Literature DB >> 23053628

Metallothionein 2A genetic polymorphisms and risk of ductal breast cancer.

Anna Krześlak1, Ewa Forma, Paweł Jóźwiak, Agnieszka Szymczyk, Beata Smolarz, Hanna Romanowicz-Makowska, Waldemar Różański, Magdalena Bryś.   

Abstract

Metallothioneins (MTs) are a family of metal binding proteins that play an important role in cellular processes such as proliferation and apoptosis. Metallothionein 2A is the most expressed MT isoform in the breast cells. A number of studies have demonstrated increased MT2A expression in various human tumors, including breast cancer. We carried out an association study to examine whether MT2A gene polymorphisms are associated with risk of breast cancer. Information on lifestyle risk factors was collected via a self-administered questionnaire. Genotyping was conducted using polymerase chain reaction-restriction fragment length polymorphism technique. Three single nucleotide polymorphisms (SNP) rs28366003, rs1610216 and rs10636 were genotyped in 534 breast cancer cases and 556 population controls. One SNP in MT2A (rs28366003) showed a positive association with breast cancer. Compared with homozygous common allele carriers, heterozygous for the G variant [odds ratio (OR) = 1.92, 95 % confidence interval (CI):1.28-2.81, p trend <0.01; the OR assuming a dominant model 1.93 (95 % CI: 1.29-2.89, (p dominant) <0.02) after adjustment for age, family history, smoking status, BMI, menarche, parity, menopausal status and use of contraceptive and menopausal hormones] had a significantly increased risk of breast cancer in Polish population, as well as women with haplotypes, including variant allele of rs28366003 SNP (OR = 1.58, CI: 0.41-6.33, p global = 0.03). Our data suggest that the rs28366003 SNP in MT2A is associated with risk of breast cancer in Polish population.

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Year:  2012        PMID: 23053628      PMCID: PMC3907692          DOI: 10.1007/s10238-012-0215-4

Source DB:  PubMed          Journal:  Clin Exp Med        ISSN: 1591-8890            Impact factor:   3.984


Introduction

Metallothioneins (MTs) are a family of proteins with low molecular mass (6–7 kDa), high content of cysteine and complete absence of aromatic amino acids [1-3]. MTs bind to biologically essential metals like Zn and Cu and can participate in regulation of these metals homeostasis. Moreover, MTs absorb the heavy metals such as Cd, Pb, Hg and As and assist with their transportation and extraction [1-4]. Apart from their role in protection of tissue against heavy metals, MTs can act as potent antioxidants against oxidative damages [1-4]. They are known to participate also in cell proliferation and apoptosis which are very important processes in carcinogenesis [5-7]. In human, MTs are encoded by a family of genes located on chromosome 16q13 consisting of ten functional MT isoforms. The encoded proteins are subdivided into four groups: MT1, MT2, MT3 and MT4 proteins. Human MT isoforms have tissue-specific expression patterns [3]. MTs expression increases in response to various inducers such as metals, interleukins, interferon, tumor necrosis factor alpha and glucocorticoid hormones [8]. A number of studies have demonstrated increased expression of MT1 and MT2 mRNA and protein in various human tumors such as kidney, lung, nasopharynx, ovary, prostate, salivary gland, testes, urinary bladder, cervical, endometrial, skin and pancreatic cancers as well as melanoma [7, 9, 10]. In some cases, high expression of MT1 and MT2 correlates with tumor grade/stage, chemotherapy resistance and poor prognosis. However, MT1/2 can also be down-regulated in certain tumors, for example, hepatocellular carcinoma and liver adenocarcinoma [7]. MT2A is the most expressed isoform in the breast cells. The MT2A mRNA expression is positively correlated with histological grade [7]. Histological grade 3 tumors were observed to have a higher expression of MT2A mRNA than grade 1 and 2 tumors. Immunohistochemical studies have shown that cytoplasmic and/or nuclear MT1/2 protein expression is associated with tumor grade, increased recurrence rate and poor survival in the highly malignant invasive ductal breast carcinomas [5, 7, 9, 10]. Some studies have shown an inverse correlation between MTs expression and progesterone and estrogen receptors positivity [11]. Based on correlation of MT expression and clinicopathological parameters of breast cancer showed in many reports, Bay et al. [12] suggested that metallothionein is a promising prognostic biomarker in breast cancer. Taking into account the potential role of MT2A in breast carcinogenesis, we have analyzed an association between breast cancer and three known single nucleotide polymorphisms (SNPs) of MT2A gene. We selected SNPs that could potentially affect gene expression. The SNPs analyzed by us in this study concerned A/G transitions in promoter region at loci −5 and −209 (rs28366003 and rs1610216, respectively) and C/G transition in 3’UTR region at locus +838 (rs10636). Therefore, we comprehensively evaluated the association of this SNP with breast cancer risk in a Polish population-based case–control study.

