.6)a | 45 (23.3)c |
asbestos | Yes | 166 (73.8) | 148 (76.7) |
No | 120 (53.3)a | 101(52.6)d | |
Smoking | Yes | 105 (46.7) | 91(47.4) |
Gemcitabine/ Cisplatin | 132 (60.0)b | 132 (68.0) | |
Pemetrexed/Cisplatin | 62 (28.2) | 62 (32.0) | |
Treatment | chemotherapy Without | 16 (7.3) | - |
Other forms of chemotherapy | 10 (4.5) | - |
Data are missing for: a 6 patients, b 11 patients, c 1 patient and d 2 patients. ECOG = Eastern Cooperative Oncology Group
In addition, 316 healthy blood donors, 235 men and 81 women, whose median (25%–75% range) age was 49 (45-55) years were also included in the molecular-genetic part of the study.
The genotype frequency distribution for the investigated polymorphisms in 231 MM patients and in 316 controls, their minor allele frequencies (MAF) and the risk of developing MM are shown in Table 2. The genotypes’ distribution was in Hardy-Weinberg equilibrium (HWE), except for the distribution of
Distribution of
Patients | Controls | |||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|
SNP | Role | Genotype | N (%) | MAF | PHWE | N (%) | MAF | PHWE | OR (95% CI) | P | OR (95% CI)adj | Padj |
rs28362731a | p.Gly165Asp | GG | 210 (92.1) | 0.039 | 0.535 | 288 (91.7) | 0.041 | 0.444 | Ref. | - | Ref. | - |
GA | 18 (7.9) | 26 (8.3) | 0.95 | 0.871 | 0.94 | 0.885 | ||||||
(0.51–1.78) | (0.38–2.30) | |||||||||||
rs1049305b | c.*578G>C | GG | 107 (46.5) | 0.337 | 0.082 | 128 (40.8) | 0.373 | 0.288 | Ref. | - | Ref. | - |
GC | 91 (39.6) | 138 (43.9) | 0.79 | 0.207 | 0.59 | |||||||
(0.55–1.14) | (0.35–0.97) | |||||||||||
CC | 32 (13.9) | 48 (15.3) | 0.80 | 0.390 | 0.63 | 0.199 | ||||||
(0.48–1.13) | (0.32–1.27) | |||||||||||
GC+CC | 123 (53.5) | 186 (59.2) | 0.79 | 0.181 | 0.60 | |||||||
(0.56–1.12) | (0.37–0.96) | |||||||||||
rs1476597c | c.-783G>C | GG | 157 (68.0) | 0.255 | <0.001 | 220 (70.1) | 0.247 | <0.001 | ||||
GC | 30 (13.0) | 33 (10.5) | ||||||||||
CC | 44 (19.0) | 61 (19.4) |
Data are missing for: a2 controls and 3 patients, b2 controls and 1 patient, c2 controls. adj = adjusted by gender and age; MAF = minor allele frequency; PHWE = P for Hardy-Weinberg equilibrium; Ref. = reference genotype
In univariate analysis no polymorphism was associated with the risk of developing MM (Table 2). Higher age was associated with a higher risk of developing MM (OR = 1.21, 95% CI = 1.17–1.25, P < 0.001) but gender (OR = 1.04, 95% CI = 0.71–1.53, P = 0.838) was not.
Clinical characteristics of MM patients treated with cisplatin based chemotherapy are presented in Table 3. The majority (68.0%) of patients were treated with gemcitabine in combination with cisplatin. In chemotherapy response a third (32.8%) of patients responded with partial response (PR) and only in few patients (3.2%) the response was complete (CR). A half (49.5%) of patients had stable disease (SD) and a few (14.5%) of them had progressive disease (PD). Median progression free survival (PFS) was 7.8 months, median overall survival (OS) 18.1 months and median follow-up from the start of chemotherapy 49.2 months.
