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Research ArticleExperimental Studies
Open Access

Contribution of Methylenetetrahydrofolate Reductase Genotypes to Brain Tumor Risk Determination in Taiwan

CHAO-HSUAN CHEN, CHUN-CHUNG CHEN, XIAN-XIU CHEN, WEN-SHIN CHANG, CHIA-WEN TSAI, MEI-CHIN MONG, SHIH-WEI HSU and DA-TIAN BAU
Anticancer Research May 2025, 45 (5) 1861-1870; DOI: https://doi.org/10.21873/anticanres.17565
CHAO-HSUAN CHEN
1Department of Neurosurgery, China Medical University Hospital, Taichung, Taiwan, R.O.C.;
2Department of Surgery, School of Medicine, China Medical University, Taichung, Taiwan, R.O.C.;
3Graduate Institute of Biomedical Sciences, China Medical University, Taichung, Taiwan, R.O.C.;
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CHUN-CHUNG CHEN
1Department of Neurosurgery, China Medical University Hospital, Taichung, Taiwan, R.O.C.;
2Department of Surgery, School of Medicine, China Medical University, Taichung, Taiwan, R.O.C.;
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XIAN-XIU CHEN
1Department of Neurosurgery, China Medical University Hospital, Taichung, Taiwan, R.O.C.;
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WEN-SHIN CHANG
3Graduate Institute of Biomedical Sciences, China Medical University, Taichung, Taiwan, R.O.C.;
4Terry Fox Cancer Research Laboratory, Department of Medical Research, China Medical University Hospital, Taichung, Taiwan, R.O.C.;
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CHIA-WEN TSAI
3Graduate Institute of Biomedical Sciences, China Medical University, Taichung, Taiwan, R.O.C.;
4Terry Fox Cancer Research Laboratory, Department of Medical Research, China Medical University Hospital, Taichung, Taiwan, R.O.C.;
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MEI-CHIN MONG
5Department of Food Nutrition and Health Biotechnology, Asia University, Taichung, Taiwan, R.O.C.;
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SHIH-WEI HSU
3Graduate Institute of Biomedical Sciences, China Medical University, Taichung, Taiwan, R.O.C.;
6National Defense Medical Center, Tri-service General Hospital, Taipei, Taiwan, R.O.C.;
7Taichung Armed Forces General Hospital, Taichung, Taiwan, R.O.C.;
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  • For correspondence: hsushihwei690624@gmail.com
DA-TIAN BAU
3Graduate Institute of Biomedical Sciences, China Medical University, Taichung, Taiwan, R.O.C.;
5Department of Food Nutrition and Health Biotechnology, Asia University, Taichung, Taiwan, R.O.C.;
8Department of Bioinformatics and Medical Engineering, Asia University, Taichung, Taiwan, R.O.C.
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  • For correspondence: 013280@tool.caaumed.org.tw
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Abstract

Background/Aim: Methylenetetrahydrofolate reductase (MTHFR) is an essential enzyme in folate metabolism, playing a critical role in DNA methylation and nucleotide synthesis. Variants of the MTHFR gene have been associated with varying susceptibility to brain tumors, particularly gliomas. This study aimed to investigate the role of MTHFR genotypes in determining brain tumor risk in Taiwan.

Materials and Methods: In this hospital-based case-control study, we assessed the contribution of MTHFR C677T (rs1801133) and A1298C (rs1801131) genotypes to brain tumor risk. A total of 52 patients with brain tumor and 520 age- and sex-matched non-cancer healthy controls were included. Genotyping of MTHFR rs1801133 and rs1801131 was performed using polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP).

Results: Our findings revealed a significant difference in the genotypic distribution of MTHFR rs1801131 between brain tumor cases and non-cancer controls (p for trend=0.0099). Specifically, individuals with the MTHFR rs1801131 homozygous CC genotype demonstrated a 3.69-fold increased risk of brain tumors [95% confidence interval (95%CI)=1.52-9.00, p=0.0062]. In contrast, the AC genotype did not show a statistically significantly increased risk [odds ratio (OR)=1.54, 95%CI=0.83-2.85, p=0.2278]. Allelic frequency analysis revealed that the C allele of MTHFR rs1801131 was associated with an elevated risk of brain tumors (OR=1.83, 95%CI=1.20-2.80, p=0.0071). No significant association was found for MTHFR rs1801133. Stratified analysis showed that the MTHFR rs1801131 CC genotype particularly increased the risk in individuals older than 60 years (OR=4.68, 95%CI=1.42-15.42, p=0.0202) and in females (OR=3.79, 95%CI=1.22-11.77, p=0.0410).

Conclusion: The CC genotype of MTHFR rs1801131 may serve as a valuable marker for brain tumor susceptibility. Stratifying patients with brain tumors based on their MTHFR genotypes could help identify individuals at high risk, enabling more frequent monitoring and preventive measures to reduce the occurrence of brain tumors in Taiwan.