Materials and methods

Study population

This case–control study involved 534 women with invasive ductal breast cancer (age range 34–81, mean age 54.76 ± 7.35) recruited between May 2003 and November 2010. The patients had a confirmed diagnosis of ductal breast cancer based on histopathological evaluation and were under treatment at the Polish Mothers Memorial Hospital Research Institute, Lodz, Poland. None of the recruited patients received preoperative chemo- or radiotherapy. Patients with recurrence of breast cancer and patients who had previously diagnosed with other types of primary cancers (excluding skin cancer) were excluded. A group of 556 healthy Polish individuals were collected from the Polish Mothers Memorial Hospital Research Institute from periodic health checkups and used as reference. They were non-related women who have never been diagnosed with breast tumors or other tumors and were randomly selected and matched to the cases on 10 years age groups (age range 34–83, mean age 51.27 ± 11.18). We enrolled only Caucasian women born and living in central Poland (Łódź region). We queried the cancer registry database every 2 months and identified all histopathologically confirmed incident primary breast cancer cases reported within 4 months of diagnosis preceding the recruitment. Informed consent was obtained from patients and controls, and the Ethical Committee approved the study.

Lifestyle risk factors

Study participants were interviewed using questionnaire that included socio-demographic, health related information, smoking status, menstrual and reproductive histories and exogenous hormone use. A positive family history of breast cancer was defined as reporting of breast cancer in one or more first-degree relatives. Body mass index (BMI) was calculated from current weight in kilograms divided by height in meter square (measurements were extracted from patient’s medical record). Smoking was grouped into “never,” “former” and “current” based on self-reported usage. Participants who reported smoking at least 100 cigarettes in their lifetime and who, at the time of survey, smoked either every day or some days were defined as current smoker. Eight participants reported smoking at least 100 cigarettes in their lifetime but had not been smoking for 1–2 months. They were classified as current smoker. Participants who reported smoking at least 100 cigarettes in their lifetime and who had not been smoking for at least 3 months were defined as former smoker. Participants who reported never having smoked 100 cigarettes were defined as never smoker. Natural age at menopause was defined as the age at the last menstrual period, which can only be defined retrospectively after at least 12 consecutive months of amenorrhea. This last menstrual period should not be induced by surgery or other obvious causes, such as irradiation or hormone therapy. None of the women involved in the study had undergone a hysterectomy and oophorectomy. Regular drug use was defined as self-report use of oral contraceptives or menopausal hormones for 6 months or longer. For any missing survey data, patients were subsequently queried which lead to complete responses by all participants.

Questionnaire and the matching techniques

An analysis of the computerized medical records identified 916 ductal breast cancer patients in the age group 30–85 years. From the same hospital registry of women undergoing periodic health checkups, a control population of 1,082 individuals in the same age group (30–85 years) was randomly selected. A postal questionnaire was sent to both the cases and controls. The response rate in the survey for the ductal breast cancer patients was 58.3 % and for the controls 56.3 % thus leaving a group of n = 534 cases and a population of n = 609 controls. Finally, the study group was 534 cases and 556 controls.

