Abstract
Background/Aim: The tissue inhibitor of metalloproteinase-2 (TIMP-2) is a critical inhibitor of matrix metalloproteinases (MMPs). Along with MMPs, TIMP-2 regulates the breakdown and remodeling of the extracellular matrix (ECM) and basement membranes. This study investigated the role of genotypes of the TIMP-2 -418G/C (rs8179090) single nucleotide polymorphism on lung risk. Materials and Methods: A total of 358 lung cancer patients and 716 healthy subjects were recruited in this study. Genotypes were identified via the polymerase chain reaction-restriction fragment length polymorphism methodology. Results: The distribution of alleles and genotype frequencies of TIMP-2 -418G/C genotypes between the two groups were compared and no statistically significant difference (p>0.05) was found. The heterozygous and homozygous variant genotypes showed no differential distribution between the control and case groups (p>0.05). Conclusion: TIMP-2 -418G/C variants might not be associated with lung cancer susceptibility and could not serve as predictors.
Lung cancer is the leading cause of cancer-related mortality worldwide for both genders (1). There are approximately 2.1 million newly diagnosed patients with lung cancer and approximately 1.8 million annual deaths. (2). Among the different histopathologic types, non-small cell lung cancer (NSCLC) is the main type of lung cancer, accounting for approximately 80% of all cases, including adenocarcinoma, squamous cell carcinoma, and large-cell carcinoma (3, 4). Despite the rapid developments in therapeutic drugs and hospital care, there are no obvious clinical manifestations in the early stage of NSCLC, and frequently metastases are identified in most NSCLC patients at the time of diagnosis. As a result, currently, NSCLC cases have a relatively poor prognosis, and the 5-year survival rates are only approximately 20% (5). According to information listed above, it is of critical importance to identify practical biomarkers for effective early diagnosis of NSCLC.
There is evidence that genetics play a role in lung cancer development (6), and statistical data showed that heritability contributes to lung cancer genetic risk by approximately 8% (7). Smoking has been reported to induce gene mutations, which may contribute to an extremely heavy mutation load and lung cancer development (8, 9). Therefore, smoking together with the unrevealed genetic factors can all contribute to lung cancer risk.
Tissue inhibitor of metalloproteinase-2 (TIMP-2), a 21-KD endogenous protein, is a major inhibitor of matrix metalloproteinase-2 (MMP-2) (10), a critical enzyme in the regulation of the proliferative and metastatic behaviors of tumor cells (11). In literature, MMP-2 is frequently reported to be over-expressed in tumor tissues (12, 13), and its regulation and signaling may determine a poor prognosis (14-16). TIMP-2 forms a complex with MMP-2 more effectively than TIMP-1 and regulates its proteolytic activity. In 2000, Ara et al. demonstrated that TIMP-2 mutations can influence its binding with MMP-2, leading to carcinogenesis (17). Epidemiological studies on TIMP-2 are limited and inconclusive. In 2014, Yaykaşli et al. reported that TIMP-2 genotypes are associated with prostate cancer risk (18). In 2015, Zhang et al. showed that TIMP-2 genotypes can contribute to gastric cancer development (19). In 2020, TIMP-2 genotypes were found to significantly associate with an increased risk of colorectal cancer (20). On the contrary, Wang et al. have provided evidence showing that TIMP-2 gene polymorphisms are not associated with an increased risk of breast cancer (21). However, surprisingly, there is no literature on the effect of TIMP-2 genotypes on lung cancer. This point may be explained that TIMP-2 is so essential and its substrates are so complicated that the expression level could not be dramatically altered (22). Only slight regulation, such as polymorphism(s) could be happened, while the key point(s) is not found yet. In this study, we examined the genotypes of TIMP-2 rs8179090 polymorphism and evaluated their contribution to the risk of lung cancer in Taiwan.
Materials and Methods
Patient population. This study was approved by the ethics committee of China Medical University Hospital (DMR100-IRB-284). Written informed consent was obtained from all study subjects. We enrolled 358 lung cancer patients and 712 healthy non-cancer controls. Only Chinese patients diagnosed via pathological diagnosis were included. Cases with any other type of cancer, possible tumors, severe infectious disease, and immune disease were excluded. The control group was recruited from the physical examination center of the hospital during the same period. Demographics of the cohort and controls have also been used in our previous study (23) and are summarized in Table I.