Key Words:
  • Brain tumor
  • genotype
  • methylenetetrahydrofolate reductase (MTHFR)
  • polymorphism
  • Taiwan

Introduction

Among central nervous system neoplasms, malignant gliomas are distinguished by their extreme aggressiveness and poor prognosis (1, 2). Glioblastoma, classified as a grade IV malignant glioma, represents the most prevalent and lethal form of primary brain cancer, characterized by rapid proliferation and extensive infiltration into surrounding brain tissue (3-5). Clinical manifestations often stem from the tumor’s anatomical localization, which can impair neurological function; moreover, neoplastic lesions may remain undetected by magnetic resonance imaging for prolonged periods, further complicating early diagnosis (6-8). Despite advancements in neuroimaging and therapeutic modalities, glioblastoma recurrence typically occurs within 25 to 40 weeks following surgical resection and concurrent chemo-radiotherapy, with a median overall survival of approximately 14 months post-diagnosis (9-12). Therefore, the identification of reliable biomarkers for brain tumor susceptibility and prognosis is crucial for improving early detection and clinical outcomes.

Methylenetetrahydrofolate reductase (MTHFR, EC 1.5.1.20) is a crucial enzyme in the one-carbon metabolism pathway, playing a pivotal role in folate metabolism and homocysteine regulation (13). MTHFR also affects the cell proliferation rates and cancer progression, as tumor cells frequently rely on the folate metabolic process as a major resource of one-carbon units for their essential functions including nucleic acid synthesis and DNA methylation (14-17). The MTHFR gene, located on chromosome 1p36.3, encodes the MTHFR enzyme, which catalyzes the reduction of 5,10-methylenetetrahydrofolate to 5-methyltetrahydrofolate, the predominant circulatory form of folate required for homocysteine remethylation to methionine (18). Genetic polymorphisms within MTHFR, particularly C677T (rs1801133) and A1298C (rs1801131), have been extensively studied due to their impact on enzyme activity and potential associations with various pathological conditions, including cardiovascular diseases (19, 20), neural tube defects (21, 22), and certain types of cancer (23-25). The association between MTHFR genotypes and brain tumor risk remains insufficiently studied, with existing literature being limited and inconclusive (26, 27).

Building on these findings, this study sought to examine the correlation between MTHFR rs1801133 and rs1801131 polymorphisms (Figure 1) and brain tumor susceptibility in a Taiwanese population. The analysis included 52 individuals diagnosed with brain tumors and 520 non-cancer healthy controls.

Figure 1.
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Figure 1.

The physical map for the MTHFR rs1801133 and rs1801131 polymorphic sites.

Materials and Methods

Recruitment of brain tumor cases and non-cancer healthy controls in central Taiwan. A cohort of 52 individuals diagnosed with brain tumors was enrolled from patients undergoing treatment at the Department of General Surgery, China Medical University Hospital. Comprehensive pathological data were systematically recorded for each subject. Controls were selected in a 1:10 ratio, ensuring matching by age and sex. Demographic information, including age and sex, as well as clinical parameters such as metastatic progression and recurrence status, were retrieved from the E-medical recording system. Prior to participation, all individuals provided written informed consent, and venous blood samples (3–5 ml) were collected for genetic analysis, in accordance with ethical approval granted by the Institutional Review Board of China Medical University Hospital (CMUH113-REC2-021). All clinical assessments were conducted in compliance with the ethical guidelines of the Declaration of Helsinki. Table I presents an overview of the demographic and clinical features, including age, sex, metastatic status, and recurrence status, of the study participants.

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Table I.

Subject characteristics and clinical parameters of the brain tumor and control groups.

DNA extraction and storage. In this investigation, genomic DNA was isolated from peripheral blood leukocytes obtained from each subject within 24 hours of sample collection. The extraction process was carried out using the DNA isolation kit (Blossom, Taipei, Taiwan, ROC), following standardized protocols consistent with those applied in other cancer studies. The purified DNA was stored at −80°C for long-term preservation. Furthermore, the DNA samples were diluted, aliquoted, and prepared as working stocks for brain tumor genotyping in accordance with established protocols (28, 29). These working stocks were maintained at −20°C until subsequent analysis.

Determination of brain tumor MTHFR genotypic patterns. Genotyping of MTHFR was conducted following the protocol outlined in our previous study (30). Specific primers for the identification of MTHFR rs1801133 and rs1801131 polymorphisms were designed at the Terry Fox Cancer Research Laboratory. The primer sequences for MTHFR rs1801133 were: forward 5′-TGA AGG AGA AGG TGT CTG CGG GA-3′ and reverse 5′-AGG ACG GTG CGG TGA GAG TG-3′, while those for MTHFR rs1801131 were: forward 5′-GGG AGG AGC TGA CCA GTG CAG-3′ and reverse 5′-GGG GTC AGG CCA GGG GCA G-3′. Polymerase chain reaction (PCR) amplification was performed, with the following cycling parameters: an initial denaturation step at 95°C for 5 min, followed by 35 cycles of denaturation at 95°C for 30 s, annealing at 54°C for 30 s, and extension at 72°C for 1 min, concluding with a final elongation at 72°C for 7 min. The amplified PCR products, 198 bp for MTHFR rs1801133 and 138 bp for MTHFR rs1801131, were subsequently digested using HinfI and Fnu4HI (New England Biolabs, Beverly, MA, USA), respectively. For MTHFR rs1801133, the fragment containing the C allele remained intact (198 bp), whereas that containing the T allele was enzymatically cleaved into fragments of 175 bp and 23 bp. Similarly, for MTHFR rs1801131, the fragment containing the A allele remained undigested (138 bp), while that containing the C allele was cleaved into 119 bp and 19 bp fragments.