Clinical characteristics of MM patients treated with cisplatin based chemotherapy (N = 194)
Characteristic | N (%) | |
---|---|---|
Gemcitabine and cisplatin | 132 (68.0) | |
Chemotherapy type | Pemetrexed and cisplatin | 62 (32.0) |
Complete response (CR) | 6 (3.2) | |
Partial response (PR) | 61 (32.8) | |
Chemotherapy responsea | Stable disease (SD) | 92 (49.5) |
Progressive disease (PD) | 27 (14.5) | |
Progression of diseaseb | No | 20 (10.5) |
Yes | 171 (89.5) | |
No | 58 (29.9) | |
Death | Yes | 136 (70.1) |
PFS | Median (25%–75%) (month) | 7.8 (5.3–13.8) |
OS | Median (25%–75%) (month) | 18.1 (9.4–28.7) |
Follow-chemotherapy up from the start of | Median (25%–75%) (month) | 49.2 (18.9–75.5) |
CRP | Median (25%–75%) | 20.5 (9–58) |
LDH | Median (25%–75%) | 2.67 (2.26–3.11) |
Painb | No | 79 (41.4) |
Yes | 112 (58.6) | |
No | 68 (35.8) | |
Weight lossc | Yes | 122 (64.2) |
Data are missing for: a8 patients, b3 patients, c4 patients. CRP = C reactive protein; LDH = lactate dehydrogenase; OS = overall survival; PFS = progression free survival
In the survival analysis
Influence of
Progress free | survival | Overall survival | Chemotherapy response | ||||||||
---|---|---|---|---|---|---|---|---|---|---|---|
SNP | Genotype | PFS median (25%–75%) month | HR (95% CI) | P | OS median (25%–75%) month | HR (95% CI) | P | Poor response N (%) | Good response N (%) | OR (95% CI) | P |
GG | 7.7 (5.2–13.6) | Ref. | - | 18.1 (9.1–28.0) | Ref. | - | 112 (65.1) | 60 (34.9) | Ref. | - | |
rs28362731 | GA | 11.1 (7.0–14.7) | 0.72 (0.39–1.33) | 0.299 | 26.5 (14.4–47.8) | 0.56 (0.26–1.19) | 0.130 | 6 (54.5) | 5 (45.5) | 1.56 (0.46–5.31) | 0.481 |
GG | 7.9 (5.4–12.1) | Ref. | - | 18.1 (9.0–26.8) | Ref. | - | 55 (64.7) | 30 (35.3) | Ref. | - | |
GC | 7.8 (5.2–15.0) | 0.80 (0.58–1.11) | 0.187 | 22.1 (10.1–29.7) | 0.72 (0.50–1.05) | 0.091 | 43 (58.1) | 31 (41.9) | 1.32 (0.70–2.51) | 0.394 | |
rs1049305 | CC | 7.4 (4.8–14.1) | 0.92 (0.59–1.46) | 0.736 | 13.3 (8.1–25.4) | 1.10 (0.67–1.80) | 0.712 | 20 (76.9) | 6 (23.1) | 0.55 (0.20–1.52) | 0.248 |
GC+CC | 7.8 (4.9–15.0) | 0.83 (0.62–1.13) | 0.233 | 18.2 (9.5–28.7) | 0.81 (0.58–1.14) | 0.220 | 63 (63.0) | 37 (37.0) | 1.08 (0.59–1.97) | 0.810 |
SNP = single nucleotide polymorphisms; OS = overall survival; PFS = progression free survival; Ref. = reference genotype
The association between SNPs and side effects in cisplatin based treatment is shown in Tables 5 and 6.
Association between
Anemia grade ≥ 2a | Thrombocytopeniab | Leukopenia grade ≥ 2c | Neutropenia grade ≥ 2 | ||||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
SNP | Genotype | N (%) | OR (95% CI) | P | OR (95% CI)adj1 | P adj1 | N (%) | OR P (95% CI) | OR (95% CI)adj2 | Padj2 | N OR (%) (95% CI) | P | N (%) | OR P (95% CI) | |
rs28362731 | GG | 79 (49.4) | Ref. | - | Ref. | - | 21 (13.3) | Ref. - | Ref. | - | 39 Ref. (25.2) | - | 59 (36.4) | Ref. - | |
GA | 3 (27.3) | (0.100.38 –1.50) | 0.169 | (0.130.53 –2.12) | 0.370 | (36.44 ) | (1.003.73 –13.84) |
(1.134.63 –19.05) | (18.22 ) (0.140.66 –3.19) | 0.606 | 3 (27.3) | (0.170.66 –2.56) 0.543 | |||
GG | (56.846 ) | Ref. | - | Ref. | - | (12.510 ) | Ref. - | Ref. | - | (14 17.5) Ref. | - | 25 (30.9) | Ref. - | ||
GC | (34.323 ) | (0.200.40 –0.78) | (0.230.46 –0.92) | (11.88 ) | (0.350.93 –2.52) 0.892 | (0.240.71 –1.08) | 0.529 | (18 27.7) (0.821.81 –3.99) | 0.144 | 26 (37.1) | (0.671.32 –2.60) 0.416 | ||||
rs1049305 | CC | (52.013 ) | (0.340.82 –2.03) | 0.674 | (0.280.74 –1.94) | 0.536 | (30.47 ) | (1.013.06 –9.28) |
(0.692.18 –6.94) | 0.185 | (36.19 ) (1.103.03 –8.38) | 11 (45.8) | (0.751.90 –4.81) 0.178 | ||
GC +CC | (39.136 ) | (0.270.49 –0.90) | (0.270.52 –0.99) | (16.515 ) | (0.581.38 –3.28) 0.463 | (0.431.07 –2.69) | 0.885 | (30.727 ) (1.002.09 –4.35) | 37 (39.4) | (0.781.45 –2.72) 0.242 |
Data are missing for: a2 patients, b4 patients, c7 patients. adj1 = adjusted by CRP; adj2 = adjusted by pain at diagnosis; SNP = single nucleotide polymorphisms
The investigated polymorphisms did not statistically significantly influence neutropenia grade ≥ 2, nephrotoxicity or nausea and/or vomiting (Tables 5 and 6).