Venipuncture, blood sample collection and genotyping

The larger median cubital, basilic or cephalic veins were selected and the tourniquet was applied 3–4 inches above the collection site. Next, the puncture site was cleaned by the 70 % alcohol pad, 21G needle was inserted into a vein, and blood started to flow to collection tube with EDTA as an anticoagulant (lavender top). After blood collection, tube was inverted 8–10 times and placed in refrigerator at −20 °C. Blood samples obtained from the participants were stored at −20 °C within 2 h of removal. DNA was isolated by standard method using proteinase K digestion, phenol chloroform extraction and ethanol precipitation. The quantity and purity of the DNA extracts were assessed by spectrophotometry using the Helios Alpha UV–vis spectrophotometer system (Thermo Fisher Scientific Inc.). The absorbances at 230, 260 and 280 nm were measured in 2 μl of each sample. Concentration of DNA was estimated by spectrophotometric quantification at 260 nm. The overall purity was assessed by calculating the absorbance ratios 260/280 and 260/230. High values for both ratio (260/280 > 1.8, 260/230 > 2) are commonly accepted as good indicators for pure DNA. PCR reactions were performed, using Perkin–Elmer DNA Thermal cycler 480, in a total volume of 50 μl to amplify MT2A −5A/G, −209A/G and +838C/G. The reaction mixtures consisted of 100 ng of genomic DNA and the following set of primers: 10 μM of MT2A −5A/G primers (5′-GGGCCGCCTTCAGGGAACTG-3′ and 5′-GGACTTGGAGGAGGCGTGGT-3′) MT2A −209A/G primers (5′-GGCTCAGGTTCGAGTACAGG-3′ and 5′-AAGTCACTTGCGGCTCCA-3′) or of MT2A +838 primers (5′-CCGCTCCCAGATGTAAAGAA-3′ and 5′-GGCATATAAAGAAAACCAGAGACA-3′). The DNA samples were amplified in the presence of 200 μmol dNTPs, 10 % dimethylsulfoxide, 1× Taq polymerase buffer, 1.5 mM MgCl2 and 0.5 U AmpliTaq Gold (Applied Biosystems, Foster, CA). The PCR condition for MT2A −5A/G comprised an initiation denaturation step at 94 °C for 4 min, followed by 30 cycles of 96 °C for 1 min, 61 °C for 1 min, 72 °C for 1 min and final extension step at 72 °C for 10 min. MT2A −209A/G was amplified 35 cycles at an annealing temperature of 62 °C for 1 min, and extension at 72 °C for 10 min. The conditions for MT2A +838C/G was 30 cycles at 61 °C annealing temperature for 1 min and extension at 72 °C for 10 min. Subsequently, RFLP analysis was performed on 20 microliters each of the respective PCR products by subjecting them to the following restriction enzymes: at a 5 U concentration: Bsg I (at 37 °C for 3 h) for MT2A −5A/G and Sma I (at 25 °C for 3 h) for MT2A −209A/G (both from New England Biolabs, UK), and Mae III (Roche Molecular Systems, Branchburg, USA) for MT2A +838C/G with 3 U concentration and overnight incubation at 55 °C [13-15]. In the case of MT2A −5A/G, the lengths of fragments obtained by digestion of each 185-bp fragment by Bsg I were 144 and 41 bp for the A/A genotype, 185, 144 and 41 bp for the A/G type and 185 bp for the G/G genotype. For MT2A −209A/G, after digestion by Sma I of the PCR products of 246 bp fragment for A/A homozygotes, 131 and 115 bp for G/G homozygotes and all three fragments for heterozygotes A/G were registered. Analogously, in the case of MT2A +838C/G, after digestion by Mae III of the PCR products of 157-bp fragment for A/A homozygotes, 95 and 62 bp for G/G homozygotes and 157, 95 and 62 bp for heterozygotes A/G were observed. The products were analyzed by electrophoresis on 3 % agarose gel and ethidium bromide-stained. Positive and negative controls were included in each gel. Quality control was ensured by including a random 5 % of the samples as duplicates.

Statistical data analysis

Genotype distributions were evaluated for agreement with Hardy–Weinberg equilibrium by the Chi-square test. All genotype distributions of MT2A fit Hardy–Weinberg equilibrium. Unconditional multiple logistic regression models were used to calculate odds ratios (ORs) and 95 % confidence intervals (CIs) for the association of genotype with breast cancer risk. Genotype data were analyzed with the homozygote of the common allele as the reference group. Variants of homozygotes and heterozygotes were combined to evaluate the dominant effect. For each SNP, trend tests were conducted by assigning the values 1, 2 and 3 to homozygous wild type, heterozygous and homozygous variant genotypes, respectively, and by adding these scores as a continuous variable in logistic regression model. The haplotype effects of the polymorphisms on breast cancer risk were analyzed using the Chaplin 1.2 (genetics.emory.edu) and THESIAS software (www.genecanvas.org). All haplotypes were examined simultaneously in regression models with the most common haplotype as the reference. Haplotypes were evaluated for association with breast cancer in unadjusted and adjusted logistic regression models as done for the individual SNPs. All multivariate models were adjusted for age, family history, obesity, smoking status, parity, menopausal status and use of contraceptive and menopausal hormones. Reported p values were two sided. Probabilities were considered significant whenever p value was lower than 0.05. All analyses were completed using STATA software (version 11.0 StataCorp., Texas, USA).

