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Genetic polymorphisms and gene expression of one-carbon metabolizing enzymes and their relation to breast cancer

Abstract

Background

Breast cancer is considered the leading cause of cancer-related death among Egyptian women (15.41%). One of the common BC risk factors is the genetic factor. One-carbon metabolism is one of the pathways reported to increase BC risk by influencing DNA synthesis and methylation. Methyl tetrahydrofolate reductase (MTHFR), thymidylate synthase (TYMS) and DNA methyltransferase (DNMT) enzymes are key enzymes in one-carbon metabolism directly and through influencing folate metabolism. We aimed to study the association of the gene expression level and polymorphisms of MTHER C677T (rs1801133), TYMS (rs45445694), TYMS 3′UTR 1494del6 and ΔDNMT3B − 149C>T with breast cancer risk in a sample of Egyptian women.

Methods

This study was conducted on one hundred female breast cancer patients. Genotyping and gene expression of the MTHFR and TYMS (1494del6, rs45445694) and DNMT3B genes were performed.

Results

There was no significant difference (OR 1.493; 95% CI 0.78–2.84; P = 0.288) in the frequency of the MTHFR (C677T) genotypes between breast cancer patients and control subjects and no significant difference in the frequency of the MTHFR mutant T allele. TYMS tandem repeats showed a significant difference (OR 2.232; CI 1.21–4.12; P = 0.01) in the frequency of the genotype 2R/3R among breast cancer patients and control subjects; however, the frequency of the 2R allele was not significantly different from that of the 3R allele (OR 1.461; 95% CI 0.96–2.21; P = 0.073). TYMS 3′-UTR 1494del6 showed a significant difference in the distribution of (+ 6/ + 6), (+ 6/− 6) and (− 6/− 6) genotypes between the patient and control groups (P ≤ 0.001*), and its corresponding mutant allele showed P value ≤ 0.001, 95% CI = 1.64–3.76 and OR = 2.483. The expression of MTHFR was downregulated by 0.62-fold in all malignant tissues compared to normal adjacent tissues (0.57 ± 0.20, P < 0.001*). On the other hand, no significant difference (P = 0.143) in the expression level of TYMS was found. Gene expression of DNMT3B was upregulated by 1.65-fold in all breast cancerous tissue samples compared with the control normal adjacent tissue with mean ± SD of 1.81 ± 0.63. (P ≤ 0.001*).

Conclusion

The current study showed that the 2R/3R TYMS allele and DNMT3B (− 149C>T) SNP are associated with a high risk of breast cancer and that there is a correlation between the 3′-UTR 1494del6 polymorphism (genotype − 6/− 6) and breast cancer risk. A significant reduction was found in the MTHFR gene expression level in BC compared with control tissues, and the DNMT3B (− 149C>T) SNP did affect the DNMT3B expression level.

Background

Breast cancer (BC) is described as the most frequent incident cancer and cause of death among women in Arab countries, although its incidence is lower than the global incidence. In Egypt, BC is the most diagnosed cancer and is considered the leading cause of cancer-related death among Egyptian women (15.41%). According to the American Cancer Society, the incidence rate of BC in Egypt is 46.8–59.6 per 100,000 (rates from 2011 to 2015), which is a great burden on population health [1, 2].

Breast cancer affects mainly females, and its risk increases with age. BC has many risk factors including environmental, hormonal and genetic factors, which are considered as a common risk factor for BC [3, 4]. Genome-wide association studies (GWAS) have described more than 170 single-nucleotide polymorphisms (SNPs) associated with the perceptivity to breast cancer. In addition, numerous genetic polymorphisms have been explored to explain their potential association with BC [5, 6].

Aberrantly, one-carbon metabolism is one of the pathways reported to increase BC risk by influencing DNA synthesis and methylation [7, 8]. One-carbon metabolism has two important functions in DNA synthesis and methylation. First, it is related to purine and thymidine production, which are both important for DNA synthesis. Second, it is related to its role in the supply of methyl groups through methionine metabolism [9].

Several enzymes are related to one-carbon metabolism, including (a) methyl tetrahydrofolate reductase (MTHFR), which catalyzes the irreversible conversion of 5,10-methylenetetrahydrofolate to 5-methyltetrahydrofolate, which produces a methyl donor essential for the conversion of homocysteine to methionine. Methionine then allows the formation of S-adenosyl methionine (SAM), which is essential during DNA methylation [10]; (b) thymidylate synthase (TYMS), which plays an essential role in nucleotide synthesis (thymidylate) by converting 5,10-methylene tetrahydrofolate to dihydrofolate; and (c) DNA methyltransferases (DNMTs) catalyze the transfer of a methyl group from S-adenosyl methionine (SAM) to a cytosine ring usually located within the context of a CpG dinucleotide in DNA [11, 12].

These enzymes, through their role in one-carbon metabolism, also influence folate metabolism, which mediates the transfer of one carbon in many biochemical reactions and is essential in the synthesis of S-adenosyl methionine and crucial in DNA, RNA and protein methylation; thus, mutations in these enzyme genes affect DNA stability and DNA integrity and lead to mutagenesis and cancer development [12].

The MTHFR gene consists of 11 exons encoding a protein of 656 amino acids and is located on the short arm of chromosome 1p36.3; its length is 2.2 Kb, and it has two promoters and two isoforms (70 kDa and 77 kDa) [13, 14]. The C677T polymorphism is a point mutation missense or nonsynonymous at position 677 in the MTHFR gene with the substitution of cysteine to thymine nucleotide at that position. The C677T (rs1801133) polymorphism, which is located in exon 4, results in the conversion of alanine to valine at codon 222 in the N-terminal catalytic domain and is the most public SNP that reduces the activity of this enzyme [15, 16]. The amino acid variants that result from this polymorphism cause a reduction in enzyme activity, thus changing folate and homocysteine concentrations. The low plasma folate and high homocysteine concentrations resulted from this polymorphism influence the synthesis and DNA [17]. These changes in MTHFR enzyme activity result in tumor progression [18, 19]. Individuals with the 677TT homozygous variant have no more than 30% normal enzyme activity, and heterozygotes with the CT genotype have 65% normal enzyme activity with increased thermal instability [20]. The incidence of MTHFR 677C>T varies according to the different ethnicities and populations.

The thymidylate synthase (TS) gene has three known polymorphisms: The first 2 polymorphisms occur in the 5′ untranslated region (UTR) of the TS gene, while the third polymorphism is located in the 3′UTR. These three polymorphisms are the tandem repeat polymorphism in the thymidylate synthase enhancer region (TSER), the G to C single-nucleotide polymorphism (G/C SNP) and the 6-bp deletion at base pair 1494 (TS1494del6). From the tandem repeats, the triple and double repeats are the most frequent, where triple repeats result in higher TS expression [21, 22].

