Oxidative Stress Induction By Pesticides May Cause Lung Cancer Incidence

Background and aims: Pesticides are nowadays known as one of the most important causes of human disorders worldwide. The aim of the present study was to investigate the role of organochlorine pesticides (OCPs) and organophosphorus pesticides (OPPs) in the development of lung cancer. Methods We determined the levels of seven derived OCP residues (α-HCH, β-HCH, γ-HCH, 2,4 DDT, 4,4 DDT, 2,4 DDE, and 4,4 DDE) and enzymatic antioxidant biomarkers including paraoxonase-1 (PON-1), erythrocyte's acetylcholinesterase (AChE), glutathione peroxidase (GPx), superoxide dismutase (SOD), catalase (CAT), and non-enzymatic antioxidant biomarkers including total antioxidant capacity (TAC), protein carbonyl (PC), malondialdehyde (MDA), and nitric oxide (NO) in the blood samples of 51 lung cancer patients and 51 healthy subjects as controls. Furthermore, the effects of OPP exposure on the development of lung cancer and oxidative stress (OS) are indirectly assessed by measuring AChE and PON-1 enzyme activities. The average values of all the measured OCPs were signicantly higher in lung cancer patients when compared with healthy control subjects. AChE, PON-1, GPx, and CAT activity levels as well as the amounts of PC, MDA, and NO were higher in patients with lung cancer than in the control subjects, while TAC values were lower in the patients. Moreover, our data showed a signicant association between OCP concentrations and OS parameters. The results suggest that OCPs and OPPs may have a role in lung cancer incidence in southeastern Iran, and at least one of the mechanisms by which OCPs and OPPs may contribute to increasing the development of lung cancer in the studied area is through OS generation. The aim of this study was to evaluate the serum OCP levels (including α-HCH, β-HCH, γ-HCH, 2,4 DDE, 4,4 DDE, 2,4 DDT, and 4,4 DDT) in lung cancer and healthy subjects in southeastern Iran to assess whether lung cancer risk can be related to serum OCP and OPP levels. To this end, we also investigated the effects of OPPs and OCPs on OS status in lung cancer and healthy subjects via the evaluation and comparison of non-enzymatic antioxidants, including nitric oxide (NO), malondialdehyde (MDA), and protein carbonyl (PC), and antioxidant enzyme activities, including catalase (CAT), superoxide dismutase (SOD), and glutathione peroxidase (GPx) activities, along with the activity of paraoxonase-1 (PON-1) and AChE in the lung cancer patients and control subjects. identication of OCPs. The retention time (used for qualitative analysis), peak area (used for quantitative analysis), and the internal standard method were utilized to calculate the serum levels of OCPs. Therefore, a set of OCP standard solutions with certain concentrations (0.78, 1.56, 3.12, 6.25, 12.5, 25, 50, 100, 200, and 400 µg/mL) was prepared and then equal levels of DBP (100 µg/mL) were added to each OCP standard solution. Afterward, the peak areas of OCP standards and DBP were calculated, and calibration curves were obtained for each OCP compound, displaying the ratio of the peak area of the OCP standard to that of the internal standard versus the concentration. The peak areas of the OCPs and the internal standard for unknown samples were calculated and the ratio of the peak area was reported. In the nal step, the OCP standard curves were used to determine OCP concentrations. The analytical limit of detection (LOD) was estimated to be 0.9 ng/mL for α-HCH, 0.56 ng/mL for β-HCH, 0.31 ng/mL for γ-HCH, 0.59 ng/mL for 2,4 DDE, 0.68 ng/mL for 4,4 DDE, 0.29 ng/mL for 2,4 DDT, and 0.58 ng/mL for 4,4 DDT. signicantly associated w DDT. MDA was positivity signicantly associated with β-HCH, 2,4 DDE, and 4,4 DDT. TAC was inversely signicantly associated with α-HCH, β-HCH, γ-HCH, 4,4 signicantly associated with 2,4 DDE and 2,4 DDT. PC was positivity signicantly related to β-HCH, γ-HCH, 2,4 DDE, and 4,4 DDT. GPx3 activity was inversely activity was inversely signicantly associated with β-HCH, γ-HCH, 4,4-DDE, 2,4 DDT, and 4,4 DDT.