Associations between
Alopeciaa | Nephrotoxicityb | Nausea/Vomitingc | ||||||||
---|---|---|---|---|---|---|---|---|---|---|
SNP | Genotype | N (%) | OR (95% CI) | P | N (%) | OR (95% CI) | P | N (%) | OR(95% CI) | P |
GG | 60 (45.8) | Ref. | - | 74 (46.8) | Ref. | - | 73 (53.7) | Ref. | - | |
rs28362731 | GA | 5 (55.6) | 1.48 (0.38–5.76) | 0.572 | 3 (27.3) | 0.43 (0.11–1.66) | 0.219 | 5 (55.6) | 1.08 (0.28–4.19) | 0.913 |
GG | 30 (46.2) | Ref. | - | 35 (43.8) | Ref. | - | 36 (52.9) | Ref. | - | |
GC | 20 (35.7) | 0.65 (0.31–1.35) | 0.246 | 34 (50.0) | 1.29 (0.67–2.46) | 0.448 | 26 (44.8) | 0.72 (0.36–1.46) | 0.364 | |
rs1049305 | CC | 15 (71.4) | 2.92 (1.00–8.46) | 10 (43.5) | 0.99 (0.39–2.52) | 0.982 | 15 (71.4) | 2.22 (0.77–6.41) | 0.140 | |
GC+CC | 35 (45.5) | 0.97 (0.50–1.89) | 0.934 | 44 (48.4) | 1.20 (0.66–2.20) | 0.547 | 41 (51.9) | 0.96 (050–1.84) | 0.900 |
Data are missing for: a 33 patients, b 4 patients and c 28 patients. SNP = single nucleotide polymorphisms
Multiplicative interaction analysis did not show any interactions between
Influence of interactions on the risk of occurrence of side effects
Interaction 1rs28362731 | Interaction 2 | Interaction 3 | ||||
---|---|---|---|---|---|---|
Side effect | -rs1049305 | P1 | rs28362731 - smoking | P2 | rs1049305 - smoking | P3 |
OR (95% CI) | OR (95% CI) | OR (95% CI) | ||||
Anemia grade ≥ 2a | 1.84 (0.10–32.37) | 0.676 | - | 0.999 | 0.34 (0.10–1.16) | 0.085 |
Leukopenia grade ≥ 2b | 0.95 (0.04–23.07) | 0.974 | - | 0.999 | 0.92 (0.21–4.02) | 0.915 |
Neutropenia grade ≥ 2 | 0.55 (0.03–9.76) | 0.686 | 7.55 (0.39–145.1) | 0.180 | 0.67 (0.19–2.35) | 0.526 |
Thrombocytopeniac | 1.73 (0.11–26.38) | 0.693 | 3.06 (0.20–46.56) | 0.422 | 0.95 (0.16–5.66) | 0.955 |
Nephrotoxicityc | 0.68 (0.04–11.98) | 0.794 | - | 0.999 | 1.01 (0.30–3.43) | 0.982 |
Alopeciad | 2.06 (0.11–40.01) | 0.633 | - | 0.999 | 0.60 (0.16–2.29) | 0.453 |
Nausea/Vomitinge | 2.12 (0.11–40.98) | 0.620 | 6.83 (0.35–132.4) | 0.204 | 0.71 (0.19–2.64) | 0.608 |
Data are missing for: a 2 patients, b 7 patients, c 4 patients, d 33 patients and e 28 patients. Interaction 1: interaction between rs28362731 and rs1049305. Interaction 2: interaction between rs28362731 and smoking. Interaction 3: interaction between rs1049305 and smoking.
Haplotypes
In the present study we investigated the influence of
The statistical analyses have shown that the genotype distribution for the third investigated polymorphism
We have also assessed the impact of
Our study also showed that
We have also observed that
The major limitation of our study was that we had no information on asbestos exposure in healthy controls. Furthermore, MM patients were older than controls, as blood donors can only be up to 65 years old, however we accounted for that with adjustment for age in the statistical analysis. Despite the limited number of patients included in our study, all patients were monitored in the same institution and by the same oncologists, so there were no differences in the clinical assessments. Furthermore, all the patients and controls came from an ethnically homogeneous Slovenian population, so there were no differences due to genetic heterogeneity.50, 51
Our study brings novel findings of the associations between
In conclusion, our study suggests that the investigated