Results and discussion

The distributions of socio-demographic characteristics and lifestyle risk factors are shown in Table 1. Our sample is as a whole Caucasian and closely mirrors the Polish population. The cases were slightly older (54.76 ± 7.35 vs. 51.27 ± 11.18 years for controls), more likely to use oral contraceptives (64.4 vs. 50.1 % for controls), more likely to be a current smoker (37.1 vs. 26.2 % for controls) and more likely to have a BMI greater or equal than 30 (39.9 vs. 28.9 % for controls).
Table 1

Selected baseline characteristics of breast cancer cases and controls with questionnaire data

Cases (n (%))Controls (n (%)) p
Age (years)
35–44123 (23.0)189 (34.0)
45–54133 (25.0)139 (25.0)
55–64150 (28.1)122 (21.9)
65–7496 (18.0)89 (16.0)
75–8432 (5.9)17 (3.1)<0.001
Family history of breast cancer a
Yes64 (11.9)50 (9.0)
No470 (88.1)506 (91.0)0.11
Obesity (BMI ≥ 30 kg/m2) b
Yes213 (39.9)161 (28.9)
No321 (60.1)395 (71.1)<0.001
Smoking status
Never96 (18.0)155 (27.9)
Former240 (44.9)255 (45.9)
Current198 (37.1)146 (26.2)<0.001
Menarche (years)
1011 (2.1)0 (0.0)
11101 (18.9)106 (19.2)
12171 (32.1)200 (35.9)
13144 (26.9)167 (30.0)
1491 (17.1)72 (12.9)
≥1516 (2.9)11 (2.0)<0.01
Used oral contraceptives c
Yes344 (64.4)283 (50.1)
No190 (35.6)273 (49.9)<0.0001
Parity
Nulliparous114 (21.3)128 (23.0)
1125 (23.4)144 (25.9)
2140 (26.2)156 (28.0)
398 (18.3)94 (16.9)
≥457 (10.8)34 (6.2)0.07
Age at menopause(years)d 50.1 ± 4.349.8 ± 4.60.23
Use of menopausal hormones e
Never308 (57.7)384 (69.1)
Estrogen144 (27.0)94 (16.9)
Progestin32 (6.0)23 (4.1)
Combined50 (9.3)55 (9.9)<0.001

aFamily history defined as self-reporting of at least one first-degree relative with known breast cancer

bBody mass index (BMI) was calculated as current weight in kilograms divided by height in meter square (according to WHO classification)

cRegular drug use was defined as self-report use of oral contraceptives for 6 months or longer

dNatural age at menopause was defined as the age at the last menstrual period, which can only be defined retrospectively after at least 12 consecutive months of amenorrhea. This last menstrual period should not be induced by surgery or other obvious causes, such as irradiation or hormone therapy

eRegular drug use was defined as self-report use of menopausal hormones for 6 months or longer

