Int J Med Sci 2019; 16(6):774-782. doi:10.7150/ijms.33195 This issue Cite
Research Paper
1. School of Medicine, Chung Shan Medical University, Taichung, Taiwan
2. Department of Obstetrics and Gynecology, Chung Shan Medical University Hospital, Taichung, Taiwan
3. Institute of Medicine, Chung Shan Medical University, Taichung, Taiwan
4. Radiation Oncology Department, Chung Shan Medical University Hospital, Taichung, Taiwan
5. Department of Obstetrics and Gynecology, Chiayi Chang Gung Memorial Hospital, Chiayi, Taiwan
6. Department of Nursing, Chang Gung University of Science and Technology, Chiayi Campus, Chiayi, Taiwan
7. Department of Medical Research, Chung Shan Medical University Hospital, Taichung, Taiwan
8. Department of Obstetrics and Gynecology, Changhua Christian Hospital, Changhua, Taiwan
The purposes of this study were to examine whether there were associations among matrix metalloproteinase-11 (MMP-11) gene polymorphisms, development and clinicopathological characteristics of uterine cervical cancer as well as patient survival or not. Five single-nucleotide polymorphisms (SNPs) of the MMP-11 gene rs738791, rs738792, rs2267029, rs28382575, and rs131451 from one hundred and thirty patients with invasive cancer, 99 patients with high-grade cervical intraepithelial neoplasia (CIN) of uterine and 335 normal controls were analyzed using real-time polymerase chain reaction. Our results revealed that genotypic frequencies of CT/TT in MMP-11 SNP rs738791, with CC as a reference, tended to exhibit significantly different distributions (p=0.044, AOR: 0.63, 95% CI: 0.41-0.99) between patients with cervical invasive cancer and normal control women when controlling age. After multiple significance adjustment, the tendency becomes insignificant (Holm's adjusted p 0.176). Although CT/TT genotype of MMP-11 gene rs738791 tended to increase the risk of developing stage II disease at least (p=0.035; OR: 2.16, 95% CI: 1.05-4.44) and deep stromal invasion more than 10 mm (p=0.043; OR: 2.08, 95% CI: 1.02-4.26) with CC as a reference in patients with uterine cervical cancer. They became insignificant after multiple significance adjustment and the Holm's adjusted p values would become as 0.245 and 0.258, respectively. However, lymph node metastasis exhibited significant worse recurrence-free survival (p=0.033; HR: 2.83, 95% CI: 1.09-7.35), and overall survival (p=0.001; HR: 4.80, 95% CI: 1.82-12.62) compared to those without pelvic lymph node metastasis. In conclusion, it indicates no impact of the MMP-11 SNPs on uterine cervical cancer in Taiwanese women.
Keywords: matrix metalloproteinase-11, gene polymorphisms, uterine cervical cancer, single nucleotide polymorphism
Uterine cervical cancer is one of the leading causes of cancer mortality and presents the fourth most frequent malignancy in women worldwide [1]. It is also a serious health problem in Taiwan. The 2013 annual cancer registry report revealed that uterine cervical cancer was the third leading cancer in Taiwanese women. High preoperative primary tumor size and metastatic pelvic lymph node are vital prognoses of adverse events or death [2]. Uterine cervical cancer is usually developed by a pre-invasive phase cervical intraepithelial neoplasia (CIN) [3]. CIN can be categorized into three grades, including CIN1 (mild dysplasia; low-grade CIN), CIN2 (moderate dysplasia) and CIN3 (severe dysplasia); furthermore, CIN 2 and CIN 3 have been regarded as high-grade CIN. Carcinogenesis of uterine cervix is considered as a continuum of neoplastic transition from dysplasia to invasive cancer. Most low-grade CIN lesions regress; however, high-grade CIN lesions significantly progress to invasive cancer [3].
Matrix metalloproteinases (MMPs) play an important role for biological behaviors of solid malignant tumors. MMPs comprise a family of endopeptidases, with the capacity of degrading the extracellular matrix (ECM) proteins and remodeling the ECM, which play essential roles for the progression of invasion and metastasis of malignant solid tumors [4]. MMP-11, also named stromelysin-3, was first identified in breast carcinoma [5]. The expression of MMP-11 is associated with embryonic development and tissue remodeling processes in normal physiologic conditions [6]; MMP-11 degrades the ECM and promotes the tumorigenesis and progress of cancer [4]. Increased expression of MMP-11 has been identified in many types of cancer, such as nonsmall cell lung cancer [7], gastric carcinoma [8], oral cancer [9], de novo colorectal cancer [10], esophageal adenocarcinoma [11] and pancreatic carcinoma [12]. Furthermore, overexpression of MMP-11 in cervical cancer [13] and a relative increased expression of MMP-11 from LSIL and HSIL samples [14] have been demonstrated.
Single nucleotide polymorphism (SNP) is a form of DNA variation among individuals [15]. In the shared sequence of a gene, a single nucleotide develops that achieves a frequency of more than 5 % of the population for a species is referred as a SNP [15]. Genetic polymorphisms of MMP-11 have been reported in several different types of cancer including oral squamous cell carcinoma [16], hepatocellular carcinoma [17], and breast cancer [18]. However, the impact of MMP-11 gene polymorphisms on the risk and prognosis of cervical cancer remains poorly investigated. Therefore, we conducted a case-control study to examine whether there were associations among MMP-11 gene polymorphisms, development and clinicopathological characteristics of uterine cervical cancer as well as patient survival or not.