One of the functional SNPs that have been found in DNMTs is ΔDNMT3B − 149C>T, which is located at -149 bp from the transcription start site of the DNMT3b isoform. It was speculated that this SNP may increase the risk of many types of cancer via increasingly aberrant de novo methylation of CpG islands and thus transcriptional repression of some tumor suppressor genes [23, 24].

Data concerning these enzymes gene polymorphisms and their gene expression in Egyptian females with breast cancer are still insufficient.

The study aimed to investigate the association of MTHER C677T (rs1801133), TYMS (rs45445694), TYMS 3′UTR 1494del6 and ΔDNMT3B − 149C>T polymorphisms and their gene expression levels with breast cancer risk in a sample of Egyptian women.

Methods

This study was conducted on one hundred female breast cancer patients and one hundred healthy females as controls. Breast cancer female patients were selected from patients admitted to the Clinical and Experimental Surgery Department, Medical Research Institute, University of Alexandria, during the period from September 2016 to March 2018. This study was approved by the Ethical Committee of Medical Research Institute and Ethical Committee of Faculty of Medicine (Serial number 0105660), Alexandria University, Egypt. Consent was taken from all participants to participate in the study and agreement on publication. A well-structured questionnaire was designed to cover all the following aspects: age, menopausal status, smoking habits, use of contraceptive pills and/or hormonal replacement therapies, family history of breast cancer, medical history (diabetes, hypertension, etc.) and any other medications.

Sample size was calculated statistically based on the frequencies of these genes in Mediterranean and Caucasian populations at the 80% and 5% levels of significance.

Tissue samples were collected from 10 randomly selected breast cancer patients, one from the malignant breast tissue (MT) and the other from adjacent normal breast tissue (NT) as a control group, and kept in RNA solution and stored at − 80 °C till usage. Venous blood samples from the 200 participating females were collected in EDTA tubes and stored at − 4 °C until subjected to DNA extraction and genotyping.

Genomic DNA was extracted from whole blood according to Sambrook et al. [25]. The integrity of the extracted DNA was assessed qualitatively by electrophoresis on a 1% agarose gel. Quantitative determination of DNA concentration and purity was performed using a NanoDrop1000 Spectrophotometer (Thermo Fischer Scientific, Wilmington, Delaware USA).

Genotyping of the studied gene polymorphisms

Genotyping conditions, including primer sequences, PCR conditions and PCR product lengths for amplification of the four studied genes (MTHFR and TYMS (1494del6, rs45445694) and DNMT3B), are shown in Table 1 and Figs. 1, 2, 3, 4, 5, 6 and 7.

Table 1 Genotyping conditions of the studied genes
Fig. 1
figure 1

Agarose gel (3%) electrophoresis of PCR products of the MTHFR gene fragment containing the C677T single-nucleotide polymorphism (Lanes 2–9) at 198 bp. Lane 1 represents the 100 bp DNA ladder

Fig. 2
figure 2

Agarose gel (3%) electrophoresis for Hinf1 restriction digestion product of the PCR products of MTHFR 198 bp fragments containing C677T SNP (Lanes 2–8). Lanes 4–7 represent the CC allele, Lane 8 represents the heterozygous CT allele, and Lane 3 represents the homozygous genotype allele TT

Fig. 3
figure 3

Agarose gel (3%) electrophoresis of the PCR product of the promoter enhancer region in the 5′ UTR in the TYMS gene containing tandem repeats (rs45445694). Lanes 2, 6 and 7 represent the 2R/3R heterozygous genotype, and lanes 3, 4 and 5 represent the 2R/2R homozygous genotype

Fig. 4
figure 4

Agarose gel (2%) electrophoresis of PCR products of TYMS 3′-UTR (Lanes 2–9). Lane 1 represents 100 bp DNA molecular weight markers

Fig. 5
figure 5

Agarose gel (2%) electrophoresis of TYMS genotyping. Panel A represents wild-type homozygous, and Panel B represents mutant homozygous

Fig. 6
figure 6

Agarose gel (2%) electrophoresis of PCR products of DNMT3B (Lanes 2–9). Lane 1 represents the 100 bp DNA molecular weight ladder

Fig. 7
figure 7

Agarose gel (2%) electrophoresis of PCR–RFLP for DNMT3B. Lanes 2, 3, and 7 represent heterozygous genotypes (380 bp, 207 bp and 173 bp). Lanes 4 and 5 show homozygous wild type at 380 bp. Lane 1 represents 100 bp DNA molecular weight marker

Confirmatory sequencing of the studied genes

  1. (a)

    For each of the studied genes, the PCR products of each gene were resolved on a 3% agarose gel as previously described and purified using a DNA gel extraction kit (QIAGEN, Germany) as follows: The DNA fragments were excised from the agarose gel, and three volumes of QG buffer were added to the excised agarose fragment, after which the tubes were kept at 50 °C until dissolved completely. One volume of ice-cold isopropanol was added, and the mixtures were loaded into a QIAquick spin column in 2-mL collection tubes and centrifuged at 12,000 rpm for 1 min. The flowthrough was discarded, and 0.75 mL of washing buffer PE was added to the spin column and recentrifuged again at 12,000 rpm for 1 min. The flowthrough was then discarded, and the QIAquick column was centrifuged for an additional 1 min at 12,000 rpm. Then, the QIAquick column was transferred to a clean sterilized 1.5-mL Eppendorf tube. The PCR product was eluted from the QIAquick column by adding 50 μL of EB buffer or nuclease-free water, followed by centrifugation at 12,000 rpm for 1 min. The eluted purified PCR product was checked on 3% agarose and stored at − 20 °C until further processing. Finally, the purified PCR product was subjected to sequencing using the chain termination method with an ABI 3130X DNA sequencer (Applied Biosystems, USA). DNA sequencing was performed by capillary electrophoresis (Applied Biosystems) using the Sanger method [26] (Figs. 8, 9, 10).

Fig. 8 
figure 8

Sequence analysis of the PCR product of 323 bp of a partial fragment of the MTHFR gene containing the C677T SNP. The chromatogram shows the homozygous genotype (CC) wild type (a), homozygous genotype (TT) (b) and heterozygous genotype (CT) (c). The arrow indicates the position of the SNP

Fig. 9 
figure 9

The sequence chromatograms obtained from the DNA sequencer showing the DNMT3B (− 149C>T) SNP sequencing results. Three genotypes, CT, CC and TT, were observed

Fig. 10
figure 10

The result obtained from genotyping was confirmed by DNA sequencing of the PCR product from representative samples of the three forms with a size of 400 bp containing the TYMS 3′-UTR 1494del6 SNP

Determination of gene expression for MTHFR, DNMT3B and TYMS

Total RNA was extracted from all tissue samples using an RNeasy Mini Kit (QIAGEN Co., Hilden, Germany). Then, the eluted RNA was stored at − 80 °C until used for cDNA synthesis.