Statistical analysis. An unpaired Student’s t-test was employed to compare age distributions between brain tumor and cancer-free control groups. Pearson’s chi-square test with Yates’ correction was applied for all categorical comparisons, including the assessment of associations between MTHFR polymorphisms and brain tumor susceptibility. For stratified analyses, Pearson’s chi-square test with Yates’ correction was used when the expected count per cell was ≥5, whereas Fisher’s exact test was applied for smaller sample sizes (n<5). The association strength was quantified by calculating odds ratios (ORs) with corresponding 95% confidence intervals (CIs). Statistical significance was defined as a p-value less than 0.05.

Results

Demographic characteristics of the brain tumor and non-cancer healthy control groups. The distributions of age and sex were analyzed between the 52 patients with brain tumor and 520 cancer-free control subjects (Table I, upper section). Additionally, the metastatic and recurrence status of brain tumor cases was summarized (Table I, lower section). As the control group was matched to the brain tumor cohort based on age (±5 years) and sex during participant selection, statistical analysis confirmed no significant differences between the two groups for these variables (p=0.6989 and 1.0000, respectively) (Table I, upper section). Furthermore, records indicated that 67.3% of patients with brain tumor had metastatic disease, while 7.7% experienced recurrence (Table I, lower section).

Contribution of MTHFR genotypes to brain tumor risk prediction. The genotypic distribution of MTHFR rs1801131 and rs1801133 among 52 patients with brain tumor and 520 non-cancer healthy controls is summarized in Table II. Notably, the genotype frequencies of MTHFR rs1801133 and rs1801131 in the control group adhered to Hardy-Weinberg equilibrium (p=0.1332 and 0.7909, respectively). A significant difference was observed in the genotypic distribution of MTHFR rs1801131 between patients with brain tumor and healthy controls (p for trend=0.0099) (Table II, upper section). While the heterozygous AC genotype of MTHFR rs1801131 was not significantly associated with brain tumor risk (OR=1.54, 95%CI=0.83-2.85, p=0.2278), individuals carrying the homozygous CC genotype exhibited a 3.69-fold increased risk of brain tumors (95%CI=1.52-9.00, p=0.0062). Furthermore, when comparing individuals with the CC genotype to those with either the AA or AC genotype, the odds ratio (OR) for brain tumor development was 3.08 (95%CI=1.33-7.14, p=0.0145) (Table II, upper section). In a dominant model analysis, carriers of the AC or CC genotypes exhibited a borderline increased risk of brain tumors (OR=1.83, 95%CI=1.03-3.25, p=0.0522) compared to individuals with the AA genotype (Table II, upper section). In contrast, no significant differences were identified in the distribution of MTHFR rs1801133 genotypes across any of the models analyzed (Table II, lower section).

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Table II.

Distribution of MTHFR genotypes among the controls and brain tumor cases.

Association of MTHFR allelic frequencies with brain tumor risk. To confirm the preliminary findings presented in Table II, an allelic frequency analysis was performed to assess the association between MTHFR rs1801131 and rs1801133 polymorphisms and brain tumor risk, with the results summarized in Table III. A significant difference in the distribution of the variant C allele of MTHFR rs1801131 was observed between patients with brain tumor and healthy controls (p=0.0071). Carriers of the C allele exhibited a 1.83-fold increased odds of developing brain tumors (OR=1.83, 95%CI=1.20-2.80) compared to those carrying the wild-type A allele (Table III). In contrast, the presence of the variant T allele in MTHFR rs1801133 was not significantly associated with brain tumor risk (OR=1.42, 95%CI=0.93-2.18, p=0.1303).

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Table III.

Allelic frequencies for MTHFR genotypes among the controls and brain tumor patients.

Interactions of MTHFR rs1801131 genotypes with demographic and clinical indexes. First, a subgroup analysis was performed to examine the distribution of MTHFR rs1801131 genotypes among patients with brain tumor stratified by age, comparing those younger than 60 years with those aged 60 years or older. The results revealed no significant difference in genotype distribution between these age groups (p=0.6254, Table IV). Similarly, no significant sex-based differences were observed in the distribution of MTHFR rs1801131 genotypes between male and female patients (p=0.7862, Table IV). Further validation across the entire cohort confirmed that the variant CC genotype of MTHFR rs1801131 is associated with an increased susceptibility to brain tumors, particularly among individuals aged 60 years or older (OR=4.68, 95%CI=1.42-15.42, p=0.0202) (Table V) and females (OR=3.79, 95%CI=1.22-11.77, p=0.0410) (Table VI).

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Table IV.

Correlation between MTHFR rs1801131 genotype and demographic features of and brain tumor patients.

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Table V.

Distribution of MTHFR rs1801131 genotypes among brain tumor patients and 600 controls after stratification by age.

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Table VI.

Distribution of MTHFR rs1801131 genotypes among brain tumor patients and 600 controls after stratification by sex.

Discussion

MTHFR is a key enzyme involved in folate and homocysteine metabolism (13, 31), with an inverse association between its enzymatic activity and circulating homocysteine concentrations (32). Variations in MTHFR, along with vitamin B12 deficiency, have been implicated in modulating its function. Among these genetic variants, the MTHFR rs1801133 polymorphism, particularly the TT genotype, is characterized by thermolabile instability, leading to a substantial reduction in enzymatic activity and subsequent hyperhomocysteinemia (33, 34). This enzymatic impairment has been linked to metabolic alterations in both the highly anabolic neural parenchyma and the energy-demanding glioblastoma microenvironment (35). Nevertheless, our current investigation did not reveal a significant difference in the genotypic distribution of MTHFR rs1801133 between individuals with brain tumors and cancer-free controls (Table II).