The retrospective study was conducted by enrolling individuals consecutively. One hundred and thirty patients with invasive cancer, 99 patients with high-grade CIN of uterine cervix, and 335 normal controls were enrolled at the Department of Obstetrics and Gynecology in Chung Shan Medical University Hospital in Taichung, Taiwan from February 1994 to October 2014. One hundred and seven cervical cancer patients had squamous cell carcinoma (SCC) and 21 adenocarcinoma; 2 were unknown. Seventy five cervical cancer patients were staged I, 34 staged II, 11 staged III and 7 staged IV according to the 2009 International Federation of Gynecology and Obstetrics system. Three patients could not be staged. They received standard treatment protocols in this hospital modified from National Comprehensive Cancer Network guidelines. They underwent radical abdominal hysterectomy and pelvic lymph node dissection or plus para-aortic lymph node sampling and/or concurrent chemoradiotherapy or chemotherapy. Patients with high-grade CIN were known as precancerous lesions and underwent abdominal or vaginal total hysterectomy, large loop excision of transformation zone or simple trachelectomy. Their prognosis was well. None of them had recurrence or developed invasive cancer in the follow-up. The diagnoses of all patients with cervical invasive cancer or precancerous lesions were further verified according to the pathologic report of colposcopy-directed punch biopsy of cervix before the treatment began. Normal controls received Papanicolaou smears at outpatient department for general examination and the normal cytologic diagnosis was further verified with normal colposcopic findings in Chung Shan Medical University Hospital. All studied subjects were Taiwanese women who resided in central Taiwan. This study was approved by the institutional review board of Chung Shan Medical University Hospital (CSMUH No: CS14014).
A total of 5 SNPs in MMP-11 were selected from the International HapMap Project data for this study. The synonymous SNPs rs28382575 (Pro475Pro) and nonsynonymous SNPs rs738792 (Ala38Val) in the coding sequences of the gene were included. We examined rs2267029 with minor allelic frequencies of >5% in order to obtain adequate power to evaluate the potential association. The rs738791 and rs131451 were selected in this study as the previous cancer research [17].
Total genomic DNA was isolated from whole blood specimens using QIAamp DNA blood mini kits (Qiagen, Valencia, CA), in accord with the manufacturer's instructions. The MMP-11 SNPs were determined by using the TaqMan SNP genotyping assay (Applied Biosystems, Warrington, UK), according to the manufacturer's protocols [19].
Analysis of variance (ANOVA) was used to compare the age difference among patients with invasive cancer and those with precancerous lesions of uterine cervix, and control women. Tukey HSD test was used for post hoc analysis. Chi-square or Fisher's exact tests were used to associate genotypic distributions of MMP-11 gene single SNPs with the incidence of cervical neoplasias. The adjusted odds ratios (AORs) with their 95% confidence intervals (CIs) were applied to check the associations among genotypic distributions of MMP-11 SNPs and the incidence of cervical neoplasias (including precancerous lesions and invasive cancer) using the logistic and multinomial logistic regression models after controlling for age. Chi-square or Fisher's exact tests were applied to associate MMP-11 SNP and clinicopathological parameters factors with recurrence or death events. Holm's test was applied for multiple significance adjustment (multiple comparisons) and Holm's adjust p values could be calculated in the associations of MMP-11 SNPs with the development of cervical cancer or with clinicopathological variables. Kaplan-Meier curve model (univariate analysis over time) was used to identify factors significantly associated with recurrence-free survival rate and overall survival rate between initial standard treatment and the subsequent appearance of recurrence, death or closing date of the study (December 4, 2018). Cox proportional hazard model (multivariate analysis over time) was used to relate MMP-11 SNP with recurrence-free survival and overall survival of patients with cervical cancer, with adjusting for various clinicopathological parameters, relative to recurrence and survival time or until closing date of the study (December 4, 2018). The SPSS, version 18.0 and WinPepi Software, version 10.0 were used for statistical analysis. P <0.05 was considered as statistically significant difference.
There was significant difference in age distribution between patients with cervical neoplasia and normal control women (50.5 ± 13.7 vs. 43.9 ± 10.4, p<0.001). Based on ANOVA with Tukey HSD test for post hoc analysis, the age distribution was significantly different between patients with cervical invasive cancer and those with precancerous lesion (55.3 ± 12.3 vs. 44.1 ± 12.9, p<0.001), and between those with cervical cancer and control women (55.3 ± 12.3 vs. 43.9 ± 10.4, p<0.001) but not significantly different between those with precancerous lesions and control women (44.1 ± 12.9 vs. 43.9 ± 10.4, p= 0.992).
A total of 564 individuals participated in this study. Of these, 130 patients with invasive cancer, 99 patients with high-grade CIN of uterine, and 335 normal controls were included. Genetic polymorphism distributions of MMP-11 gene in Taiwanese women with neoplasias of the uterine cervix and normal controls were shown in Table 1. There were no significantly different genotypic distributions of MMP-11 SNPs rs738791, rs2267029, rs28382575 and rs131451 between patients with cervical neoplasias and normal control women. With TT/TC as a reference, genotypic frequencies of TT/TC and CC of MMP-11 SNP rs738792 were significantly different distributions between patients with cervical neoplasias and normal control women; however, there was no significant difference after controlling age.
After dividing the cervical neoplasias to precancerous lesions and invasive cancer, genotypic distributions of MMP-11 gene in Taiwanese women with uterine cervical invasive cancer, precancerous lesions and normal controls were shown in Table 2. There were no significantly different distributions of MMP-11 SNPs rs738791, rs738792, rs2267029, rs28382575 and rs131451 among patients with cervical invasive cancer, precancerous lesions or normal control women. However, genotypic frequencies of CT/TT in MMP-11 SNP rs738791, with CC as a reference, tended to exhibit significantly different distributions (p=0.044, AOR: 0.63, 95%CI: 0.41-0.99) between patients with cervical invasive cancer and normal control women when controlling age. After multiple significance adjustment for the associations of rs738791 with development of cervical cancer using Holm's test, the 4 p values 0.076, 0.144, 0.044 and 0.319 were adjusted as 0.228, 0.288, 0.176 and 0.319. Previous tendency became insignificant and the Holm's adjusted p value was 0.176.
The associations of genotypic distribution of MMP-11 gene variant rs738791 with clinicopathological characteristics of the patients with invasive cancer of uterine cervix were shown in Table 3. Although genotypes CT/TT of MMP-11 SNP rs738791 tended to increase the risk of developing stage II disease at least (p=0.035; OR: 2.16, 95% CI: 1.05-4.44) and deeply progressed stromal invasion more than 10 mm (p=0.043; OR: 2.08, 95% CI: 1.02-4.26) with CC as a reference in patients with uterine cervical cancer (Table 3), they were not significantly associated with stage and stromal invasion after adjusting multiple comparisons for 7 clinicopathological variables including clinical stage, pathologic type, stromal invasion depth, tumor diameter, parametrium invasion, vagina invasion and pelvic lymph node metastasis. When applying Holm's test for multiple significance adjustment, the Holm's adjusted p values for the associations of rs738792 with stage as well as rs738792 with stromal invasion became obviously insignificant as 0.245 and 0.258, respectively (Table 3). There were also no significant differences in pathologic type, tumor diameter, parametrium invasion, vaginal invasion or pelvic lymph node metastasis of invasive cervical cancer in comparing CC and CT/TT carriers of MMP-11 gene variant rs738791.