The purity of RNA was determined by measuring the absorbance at 260 and 280 nm (A260/A280, using a NanoDrop ND-1000 UV–Visible Spectrophotometer against TE buffer as a blank). The optical density ratio ranging from 1.8 to 2.0 was taken as an indicator for the purity of the prepared RNA samples. Unique patterns of intact RNA were visualized as 28S and 18S rRNA bands on agarose gels (Fig. 11).

Fig.  11
figure 11

Agarose gel (1%) electrophoresis of RNA sample isolated and purified from patient tissue. Arrows show the location of the characteristic 28S and 18S rRNA bands.

Total RNA was reverse-transcribed to cDNA using a GoScript™ Reverse Transcription System Kit (Promega, USA). The gene expression levels of MTHFR, DNMT3B and TYMS were determined using quantitative real-time PCR. The primer sequences and qPCR conditions are summarized in Table 2. The expression of targeted genes was normalized to the reference gene glyceraldehyde 3-phosphate dehydrogenase (GAPDH) expression level within the same sample to determine ∆CT. Then, ∆CT for each sample was normalized to the expression of the targeted gene in the cells of the vehicle control to calculate ∆∆CT. The fold change in the expression of the target gene for each sample was calculated [27].

Table 2 Primers conditions for quantitative RT-PCR

Results

The demographic data of the current study are shown in Table 3, where the age of the patients ranged from 24 to 74 years with a mean ± SD of 49.80 ± 11.22, while the age of the controls ranged from 21 to 74 years with a mean ± SD of 47.28 ± 10.58. Data revealed no significant differences between patients and controls regarding age (P = 0.104). The frequency of breast cancer family history, smoking status and breast-feeding in the patient group was 82%, 26% and 72%, respectively.

Table 3 Demographic and clinical data

Table 4 shows the histological grades and breast cancer types found among the studied patients, where 93% of patients had pathological grade II and 92% of them had invasive ductal carcinoma.

Table 4 Tumor histological grade and breast cancer types

The frequencies of both studied genes (genotypes and alleles) in breast cancer patients and control subjects are shown in Table 5 and Fig. 12. The frequencies of the CC, CT and TT genotypes of MTHFR (C677T) were 68%, 29% and 3% in breast cancer patients, respectively. The CC, CT and TT genotypes of MTHFR (C677T) among the control subjects were 77%, 22% and 1%, respectively. There was no significant difference (OR 1.493; 95% CI 0.78–2.84; P = 0.288) in the frequency of the CT genotype between breast cancer patients and control subjects. The frequencies of the C and T alleles were 82.5% and 17.5%, respectively, in breast cancer patients. Conversely, the frequencies of C and T alleles in control subjects were 88% and 12%, respectively. There was no significant difference in the frequency of the mutant T allele between breast cancer patients and control subjects (OR 1.556; 95% CI 0.89–2.73; P = 0.121).

Table 5 Associations between MTHFR C677T SNP, TYMS tandem repeat, DNMT3B − 149C>T and TYMS 3′-UTR 1494del6 with breast cancer risk in Egyptian women
Fig. 12
figure 12

Frequencies of MTHFR C677T SNP, TYMS tandem repeat, DNMT3B − 149C>T and TYMS 3′-UTR 1494del6 in the studied groups

Regarding the TYMS genotypes and alleles for the tandem repeats (rs45445694), it was found that the frequencies of the 2R/2R, 2R/3R and 3R/3R genotypes were 23%, 77% and 0%, respectively, in breast cancer patients. However, the frequencies of the 2R/2R, 2R/3R and 3R/3R genotypes were 40%, 60% and 0%, respectively, in control subjects. The results indicated a significant difference (OR 2.232; CI 1.21–4.12; P = 0.01) in the frequency of the genotype 2R/3R among breast cancer patients and control subjects. On the other hand, the frequencies of 2R and 3R alleles were 61.5% and 38.5%, respectively, in breast cancer patients and 70% and 30%, respectively, in control subjects. The frequency of the 2R allele was not significantly different from that of the 3R allele (OR 1.461; 95% CI 0.96–2.21; P = 0.073).

Table 5 also shows the genotyping and allele frequency of DNMT3B − 149C>T in the studied groups. There was a significant difference in the distribution of C/C, C/T and T/T genotypes between the patients and control groups (P ≤ 0.001*). The genotype (C/T) had a significant association with increased breast cancer risk in the Alexandrian population (OR = 6.907, 95% CI = 3.58–13.32) compared to the C/C genotype. The mutant allele frequencies of DNMT3B 149 C>T in patients were 30% compared to 8.5% in the control subjects. The corresponding P value, 95% CI and odds ratio (OR) were as follows for the mutant allele: P value ≤ 0.001, 95% CI = 2.58–8.25 and OR = 4.613.

The genotyping and allele frequency of TYMS 3′-UTR 1494del6 in both studied groups are also shown in Table 5. According to the results, using the (+ 6/ + 6) allele as a reference, there was a significant difference in the distribution of the (+ 6/ + 6), (+ 6/− 6) and (− 6/− 6) genotypes between the patient and control groups (P ≤ 0.001*). This observation indicated that the genotype (− 6/− 6) had a significant association with an increased risk of breast cancer in Alexandrian women (OR = 3.294, 95% CI = 1.57–6.91) compared to the (+ 6/ + 6) genotype. The mutant genotype (− 6/− 6) frequencies of TYMS 3′-UTR 1494del6 were 62% and 31% in patients and control subjects, respectively. The mutant allele frequencies of SNPs in patients were 72.5% compared with 51.5% in the controls. The corresponding P value, 95% CI and odds ratio (OR) were as follows for the mutant allele: P value ≤ 0.001, 95% CI = 1.64–3.76 and OR = 2.483.