Introduction
In the world's population, one of the most common cancers is lung cancer, which is the prominent reason for mortality (Basumallik & Agarwal, 2019). It has even been reported that lung cancer in comparison to breast cancer may cause more deaths in women ( Rybarczyk-Kasiuchnicz & Ramlau, 2018). Indeed, the number of patients with lung cancer will increase exponentially without urgent action. In other words, this disease is transforming into a major health problem (Mao et al., 2016). Despite recent advances in cancer diagnosis and treatment (Mardani et al., 2019;Mirzaei et al., 2018), this illness is still one of the major challenges in medical science (Tahmasebi-Birgani et al., 2019). Thus, to combat cancer as a serious disease, the best strategy is control and prevention (Cramb et al., 2015). Notably, the etiology and pathophysiology of lung cancer are not fully elucidated. Therefore, identifying risk factors for lung cancer is critical in preventing and controlling the disease. However, in recent years, accumulated evidence has shown that environmental and lifestyle factors contribute to the development of lung cancer. These factors include tobacco smoking (Miranda-Filho et al., degree of contamination by OCPs and OPPs in cancer patients Mortazavi et al., 2019b;Paydar et al., 2019) in Kerman Province.
The aim of this study was to evaluate the serum OCP levels (including α-HCH, β-HCH, γ-HCH, 2,4 DDE, 4,4 DDE, 2,4 DDT, and 4,4 DDT) in lung cancer and healthy subjects in southeastern Iran to assess whether lung cancer risk can be related to serum OCP and OPP levels. To this end, we also investigated the effects of OPPs and OCPs on OS status in lung cancer and healthy subjects via the evaluation and comparison of non-enzymatic antioxidants, including nitric oxide (NO), malondialdehyde (MDA), and protein carbonyl (PC), and antioxidant enzyme activities, including catalase (CAT), superoxide dismutase (SOD), and glutathione peroxidase (GPx) activities, along with the activity of paraoxonase-1 (PON-1) and AChE in the lung cancer patients and control subjects.

Samples and data collection
The current case-control study was conducted on 51 patients newly diagnosed with lung cancer in Afzalipoor Hospital of Kerman University of Medical Sciences, Kerman, Iran (July 2017-May 2019). The control group included 51 healthy individuals with no evidence of any disease. The diagnosis of lung cancer was established by a lung imaging uorescence endoscope device and whole-body positron emission tomographic imaging.
All of the participants (male and female) in this study were newly diagnosed. In addition, none of them had a history of chronic and autoimmune diseases, alcohol consumption, or hormone therapy, and they were not using any vitamin and iron supplementations. All participants signed a written consent form and the patient's refusal to participate in the study was one of the exclusion criteria. Moreover, patients who had a history of exposure to ionizing radiation or those who were consuming vitamin and iron supplementations were excluded from the study.
The participants in the control group had no history of cancer or acute and chronic diseases based on clinical records, lung imaging uorescence endoscopy, and whole-body positron emission tomographic imaging. Moreover, they were not taking antioxidant supplements, smoking, or consuming alcohol. In the present study, patients were matched to controls based on smoking. The Declaration of Helsinki was used as the cornerstone document for instructing the ethical standards to physicians and participants. The research was approved by the ethics board of Kerman University of Medical Sciences (Code No: IR.KMU.REC.1398.335).
A questionnaire was used to collect the demographic data. First, 10 mL of venous blood was collected from the participants. Then 0.5 mL of the blood sample was transferred to EDTA tubes (to measure AChE) and the remnants were transferred to tubes without anti-coagulation substances. Next, the serum was separated via centrifugation (10 min at 3000 rpm). The serum samples were transmitted to a sterile sample tube holder and were kept at −70°C until further analysis.