While correlating MMP-11 and clinicopathological variables with recurrence event in patients with cervical cancer, MMP SNPs were not found to be significantly related to recurrence event (Table 5, for rs738791 CT/TT vs CC, p=0.142, other SNPs results not showed). When they were correlated with the death event, MMP-11 SNPs were also not found to be significantly associated with survival (Table 5, for rs738791 CT/TT vs CC, p=0.160, other SNPs results not showed).
Genetic polymorphism distributions of matrix metalloproteinase-11 gene in Taiwanese women with neoplasias of the uterine cervix and normal controls.
Variables | Normal controls (n=335) | Cervical neoplasiasa (n=229) | ORs (95% CIs)a | p values | AORs (95% CIs)b | Adjusted p values |
---|---|---|---|---|---|---|
rs738791 | ||||||
CCc | 148 | 112 | 1.00 | 0.536 | 1.00 | 0.530 |
CT | 144 | 91 | 0.84 (0.58-1.20) | 0.326 | 0.82 (0.56-1.19) | 0.288 |
TT | 43 | 26 | 0.80 (0.46-1.38) | 0.420 | 0.82 (0.47-1.45) | 0.495 |
CCc | 148 | 112 | 1.00 | 0.269 | 1.00 | 0.260 |
CT/TT | 187 | 117 | 0.83 (0.59-1.16) | 0.82 (0.58-1.16) | ||
CC/CTc | 292 | 203 | 1.00 | 0.598 | 1.00 | 0.711 |
TT | 43 | 26 | 0.87 (0.52-1.46) | 0.90 (0.53-1.55) | ||
rs738792 | ||||||
TTc | 180 | 125 | 1.00 | 0.077 | 1.00 | 0.175 |
TC | 137 | 81 | 0.85 (0.60-1.22) | 0.377 | 0.86 (0.59-1.24) | 0.418 |
CC | 17 | 22 | 1.86 (0.95-3.65) | 0.070 | 1.69 (0.84-3.40) | 0.142 |
TTc | 180 | 125 | 1.00 | 0.828 | 1.00 | 0.796 |
TC/CC | 154 | 103 | 0.96 (0.69-1.35) | 0.96 (0.67-1.36) | ||
TT/TCc | 317 | 206 | 1.00 | 0.037 | 1.00 | 0.092 |
CC | 17 | 22 | 1.99 (1.03-3.84) | 1.80 (0.91-3.56) | ||
rs2267029 | ||||||
GGc | 186 | 128 | 1.00 | 0.226 | 1.00 | 0.329 |
GA | 136 | 85 | 0.91 (0.64-1.29) | 0.592 | 0.93 (0.64-1.34) | 0.681 |
AA | 13 | 16 | 1.79 (0.82-3.85) | 0.137 | 1.71 (0.78-3.75) | 0.183 |
GGc | 186 | 128 | 1.00 | 0.930 | 1.00 | 0.994 |
GA/AA | 149 | 101 | 0.99 (0.70-1.38) | 1.00 (0.70-1.42) | ||
GG/GAc | 322 | 213 | 1.00 | 0.101 | 1.00 | 0.103 |
AA | 13 | 16 | 1.86 (0.88-3.95) | 1.87 (0.88-3.97) | ||
rs28382575 | ||||||
TTc | 324 | 216 | 1.00 | 0.349 | 1.00 | 0.376 |
TC | 11 | 11 | 1.50 (0.64-3.52) | 0.352 | 1.49 (0.62-3.61) | 0.376 |
CC | 0 | 0 | u.a. | u.a. | u.a. | u.a. |
TTc | 324 | 216 | 1.00 | 0.349 | 1.00 | 0.376 |
TC/CC | 11 | 11 | 1.51 (0.64-3.52) | 1.49 (0.62-3.61) | ||
TT/TCc | 335 | 227 | 1.00 | u.a. | 1.00 | u.a. |
CC | 0 | 0 | u.a. | u.a. | ||
rs131451 | ||||||
TTc | 124 | 80 | 1.00 | 0.636 | 1.00 | 0.778 |
TC | 153 | 102 | 1.03 (0.71-1.51) | 0.864 | 1.05 (0.71-1.55) | 0.815 |
CC | 57 | 46 | 1.25 (0.77-2.02) | 0.360 | 1.20 (0.73-1.97) | 0.482 |
TTc | 124 | 80 | 1.00 | 0.622 | 1.00 | 0.648 |
TC/CC | 210 | 148 | 1.09 (0.77-1.55) | 1.09 (0.76-1.57) | ||
TT/TCc | 277 | 182 | 1.00 | 0.349 | 1.00 | 0.504 |
CC | 57 | 46 | 1.23 (0.80-.89) | 1.17 (0.74-1.83) |
Statistical analysis: logistic regression model or chi-square test
aCervical neoplasias included precancerous lesions and invasive cancer of the uterine cervix.
bThe adjusted p values as well as adjusted odds ratios and their 95% confident intervals were determined by logistic regression model after controlling age.
cUsed as a reference for comparison to determine the odds ratios of other genotypes.
ORs, odds ratios; 95% CIs, 95% confidence intervals; AOR; adjusted odds ratio; u.a., unavailable.
Genotypic distributions of matrix metalloproteinase-11 gene in Taiwanese women with uterine cervical invasive cancer or precancerous lesions and normal controls.