Table 6 shows the gene expression analysis, where the expression of MTHFR was downregulated by 0.62-fold in all malignant tissues compared to normal adjacent tissues (mean ± SD) of 0.57 ± 0.20. Accordingly, the Mann–Whitney U test determined that there exists a significant difference (P < 0.001*) in the relative gene expression of MTHFR levels in breast cancer patients compared to normal adjacent tissue as a control (Fig. 13). On the other hand, statistical analysis using the Mann–Whitney test revealed that there was no significant difference (P = 0.143) in the expression level of TYMS between breast cancer patients and normal adjacent tissue as a control. Obviously, the level of gene expression of DNMT3B was upregulated by 1.65-fold in all breast cancerous tissue samples compared with the control normal adjacent tissue with mean ± SD of 1.81 ± 0.63. Statistical analysis using the Mann–Whitney test revealed a significant difference in gene expression (P < 0.001*).

Table 6 Expression level of TYMS, MTHFR and DNMT3B genes in breast cancer tissues compared to normal adjacent tissue
Fig. 13
figure 13

Expression levels of the TYS, MTHFR and DNMT3B genes in tumor tissue and normal adjacent tissue

Discussion

Methyl tetrahydrofolate reductase (MTHFR), thymidylate synthase (TYMS) and DNA methyltransferase (DNMT) enzymes play essential roles in folate metabolism. As folate plays a vital role in nucleic acid synthesis of DNA, polymorphisms in these coding genes are correlated with cancer risk [28, 29]. To our knowledge, the study of the expression of these genes in breast cancer and the combined effect of their allele frequency is still insufficient.

There was no significant difference (OR 1.493; 95% CI 0.78–2.84; P = 0.288) in the frequency of the CT genotype between breast cancer patients and control subjects. This inferred the conclusion stating that the CT genotype is not a risk factor for breast cancer in the tested sample size. Additionally, there was no significant difference in the frequency of the mutant T allele between breast cancer patients and control subjects (OR 1.556; 95% CI 0.89–2.73; P = 0.121).

There are several research studies that correlate the MTHFR (C677T) polymorphism to hyperhomocysteinemia, folate deficiency and cancer [30]. The results in the current study are in agreement with other studies that found no association between the MTHFR (C677T) SNP and breast cancer risk [31, 32]. Unlike the present finding, a previous study stated a significant correlation between the MTHFR (C677T) SNP and breast cancer occurrence [33,34,35]. The discrepancy in findings regarding the possible role of the (C677T) SNP in the occurrence of breast cancer among different populations with different ethnic groups is mainly confined to the significant difference in genetic makeup among these populations.

Regarding the frequencies of the TYMS genotypes and alleles in breast cancer patients and control subjects for the tandem repeats (rs45445694) (Table 5), the results indicated a significant difference (OR 2.232; CI 1.21–4.12; P = 0.01) in the frequency of the genotype 2R/3R among breast cancer patients and control subjects. Subsequently, the genotype 2R/3R is considered a risk factor for breast cancer occurrence in the tested sample size of Egyptian women. On the other hand, the frequency of the 2R allele was not significantly different from that of the 3R allele (OR 1.461; 95% CI 0.96–2.21; P = 0.073).

Published data and research indicated that there were contradictory results regarding the possible role of the tandem repeats (rs45445694) of the TYMS gene in relation to breast cancer occurrence among different populations of different ethnicities. For instance, some studies did verify a positive correlation between the tandem repeats (rs45445694) of the TYMS gene and breast cancer occurrence [36, 37], while another study did not confirm this correlation with the variant alleles [38].

The genotyping and allele frequency of DNMT3B − 149C>T in the studied groups showed that there were significant differences in the distribution of the C/C, C/T and T/T genotypes between the patient and control groups (P ≤ 0.001*). The genotype (C/T) had a significant association with increased breast cancer risk in the Alexandrian population (OR = 6.907, 95% CI = 3.58–13.32) compared to the C/C genotype, and the mutant allele frequencies of DNMT3B 149 C>T in patients were 30% compared to 8.5% in the control subjects. The corresponding P value, 95% CI and odds ratio (OR) were as follows for the mutant allele: P value ≤ 0.001, 95% CI = 2.58–8.25 and OR = 4.613. (Table 5).

The present results are consistent with a previous study which stated that the DNMT3B -149C/T polymorphism was significantly associated with positive cancer risk in the Caucasian population but not in the African population [39].

In contrast, another study stated that the DNMT3B -149C/T polymorphism was relatively significantly increased head and neck cancer risk but showed no significantly elevated risk of colorectal cancer, breast cancer, hepatocellular cancer, gastric cancer or other cancers, so it was suggested that this SNP was not related to overall cancer risk [40]. This result was consistent with a study suggesting that for the − 149C>T polymorphism, there was no evidence indicating that this SNP may increase the risk of cancer [41]. In addition, a study in southern China demonstrated that DNMT3B  −  149C>T polymorphisms showed no significant associations with BC risk in the Chinese population [42]. A similar result was found in the Iranian population [43].

When using the (+ 6/ + 6) allele as a reference, there was a significant difference in the distribution of the (+ 6/ + 6), (+ 6/− 6) and (− 6/− 6) genotypes of TYMS 3′-UTR 1494del6 between the patients and control groups (P ≤ 0.001*). This observation indicated that the genotype (− 6/− 6) had a significant association with an increased risk of breast cancer in Alexandrian women (OR = 3.294, 95% CI = 1.57–6.91) compared to the (+ 6/ + 6) genotype. The mutant genotype (− 6/− 6) frequencies of TYMS 3′-UTR 1494del6 were 62% and 31% in patients and control subjects, respectively. The mutant allele frequencies of SNPs in patients were 72.5% compared with 51.5% in the controls. The corresponding P value, 95% CI and odds ratio (OR) were as follows for the mutant allele: P value ≤ 0.001, 95% CI = 1.64–3.76 and OR = 2.483.

The current results seemed to be in agreement with a previous study that concluded that the TYMS 3′-UTR polymorphism may be a genetic determinant for developing BC in the Asian population [37]. The same result was found in subjects from northeastern Mexico [44]. In another study, they found that BC risk was associated with the TYMS 3′-UTR 1494del6 polymorphism in nonsmoking and never drinking non-Hispanic white women regardless of tumor stage [45]. Moreover, this SNP has been correlated with BC risk among Asian populations [46]. Furthermore, it has been believed that the TYMS 3′-UTR polymorphism increases BC risk in Turkish women, particularly in the presence of high body mass index (BMI), age 55 years or older, early menarche, late age at first pregnancy and negative smoking history [47].

On the other hand, it has been found that 3′UTR 6-bp ins/del polymorphisms may not be associated with cancer risk according to a meta-analysis of 37 case–control studies [48].