Measurement of erythrocyte AChE activity
Hyamine 1622, acetylcholine iodide, and 5, 5-dithio-bis-2-nitrobenzoic acid (DTNB) were obtained from Sigma (Saint Louis, MO, USA). Ellman's modi ed procedure was used to calculate AChE activity in the erythrocytes of all samples (Worek et al., 1999) as described elsewhere Mortazavi et al., 2019a;Paydar et al., 2018). First, 6 mL of distilled water was used to dilute 100 µL of erythrocytes which were washed by normal saline. Next, the reaction buffer (containing 0.28 mmol DTNB, 3.2 mmol acetylcholine iodide, and 20 µM quinidine sulfate) was used to incubate 100 µL of the diluted sample at 37°C for 10 min. Finally, to stop the reaction, 1 mL of Hyamine 1622 was added to the solution. 5-thio-2-nitrobenzoic acid (with maximum absorbance at 440 nm) was the product of the reaction between thiocholine and the chromophore DTNB (Worek et al., 1999). Paydar et al., 2018). First, the rate of phenylacetate hydrolysis was assessed in order to determine arylesterase activity. Afterward, the substrate (2 mM phenylacetate), 2 mM CaCl 2 (Merck, Darmstadt, Germany), and 10 µL of serum in 100 mM Tris-HCl (Merck, Darmstadt, Germany) (pH = 8.0) were used to prepare the reaction mixture. The incubation process of the mixture was performed for 3 min at 37°C. Finally, the level of phenylacetate hydrolysis was evaluated at 270 nm.

Measurement of MDA
MDA is a compound that can be evaluated as a lipid peroxidation index. The thiobarbituric acid (TBA) assay is used for evaluating this substance as described elsewhere Mortazavi et al., 2019b;Paydar et al., 2018). In the presence of the trichloroacetic acid (TCA)-TBA-hydrochloric acid (HCL) reagent, MDA reacts with TBA and produces a pink color. To perform the assay, 200 µL of the solution buffer was added to 100 µL of serum and the absorbance was measured at 535 nm (Buege & Aust, 1978).

Total antioxidant capacity (TAC) assay
The procedure suggested by Benzie and Strain (1996) was used to evaluate the ferric-reducing ability of plasma (FRAP) (Benzie & Strain, 1996). Plasma is capable of reducing ferric tripyridyltriazine (Fe III-TPTZ) complex to an intense blue-colored ferrous (Fe II) form at low pH. The maximum absorbance of this complex is at 593 nm and the blue color intensity is relative to the antioxidant capacity of the sample as explained in prior research Mortazavi et al., 2019a;Paydar et al., 2018). Brie y, 70 µL of the FRAP reagent and 5 µL of serum were mixed. Blank was distilled water; the mixture was incubated at 37℃ for 5 min, and the absorbance was determined at 593 nm. The FRAP values are expressed in micromolar (µM).

SOD activity measurement
The total SOD activity was measured according to the Randox kit protocol (UK; Cat NO.RS504). SOD functions as a catalyst in the dismutation of the superoxide radical (O 2 − ) into hydrogen peroxide (H 2 O 2 ) and elemental oxygen (O 2 ). In the Randox assay kit, superoxide ions (O 2 − ), which are produced either by xanthine oxidase (XOD) or through the conversion of xanthine to uric acid and hydrogen peroxide, are responsible for converting nitroblue tetrazolium (NBT) to NBT-diformazan. Brie y, 250 µL of the work solution was added to 10 µL tNBT-diformazan, which absorbs light at 560 nm. SOD lowers the speed of NBT-diformazan formation by reducing the concentration of superoxide ions. SOD activity is measured by calculating the level of reduction that happens in the presence of NBT-diformazan in an experimental sample.

Determination of GPx3 activity
The GPx assay was conducted via the method described by Paglia and Valentine (1967) using the Randox kit (UK; Cat NO.SD125). The Randox GPx assay kit measures GPx activity indirectly by a coupled reaction with glutathione reductase (GR). GR is an enzyme responsible for regenerating the reduced form of oxidized glutathione (GSSG), which is generated when GPx produces an organic peroxide. The absorbance decreases at 340 nm (A340) when NADPH oxidizes to NADP+, which is a spectrophotometric means for measuring the activity of the GPx enzyme. Brie y, 10 µL of serum was added to the work solution that was included in the kit.
Determination of CAT activity CAT activity was determined according to the method described by Sinha (Sinha, 1972)