Variables | Normal controls (n =335) | Precancerous lesions (n = 99) | Invasive cancer (n = 130) | p | AORs (95% CIs)a | Ad. p | AORs (95% CIs)b | Ad. p |
---|---|---|---|---|---|---|---|---|
rs738791 | ||||||||
CCc | 148 | 42 | 70 | 0.340 | 1.00 | 1.00 | ||
CT | 144 | 43 | 48 | 1.05 (0.65-1.70) | 0.841 | 0.65 (0.41-1.05) | 0.076 | |
TT | 43 | 14 | 12 | 1.15 (0.57-2.30) | 0.698 | 0.57 (0.26-1.22) | 0.144 | |
CCc | 148 | 42 | 70 | 0.124 | 1.00 | 0.761 | 1.00 | 0.044 |
CT/TT | 187 | 57 | 60 | 1.07 (0.68-1.69) | 0.63 (0.41-0.99) | |||
CC/CTc | 292 | 85 | 118 | 0.463 | 1.00 | 0.734 | 1.00 | 0.319 |
TT | 43 | 14 | 12 | 1.12 (0.58-2.14) | 0.69 (0.33-1.43) | |||
rs738792 | ||||||||
TTc | 180 | 60 | 65 | 0.070 | 1.00 | 1.00 | ||
TC | 137 | 28 | 53 | 0.61 (0.37-1.01) | 0.056 | 1.17 (0.73-1.86) | 0.521 | |
CC | 17 | 10 | 12 | 1.76 (0.77-4.07) | 0.183 | 1.64 (0.69-3.87) | 0.263 | |
TTc | 180 | 60 | 65 | 0.236 | 1.00 | 0.201 | 1.00 | 0.384 |
TC/CC | 154 | 38 | 65 | 0.74 (0.47-1.17) | 1.22 (0.78-1.90) | |||
TT/TCc | 317 | 88 | 118 | 0.108 | 1.00 | 0.073 | 1.00 | 0.316 |
CC | 17 | 10 | 12 | 2.12 (0.93-4.79) | 1.53 (0.66-3.54) | |||
rs2267029 | ||||||||
GGc | 186 | 59 | 69 | 0.171 | 1.00 | 1.00 | ||
GA | 136 | 31 | 54 | 0.72 (0.44-1.17) | 0.184 | 1.16 (0.73-1.84) | 0.523 | |
AA | 13 | 9 | 7 | 2.19 (0.89-5.38) | 0.089 | 1.34 (0.49-3.68) | 0.574 | |
GGc | 186 | 59 | 69 | 0.614 | 1.00 | 0.475 | 1.00 | 0.483 |
GA/AA | 149 | 40 | 61 | 0.85 (0.54-1.34) | 1.17 (0.75-1.83) | |||
GG/GAc | 322 | 90 | 123 | 0.118 | 1.00 | 0.044 | 1.00 | 0.651 |
AA | 13 | 9 | 7 | 2.48 (1.02-5.99) | 1.26 (0.47-3.39) | |||
rs28382575 | ||||||||
TTc | 324 | 96 | 120 | 0.343 | 1.00 | 1.00 | ||
TC | 11 | 3 | 8 | 0.92 (0.25-3.37) | 0.901 | 2.08 (0.75-5.78) | 0.160 | |
CC | 0 | 0 | 0 | u.a | u.a. | u.a. | ||
TTc | 324 | 96 | 120 | 0343 | 1.00 | 0.901 | 1.00 | 0.160 |
TC/CC | 11 | 3 | 8 | 0.92 (0.25-3.37) | 2.08 (.075-5.78) | |||
TT/TCc | 335 | 99 | 128 | u.a. | 1.00 | 1.00 | u.a. | |
CC | 0 | 0 | 0 | u.a. | u.a | |||
rs131451 | ||||||||
TTc | 124 | 40 | 40 | 0.416 | 1.00 | |||
TC | 153 | 38 | 64 | 0.77 (0.47-1.27) | 0.310 | 1.42 (0.86-2.35) | 0.168 | |
CC | 57 | 21 | 25 | 1.14 (0.62-2.11) | 0.672 | 1.27 (0.66-2.42) | 0.477 | |
TTc | 124 | 40 | 40 | 0.304 | 1.00 | 0.556 | 1.00 | 0.186 |
TC/CC | 210 | 59 | 89 | 0.87 (0.55-1.38) | 1.38 (0.86-2.210 | |||
TT/TCc | 277 | 78 | 104 | 0.606 | 1.00 | 0.348 | 1.00 | 0.917 |
CC | 57 | 21 | 25 | 1.31 (0.75-2.29) | 1.03 (0.58-1.83) |
aAdjusted p values and adjusted odds ratios with their 95% CIs were calculated using multinomial logistic regression models after controlling age between patients with cervical precancerous lesions and control women.
bAdjusted p values and adjusted odds ratios with their 95% CIs were calculated using multinomial logistic regression models after controlling age between patients with cervical invasive cancer and control women.
cUsed as a reference for comparison to calculate the odds ratios of other genotypes.
AORs, adjusted odds ratios; 95% CIs, 95% confidence intervals; Ad. p, adjusted p value; u.a., unavailable.
The associations of MMP-11 genetic polymorphism rs738791 and various clinicopatholgical parameters with the recurrence-free survival and overall survival of the patients with uterine cervical cancer were shown in Table 5 (univariate analysis, Kaplan-Meier curves model) and 6 (multivariate analysis, Cox proportional hazard model). Pelvic lymph node metastasis was demonstrated to be an only predictor for poorer recurrence-free survival [p=0.033, hazard ration (HR): 2.83, 95% CI: 1.09-7.35] and overall survival (p=0.001, HR: 4.80, 95% CI: 1.82-12.62) of the patients with uterine cervical cancer using Cox proportional model analysis. MMP-11 genetic polymorphism rs738791 (CT/TT vs CC) and other clinicopathological characteristics, including stage, pathologic type, stromal invasion depth, tumor diameter, parametrium invasion or vaginal invasion showed no influence on recurrence-free survival or overall survival of the patients with uterine cervical cancer.