Studied gene expression

The expression of MTHFR was downregulated by 0.62-fold in all malignant tissues compared to normal adjacent tissues (mean ± SD) of 0.57 ± 0.20 with a significant difference (P < 0.001*) in breast cancer tissue compared to the control. The data obtained were in agreement with a previous study [49] where a significant association between the rs1801133 (A222 V) genotypes and an increased risk of BC development was found. Regarding relative gene expression, we found significant mRNA subexpression between the combined genotypes C/T + T/T (rs1801133) and triple-negative breast cancer (TNBC) (P = 0.034). In brief, the MTHFR gene and its protein could act as potential predictive biomarkers of BC [49].

The present study showed no significant difference (P = 0.143) in the expression level of TYMS between breast cancer patients and normal adjacent tissue. Many research groups have assessed the relationship between TYMS polymorphisms and TYMS gene expression; however, the results have been inconclusive with scarce or no data on its expression in BC tissue. Many studies have found a positive correlation between the TSER 3R allele and TYMS protein levels. Horie and his coworkers in 1995 found that the expression activity of a reporter gene linked to the promoter region of the human TYMS genes with the two types of repeated sequences was examined, and the result showed that the expression activity of the gene with the double repeat was lower than that of the gene with the triple repeat in the transient expression assay. Thus, it appears that the unique repeated sequences in the 5′-terminal region of the human TYMS gene are polymorphic and contribute to the efficiency of gene expression [50]. Mauritz and his coworkers did not detect an association between TSER genotype and TYMS activity or mRNA levels in colorectal cancer (CRC) tissue; however, they detected correlations between genotype and TYSM activity/gene expression in normal tissues from the same patients. Nevertheless, this variation in the relationship between TSER genotype and TYSM expression in cancer versus normal tissues may be explained by the complications of gene expression in cancer tissue [51]. Because proliferation, tumor suppression and apoptosis-related protein levels are disturbed in colorectal carcinoma CRC tissue, it makes sense that TYMS genotype and gene expression are associated in normal tissues but not tumors [52].

The level of DNMT3B gene expression showed a significant difference in BC tissue compared with control tissue (P < 0.001*) with upregulation by 165-fold in cancerous tissue. This result is in agreement with many previous studies that found that DNMT3B expression increases in different types of BC and is related to high histological grade [53,54,55]. DNMT3B overexpression is increased not only in BC but also in several types of primary tumors and cell lines of different cancers [56, 57], endometrioid cancers [58] and uterine cervical carcinoma [59].

Overexpression of DNMT3B is correlated with poor disease-free survival (DFS), overall survival (OS) and resistance to treatment [53, 60]. In contrast, DNMT3B expression is downregulated in serous endometrial cancer [58].

Although the level of TYMS gene expression was upregulated in BC tissue by 0.73-fold, there were no significant differences between BC tissue and normal control tissue. It was concluded previously that there was molecular diversity affecting the TYMS gene at the expression level [61]. As there are several functional polymorphisms that affect TYMS expression, the 3′-UTR 1494del6 polymorphism is one of them. Earlier, it had been suggested that the + 6 bp/ + 6 bp genotype had significantly higher TYMS protein expression in breast cancer tissue than did those with other genotypes in breast cancer [62, 63]. An identical correlation between TYMS gene expression and the 3′-UTR 1494del6 polymorphism has been established, and all of them hypothesized that the − 6 bp allele decreases the stability of TYMS mRNA, which influences protein expression [64, 65]. This hypothesis has been tested in a healthy population in Venezuela [66]. A previous study stated that the 3′-UTR 1494del6 polymorphism did not impose any statistically significant influence on mRNA expression levels [67].

On the other hand, not only do TYMS polymorphisms have an impact on the biosynthesis of TYMS, but polymorphisms of other enzymes, such as dihydropyrimidine dehydrogenase (DPYD) and methylenetetrahydrofolate reductase (MTHFR), also have an effect [61]. Moreover, it has been found that the enolase superfamily member 1 (ENOSF1) gene encodes a protein and RNAs antisense to TYMS, which suggests that ENOSF1 regulates TYMS mRNA and/or protein expression [68]. TYMS expression is influenced by multiple factors and the diversity of gene polymorphisms.

In conclusion, the results obtained from the present study clearly indicated that there was no association between the MTHFR C677T genotype and the risk of breast cancer in Egyptian women. However, the 2R/3R TYMS allele and DNMT3B (− 149C>T) SNP are associated with a high risk of breast cancer, and there is a correlation between the 3′-UTR 1494del6 polymorphism (genotype − 6/− 6) and breast cancer risk. At the level of gene expression, there was a significant reduction in the MTHFR gene expression level in breast cancer patients compared with control normal adjacent tissues, and the DNMT3B (− 149C>T) SNP did affect the DNMT3B expression level. Finally, there were no significant differences in the TYMS expression levels in breast cancer patients and control normal adjacent tissues, and the correlation between the 3′-UTR 1494del6 polymorphism and gene expression of TYMS is uncertain and not yet fully understood. Further studies are needed on these associations with special stress on future personalized gene therapy trials.

Availability of data and materials

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Abbreviations

BC:

Breast cancer

BRCA1 :

Breast cancer gene 1

BRCA2 :

Breast cancer gene 2

GWAS:

Genome-wide association studies

SNPs:

Single-nucleotide polymorphisms

MTHFR:

Methyl tetrahydrofolate reductase

SAM:

S-adenosylmethionine

TYMS:

Thymidylate synthase

DNMTs:

DNA methyltransferases

TS:

Thymidylate synthase

TSER:

Thymidylate synthase enhancer region

G/C SNP:

G to C single-nucleotide polymorphism

UTR:

5′ untranslated region

MT:

Malignant breast tissue

NT:

Normal breast tissue

GAPDH:

Glyceraldehyde 3-phosphate dehydrogenase

OR:

Odds ratio

BMI:

Body mass index

TNBC:

Triple-negative breast cancer

CRC:

Colorectal carcinoma

DPTD:

Dihydropyrimidine dehydrogenase

ENOSF1:

Enolase superfamily member 1 gene

References

  1. Hashim MJ, Al-Shamsi FA, Al-Marzooqi NA, Al-Qasemi SS, Mokdad AH, Khan G (2018) Burden of breast cancer in the Arab World: findings from global burden of disease, 2016. JEGH 8:54–58

    Article  PubMed  PubMed Central  Google Scholar 

  2. American Cancer Society (2018) Global cancer facts & figures 4ed. American Cancer Society, Atlanta

    Google Scholar 

  3. Mahvi DA, Liu R, Grinstaff MW, Colson YL, Raut CP (2018) Local cancer recurrence: the realities, challenges, and opportunities for new therapies. CA Cnacer J Clin 68:488–505