PC assay
The measurement of PCs following their covalent reaction with 2,4-dinitrophenylhydrazine (DNPH) was pioneered by Levine et al. (1990). Since PCs react with DNPH, this method is a suitable approach for their identi cation. This procedure involves treating proteins that are oxidatively modi ed (40.5 mg of protein) with 10 mM DNPH for 1 h. Brie y, 400 µL of DNPH was added to 100 µL of the serum sample. Then proteins were precipitated by adding 20% TCA to the solution. After that, precipitates were washed three times with ethanol-ethyl acetate (1:1), and the nal precipitate was dissolved in 6 M guanidine. Finally, the absorbance of the 2,4-dinitrophenyl (DNP) hydrazones was measured at 370 nm.
The biological activity of nitrite and nitrate The Griess method was used to measure the level of NO in serum. Since deproteinization is a crucial step in this measurement process, serum deproteinizing was initially performed using ZnSO 4 in the presence of 0.3 M NaOH. Then vanadium (III) chloride (VaCl 3 ) (which converts nitrate into nitrite) and the Griess reagent (2% sulphanilamide in 5% phosphoric acid and 0.1% N-(1-naphthyl) ethylenediamine dihydrochloride (NEDD) in deionized water) were mixed with the deproteinated serum, and the mixture was incubated at 37°C for 30 min. Finally, optical density (OD) measurement was performed at 540 nm (Yucel et al., 2012).
A gas chromatographic (GC) analyzer (Agilent 7890A, USA), which was coupled to a ame ionization detector (FID), was used to measure and detect the residues of serum OCPs in all the participants. The extraction of samples was repeated twice with 2 mL of hexane. Then, 200 µL of concentrated sulphuric acid was added to combined extracts in order to separate the organic part. Next, 100 mg of anhydrous sodium sulfate was used to dehydrate this organic part, and centrifugation was performed at 3000 g. After that, the transferred organic layer was completely concentrated at room temperature. Eventually, 100 µL of ethyl acetate was added to each sample in order to dissolve the extracted OCPs. GC-FID and capillary columns (HP-5) are reported as analytical methods for the identi cation of OCPs. The retention time (used for qualitative analysis), peak area (used for quantitative analysis), and the internal standard method were utilized to calculate the serum levels of OCPs. Therefore, a set of OCP standard solutions with certain concentrations (0.78, 1.56, 3.12, 6.25, 12.5, 25, 50, 100, 200, and 400 µg/mL) was prepared and then equal levels of DBP (100 µg/mL) were added to each OCP standard solution. Afterward, the peak areas of OCP standards and DBP were calculated, and calibration curves were obtained for each OCP compound, displaying the ratio of the peak area of the OCP standard to that of the internal standard versus the concentration. The peak areas of the OCPs and the internal standard for unknown samples were calculated and the ratio of the peak area was reported. In the nal step, the OCP standard curves were used to determine OCP concentrations. The analytical limit of detection (LOD) was estimated to be 0.9 ng/mL for α-HCH, 0.56 ng/mL for β-HCH, 0.31 ng/mL for γ-HCH, 0.59 ng/mL for 2,4 DDE, 0.68 ng/mL for 4,4 DDE, 0.29 ng/mL for 2,4 DDT, and 0.58 ng/mL for 4,4 DDT. QA/QC was maintained to ensure the accurate quanti cation of OCPs. All the samples were analyzed in triplicate, as well as eld blanks and equipment blanks. All the reported analytical results are the average of three values so that method performance can be evaluated. In this regard, a set of pesticide standard solutions with known concentrations (0.05, 0.1, 0.5, 0.75, 1, 2, 4, 8, 16, 25, 50, 100 µg/L) were spiked in the pooled sample, and the calibration curves were obtained. Procedure blanks were prepared using ethyl acetate and routinely analyzed to check for inlet, column, and detector contamination during extraction and injection processes, examine the cross-contamination, and monitor the background contamination of the instrument.