Although MTHFR rs1801131 has been less extensively studied compared to rs1801133, the C allele of MTHFR rs1801131 has been associated with reduced MTHFR enzyme activity, similarly to the T allele of MTHFR rs1801133 (36). Low folate levels can decrease the availability of 5-methyltetrahydrofolate, impairing the remethylation process and leading to homocysteine accumulation (37, 38). While the precise mechanisms linking hyperhomocysteinemia to brain tumor development remain largely unclear, total homocysteine levels in the bloodstream have been proposed as a potential biomarker for monitoring patients with primary malignant brain tumor both before and after surgery (39). Therefore, individuals carrying the MTHFR rs1801131 CC genotype may experience higher homocysteine levels, potentially correlating with an increased risk of brain tumors.

Studies investigating MTHFR genotypic profiles in brain tumors remain relatively scarce in the literature. A pioneering study by Linnebank and his colleagues, published in 2008, followed a cohort of 214 patients with glioblastoma over a 10-year period to examine the impact of MTHFR genotypes on patient survival. Their findings suggested that the MTHFR rs1801133 T variant was associated with a poorer overall survival rate in patients with glioblastoma (40). In the same year, a study from Thailand identified that the homozygous CC allele of MTHFR rs1801131 increased the risk of developing embryonal central nervous system tumors (41). Notably, Bethke and colleagues conducted an extensive global study with 1101 controls and 1005 patients with glioma, revealing that the MTHFR rs1801131-rs1801133 diplotypes were significantly associated with glioma risk (36). Conversely, a 2015 study by Greenop and colleagues found no significant effect of either MTHFR rs1801131 or rs1801133 genotypes on the susceptibility to pediatric brain tumors in an Australian cohort (42). The following year, Tanyildiz and his colleagues reported that the MTHFR rs1801131 CC genotype was significantly associated with pediatric glioma in a cohort recruited over 10 years (43). In 2018, Pandith’s team published data from an Indian glioma cohort, which found no significant association between MTHFR rs1801133 genotypes and glioma risk (44). The challenge of collecting brain tumor samples due to their rarity makes such studies difficult to conduct, contributing to the limited number of investigations in this field.

Our findings suggest the potential application of folic acid supplementation as a therapeutic strategy for patients with brain tumor, with the possibility of extending this approach to other human diseases as well. Previous research has highlighted the role of homocysteine in various health conditions, including its impact on bone metabolism and inflammation (45, 46). For example, in pregnant women, MTHFR polymorphisms, including rs1801131, have been studied for their role in neural tube defects (NTDs) (21, 47, 48). Adequate folic acid intake is critical for reducing the risk of NTDs, particularly for individuals carrying genetic variants that affect folate metabolism. Furthermore, in neurological and psychiatric disorders such as depression (49, 50) and schizophrenia (51, 52), MTHFR polymorphisms have been linked to altered folate metabolism and an increased risk of these conditions. Folic acid supplementation may thus offer therapeutic benefits in such cases.

An intriguing finding from our study is that individuals older than 60 years (both males and females) who carry the CC genotype at MTHFR rs1801131 exhibit a higher risk of brain tumors compared to their younger counterparts (Table V). In terms of sex, carriers of the MTHFR rs1801131 CC genotype were found to be at an increased risk for brain tumors in both males and females (Table VI). However, the results reached statistical significance only in the female group (Table VI). This discrepancy may be attributed to the limited sample size analyzed. To better understand the interactions between MTHFR genotypes and demographic factors such as age and sex, as well as lifestyle and clinical parameters, further studies with larger and more diverse ethnic cohorts are needed.

Conclusion

Our pilot study offers preliminary evidence indicating that the variant C allele at MTHFR rs1801131 may act as a predictive marker for brain tumor risk in the Taiwanese population. However, further research is needed to better understand the mechanisms by which MTHFR genotypes and folate metabolism contribute to brain tumor development. Additionally, folic acid supplementation therapy could potentially play a role in the prevention and treatment of brain tumors, warranting further exploration in clinical studies.

Acknowledgements

The Authors are grateful to Hou-Yu Shih, Yun-Chi Wang and Yi-Wen Hung for their technical support. The cooperation of all the participants is highly appreciated. This study was financially supported by Taichung Armed Forces General Hospital (TCAFGH_D_114008) and China Medical University and Asia University (CMU113-ASIA-02).

Footnotes

  • Authors’ Contributions

    Conceptualization: Chen CH, Bau DT, and Hsu SW; Data curation: Chen CH, Chen XX, and Chen CC; Formal analysis: Chen CH, Chang WS, and Tsai CW; Methodology: Mong MC, Chen CH, and Hsu SW; Investigation: Mong MC, Chen CH, and Hsu SW; Writing – original draft: Hsu SW, Tsai CW, and Bau DT; Writing – review and editing: Hsu SW and Bau DT.

  • Conflicts of Interest

    The Authors declare no conflicts of interest regarding this study.

  • Artificial Intelligence (AI) Disclosure

    No artificial intelligence (AI) tools, including large language models or machine learning software, were used in the preparation, analysis, or presentation of this manuscript.