    Article  Google Scholar 

  4. Narod A (2018) Personalized medicine and population health: breast and ovarian cancer. Hum Genet 137:769–778

    Article  CAS  PubMed  Google Scholar 

  5. Rivandi M, Martens JW, Hollestelle A (2018) Elucidating the underlying functional mechanisms of breast cancer susceptibility through post-GWAS analyses. Front Genet 2018:9

    Google Scholar 

  6. Patrinos GP, Ansorge WJ, Danielson PB (2016) Molecular diagnostics, 3rd edn. Academic Press, London

    Google Scholar 

  7. Naushad SM, Divya C, Ramaiah MJ, Hussain T, Alrokayan SA, Kutala VK (2016) Population-level diversity in the association of genetic polymorphisms of one-carbon metabolism with breast cancer risk. J Community Genet 7:279–290

    Article  PubMed  PubMed Central  Google Scholar 

  8. Kakkoura MG, Demetriou CA, Loizidou MA, Loucaides G, Neophytou I, Marcou Y et al (2015) Single-nucleotide polymorphisms in one-carbon metabolism genes, Mediterranean diet and breast cancer risk: a case–control study in the Greek-Cypriot female population. Genes Nutr 10:1–5

    Article  CAS  Google Scholar 

  9. Ho V, Massey TE, King WD (2013) Effects of methionine synthase and methylenetetrahydrofolate reductase gene polymorphisms on markers of one-carbon metabolism. Genes Nutr 8:571–580

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  10. Byrd-Bredbenner C, Moe G, Beshgetoor D, Berning J, Kelley D (2019) Wardlaw’s perspectives in nutrition, 11th edn. McGraw-Hill Education, New York

    Google Scholar 

  11. Wang C, Jia Z, Cao D, You L, Jin M, Wu X et al (2015) Polymorphism of DNA methyltransferase 3b and association with development and prognosis in gastric cancer. PLoS ONE 10:e0134059

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  12. Nazki FH, Sameer AS, Ganaie BA (2014) Folate: metabolism, genes, polymorphisms and the associated diseases. Gene 53:11–20

    Article  CAS  Google Scholar 

  13. Aly RM, Taalab MM, Ghazy HF (2014) MTHFR A1298C and C677T gene polymorphisms and susceptibility to chronic myeloid leukemia in Egypt. Int J Clin Exp Pathol 7P:571–2578

    Google Scholar 

  14. Al-Achkar W, Wafa A, Ammar S, Moassass F, Jarjour RA (2018) C677T and A1298C polymorphisms of Methylenetetrahydrofolate reductase (MTHFR) gene: effect and risk to develop chronic myeloid leukemia: a study on Syrian patients. J Genrep 12:230–234

    Google Scholar 

  15. Bănescu C, Iancu M, Trifa AP, Macarie I, Dima D, Dobreanu M (2015) The methylenetetrahydrofolate reductase (MTHFR) 677 C>T polymorphism increases the risk of developing chronic myeloid leukemia a case–control study. Tumor Biol 36:3101–3107

    Article  CAS  Google Scholar 

  16. Ericson U, Sonestedt E, Ivarsson MI, Gullberg B, Carlson J, Olsson H, Wirfält E (2009) Folate intake, methylenetetrahydrofolate reductase polymorphisms, and breast cancer risk in women from the Malmö Diet and Cancer cohort. Cancer Epidemiol Biomarkers Prev 18:1101–1110

    Article  CAS  PubMed  Google Scholar 

  17. Hubner RA, Muir KR, Liu JF, Sellick GS, Logan RF, Grainge M, United Kingdom Colorectal Adenoma Prevention Consortium (2006) Folate metabolism polymorphisms influence risk of colorectal adenoma recurrence. Cancer Epidemiol Biomarkers Prev 15:1607–1613

    Article  CAS  PubMed  Google Scholar 

  18. Liew SC (2016) Folic acid and diseases-supplement it or not? RAMB 62:90–100

    PubMed  Google Scholar 

  19. Niu YM, Deng MH, Chen W, Zeng XT, Luo J (2015) MTHFR C677T gene polymorphism and head and neck cancer risk: a meta-analysis based on 23 publications. Dis Markers 2015:681313

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  20. Van der Put NM, Gabreëls F, Stevens EM, Smeitink JA, Trijbels FJ, Eskes TK, Blom HJ (1998) A second common mutation in the methylenetetrahydrofolate reductase gene: an additional risk factor for neural-tube defects? AJHG 62:1044–1105

    Article  PubMed  PubMed Central  Google Scholar 

  21. Ho V, Massey TE, King WD (2010) Influence of thymidylate synthase gene polymorphisms on total plasma homocysteine concentrations. Mol Genet Metab 101(1):18–24

    Article  CAS  PubMed  Google Scholar 

  22. Marsh S, McKay JA, Cassidy J, McLeod HL (2001) Polymorphism in the thymidylate synthase promoter enhancer region in colorectal cancer. Int J Oncol 9:383–386

    Google Scholar 

  23. Neves M, Ribeiro J, Medeiros R, Sousa H (2016) Genetic polymorphism in DNMTs and gastric cancer: a systematic review and meta-analysis. PBJ 1:164–172

    PubMed  PubMed Central  Google Scholar 

  24. Chung CJ, Chang CH, Liu CS, Huang CP, Chang YH, Chien SN et al (2014) Association of DNA methyltransferases 3A and 3B polymorphisms and plasma folate levels with the risk of urothelial carcinoma. PLoS ONE 9:e104968

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  25. Sambrook J, Russell DW (2001) Molecular cloning: a laboratory MANUAL, 3rd edn. Cold Spring Harbor Laboratory Press, New York

    Google Scholar 

  26. Heather JM, Chain B (2016) The sequence of sequencers: The history of sequencing DNA. J Geno 107:1–8

    Article  CAS  Google Scholar 

  27. Schmittgen TD, ivak KJ. (2008) Analysing real-time PCR data by the comparative C (T) method. Nat Protoc 2008(3):1101–1108

    Article  CAS  Google Scholar 

  28. Yazıcıoğlu B, Kaya Z, Güntekin Ergun S, Perçin F, Koçak Ü, Yenicesu İ et al (2017) Influence of folate-related gene polymorphisms on high-dose methotrexate-related toxicity and prognosis in Turkish children with acute lymphoblastic leukemia. Turk J Haematol 5:143–150

    Article  CAS  Google Scholar 

  29. Tayyeb B, Parvin M (2016) Pathogenesis of breast cancer metastasis to brain: a comprehensive approach to the signaling network. Mol Neurobiol 53:446–454