Statistical analysis
Mean ± standard error of the mean (SEM) are used to represent all continuous variable data and numbers (percentages) are used to represent categorical variables. The Kolmogorov-Smirnov test was used to assess data distribution. One-way ANOVA or Kruskal-Wallis with post-hoc Tukey and Mann-Whitney U tests, as well as the chi-square test, were used to analyze the differences between the groups. Pearson and Spearman's rho correlation coe cients were employed to manifest the correlations between continuous variables. In the present study, linear regression was carried out to determine the effects of OCPs (as independent variables) on OS development (as a dependent variable). The associations between continuous OCP concentrations and OS parameters in all plasma samples were explored using multivariable linear regression models. The associations between lung cancer development and OCPs were evaluated by the continuous logistic regression model based on adjustments for body mass index (BMI) and total lipids. The present study assessed exposure as a categorical variable, by classifying each OCP as quartiles of exposure in the study population. For each OCP, we determined the odds ratios (OR) for lung cancer, comparing each quartile with quartile 1. SPSS software version 22.0 for Windows (SPSS Inc., Chicago, IL) was applied for the statistical analyses. Pvalues < 0.05 were considered statistically signi cant. All measurements for the studied pesticides were detected above the LOD. The measurement of LOD was based on the standard deviation of the regression line and the slope of the calibration curve. Moreover, we used both wet-weight concentrations adjusted for serum cholesterol and TG and lipid-standardized concentrations by dividing wet-weight concentrations by total lipids. Total lipids were calculated using the following formula: Total lipids (mg/dL) = 2.27 × total cholesterol + TG + 62.3 (Phillips et al., 1989). In addition to the individual OCPs, we calculated the molar sums (mmol/L) of DDT and its metabolites (2,4 DDT and 4,4 DDT), PHCHs (α-HCH, β-HCH, γ-HCH), and DDE (2,4 DDE and 4,4 DDE) using a previously reported method (Kobrosly et al., 2014).

Demographic variables and clinical characteristics
The current case-control study was performed at Afzalipoor Hospital, Kerman, Iran, from February 2018 to September 2019. The study included 51 patients with pathologically con rmed lung cancer and 51 healthy individuals as the case and control groups, respectively. Notably, the two groups were matched in terms of age and gender. The mean age of the participants was 65.50 ± 15.01 years for the lung cancer group and 63.15 ± 9.60 years for the control group, which did not differ signi cantly. In the lung cancer group, there were 38 male subjects (74.5%) and 13 female subjects (25.5%). There were 39 male subjects (76.5%) and 12 female subjects (23.5%) in the control group. Sociodemographic variables and clinical features of the study participants are shown in Table 1.
About 49% of the participants were current smokers; 51.02% (25 out of 51) of the lung cancer patients and 48.98% (24 out of 51) of the control patients were currently smoking. A total of 58 individuals were active in the agricultural sector (farming), including 35 (60.34%) subjects with lung cancer and 23 (39.66%) subjects in the control group. As shown in Table 1, BMI (P = 0.001), education (P = 0.04), farming (P = 0.016), living region (P = 0.028), TG levels (P = 0.022), and cholesterol levels (P = 0.012) in patients with lung cancer indicated signi cant differences compared to the control group. Other sociodemographic variables and clinical characteristics, such as smoking, HDL-C, LDL-C, and total protein, did not show any signi cant differences between patients with lung cancer and the control group. In addition, clinical and sociodemographic parameters were separately compared between men and women in the two groups (Table 1). Data are expressed as numbers of individuals or means ± SEM and comparisons were made by the Chi-square test or Student's-sample t-test, respectively. TG: Triglyceride; HDL: High-density lipoprotein; LDL: Low-density lipoprotein; BMI increased signi cantly in the patients compared to the control group. The participants with higher educational level also were observed in the control group. In addition, farming experience and TG and cholesterol levels were signi cantly higher in the patient group rather than the control group. The HDL level was signi cantly lower in healthy female compared to female with lung cancer.

Oxidant and antioxidant parameters
To evaluate oxidant and antioxidant conditions, MDA, TAC, NO, and CP levels as well as the activity of SOD, GPx, AChE, PON-1, and CAT were assessed in patients with lung cancer and the healthy control group. As shown in Figure 1, the mean SOD activity level was not signi cantly different between the two groups (P = 0.23). However, according to this gure, AChE, PON-1, CAT, and GPx activity levels in patients with lung cancer were signi cantly lower than those in the control subjects (P < 0.001, P < 0.001, P = 0.001, and P < 0.005, respectively). Similarly, the results showed a signi cant decrease in TAC values in patients with lung cancer compared to healthy control subjects (P < 0.001). Moreover, Figure 1 shows the comparison of oxidant and antioxidant parameters between men and women in the two groups separately. As observed, the mean GPx activity level was not signi cantly different between the female participants of the two groups (P = 0.28). In addition, Figure 1 indicates that the mean PC, MDA, and NO concentrations were statistically higher in lung cancer patients compared to the healthy controls (P < 0.001 for the three comparisons).