  • Received March 31, 2025.
  • Revision received April 10, 2025.
  • Accepted April 11, 2025.
  • Copyright © 2025 International Institute of Anticancer Research (Dr. George J. Delinasios), All rights reserved.

This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY-NC-ND) 4.0 international license (https://creativecommons.org/licenses/by-nc-nd/4.0).

References

  1. ↵
    1. Lim M,
    2. Xia Y,
    3. Bettegowda C,
    4. Weller M
    : Current state of immunotherapy for glioblastoma. Nat Rev Clin Oncol 15(7): 422-442, 2018. DOI: 10.1038/s41571-018-0003-5
    OpenUrlCrossRefPubMed
  2. ↵
    1. Zheng Y,
    2. Fuse H,
    3. Alzoubi I,
    4. Graeber MB
    : Microglia-derived brain macrophages associate with glioblastoma stem cells: a potential mechanism for tumor progression revealed by AI-assisted analysis. Cells 14(6): 413, 2025. DOI: 10.3390/cells14060413
    OpenUrlCrossRef
  3. ↵
    1. Gomes I,
    2. Oliveira RJDS,
    3. Girol AP
    : Signaling pathways in glioblastoma. Crit Rev Oncol Hematol 209: 104647, 2025. DOI: 10.1016/j.critrevonc.2025.104647
    OpenUrlCrossRefPubMed
    1. Luo D,
    2. Xu X,
    3. Li J,
    4. Chen C,
    5. Chen W,
    6. Wang F,
    7. Xie Y,
    8. Li F
    : The PDK1/c-Jun pathway activated by TGF-β induces EMT and promotes proliferation and invasion in human glioblastoma. Int J Oncol 53(5): 2067-2080, 2018. DOI: 10.3892/ijo.2018.4525
    OpenUrlCrossRefPubMed
  4. ↵
    1. Taslimi S,
    2. Brogly S,
    3. Hanna TP,
    4. Shellenberger J,
    5. Whitehead M,
    6. Alkins R
    : A population-based cohort study of glioblastoma (World Health Organization Grade 4 Gliomas) in Ontario: continued improvement in care over 25 years. World Neurosurg 196: 123821, 2025. DOI: 10.1016/j.wneu.2025.123821
    OpenUrlCrossRefPubMed
  5. ↵
    1. Ramya M,
    2. Kirupa G,
    3. Rama A
    : Brain tumor classification of magnetic resonance images using a novel CNN-based medical image analysis and detection network in comparison with AlexNet. J Popul Ther Clin Pharmacol 29(1): e97-e108, 2022. DOI: 10.47750/jptcp.2022.898
    OpenUrlCrossRef
    1. Sankareswaran SP,
    2. Krishnan M
    : Unsupervised end-to-end brain tumor magnetic resonance image registration using RBCNN: rigid transformation, B-spline transformation and convolutional neural network. Curr Med Imaging 18(4): 387-397, 2022. DOI: 10.2174/1573405617666210806125526
    OpenUrlCrossRefPubMed
  6. ↵
    1. Gyorfi A,
    2. Kovacs L,
    3. Szilagyi L
    : A feature ranking and selection algorithm for brain tumor segmentation in multi-spectral magnetic resonance image data. Annu Int Conf IEEE Eng Med Biol Soc 2019: 804-807, 2019. DOI: 10.1109/EMBC.2019.8857794
    OpenUrlCrossRefPubMed
  7. ↵
    1. Luckett PH,
    2. Olufawo M,
    3. Lamichhane B,
    4. Park KY,
    5. Dierker D,
    6. Verastegui GT,
    7. Yang P,
    8. Kim AH,
    9. Chheda MG,
    10. Snyder AZ,
    11. Shimony JS,
    12. Leuthardt EC
    : Predicting survival in glioblastoma with multimodal neuroimaging and machine learning. J Neurooncol 164(2): 309-320, 2023. DOI: 10.1007/s11060-023-04439-8
    OpenUrlCrossRefPubMed
    1. Chang K,
    2. Zhang B,
    3. Guo X,
    4. Zong M,
    5. Rahman R,
    6. Sanchez D,
    7. Winder N,
    8. Reardon DA,
    9. Zhao B,
    10. Wen PY,
    11. Huang RY
    : Multimodal imaging patterns predict survival in recurrent glioblastoma patients treated with bevacizumab. Neuro Oncol 18(12): 1680-1687, 2016. DOI: 10.1093/neuonc/now086
    OpenUrlCrossRefPubMed
    1. Delgado-López PD,
    2. Corrales-García EM
    : Survival in glioblastoma: A review on the impact of treatment modalities. Clin Transl Oncol 18(11): 1062-1071, 2016. DOI: 10.1007/s12094-016-1497-x
    OpenUrlCrossRefPubMed
  8. ↵
    1. Rajesh Y,
    2. Pal I,
    3. Banik P,
    4. Chakraborty S,
    5. Borkar SA,
    6. Dey G,
    7. Mukherjee A,
    8. Mandal M
    : Insights into molecular therapy of glioma: current challenges and next generation blueprint. Acta Pharmacol Sin 38(5): 591-613, 2017. DOI: 10.1038/aps.2016.167