Our study revealed that genotypes CT/TT tended to reduce the susceptibility of Taiwanese women to invasive cancer with CC as a reference in MMP-11 SNP rs738791 (p= 0.044, Table 2). Furthermore, our finding showed that, for MMP-11 gene, carriers of the genotypes CT/ TT of rs738791 tended to have a higher risk than CC carriers of developing ≥ stage II disease at least (p=0.035) and stromal invasion more than 10 mm (p=0.043) for patients with invasive cancer of uterine cervix (Table 3). However, above tendency would become insignificant after multiple significance adjustment. There were no significant differences between CC or CT/ TT carriers of MMP-11 rs739791 in recurrence-free survival or overall survival. All above p values seemed close to 0.05 in this study for MMP-11 SNP rs738791 which was associated with clinical stage and stromal deep invasion and exerted different distribution between patients with cervical invasive cancer and control women, the ORs and 95% CIs were 2.16 (1.05-4.44), 2.08 (1.02-4.26) and AOR 0.63 (0.41-0.99), respectively. They became obviously insignificant after multiple significance adjustment (p=0.245, 0.258 and 0.176, respectively). It implies that even when the number of patients could increase, the role of SNPs in this gene do not impact on clinicopathological variables and development of cervical cancer. These findings suggest that MMP-11 SNPs may show poor impacts of the SNPs in MMP-11 genes on the development of cervical cancer and clinicopathological variables and patient survival.
Associations of genotypic distribution of matrix metalloproteinase-11 gene variant rs738791 with clinicopathological characteristics of the patients with invasive cancer of uterine cervix.
MMP-11 (rs738791) | |||||
---|---|---|---|---|---|
Variablesa | CCb | CT/ TT | p value | ORs (95% CIs) | Holm's adjusted p value |
Clinical stage | 0.035 | 0.245 | |||
stage Ib | 46 | 29 | 1.00 | ||
≥ stage II | 22 | 30 | 2.16 (1.05-4.44) | ||
Pathologic type | 0.527 | 1.000 | |||
squamous cell carcinomab | 59 | 48 | 1.00 | ||
adenocarcinoma | 10 | 11 | 1.35 (0.53-3.45) | ||
Stromal invasion depth | 0.043 | 0.258 | |||
≤10 mmb | 41 | 25 | 1.00 | ||
>10 mm | 26 | 33 | 2.08 (1.02-4.26) | ||
Tumor diameter | 0.633 | 1.000 | |||
≤ 4cmb | 38 | 30 | 1.00 | ||
>4cm | 31 | 29 | 1.18 (0.59-2.38) | ||
Parametrium | 0.747 | 1.000 | |||
no invasionb | 46 | 37 | 1.00 | ||
invasion | 22 | 20 | 1.13 (0.54-2.38) | ||
Vagina | 0.169 | 0.845 | |||
no invasionb | 50 | 36 | 1.00 | ||
invasion | 19 | 23 | 1.68 (0.80-3.53) | ||
Pelviclymph node | 0.433 | 1.000 | |||
no metastasisb | 53 | 41 | 1.00 | ||
metastasis | 16 | 17 | 1.37 (0.62-3.04) |
Statistical analyses: chi-square or Fisher's exact tests and Holm's test
aSome clinicopathological data could not be obtained from the patients with cervical invasive cancer due to incomplete records of medical chart.
bAs a reference. ORs, odds ratios; 95% CIs, 95% confidence intervals.
Analysis of matrix metalloproteinase-11 gene variant rs738791 and clinicopathological variables for recurrence or survival events in cervical cancer patients
Recurrence | Survival | |||||||
---|---|---|---|---|---|---|---|---|
Variablesa | + | - | p value | ORs (95% CIs) | + | - | p value | ORs (95% CIs) |
MMP-11 | 0.142 | 0.160 | ||||||
rs738791 | ||||||||
CCb | 11 | 55 | 1.00 | 54 | 12 | 1.00 | ||
CT/TT | 16 | 42 | 1.90 (0.74-5.03) | 42 | 17 | 1.82 (0.73-4.66) | ||
Clinical stage | 0.004 | <0.001 | ||||||
stage Ib | 9 | 62 | 1.00 | 65 | 6 | 1.00 | ||
≥ stage II | 18 | 34 | 3.65 (1.36-10.18) | 29 | 23 | 8.59 (2.94-28.09) | ||
Pathologic type | 0.041 | 0.246 | ||||||
squamous cell carcinomab | 19 | 85 | 1.00 | 82 | 22 | 1.00 | ||
adenocarcinoma | 8 | 12 | 2.98 (0.91-9.19) | 13 | 7 | 2.01 (0.60-6.19) | ||
Stromal invasion depth | 0.003 | <0.001 | ||||||
≤10 mmb | 7 | 55 | 1.00 | 56 | 6 | 1.00 | ||
>10 mm | 20 | 39 | 4.03 (1.44-12.28) | 37 | 22 | 5.55 (1.92-18.110) | ||
Tumor diameter | 0.003 | <0.001 | ||||||
≤ 4cmb | 7 | 57 | 1.00 | 58 | 6 | 1.00 | ||
>4cm | 20 | 40 | 4.07 (1.46-12.38) | 37 | 23 | 6.01 (2.09-19.51) | ||
Parametrium | 0.065 | <0.001 | ||||||
no invasionb | 13 | 66 | 1.00 | 70 | 9 | 1.00 | ||
invasion | 13 | 29 | 2.28 (0.85-6.04) | 23 | 19 | 6.43 (2.34-18.24) | ||
Vagina | 0.026 | 0.061 | ||||||
no invasionb | 13 | 69 | 1.00 | 67 | 15 | 1.00 | 1.00 | |
invasion | 14 | 28 | 2.65 (1.01-6.96) | 28 | 14 | 2.23 (0.87-5.69) | ||
Pelvic lymph node | 0.001 | <0.001 | ||||||
no metastasisb | 13 | 77 | 1.00 | 80 | 10 | 1.00 | ||
metastasis | 14 | 19 | 4.36 (1.59-11.88) | 14 | 19 | 10.86 (3.79-31.55) |
Statistical analysis: Chi-square or Fisher's exact tests
aSome clinicopathological data could not be obtained from the patients with cervical invasive cancer due to incomplete records of medical chart.
bAs a reference. MMP-11, matrix metalloproteinase-11. Recurrence; +, recurrence; -, no recurrence. Survival; +, survival, -, dead.