Selected baseline characteristics of breast cancer cases and controls with questionnaire data aFamily history defined as self-reporting of at least one first-degree relative with known breast cancer bBody mass index (BMI) was calculated as current weight in kilograms divided by height in meter square (according to WHO classification) cRegular drug use was defined as self-report use of oral contraceptives for 6 months or longer dNatural age at menopause was defined as the age at the last menstrual period, which can only be defined retrospectively after at least 12 consecutive months of amenorrhea. This last menstrual period should not be induced by surgery or other obvious causes, such as irradiation or hormone therapy eRegular drug use was defined as self-report use of menopausal hormones for 6 months or longer Genotype and allele distributions for MT2A polymorphisms in 534 breast cancer patients and 556 control subjects are summarized in Table 2. Approximately, 95 % of the PCR–RFLP reactions were successful (4.7 % cases and 5.3 controls had unsuccessful PCR reactions). One SNP in MT2A (rs28366003) showed a positive association with breast cancer. Having one copy of the risk allele (G) conferred an estimated 90 % increase in breast cancer in the model adjusted for age, family history, smoking status, BMI, menarche, parity, menopausal status and use of contraceptive and menopausal hormones (OR = 1.94, 95 % CI: 1.31–2.90, p dominant <0.02). Homozygous variant allele carriers were not present in healthy controls. No other SNP was statistically significantly associated with breast cancer. Four haplotypes were estimated to have a population frequency of at least 5 %. One haplotype GAG, including variant allele of rs28366003 SNP, showed evidence of a statistically significantly increased risk of breast cancer in Polish population, with an approximately 50 % increase in risk for (OR = 1.58, CI: 0.41–6.33, p global = 0.03) (Table 3).
Table 2

Associations between MT2A SNPs and breast cancer risk

SNP genotypeCases (%)/controls (%)OR (95 % CI)a p OR (95 % CI)b p
rs28366003 (SNP1)
AA465 (87.1)/516 (92.8)1.00 (reference)1.00 (reference)
AG66 (12.3)/40 (7.2)1.83 (1.21–2.77)1.92 (1.28–2.81)
GG3 (0.6)/0 (0.0)
p trendc <0.001<0.01
AG or GG vs. AAd 69 (12.9)/40 (7.2)1.91 (1.27–2.88)<0.011.93 (1.29–2.89)<0.02
AG or AA vs. GGe 531 (99.4)/556 (100)
rs1610216 (SNP2)
AA408 (76.4)/402 (72.3)1.00 (reference)1.00 (reference)
AG125 (23.4)/153 (27.5)0.80 (0.61–1.06)0.81 (0.63–1.09) 
GG1 (0.2)/1 (0.2)0.98 (0.06–15.83)1.06 (0.09–16.72)
p trendc 0.130.73
AG or GG vs. AAd 126 (23.6)/154 (27.7)0.81 (0.61–1.06)0.120.82 (0.64–1.11)0.24
AG or AA vs. GGe 533 (99.8)/555 (99.8)1.04 (0.06–16.69)0.980.97 (0.07–15.41)0.87
rs10636 (SNP3)
GG305 (57.1)/280 (50.3)1.00 (reference)1.00 (reference)
GC205 (38.4)/253 (45.5)0.74 (0.58–0.95)0.69 (0.52–0.94)
CC24 (4.5)/23 (4.2)0.96 (0.53–1.74)0.91 (0.64–1.71)
p trendc 0.070.17
CG or CC vs. GGd 510 (95.5)/504 (90.6)0.76 (0.60–0.97)0.020.73 (0.57–0.96)0.06
CG or GG vs. CCe 229 (42.9)/301 (54.1)1.09 (0.61–1.96)0.071.11 (0.64–2.03)0.94

aCrude

bAdjusted for age, family history, smoking status, BMI, menarche, parity, menopausal status and use of contraceptive and menopausal hormones

cTesting additive genetic model (Cochran–Armitage test for trend)

dTesting dominant genetic model

eTesting recessive genetic model

Table 3

Associations between MT2A haplotypes and breast cancer risk

Haplotypes (SNP1–SNP3)Cases (%)/controls (%)OR (95 % CI)a OR (95 % CI)b
A-A-G167 (31.27)/184 (33.09)1.00 (reference)1.00 (reference)
G-A-G142 (26.58)/121 (21.77)1.54 (0.38–6.28)1.58 (0.41–6.30)
A-A-C118 (22.10)/134 (24.10)0.84 (0.37–1.65)0.83 (0.36–1.67)
A-G-C106 (19.85)/117 (21.04)0.82 (0.42–2.190.81 (0.41–2.08)

aCrude

bAdjusted for age, family history, smoking status, BMI, menarche, parity, menopausal status and use of contraceptive and menopausal hormones