OCPs
Gas chromatography was used to measure the level of seven OCP derivatives including 2,4 DDE, 2,4 DDT, 4,4 DDT, 4,4 DDE, α-HCH, β-HCH, and γ-HCH in patients with lung cancer and healthy controls. As shown in Table 2, the mean levels of all OCPs were signi cantly higher in patients with lung cancer in comparison with healthy control subjects (P < 0.001 for all comparisons). Table 2 also compares the summation of HCH, DDE, and DDT subtypes as well as the summation of all OCP concentrations between men, women, and all the subjects of both groups separately. Data are expressed as means ± SEM and comparisons were made by using the one-way ANOVA. There were signi cantly higher levels of α-, β-and γ-HCH, The scatter dot plot was employed to more clearly depict the distribution of OCPs in patients with lung cancer and healthy control subjects ( Figure 2). It is apparent from this plot that the distribution of all the OCPs in patients with lung cancer was signi cantly higher than the healthy controls.

Correlation analysis
Spearman correlation was applied to evaluate the association of the sociodemographic variables and oxidant and antioxidant parameters with OCP levels in patients with lung cancer (Table 3 and Table 4).      and AChE activity (P = 0.011). The results also indicated that NO and PC levels had a positive correlation with 2,4 DDT (P = 043) and 4,4 DDT (P = 0.003), respectively. However, MDA, TAC, PON-1, SOD, GPx, and CAT activity levels did not show any correlation with the measured OCP levels (P > 0.05).
SOD3 activity had no signi cant association with OCPs.
Logistic regression analysis revealed that higher levels of OCPs were linked to an increased risk of lung cancer (Table 5). Moreover, analyses were adjusted for potential confounding factors, which included BMI, TG, and cholesterol. Lung cancer was associated with α-HCH (multivariable-adjusted OR = 3.19, 95% CI:  The most remarkable nding of the present work was that the mean serum levels of the seven studied OCPs in patients with lung cancer were signi cantly higher than in the healthy subjects (Table 2 (Table 1). Therefore, logistic regression analysis was performed by adjusting for BMI, TG, and cholesterol. These factors increased the risk of lung cancer, according to the ndings.
To evaluate OPP exposure levels, determining the AChE activity is the standard method (Majidi et al., 2018;Moon et al., 2015). In the present study, a signi cant decrease in AChE activity was observed in patients with lung cancer compared to the healthy subjects ( Figure 1). Consistent with our results, several studies showed that AChE activity was reduced in lung cancer patients (Xi et al., 2015). The participation of AChE in the apoptosis process, as an unconventional function of this enzyme, has been con rmed in previous studies (Jiang & Zhang, 2008). In this context, it has been reported that the downregulation of AChE by small interfering ribonucleic acids (siRNAs) could inhibit the apoptosis process (Park et al., 2004). Thus, the decrease of AChE activity may lead to tumor development by inhibiting the apoptosis process (Shehadeh Mashour et al., 2012).
However, the results showed signi cant differences in oxidant and antioxidant criteria between the two groups, except for SOD activity. MDA, NO, and PC levels were signi cantly higher in patients with lung cancer compared to healthy subjects while PON-1, GPx, and CAT activity levels and TAC levels were signi cantly lower in lung cancer patients compared to healthy controls.
There were no signi cant differences in total protein concentrations between patients with lung cancer and healthy individuals (Table 1). Our data showed a signi cant increase in PC levels in patients with lung cancer compared with healthy subjects (Figure 1). PC is an important sign of protein oxidative damages. Although the current study is based on a small sample of participants, the ndings suggest that serum levels of the studied pesticides and the redox condition have a major role in promoting lung cancer. However, future research needs to more closely examine the links between serum levels of pesticides and redox condition and lung cancer development.

Conclusion
The most important nding of the present study was that the mean serum levels of the seven studied OCPs, which are illegal, were signi cantly higher in patients with lung cancer than in the healthy subjects. On the other hand, AChE and PON-1 activity, which are important indices for OPP exposure, were signi cantly lower in lung cancer patients compared with healthy individuals. Furthermore, antioxidant parameters such as GPx, CAT, and TAC were lower and MDA, as the nal product of lipid peroxidation, was higher in cancer patients when compared with the healthy group. Therefore, based on the obtained results, it may be concluded that exposure to OCPs and OPPs led to the development of advanced oxidation processes and redox imbalance, resulting in lung cancer development.

Declarations
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