Univariate analysis for the associations of matrix metalloproteinase-11 genetic polymorphism rs738791 and various clinicopatholgical parameters with the recurrence-free survival and overall survival of the patients with uterine cervical cancer
Recurrence-free survival | Overall survival | |||
---|---|---|---|---|
Variables | p value | HR & 95% CIb | p value | HR & 95% CIb |
matrix metalloproteinase-11 genetic polymorphism | ||||
rs738791 CT/TT vs CCa | 0.122 | 1.82 (0.84-3.94) | 0.161 | 1.69 (0.80-3.50) |
Clinicopathological characteristics | ||||
Stage | ||||
≥ stage II vs stage Ia | 0.002 | 3.29 (1.47-7.35) | <0.001 | 5.39 (2.18-13.32) |
Pathologic type | ||||
squamous cell carcinomaa adenocarcinoma | 0.030 | 2.43 (1.06-5.58) | 0.120 | 1.95 (0.83-4.57) |
Stromal invasion depth | ||||
>10 mm vs ≤10 mma | 0.001 | 3.81 (1.61-9.04) | 0.001 | 4.25 (1.72-10.49) |
Tumor diameter | ||||
>4 cm vs ≤ 4cma | 0.001 | 3.91 (1.65-9.28) | <0.001 | 4.78 (1.94-11.75) |
Parametrium | ||||
invasion vs no invasiona | 0.031 | 2.29 (1.06-4.99) | <0.001 | 4.59 (2.06-10.19) |
Vagina | ||||
invasion vs no invasiona | 0.013 | 2.52 (1.18-5.37) | 0.066 | 1.96 (0.94-4.07) |
Pelvic lymph node | ||||
metastasis vs no metastasisa | <0.001 | 4.27 (1.99-9.16) | <0.001 | 6.95 (3.22-15.03) |
Statistical analyses: Kaplan-Meier curves model
aAs a comparison reference
bHR, hazard ratio and 95% CI, 95% confidence interval for matrix metalloproteinase-11 gene variant rs738791 and clinicopathological variables, compared to their respective controls.
Multivariate analysis for the associations of matrix metalloproteinase-11 genetic polymorphism rs738791 and various clinicopatholgical parameters with the recurrence-free survival and overall survival of the patients with uterine cervical cancer.
Recurrence-free survival | Overall survival | |||
---|---|---|---|---|
Variables | p value | HR & 95% CIb | p value | HR & 95% CIb |
matrix metalloproteinase-11 genetic polymorphism | ||||
rs738791 CT/TT vs CCa | 0.355 | 1.49 (0.64-3.48) | 0.130 | 1.94 (0.82-4.58) |
Clinicopathological characteristics | ||||
Stage | ||||
≥ stage II vs stage Ia | 0.601 | 1.35 (0.44-4.17) | 0.329 | 1.91 (0.52-6.97) |
Pathologic type | ||||
squamous cell carcinomaa adenocarcinoma | 0.059 | 2.39 (0.97-5.90) | 0.468 | 1.48 (0.52-4.21) |
Stromal invasion depth | ||||
>10 mm vs ≤10 mma | 0.348 | 1.71 (0.56-5.24) | 0.483 | 1.56 (0.45-5.38) |
Tumor diameter | ||||
>4 cm vs ≤ 4cma | 0.324 | 1.92 (0.53-6.99) | 0.657 | 1.41 (0.31-6.30) |
Parametrium | ||||
invasion vs no invasiona | 0.349 | 0.59 (0.19-1.78) | 0.425 | 1.71 (0.46-6.33) |
Vagina | ||||
invasion vs no invasiona | 0.623 | 1.33 (0.43-4.10) | 0.063 | 0.39 (0.14-1.05) |
Pelvic lymph node | ||||
metastasis vs no metastasisa | 0.033 | 2.83 (1.09-7.35) | 0.001 | 4.80 (1.82-12.62) |
Statistical analyses: Cox proportional hazard model
aAs a comparison reference
bHR, hazard ratio and 95% CI, 95% confidence interval for matrix metalloproteinase-11 gene variant rs738791 genetic polymorphism and clinicopathological variables, compared to their respective controls.
To the best of our knowledge, this is the first study to investigate the association between MMP-11 genetic polymorphisms and clinicopathologic characteristics, as well as survival, in patients with uterine cervical cancer. The influence of the MMP-11 gene on the metastatic phenotype of uterine cervical cancer was examined. There was no significant difference between patients carrying the rs738791 CT/TT genotype and CC carriers in pelvic lymph node metastasis, stromal invasion depth and stage. Furthermore, MMP-11 SNPs were not found to be significantly associated with cervical cancer patient survival in this study. Considering clinicopathological characteristics, only pelvic lymph node metastasis displayed a critical predictor of recurrence-free survival and overall survival in this limited sample study. This corroborates the finding of other studies that lymph node metastasis is the most pivotal prognostic variable for cervical cancer patient survival [2, 20-22]. The 5-year survival rate was significantly declined from 85%-90% in cervical cancer patients with negative pelvic lymph nodes to 30%-50% in those with positive pelvic lymph nodes [23].
Only 21 cases of adenocarcinoma were involved in this study. The sample size was too small to analyze the associations among MMP-11 SNPs, the development of cervical cancer, and clinicopathological variables. Therefore, it seems unreasonable to categorize our cases into adenocarcinoma group for statistical analysis. However, we cannot find any significant association between MMP-11 SNPs and the development of cervical adenocarcinoma in the limited samples (the data not showed). No significant difference was also found between MMP-1 SNPs and clinicopathological variables of cervical adenocarcinoma (the data not showed).
MMP-11 is secreted into microenvironment, degrades the ECM and promotes the tumorigenesis and progress of cancer [4]. Several potential physiological substrates of MMP-11 have been identified, including insulin-like growth factor-binding protein-1 (IGFBP-1), proteinase inhibitor, laminin receptor and collagen VI [4, 24-27]. The role of MMP-11 might play activator or repressor functions in the metastatic process, probably depending on various spatiotemporal occasions [4]. The complexity of MMP-11 function was shown by an animal study, including favoring implantation and growth of lung metastasis during metastasis process but limiting lung foci number and repressing dissemination to other organs [28]. In the cervical cancer, increased transcription of gene MMP-11 was observed [13]. Expressions of MMP-11 in LSIL, HSIL and cervical cancer have been investigated [14]. A relative increased expression of MMP-11 from LSIL and HSIL samples was demonstrated by real time RT-PCR or immunohistochemistry assay [14]. Positive samples for MMP-11 expression were also increased according to disease progression [14].