    OpenUrlCrossRefPubMed
  9. ↵
    1. Raghubeer S,
    2. Matsha TE
    : Methylenetetrahydrofolate (MTHFR), the one-carbon cycle, and cardiovascular risks. Nutrients 13(12): 4562, 2021. DOI: 10.3390/nu13124562
    OpenUrlCrossRefPubMed
  10. ↵
    1. Lemée JM,
    2. Clavreul A,
    3. Menei P
    : Intratumoral heterogeneity in glioblastoma: don’t forget the peritumoral brain zone. Neuro Oncol 17(10): 1322-1332, 2015. DOI: 10.1093/neuonc/nov119
    OpenUrlCrossRefPubMed
    1. Pavlova NN,
    2. Thompson CB
    : The emerging hallmarks of cancer metabolism. Cell Metab 23(1): 27-47, 2016. DOI: 10.1016/j.cmet.2015.12.006
    OpenUrlCrossRefPubMed
    1. Cheng TY,
    2. Makar KW,
    3. Neuhouser ML,
    4. Miller JW,
    5. Song X,
    6. Brown EC,
    7. Beresford SA,
    8. Zheng Y,
    9. Poole EM,
    10. Galbraith RL,
    11. Duggan DJ,
    12. Habermann N,
    13. Bailey LB,
    14. Maneval DR,
    15. Caudill MA,
    16. Toriola AT,
    17. Green R,
    18. Ulrich CM
    : Folate-mediated one-carbon metabolism genes and interactions with nutritional factors on colorectal cancer risk: Women’s Health Initiative Observational Study. Cancer 121(20): 3684-3691, 2015. DOI: 10.1002/cncr.29465
    OpenUrlCrossRefPubMed
  11. ↵
    1. Kinnaird A,
    2. Zhao S,
    3. Wellen KE,
    4. Michelakis ED
    : Metabolic control of epigenetics in cancer. Nat Rev Cancer 16(11): 694-707, 2016. DOI: 10.1038/nrc.2016.82
    OpenUrlCrossRefPubMed
  12. ↵
    1. Cai Y,
    2. Liu B,
    3. Zhang Y,
    4. Zhou Y
    : MTHFR gene polymorphisms in diabetes mellitus. Clin Chim Acta 561: 119825, 2024. DOI: 10.1016/j.cca.2024.119825
    OpenUrlCrossRef
  13. ↵
    1. Siddiqi SM,
    2. Liu L,
    3. Du Y,
    4. Song Y,
    5. Chen P,
    6. Li S,
    7. He Q,
    8. Zhou Z,
    9. Xu J,
    10. Bai J,
    11. Wang B,
    12. Qin X,
    13. Mehmood A,
    14. Xiuqing L,
    15. Cheng X,
    16. Shi HP
    : Association of MTHFR C677T, MTHFRA1298C, and MTRRA66G gene polymorphisms with hyperhomocysteinemia and its modulation by the combined effect of vitamin B12 and folate in Chinese population with hypertension. J Nutr, 2024. DOI: 10.1016/j.tjnut.2024.09.003
    OpenUrlCrossRef
  14. ↵
    1. Söderström E,
    2. Andersson J,
    3. Söderberg S,
    4. van Guelpen B,
    5. Nilsson TK,
    6. Hultdin J
    : CTH G1208T and MTHFR A1298C polymorphisms are associated with a higher risk of a first myocardial infarction with fatal outcome among women. Drug Metab Pers Ther 38(1): 57-63, 2023. DOI: 10.1515/dmpt-2022-0119
    OpenUrlCrossRefPubMed
  15. ↵
    1. Nasri K,
    2. Ben Jamaa N,
    3. Gaigi SS,
    4. Feki M,
    5. Marrakchi R
    : Association of MTHFR (C677T, A1298C) and MTRR A66G polymorphisms with fatty acids profile and risk of neural tube defects. Birth Defects Res 116(5): e2333, 2024. DOI: 10.1002/bdr2.2333
    OpenUrlCrossRef
  16. ↵
    1. Nasri K,
    2. Midani F,
    3. Kallel A,
    4. Ben Jemaa N,
    5. Aloui M,
    6. Boulares M,
    7. Lassoued M,
    8. Ben Halima M,
    9. Ben Wafi S,
    10. Soussi M,
    11. Mahjoubi I,
    12. Baara A,
    13. Ben Fradj MK,
    14. Omar S,
    15. Feki M,
    16. Jemaa R,
    17. Gaigi SS,
    18. Marrakchi R
    : Association of MTHFR C677T, MTHFR A1298C, and MTRR A66G polymorphisms with neural tube defects in Tunisian parents. Pathobiology 86(4): 190-200, 2019. DOI: 10.1159/000499498
    OpenUrlCrossRefPubMed
  17. ↵
    1. He Q,
    2. Wei Y,
    3. Zhu H,
    4. Liang Q,
    5. Chen P,
    6. Li S,
    7. Song Y,
    8. Liu L,
    9. Wang B,
    10. Xu X,
    11. Dong Y
    : The combined effect of MTHFR C677T and A1298C polymorphisms on the risk of digestive system cancer among a hypertensive population. Discov Oncol 15(1): 97, 2024. DOI: 10.1007/s12672-024-00960-y
    OpenUrlCrossRefPubMed
    1. Alkanli N,
    2. Ay A