Genotyping methodology of the TIMP-2 rs8179090 polymorphism. Peripheral blood was collected from each participant and genomic DNA was extracted within 24 h by using the Genome DNA Extraction Kit (Qiagen, Valencia, CA, USA) according to the manufacturer’s instructions (23-25). The single nucleotide polymorphism (SNP) TIMP-2 rs8179090 was genotyped by using the polymerase chain reaction restriction fragment length polymorphism (PCR-RFLP) methodology as previously described (26, 27). The primer sequences of TIMP-2 rs8179090 were designed by Terry Fox Cancer Research Lab and the forward and reverse primer pair was: TTCTAAGGCCTCCATTTGAA and GTTCTTCCAGGACACCAGGC, respectively. The PCR reaction was performed in a total volume of 25 μl and the PCR conditions were as follows: pre-denaturation at 94°C for 2 min; followed by 35 cycles denaturation at 94°C for 20 s, annealing at 57°C for 20 s, extension at 72°C for 20 s; and finally, extension at 72°C for 20 min. The PCR products were examined by 3% agarose gel electrophoresis. The PCR products were digested by Mnl I; the digestible G allele produced two fragments of 117 and 119 bps, whereas the undigested T allele was of 236 bp. Random samples of the PCR products were chosen for direct sequencing to verify the accuracy and reliability of the genotyping results.
Statistical methodology. The Student’s t-test was adopted for the comparisons of the distributions of ages between the case and control groups. The Pearson’s Chi-square methodology was used to examine the distribution pattern of TIMP-2 genotypes and the interaction between TIMP-2 genotypes and smoking status. The contribution of TIMP-2 genotypes to lung cancer risk was also estimated by the odds ratios (ORs) and the 95% confidence intervals (CIs). p-Values less than 0.05 were considered to indicate statistically significant differences.
Results
The distributions of age, gender, and smoking status in the selected 358 lung cancer cases and 716 healthy controls are presented in Table I. Additionally, the histology of the lung cancer cases is also shown in Table I. During selection of healthy controls, we applied matching strategies for age, gender, and smoking status, and the results showed that there was no difference in the distributions of age, gender, and smoking behavior between the cases and controls (p-Values all >0.05) (Table I). We have to emphasize that since we matched the frequency of smoking behaviors in addition to age and gender, the percentage of smokers in the control became as high as 78.6% and this percentage is not representative of the Taiwanese population. Also, this matching strategy could not show whether smoking is a lung cancer risk factor. Regarding the histopathologic subtypes, 60.9% (218 cases) were adenocarcinoma, 29.6% (106 cases) were squamous cell carcinoma, and 9.5% (34 cases) were other types.
The genotypic distributions of TIMP-2 rs8179090 among the 716 controls and the 358 patients with lung cancer are presented and analyzed in Table II and Table III, respectively. The p-Value for Hardy-Weinberg equilibrium analysis was 0.9917 for the control group. The results showed that the genotypes of TIMP-2 rs8179090 were not distributed differently between the lung cancer and healthy control groups (p for trend=0.5167) (Table II). In detail, the TIMP-2 rs8179090 heterozygous CG and homozygous CC genotypes were negatively associated with an altered lung cancer risk, compared with the wild-type homozygous GG genotype (OR=1.02 and 1.60, 95%CI=0.75-1.37 and 0.71-3.56, p=0.9204 and 0.2505, respectively; Table II). In the recessive model, a 1.60-fold non-significant increase in lung cancer risk was observed for the CC genotype carriers at TIMP-2 rs8179090 compared with those carrying the GG+CG genotypes (OR=1.60, 95%CI=0.71-3.54, p=0.2523). In the dominant model, there was a non-significant 1.06-fold increase in lung cancer risk for the CG+CC genotype carriers at TIMP-2 rs8179090, compared with GG carriers (OR=1.06, 95%CI=0.80-1.41, p=0.6952).
To validate the results in Table II, an allelic frequency distribution analysis for the TIMP-2 rs8179090 was performed and the results are shown in Table III. The variant C allele was 15.1% in the lung cancer group and 14.0% in the control group (OR=1.09, 95%CI=0.85-1.41). There was no significant difference in the allelic frequencies of TIMP-2 rs8179090 between the two groups (p=0.4861, Table III).
As mentioned above, smoking behavior is a well-known risk factor of lung cancer worldwide. Therefore, we were interested in examining the interactions between TIMP-2 rs8179090 genotypes and smoking habit. The data showed that among the non-smokers, those with TIMP-2 rs8179090 CG and CC genotypes were at 1.33- and 1.93-fold odds of having lung cancer (95%CI=0.67-2.62 and 0.42-8.98, p=0.4120 and 0.3927, respectively). Among smokers, those with TIMP-2 rs8179090 CG and CC genotypes were at 0.95- and 1.53-fold odds of having lung cancer (95%CI=0.68-1.33 and 0.60-3.94, p=0.7690 and 0.3716). However, the differences did not reach statistical significance. After adjusting for age, gender, and alcohol drinking status, there were still no statistically significant differences between the two variant genotypes at TIMP-2 rs8179090, among non-smokers and smokers (Table IV).