SNPs may associate with diseases by influencing promoter activity, messenger RNA conformation, subcellular localization of messenger RNAs and/or proteins [15]. Identifying variations in genes and analyzing their effects on diseases may lead to understanding the impacts on health of an individual [15]. Furthermore, Genetic polymorphisms, in exons or promoter regions, may affect gene expression. When a SNP occurs in a coding sequence, the encoded amino acids may be changed in the related protein and is referred to nonsynonymous. If the same amino acid is produced, it is known as synonymous. A SNP occuring in the 3'-untranslated region of a gene may exert an impact on biological processes [15]. SNPs, in introns, can play important biological roles and may have a strong influence on disease progressing [29]. In this study, MMP-11 SNPs rs28382575 (Pro475Pro) is synonymous and SNPs rs738792 (Ala38Val) is nonsynonymous. However, rs738791, rs2267029 and rs131451 are all located in the intron regions. Until now, the mechanisms that MMP-11 rs738791 exerts the influence on its gene expressions have not be delineated. Rs738791 may present as a functional intronic polymorphism which can affect the expression of this gene that hosts it [30-32]. Genetic variants in intron can induce aberrant splicing that is readily distinguishable from normal splicing by RNA analysis. Introns probably represent a variety of mutational targets because of their containing a multiplicity of functional elements including intron splicing enhancers, silencers which can regulate alternative slicing and other regulatory elements [33-36]. By functional intronic polymorphisms, the susceptibility to disease may be conferred. This also modulates genotype-biological phenotype relationship and may affect biological phenotypes depending on various spatiotemporal occasions [30-32]. Because there were no significant associations after multiple significance test, the role of SNPs in this gene do not impact on uterine cervical cancer based on the current study. The molecular mechanism of functional intronic polymorphisms actually could not be related to MMP-11 SNPs. MMP-11 SNP rs738791, intron variant, could play a role for development, progression or protection in different type of cancer. Carriers of MMP-11 rs738791 CT+TT were at higher risk of Hepatocellular carcinoma (HCC) than carriers of wild type (CC) [17]. Individuals with CT/CC genotype at the MMP-11 SNP rs28382575 were at greater risk of developing large tumors, stage III/IV disease or lymph node metastasis. The authors claimed that genetic variations in the MMP-11 gene may be helpful in predicting early-stage HCC [17]. In a transgenic animal model study found that dual MMP-11 function, including tumor enhancing or repressing in processes, led to local or distal invasion [37]. A previous research demonstrated no significant difference in the incident of oral squamous cell carcinoma (OSCC) amongst individuals with MMP-11 genetic polymorphisms in rs738791, rs2267029, rs738792 or rs28382575; however, the effect of MMP-11 gene polymorphisms might be collaborated with environmental carcinogens (betel nut chewing or tobacco use) to increase risk of developing OSCC [16]. These findings demonstrate different MMP-11 polymorphisms play different functions on cancer development.
In conclusion, our study demonstrates no impact of the MMP-11 gene polymorphisms on the development and clinicopathological variables of cervical cancer as well as patient survival in Taiwan. Further studies are needed to examine the impact of MMP-11 on the pathogenesis and pathway.
This work was supported by grants from the Changhua Christian Hospital Research Foundation (108-CCH-IRP-132) and Chung Shan Medical University Hospital (CSH-2018-D-004).
The authors have declared that no competing interest exists.
1. Small W Jr, Bacon MA, Bajaj A, Chuang LT, Fisher BJ, Harkenrider MM. et al. Cervical cancer: A global health crisis. Cancer. 2017;123:2404-2412
2. Sarker A, Im HJ, Cheon GJ, Chung HH, Kang KW, Chung JK. et al. Prognostic Implications of the SUVmax of Primary Tumors and Metastatic Lymph Node Measured by 18F-FDG PET in Patients With Uterine Cervical Cancer: A Meta-analysis. Clin Nucl Med. 2016;41:34-40
3. Martin CM, O'Leary JJ. Histology of cervical intraepithelial neoplasia and the role of biomarkers. Best Pract Res Clin Obstet Gynaecol. 2011;25:605-615
4. Zhang X, Huang S, Guo J, Zhou L, You L, Zhang T. et al. Insights into the distinct roles of MMP-11 in tumor biology and future therapeutics (Review). Int J Oncol. 2016;48:1783-1793
5. Basset P, Bellocq JP, Wolf C, Stoll I, Hutin P, Limacher JM. et al. A novel metalloproteinase gene specifically expressed in stromal cells of breast carcinomas. Nature. 1990;348:699-704
6. Lefebvre O, Regnier C, Chenard MP, Wendling C, Chambon P, Basset P. et al. Developmental expression of mouse stromelysin-3 mRNA. Development. 1995;121:947-955
7. Kettunen E, Anttila S, Seppanen JK, Karjalainen A, Edgren H, Lindstrom I. et al. Differentially expressed genes in nonsmall cell lung cancer: expression profiling of cancer-related genes in squamous cell lung cancer. Cancer Genet Cytogenet. 2004;149:98-106
8. Zhao ZS, Chu YQ, Ye ZY, Wang YY, Tao HQ. Overexpression of matrix metalloproteinase 11 in human gastric carcinoma and its clinicopathologic significance. Hum Pathol. 2010;41:686-696
9. Arora S, Kaur J, Sharma C, Mathur M, Bahadur S, Shukla NK. et al. Stromelysin 3, Ets-1, and vascular endothelial growth factor expression in oral precancerous and cancerous lesions: correlation with microvessel density, progression, and prognosis. Clin Cancer Res. 2005;11:2272-2284