    : Investigation of the roles of MTHFR (C677T and A1298C) and MMP-2 (−1306C>T) variations in bladder cancer development. Urol Res Pract 49(1): 33-39, 2023. DOI: 10.5152/tud.2023.22185
    OpenUrlCrossRefPubMed
  18. ↵
    1. Mouhoub-Terrab R,
    2. Chibane AA,
    3. Khelil M
    : No association between MTHFR gene C677T/A1298C polymorphisms, serum folate, vitamin B12, homocysteine levels, and prostate cancer in an Algerian population. Mol Genet Genomic Med 11(9): e2194, 2023. DOI: 10.1002/mgg3.2194
    OpenUrlCrossRef
  19. ↵
    1. Xu C,
    2. Yuan L,
    3. Tian H,
    4. Cao H,
    5. Chen S
    : Association of the MTHFR C677T polymorphism with primary brain tumor risk. Tumour Biol 34(6): 3457-3464, 2013. DOI: 10.1007/s13277-013-0922-9
    OpenUrlCrossRefPubMed
  20. ↵
    1. Salnikova LE,
    2. Belopolskaya OB,
    3. Zelinskaya NI,
    4. Rubanovich AV
    : The potential effect of gender in CYP1A1 and GSTM1 genotype-specific associations with pediatric brain tumor. Tumour Biol 34(5): 2709-2719, 2013. DOI: 10.1007/s13277-013-0823-y
    OpenUrlCrossRefPubMed
  21. ↵
    1. Hung CC,
    2. Wang YC,
    3. Shih HY,
    4. Liu CH,
    5. He JL,
    6. Chen JC,
    7. Chang WS,
    8. Su CH,
    9. Bau DT,
    10. Tsai CW
    : Significant association of matrix metalloproteinase-9 polymorphisms with triple negative breast cancer risk. Cancer Genomics Proteomics 22(2): 258-270, 2025. DOI: 10.21873/cgp.20500
    OpenUrlAbstract/FREE Full Text
  22. ↵
    1. Yang MD,
    2. Lin KC,
    3. Lu MC,
    4. Jeng LB,
    5. Hsiao CL,
    6. Yueh TC,
    7. Fu CK,
    8. Li HT,
    9. Yen ST,
    10. Lin CW,
    11. Wu CW,
    12. Pang SY,
    13. Bau DT,
    14. Tsai FJ
    : Contribution of matrix metalloproteinases-1 genotypes to gastric cancer susceptibility in Taiwan. Biomedicine (Taipei) 7(2): 10, 2017. DOI: 10.1051/bmdcn/2017070203
    OpenUrlCrossRefPubMed
  23. ↵
    1. Kuo CC,
    2. Tsai CH,
    3. Chuang FK,
    4. Wang YC,
    5. Mong MC,
    6. Yang YC,
    7. Shih HY,
    8. Hsu SW,
    9. Chang WS,
    10. Bau DT,
    11. Tsai CW
    : Impacts of methylenetetrahydrofolate reductase genotypes on hallux valgus. In Vivo 39(1): 172-179, 2025. DOI: 10.21873/invivo.13815
    OpenUrlAbstract/FREE Full Text
  24. ↵
    1. Clement A,
    2. Viot G,
    3. Elder K,
    4. Clement P,
    5. Menezo YJR
    : Can some metabolic one-carbon cycle linked diseases be prevented? The impact of treating hypo-fertile couples carrying MTHFR SNPs with folic acid and 5-MTHF on outcomes in the offspring: a case retrospective series. J Assist Reprod Genet 42(2): 533-539, 2025. DOI: 10.1007/s10815-024-03343-y
    OpenUrlCrossRefPubMed
  25. ↵
    1. Varga EA,
    2. Sturm AC,
    3. Misita CP,
    4. Moll S
    : Homocysteine and MTHFR mutations: relation to thrombosis and coronary artery disease. Circulation 111(19): e289-93, 2005. DOI: 10.1161/01.CIR.0000165142.37711.E7
    OpenUrlFREE Full Text
  26. ↵
    1. Yuan H,
    2. Fu M,
    3. Yang X,
    4. Huang K,
    5. Ren X
    : Single nucleotide polymorphism of MTHFR rs1801133 associated with elevated Hcy levels affects susceptibility to cerebral small vessel disease. PeerJ 8: e8627, 2020. DOI: 10.7717/peerj.8627
    OpenUrlCrossRefPubMed
  27. ↵
    1. Wang XB,
    2. Qiao C,
    3. Wei L,
    4. Han YD,
    5. Cui NH,
    6. Huang ZL,
    7. Li ZH,
    8. Zheng F,
    9. Yan M
    : Associations of polymorphisms in MTHFR gene with the risk of age-related cataract in Chinese Han population: a genotype-phenotype analysis. PLoS One 10(12): e0145581, 2015. DOI: 10.1371/journal.pone.0145581
    OpenUrlCrossRefPubMed
  28. ↵
    1. Raichle ME
    : The restless brain: how intrinsic activity organizes brain function. Philos Trans R Soc Lond B Biol Sci 370(1668): 20140172, 2015. DOI: 10.1098/rstb.2014.0172
    OpenUrlCrossRefPubMed
  29. ↵
    1. Bethke L,
    2. Webb E,
    3. Murray A,
    4. Schoemaker M,
    5. Feychting M,
    6. Lönn S,
    7. Ahlbom A,
    8. Malmer B,
    9. Henriksson R,
    10. Auvinen A,
    11. Kiuru A,
    12. Salminen T,