Discussion
The regulation of the components of the extracellular matrix is very complex. For instance, there are tens of types of MMPs that metabolize various substrates, such as collagenases, gelatinases, matrilysins, stromelysins, and others (28-31). MMPs are also thought to play a critical role in cellular activities such as proliferation, differentiation, angiogenesis, apoptosis and metastatic behaviors (32, 33). TIMP-2 acts as an inhibitor of several MMPs. Typically, TIMPs inhibit MMPs, but different TIMPs inhibit different MMPs more effectively than others. For instance, TIMP-1 inhibits MMP-1, MMP-3, MMP-7, MMP-9, and TIMP-1 inhibits MMP-3 better than TIMP-2, while TIMP-2 inhibits MMP-2 more effectively than TIMP-1, TIMP-3 and TIMP-4 (34). Since TIMP-2 plays a major role in the metabolism of MMPs, subtle genetic variants of TIMP-2 may cause an imbalance between extracellular matrix contents, promoting carcinogenesis. Therefore, variations in TIMP-2 genotypes, such as those of TIMP-2 rs8179090 polymorphism, may be associated with lung cancer risk.
To our surprise, there were no published articles on the role of TIMP-2 genotypes in lung cancer risk. Therefore, we first examined the contribution of TIMP-2 rs8179090 genotypes to lung cancer risk. The results showed that the genotypes GG, GC, and CC at TIMP-2 rs8179090 among healthy Taiwanese were 74%, 24%, and 2%, respectively (Table II). In the lung cancer group, TIMP-2 rs8179090 CC seemed to have a higher frequency (3.1%) but was not statistically significant (Table II). Allelic frequency analysis indicated that the variant C allele may not contribute to lung cancer risk (Table III). Cigarette smoking is the major environmental contributor to lung cancer risk (35, 36), however, its interaction with specific genotypes is seldomly examined, not to mention TIMP-2 rs8179090. The present study is the first to reveal the interaction between TIMP-2 rs8179090 genotypes and smoking in lung cancer risk.
This study opened new directions of research. First, it would be interesting to examine whether TIMP-2 rs8179090 genotypes are correlated with metastatic status, which should be affected by the composition of the extracellular matrix. We examined the possibility for TIMP-2 rs8179090 genotypes to predict tumor size, stage, and metastasis, but no significant association was found (data not shown). One explanation for the lack of significance is that the sample size of CC genotypes of TIMP-2 rs8179090 was extremely small. Second, it is also important to examine the differential expression of TIMP-2 mRNA and protein among the controls and cases according to various TIMP-2 rs8179090 genotypes. Third, the size of the sample should be increased to further validate our current findings, such as those indicating a possible association of TIMP-2 rs8179090 genotypes with smoking. Forth, it is also critical to investigate the effect of other polymorphic sites on protein function. For instance, rs4789936 and rs2003241 are intronic polymorphic sites of TIMP-2, which have never been investigated with regard to their contributions to lung cancer either. We cannot exclude the possibility that SNP(s) other than rs8179090, can serve as predictive marker(s) for lung cancer. Last, the role of TIMP-2 rs8179090 genotypes in cancer risk determination is inconclusive, and additional studies are required to validate the current findings. For instance, in colorectal cancer (20), the C allele in TIMP-2 rs8179090 is associated with decreased cancer risk, while in gastric cancer, the C allele is associated with increased cancer risk (19).
In conclusion, this study provides evidence that the C allele at TIMP-2 rs8179090 cannot serve as a predictor of lung cancer. In addition, no obvious interaction between smoking status and TIMP-2 rs8179090 genotype regarding personal susceptibility to lung cancer was observed.
Acknowledgements
The Authors are grateful to Tai-Lin Huang and Yu-Ting Chin for performing the PCR-RFLP assays. This study was supported by the grant from China Medical University Hospital and Asia University (ASIA-109-CMUH-14).
Footnotes
Authors’ Contributions
Research Design: Liao WC, Huang CW and Hsia TC; Patient and Questionnaire: Liao WC, Hsia TC and Shen YC; Experiment Data analysis: Chang WS and Wang YC; Statistical Analysis: Tsai CW and Yin MC; Manuscript Writing: Tsai CW and Bau DT; Reviewing and Revising: Bau DT.
Conflicts of Interest
All the Authors declare no conflicts of interest regarding this study.
- Received August 25, 2021.
- Revision received October 5, 2021.
- Accepted October 6, 2021.
- Copyright © 2021 International Institute of Anticancer Research (Dr. George J. Delinasios), All rights reserved.