Associations between MT2A SNPs and breast cancer risk aCrude bAdjusted for age, family history, smoking status, BMI, menarche, parity, menopausal status and use of contraceptive and menopausal hormones cTesting additive genetic model (Cochran–Armitage test for trend) dTesting dominant genetic model eTesting recessive genetic model Associations between MT2A haplotypes and breast cancer risk aCrude bAdjusted for age, family history, smoking status, BMI, menarche, parity, menopausal status and use of contraceptive and menopausal hormones In this breast cancer case–control study in a Polish population, we examined the association of three single nucleotide polymorphisms of MT2A gene with the risk of breast cancer. The SNPs analyzed by us concerned A/G transition in the promoter region at loci −5 and −209 (rs28366003 and rs1610216, respectively) and C/G transition in the untranslated region at locus +838 (rs10636). Our results suggest that one of three SNPs (rs28366003) influences significantly susceptibility of breast cancer. MT2A −5A/G single nucleotide polymorphism (rs28366003) is located at the core promoter region of MT2A gene between the TATA box and the site of initiation of transcription. This SNP is an A/G substitution located in the center of the consensus sequence TGCACTC. This conversion in turn may reduce the binding, to the core promoter region, of a nuclear protein that is involved in MT2A gene basic transcription [13]. In the literature, there are a few studies concerning rs1610216, rs28366003r and rs10636 polymorphisms of MT2A. The −5A/G polymorphism has been studied in Japanese and Turkish populations and genotype frequencies of AA, AG and GG are 82, 17 and 0,9 % for Japanese and 87, 12,3 and 0,7 % for Turkish [13, 16]. McElroy et al. [17] determined the frequency of the A and G alleles at rs28366003 in the promoter region of MT2A in White and Black females in the Midwestern United States. The frequency of the G allele was 1.1 % for Blacks and 6.4 % for Whites. Data demonstrated that the G allele is not common in both the Midwestern US Black and White female population and is less frequent than that reported for an Asian population. In our study regarding −5 A/G polymorphism, the allelic frequencies of the A/A, A/G, and G/G genotypes in the control group (healthy subjects) were 92.8, 7.2 and 0 %, respectively. Thus, similarly to the results obtained in Midwestern US, female population frequency of G allele was rather low in Polish women population. The rs28366003 polymorphism was extensively studied in Turkish population in relation to cadmium and other metals levels in tissues and blood [18-20]. The other metallothionein 2A gene polymorphisms have been studied for their associations with risk for a variety of diseases. Giacconi et al. [14] reported a significant relationship between −209A/G MT2A polymorphism, diabetes type II and atherosclerosis. The positive association between +838 C/G MT2A polymorphism and carotid artery stenosis in elderly people was also found [15]. Yang et al. [21] showed that rs10636 was significantly associated with incidence of type 2 diabetes mellitus with neuropathy in Chinese population. The role of MT in carcinogenesis and progression of breast cancer is not fully understood but it is suggested that metallothionein may play a role in cell proliferation, apoptosis and differentiation which are very important processes in carcinogenesis. The MT2A expression in breast cancer tissue correlates with increased proliferation indicated by Ki-67 immunopositivity [22]. Moreover, it was demonstrated that overexpression of MT2A in breast MCF-7 cells resulted in a twofold increase in cell multiplication [23]. Lim et al. [24] suggested that MT2A could plausibly modulate cell cycle progression from G1 to S phase via the ATM/Chk2/cdc25A pathway. Antisense down-regulation of MT2A was associated with increased apoptosis [11]. It is suggested that metallothionein participates in the regulation of apoptosis by inhibiting cell death and improving cell survival in periods of stress due to its ability to prevent oxidative damage and ability to interact with different apoptotic signal mechanisms [25, 26]. Metallothionein may also play a role in cancer progression. Kim et al. [27] have shown that metallothionein overexpression in MDA-MB-231 cells increased the expression of metalloproteinase-9. They suggest that up-regulation of MMP-9 is one of the mechanisms by which MT2A promotes invasion of breast cancer cells. Taking into account these molecular and cellular studies, it seemed to be very likely that genetic polymorphisms in the MT genes may affect susceptibility to breast cancer. In the literature, there is only one study of MT2A polymorphism concerning breast cancer patients. Seibold et al. [28] have found the association of MT2A polymorphisms with postmenopausal breast cancer risk. The two significant SNPs (rs1008766 and rs1580833) analyzed by them are located in flanking regions of the gene. Our results suggest that another SNP (rs28366003) might also be associated with breast cancer risk. There are several limitations of our study. One of them is the small sample size and the small number of homozygote individuals with rare alleles which may affect odds ratio estimates. Our results are limited to Caucasian women born and living in central Poland. Further studies are needed in other populations. Moreover, all cases used in this study are invasive ductal breast cancer, the most common type of invasive breast cancer. Our findings may not generalize to less frequently diagnosed invasive breast cancer subtypes. While confirmation of our results in other populations will be necessary, the results of this study are consistent with other studies suggesting the potential role of MT2A gene in breast carcinogenesis. Since the −5 position is located in the promoter region, it is possible that the substitution A/G produces allele-specific MT2A gene expression. Our future research will address just this issue in relation to the concentration of metals in breast cancer tissue. In summary, we found that in Polish population, the −5A/G (rs28366003) polymorphism in the MT2A gene may play role in susceptibility to breast cancer.
  23 in total