    Article  CAS  PubMed  Google Scholar 

  30. López-Cortés A, Jaramillo-Koupermann G, Muñoz MJ, Cabrera A, Echeverría C, Paz-y-Miño C, Vivar N (2013) Genetic polymorphisms in MTHFR (C677T, A1298C), MTR (A2756G) and MTRR (A66G) genes associated with pathological characteristics of prostate cancer in the Ecuadorian population. Am J Med Sci 346:447–454

    Article  PubMed  Google Scholar 

  31. Rezende LM, Marson FAL, Lima CSP, Bertuzzo CS (2017) Can MTHFR C677T and A1298C polymorphisms alter the risk and severity of sporadic breast cancer in Brazilian women? CBC 17:e199–e208

    CAS  Google Scholar 

  32. Pooja S, Carlus J, Sekhar D, Francis A, Gupta N, Konwar R, Rajender S (2015) MTHFR 677C> T polymorphism and the risk of breast cancer: evidence from an original study and pooled data for 28031 cases and 31880 controls. PLoS ONE 10:120654

    Google Scholar 

  33. Waseem M, Hussain SR, Kumar S, Serajuddin M, Mahdi F, Sonkar SK (2016) Association of MTHFR (C677T) gene polymorphism with breast cancer in North India. Biomark 8:111–117

    CAS  Google Scholar 

  34. Ramos-Silva A, Figuera LE, Soto-Quintana OM, Puebla-Pérez AM, Ramírez-Patiño R, Gutiérrez-Hurtado I, Gallegos-Arreola MP (2015) Association of the C677T polymorphism in the methylenetetrahydrofolate reductase gene with breast cancer in a Mexican population. Genet Mol Res 2015(14):4015

    Article  CAS  Google Scholar 

  35. Wang J, Shi D, Guo X, Zhang J, Yu S, Song J, Dong W (2014) Thymidylate synthase genetic polymorphisms and colorectal cancer risk: a meta-analysis. CLINRE 38:481–490

    CAS  Google Scholar 

  36. Junior JDSN, de Lima MFA, Bertuzzo CS (2012) Thymidylate synthase gene (TYMS) polymorphisms in sporadic and hereditary breast cancer. BMC Res Notes 5:676

    Article  PubMed Central  CAS  Google Scholar 

  37. Wang J, Wang B, Bi J, Di J (2011) The association between two polymorphisms in the TYMS gene and breast cancer risk: a meta-analysis. Breast Cancer Res Treat 128:203–209

    Article  PubMed  Google Scholar 

  38. Quintero-Ramos A, Gutiérrez-Rubio SA, Del Toro-Arreola A, Franco-Topete RA, Oceguera-Villanueva A, Jiménez-Pérez LM, Daneri-Navarro A (2014) Association between polymorphisms in the thymidylate synthase gene and risk of breast cancer in a Mexican population. Genet Mol Res 13:8749–8756

    Article  CAS  PubMed  Google Scholar 

  39. Duan F, Cui S, Song C, Dai L, Zhao X, Zhang X (2015) Systematic evaluation of cancer risk associated with DNMT3B polymorphisms. J Cancer Res Clin Oncol 141:1205–1220

    Article  CAS  PubMed  Google Scholar 

  40. Zhu J, Du S, Zhang J (2015) Polymorphism of DNA methyltransferase 3B–149C/T and cancer risk: a meta-analysis. Med Oncol 32:399

    Article  PubMed  CAS  Google Scholar 

  41. Zhu S, Zhang H, Tang Y, Liu P, Wang J (2012) DNMT3B polymorphisms and cancer risk: a meta-analysis of 24 case–control studies. Mol Biol Rep 39:4429–4437

    Article  CAS  PubMed  Google Scholar 

  42. Sun M, Yang XX, Xu WW, Yao GY, Pan HZ, Li M (2012) Association of DNMT1 and DNMT3B polymorphisms with breast cancer risk in Han Chinese women from South China. Genet Mol Res 11:4330–4341

    Article  CAS  PubMed  Google Scholar 

  43. Eftekhar E, Rasti M, Nahgibalhossaini F, Sadeghi Y (2014) The study of DNA methyltransferase-3b promoter variant genotype among Iranian sporadic breast cancer patients. Iran. J Med Sci 39:268–274

    PubMed  PubMed Central  Google Scholar 

  44. Jaramillo-Rangel G, Ortega-Martínez M, Cerda-Flores RM, Barrera-Saldaña HA (2017) Polymorphism in the 3′-UTR of the thymidylate synthase gene and breast cancer risk in northeastern Mexico. Int J Clin Exp Med 10:12600–12604

    Google Scholar 

  45. Guan X, Liu H, Ju J, Li Y, Li P, Wang LE et al (2015) Genetic variant rs16430 6 bp > 0 bp at the microRNA-binding site in TYMS and risk of sporadic breast cancer risk in non-hispanic white women aged 55 years. Mol Carcinog 29:281–290

    Article  CAS  Google Scholar 

  46. Zhou JY, Shi R, Yu HL, Zeng Y, Zheng WL, Ma WL (2012) The association between two polymorphisms in the TS gene and risk of cancer: a systematic review and pooled analysis. Int J Cancer 131:2103–2116

    Article  CAS  PubMed  Google Scholar 

  47. Eras N, Nayir E, Arican A, Bahar L, Guler M, Akbas E (2016) TS 1494del6 polymorphism and increased risk of developing breast cancer. Int J Clin Exp Med 9:11756–11763

    CAS  Google Scholar 

  48. Jian T, Wang PP, Zhuang YY, Chen WJ, Huang FT, Zhang SN (2012) Thymidylate synthase genetic polymorphisms and cancer risk: a meta-analysis of 37 case–control studies. Chin Med J 125:2582–2588

    Google Scholar 

  49. López-Cortés A, Echeverría C, Oña-Cisneros F, Sánchez ME, Herrera C, Cabrera-Andrade A, Paz-y-Miño C (2015) Breast cancer risk associated with gene expression and genotype polymorphisms of the folate-metabolizing MTHFR gene: a case–control study in a high-altitude Ecuadorian mestizo population. Tumor Biol 2015(36):6451–6461

    Article  CAS  Google Scholar 

  50. Horie N, Aiba H, Oguro K, Hojo H, Takeishi K (1995) Functional analysis and DNA polymorphism of the tandemly repeated sequences in the 5′-terminal regulatory region of the human gene for thymidylate synthase. Cell Struct Funct 20:191–197