10. Wlodarczyk J, Stolte M, Mueller J. E-cadherin, beta-catenin and stromelysin-3 expression in de novo carcinoma of the colorectum. Pol J Pathol. 2001;52:119-124
11. Hourihan RN, O'Sullivan GC, Morgan JG. Transcriptional gene expression profiles of oesophageal adenocarcinoma and normal oesophageal tissues. Anticancer Res. 2003;23:161-165
12. von Marschall Z, Riecken EO, Rosewicz S. Stromelysin 3 is overexpressed in human pancreatic carcinoma and regulated by retinoic acid in pancreatic carcinoma cell lines. Gut. 1998;43:692-698
13. Vazquez-Ortiz G, Pina-Sanchez P, Vazquez K, Duenas A, Taja L, Mendoza P. et al. Overexpression of cathepsin F, matrix metalloproteinases 11 and 12 in cervical cancer. BMC Cancer. 2005;5:68
14. Valdivia A, Peralta R, Matute-Gonzalez M, Garcia Cebada JM, Casasola I, Jimenez-Medrano C. et al. Co-expression of metalloproteinases 11 and 12 in cervical scrapes cells from cervical precursor lesions. Int J Clin Exp Pathol. 2011;4:674-682
15. Shastry BS. SNPs: impact on gene function and phenotype. Methods Mol Biol. 2009;578:3-22
16. Lin CW, Yang SF, Chuang CY, Lin HP, Hsin CH. Association of matrix metalloproteinase-11 polymorphisms with susceptibility and clinicopathologic characteristics for oral squamous cell carcinoma. Head Neck. 2015;37:1425-1431
17. Wang B, Hsu CJ, Lee HL, Chou CH, Su CM, Yang SF. et al. Impact of matrix metalloproteinase-11 gene polymorphisms upon the development and progression of hepatocellular carcinoma. Int J Med Sci. 2018;15:653-658
18. Koleck TA, Bender CM, Clark BZ, Ryan CM, Ghotkar P, Brufsky A. et al. An exploratory study of host polymorphisms in genes that clinically characterize breast cancer tumors and pretreatment cognitive performance in breast cancer survivors. Breast Cancer (Dove Med Press). 2017;9:95-110
19. Hua KT, Liu YF, Hsu CL, Cheng TY, Yang CY, Chang JS. et al. 3'UTR polymorphisms of carbonic anhydrase IX determine the miR-34a targeting efficiency and prognosis of hepatocellular carcinoma. Sci Rep. 2017;7:4466
20. Li H, Wu X. Advances in diagnosis and treatment of metastatic cervical cancer. J Gynecol Oncol. 2016;27:e43
21. Kamura T, Tsukamoto N, Tsuruchi N, Saito T, Matsuyama T, Akazawa K. et al. Multivariate analysis of the histopathologic prognostic factors of cervical cancer in patients undergoing radical hysterectomy. Cancer. 1992;69:181-186
22. Choi KH, Kim JY, Lee DS, Lee YH, Lee SW, Sung S. et al. Clinical impact of boost irradiation to pelvic lymph node in uterine cervical cancer treated with definitive chemoradiotherapy. Medicine (Baltimore). 2018;97:e0517
23. Monk BJ, Cha DS, Walker JL, Burger RA, Ramsinghani NS, Manetta A. et al. Extent of disease as an indication for pelvic radiation following radical hysterectomy and bilateral pelvic lymph node dissection in the treatment of stage IB and IIA cervical carcinoma. Gynecol Oncol. 1994;54:4-9
24. Fiorentino M, Fu L, Shi YB. Mutational analysis of the cleavage of the cancer-associated laminin receptor by stromelysin-3 reveals the contribution of flanking sequences to site recognition and cleavage efficiency. Int J Mol Med. 2009;23:389-397
25. Manes S, Mira E, Barbacid MM, Cipres A, Fernandez-Resa P, Buesa JM. et al. Identification of insulin-like growth factor-binding protein-1 as a potential physiological substrate for human stromelysin-3. J Biol Chem. 1997;272:25706-25712
26. Motrescu ER, Blaise S, Etique N, Messaddeq N, Chenard MP, Stoll I. et al. Matrix metalloproteinase-11/stromelysin-3 exhibits collagenolytic function against collagen VI under normal and malignant conditions. Oncogene. 2008;27:6347-6355
27. Deng H, Guo RF, Li WM, Zhao M, Lu YY. Matrix metalloproteinase 11 depletion inhibits cell proliferation in gastric cancer cells. Biochem Biophys Res Commun. 2005;326:274-281
28. Brasse D, Mathelin C, Leroux K, Chenard MP, Blaise S, Stoll I. et al. Matrix metalloproteinase 11/stromelysin-3 exerts both activator and repressor functions during the hematogenous metastatic process in mice. Int J Cancer. 2010;127:1347-1355
29. Sailaja K, Rao VR, Yadav S, Reddy RR, Surekha D, Rao DN. et al. Intronic SNPs of TP53 gene in chronic myeloid leukemia: Impact on drug response. J Nat Sci Biol Med. 2012;3:182-185
30. Manolio TA, Collins FS, Cox NJ, Goldstein DB, Hindorff LA, Hunter DJ' et al. Finding the missing heritability of complex diseases. Nature. 2009;41:747-753
31. McCauley JL, Kenealy SJ, Margulies EH, Schnetz-Boutaud N, Gregory SG, Hauser SL. et al. SNPs in multi-species conserved Sequences (MCS) as useful markers in association studies: A practical approach. BMC Genomics. 2007;8:266
32. Millar DS, Horan M, Chuzhanova NA, Cooper DN. Characterisation of a functional intronic polymorphism in the human growth hormone (GH1) gene. Hum Genomics. 2010;4:289-301
33. Kra´lovicova´ J, Lei H, Vorechovsky´ I. Phenotypic conse-quences of branch point substitutions. Hum Mutat. 2006;27:803-813
34. Tress ML, Martelli PL, Frankish A, Reeves GA, Wesselink JJ, Yeats C. et al. The implications of alternative splicing in the ENCODE protein complement. Proc Natl Acad Sci. USA. 2007;104:5495-5500
35. Gingeras TR. Implications of chimaeric non-co-linear transcripts. Nature. 2009:461 206-11
36. Solis AS, Shariat N, Patton JG. Splicing fidelity, enhancers, and disease. Front Biosci. 2008;13:1926-1942
37. Andarawewa KL, Boulay A, Masson R, Mathelin C, Stoll I, Tomasetto C. et al. Dual stromelysin-3 function during natural mouse mammary tumor virus-ras tumor progression. Cancer Res. 2003;63:5844-5849
Corresponding author: Yi-Hsuan Hsiao, MD., Ph.D., Department of Obstetrics and Gynecology, Changhua Christian Hospital, Changhua, Taiwan; E-mail: 54315org.tw
Received 2019-1-16
Accepted 2019-5-11
Published 2019-6-2