1.  Metallothionein inhibits peroxynitrite-induced DNA and lipoprotein damage.

Authors:  L Cai; J B Klein; Y J Kang
Journal:  J Biol Chem       Date:  2000-12-15       Impact factor: 5.157

Review 2.  Signaling events for metallothionein induction.

Authors:  Farzana Haq; Meghan Mahoney; James Koropatnick
Journal:  Mutat Res       Date:  2003-12-10       Impact factor: 2.433

3.  Metallothionein as a prognostic biomarker in breast cancer.

Authors:  Boon-Huat Bay; Rongxian Jin; Jingxiang Huang; Puay-Hoon Tan
Journal:  Exp Biol Med (Maywood)       Date:  2006-10

4.  Potential effect on cellular response to cadmium of a single-nucleotide A --> G polymorphism in the promoter of the human gene for metallothionein IIA.

Authors:  Kayoko Kita; Nobuhiko Miura; Minoru Yoshida; Kentaro Yamazaki; Takayoshi Ohkubo; Yutaka Imai; Akira Naganuma
Journal:  Hum Genet       Date:  2006-08-23       Impact factor: 4.132

5.  Genetic variation at a metallothionein 2A promoter single-nucleotide polymorphism in white and black females in Midwestern United States.

Authors:  Jane A McElroy; Elizabeth C Bryda; Stephanie D McKay; Robert D Schnabel; Jeremy F Taylor
Journal:  J Toxicol Environ Health A       Date:  2010

6.  Polymorphisms in metallothionein-1 and -2 genes associated with the risk of type 2 diabetes mellitus and its complications.

Authors:  Lina Yang; Hongyan Li; Ting Yu; Haijun Zhao; M George Cherian; Lu Cai; Ya Liu
Journal:  Am J Physiol Endocrinol Metab       Date:  2008-03-18       Impact factor: 4.310

Review 7.  Expression of metallothioneins in tumor cells.

Authors:  Piotr Dziegiel
Journal:  Pol J Pathol       Date:  2004       Impact factor: 1.072

Review 8.  The role of metallothionein in oncogenesis and cancer prognosis.

Authors:  Mie Ø Pedersen; Agnete Larsen; Meredin Stoltenberg; Milena Penkowa
Journal:  Prog Histochem Cytochem       Date:  2008-12-01

9.  The +838 C/G MT2A polymorphism, metals, and the inflammatory/immune response in carotid artery stenosis in elderly people.

Authors:  Robertina Giacconi; Elisa Muti; Marco Malavolta; Catia Cipriano; Laura Costarelli; Gianni Bernardini; Nazzarena Gasparini; Erminia Mariani; Vittorio Saba; Gianfranco Boccoli; Eugenio Mocchegiani
Journal:  Mol Med       Date:  2007 Jul-Aug       Impact factor: 6.354

10.  Silencing the Metallothionein-2A gene inhibits cell cycle progression from G1- to S-phase involving ATM and cdc25A signaling in breast cancer cells.

Authors:  Daina Lim; Koh Mei-Xin Jocelyn; George Wai-Cheong Yip; Boon-Huat Bay
Journal:  Cancer Lett       Date:  2008-12-04       Impact factor: 8.679

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  13 in total

1.  Genetic polymorphism of metallothionein 2A and risk of laryngeal cancer in a Polish population.

Authors:  Katarzyna Starska; Anna Krześlak; Ewa Forma; Jurek Olszewski; Iwona Lewy-Trenda; Ewa Osuch-Wójcikiewicz; Magdalena Bryś
Journal:  Med Oncol       Date:  2014-06-22       Impact factor: 3.064

2.  Identification of XAF1-MT2A mutual antagonism as a molecular switch in cell-fate decisions under stressful conditions.