    Article  CAS  PubMed  Google Scholar 

  51. Mauritz R, Giovannetti E, Beumer IJ, Smid K, Van Groeningen CJ, Pinedo HM, Peters GJ (2009) Polymorphisms in the enhancer region of the thymidylate synthase gene are associated with thymidylate synthase levels in normal tissues but not in malignant tissues of patients with colorectal cancer. CCCLC 8:146–154

    CAS  Google Scholar 

  52. Giovannetti E, Backus HHJ, Wouters D, Ferreira CG, Van Houten VMM, Brakenhoff RH, Peters GJ (2007) Changes in the status of p53 affect drug sensitivity to thymidylate synthase (TS) inhibitors by altering TS levels. Br J Cancer 96:769–775

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  53. Jahangiri R, Jamialahmadi K, Gharib M, Razavi AE, Mosaffa F (2019) Expression and clinicopathological significance of DNA methyltransferase 1, 3A and 3B in tamoxifen-treated breast cancer patients. J gene 685:24–31

    Article  CAS  Google Scholar 

  54. Yu J, Qin B, Moyer AM, Nowsheen S, Liu T, Qin S et al (2018) DNA methyltransferase expression in triple-negative breast cancer predicts sensitivity to decitabine. J Clin Investig 128:2376–2388

    Article  PubMed  PubMed Central  Google Scholar 

  55. Mirza S, Sharma G, Parshad R, Gupta SD, Pandya P, Ralhan R (2013) Expression of DNA methyltransferases in breast cancer patients and to analyse the effect of natural compounds on DNA methyltransferases and associated proteins. JBC 16:23–31

    Google Scholar 

  56. Zhang Y, Charlton J, Karnik R, Beerman I, Smith ZD, Gu H et al (2018) Targets and genomic constraints of ectopic Dnmt3b expression. Elife 7:e40757

    Article  PubMed  PubMed Central  Google Scholar 

  57. Peralta-Arrieta I, Hernández-Sotelo D, Castro-Coronel Y, Leyva-Vázquez MA, Illades-Aguiar B (2017) DNMT3B modulates the expression of cancer-related genes and downregulates the expression of the gene VAV3 via methylation. AJCR 7:77–87

    CAS  PubMed  PubMed Central  Google Scholar 

  58. Xiong Y, Dowdy SC, Xue A, Shujuan J, Eberhardt NL, Podratz KC, Jiang SW (2005) Opposite alterations of DNA methyltransferase gene expression in endometrioid and serous endometrial cancers. Gynecol Oncol 96:601–609

    Article  CAS  PubMed  Google Scholar 

  59. Łuczak MW, Roszak A, Pawlik P, Kędzia H, Kędzia W, Malkowska-Walczak B et al (2012) Transcriptional analysis of CXCR4, DNMT3A, DNMT3B and DNMT1 gene expression in primary advanced uterine cervical carcinoma. Int J Oncol 40:860–866

    PubMed  Google Scholar 

  60. Amara K, Ziadi S, Hachana M, Soltani N, Korbi S, Trimeche M (2010) DNA methyltransferase DNMT3b protein overexpression as a prognostic factor in patients with diffuse large B cell lymphomas. Cancer Sci 101:1722–1730

    Article  CAS  PubMed  Google Scholar 

  61. Schwarzenbach H, Goekkurt E, Pantel K, Aust DE, Stoehlmacher J (2010) Molecular analysis of the polymorphisms of thymidylate synthase on cell-free circulating DNA in blood of patients with advanced colorectal carcinoma. IJC 127:881–888

    CAS  Google Scholar 

  62. Fujishima M, Inui H, Hashimoto Y, Azumi T, Yamamoto N, Kato H et al (2010) Relationship between thymidylate synthase (TYMS) gene polymorphism and TYMS protein levels in patients with high-risk breast cancer. Anticancer Res 30:4373–4379

    CAS  PubMed  Google Scholar 

  63. Kumar K, Vamsy M, Jamil K (2010) Thymidylate synthase gene polymorphisms effecting 5-FU response in breast cancer patients. CBM 6:83–93

    Article  CAS  Google Scholar 

  64. Amirfallah A, Kocal G, Unal O, Ellidokuz H, Oztop I, Basbinar Y (2018) DPYD, TYMS and MTHFR genes polymorphism frequencies in a series of Turkish colorectal cancer patients. J Pers Med 8:40–45

    Article  Google Scholar 

  65. Ntavatzikos A, Spathis A, Patapis P, Machairas N, Peros G, Konstantoudakis S et al (2017) Integrating TYMS, KRAS and BRAF testing in patients with metastatic colorectal cancer. World J Gastroenterol 23:5913

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  66. Villegas Mendoza CA, Gregorio Flores-Angulo CJ, Mora Pineda YK, Martínez JA, Oropeza Araujo TC, Moreno N (2015) Thymidylate synthase gen polymorphism 1494del6 in a population from the central region of Venezuela. ABCL 49:321–327

    Google Scholar 

  67. Vignoli M, Nobili S, Napoli C, Putignano AL, Morganti M, Papi L et al (2011) Thymidylate synthase expression and genotype have no major impact on the clinical outcome of colorectal cancer patients treated with 5-fluorouracil. Pharmacol Res 64:242–248

    Article  CAS  PubMed  Google Scholar 

  68. Rosmarin D, Palles C, Pagnamenta A, Kaur K, Pita G, Martin M et al (2015) A candidate gene study of capecitabine-related toxicity in colorectal cancer identifies new toxicity variants at DPYD and a putative role for ENOSF1 rather than TYMS. Gut 64:111–120

    Article  CAS  PubMed  Google Scholar 

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Authors

Contributions

All authors contributed in the research in various ways from collecting samples, tests performance, results analysis, statistical interpretation of results, paper writing and revision. MS and EE collected the patients’ samples, performed analysis of samples and wrote the research article. HS wrote the paper and performed results interpretation and data analysis. AE performed isolation and purification of nucleic acids under investigation and, in addition, interpretation of the results. RR performed fresh breast tissue samples collection and verified the diagnosis of the case through histopathological examination of the tissue specimens. AF performed selection of patients according to the well-defined criteria and surgical operation with obtaining the suitable breast cancer and normal adjunct tissues. ME performed appropriate samples selection according to clinical and laboratory data and interpretation of the results according to clinical, medical impacts and guidelines. In addition, ME participated in writing the research article. All authors read and approved the final manuscript.

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Correspondence to Mona Kamal Eldeeb.

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Eldeeb, M.K., Shoaib, M.M.AE., Abd-Elmonem, E.A. et al. Genetic polymorphisms and gene expression of one-carbon metabolizing enzymes and their relation to breast cancer. Egypt J Med Hum Genet 23, 96 (2022). https://doi.org/10.1186/s43042-022-00296-8

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