Authors:  Cheol-Hee Shin; Min-Goo Lee; Jikhyon Han; Seong-In Jeong; Byung-Kyu Ryu; Sung-Gil Chi
Journal:  Proc Natl Acad Sci U S A       Date:  2017-05-15       Impact factor: 11.205

3.  Polymorphisms in MMP-1, MMP-2, MMP-7, MMP-13 and MT2A do not contribute to breast, lung and colon cancer risk in polish population.

Authors:  Katarzyna Białkowska; Wojciech Marciniak; Magdalena Muszyńska; Piotr Baszuk; Satish Gupta; Katarzyna Jaworska-Bieniek; Grzegorz Sukiennicki; Katarzyna Durda; Tomasz Gromowski; Marcin Lener; Karolina Prajzendanc; Alicja Łukomska; Cezary Cybulski; Tomasz Huzarski; Jacek Gronwald; Tadeusz Dębniak; Jan Lubiński; Anna Jakubowska
Journal:  Hered Cancer Clin Pract       Date:  2020-07-31       Impact factor: 2.857

4.  Genetic variation in metallothionein and metal-regulatory transcription factor 1 in relation to urinary cadmium, copper, and zinc.

Authors:  Scott V Adams; Brian Barrick; Emily P Christopher; Martin M Shafer; Karen W Makar; Xiaoling Song; Johanna W Lampe; Hugo Vilchis; April Ulery; Polly A Newcomb
Journal:  Toxicol Appl Pharmacol       Date:  2015-10-31       Impact factor: 4.219

5.  Metallothionein 2A core promoter region genetic polymorphism and its impact on the risk, tumor behavior, and recurrences of sinonasal inverted papilloma (Schneiderian papilloma).

Authors:  Katarzyna Starska; Magdalena Bryś; Ewa Forma; Jurek Olszewski; Piotr Pietkiewicz; Iwona Lewy-Trenda; Olga Stasikowska-Kanicka; Marian Danilewicz; Anna Krześlak
Journal:  Tumour Biol       Date:  2015-06-03

6.  Genetic polymorphisms (rs10636 and rs28366003) in metallothionein 2A increase breast cancer risk in Chinese Han population.

Authors:  Di Liu; Meng Wang; Tian Tian; Xi-Jing Wang; Hua-Feng Kang; Tian-Bo Jin; Shu-Qun Zhang; Hai-Tao Guan; Peng-Tao Yang; Kang Liu; Xing-Han Liu; Peng Xu; Yi Zheng; Zhi-Jun Dai
Journal:  Aging (Albany NY)       Date:  2017-02-22       Impact factor: 5.682

7.  Exploring the Molecular Mechanism of the Drug-Treated Breast Cancer Based on Gene Expression Microarray.

Authors:  Ali Mohamed Alshabi; Ibrahim Ahmed Shaikh; Chanabasayya Vastrad
Journal:  Biomolecules       Date:  2019-07-15

Review 8.  The Functions of Metallothionein and ZIP and ZnT Transporters: An Overview and Perspective.

Authors:  Tomoki Kimura; Taiho Kambe
Journal:  Int J Mol Sci       Date:  2016-03-04       Impact factor: 5.923

Review 9.  Mammalian Metallothionein-2A and Oxidative Stress.

Authors:  Xue-Bin Ling; Hong-Wei Wei; Jun Wang; Yue-Qiong Kong; Yu-You Wu; Jun-Li Guo; Tian-Fa Li; Ji-Ke Li
Journal:  Int J Mol Sci       Date:  2016-09-06       Impact factor: 5.923

10.  Quantitative assessment of the association of polymorphisms in the metallothionein 2A gene with cancer risk.

Authors:  Jianguo Wang; Pinghua Huang; Wei Zhao; Wei Ren; Ling Ai; Liping Wu
Journal:  J Int Med Res       Date:  2020-08       Impact factor: 1.671

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