    13. Johansen C,
    14. Christensen HC,
    15. Muir K,
    16. McKinney P,
    17. Hepworth S,
    18. Dimitropoulou P,
    19. Lophatananon A,
    20. Swerdlow A,
    21. Houlston R
    : Functional polymorphisms in folate metabolism genes influence the risk of meningioma and glioma. Cancer Epidemiol Biomarkers Prev 17(5): 1195-1202, 2008. DOI: 10.1158/1055-9965.EPI-07-2733
    OpenUrlAbstract/FREE Full Text
  30. ↵
    1. Li W,
    2. Ma X,
    3. Sun Y,
    4. Dong Y,
    5. Cai Y,
    6. Shu J,
    7. Li D,
    8. Yu X,
    9. Cai C
    : RNA sequencing combined with whole-exome sequencing revealed familial homocystinemia due to MTHFR deficiency and its complex splicing events. Gene 936: 149101, 2025. DOI: 10.1016/j.gene.2024.149101
    OpenUrlCrossRefPubMed
  31. ↵
    1. Petrone I,
    2. Bernardo PS,
    3. Dos Santos EC,
    4. Abdelhay E
    : MTHFR C677T and A1298C polymorphisms in breast cancer, gliomas and gastric cancer: a review. Genes (Basel) 12(4): 587, 2021. DOI: 10.3390/genes12040587
    OpenUrlCrossRefPubMed
  32. ↵
    1. Djurovic Z,
    2. Jovanovic V,
    3. Obrenovic R,
    4. Djurovic B,
    5. Soldatovic I,
    6. Vranic A,
    7. Jakovljevic V,
    8. Djuric D,
    9. Zivkovic V
    : The importance of the blood levels of homocysteine, folate and vitamin B12 in patients with primary malignant brain tumors. J BUON 25(6): 2600-2607, 2020.
    OpenUrlPubMed
  33. ↵
    1. Linnebank M,
    2. Semmler A,
    3. Moskau S,
    4. Smulders Y,
    5. Blom H,
    6. Simon M
    : The methylenetetrahydrofolate reductase (MTHFR) variant c.677C>T (A222V) influences overall survival of patients with glioblastoma multiforme. Neuro Oncol 10(4): 548-552, 2008. DOI: 10.1215/15228517-2008-020
    OpenUrlCrossRefPubMed
  34. ↵
    1. Sirachainan N,
    2. Wongruangsri S,
    3. Kajanachumpol S,
    4. Pakakasama S,
    5. Visudtibhan A,
    6. Nuchprayoon I,
    7. Lusawat A,
    8. Phudhicharoenrat S,
    9. Shuangshoti S,
    10. Hongeng S
    : Folate pathway genetic polymorphisms and susceptibility of central nervous system tumors in Thai children. Cancer Detect Prev 32(1): 72-78, 2008. DOI: 10.1016/j.cdp.2008.02.004
    OpenUrlCrossRefPubMed
  35. ↵
    1. Greenop KR,
    2. Scott RJ,
    3. Attia J,
    4. Bower C,
    5. de Klerk NH,
    6. Norris MD,
    7. Haber M,
    8. Jamieson SE,
    9. Van Bockxmeer FM,
    10. Gottardo NG,
    11. Ashton LJ,
    12. Armstrong BK,
    13. Milne E
    : Folate pathway gene polymorphisms and risk of childhood brain tumors: results from an Australian case–control study. Cancer Epidemiol Biomarkers Prev 24(6): 931-937, 2015. DOI: 10.1158/1055-9965.EPI-14-1248
    OpenUrlAbstract/FREE Full Text
  36. ↵
    1. Tanyıldız HG,
    2. Yeşil Ş,
    3. Bozkurt C,
    4. Çandır MO,
    5. Akpınar-Tekgündüz S,
    6. Toprak Ş,
    7. Yüksel D,
    8. Şahin G
    : Are the methylenetetrahydrofolate reductase 1298 and 677 gene polymorphisms related to optic glioma and hamartoma risk in neurofibromatosis type 1 patients? Turk J Pediatr 58(2): 152-158, 2016. DOI: 10.24953/turkjped.2016.02.005
    OpenUrlCrossRefPubMed
  37. ↵
    1. Pandith AA,
    2. Qasim I,
    3. Zahoor W,
    4. Shah P,
    5. Bhat AR
    : ACE I/D sequence variants but not MTHFR C677T, is strongly linked to malignant glioma risk and its variant DD genotype may act as a promising predictive biomarker for overall survival of glioma patients. Gene 639: 62-68, 2018. DOI: 10.1016/j.gene.2017.10.013
    OpenUrlCrossRefPubMed
  38. ↵
    1. Saito M,
    2. Marumo K
    : The effects of homocysteine on the skeleton. Curr Osteoporos Rep 16(5): 554-560, 2018. DOI: 10.1007/s11914-018-0469-1
    OpenUrlCrossRefPubMed
  39. ↵
    1. De Martinis M,
    2. Sirufo MM,
    3. Nocelli C,
    4. Fontanella L,
    5. Ginaldi L
    : Hyperhomocysteinemia is associated with inflammation, bone resorption, vitamin B12 and folate deficiency and MTHFR C677T polymorphism in postmenopausal women with decreased bone mineral density. Int J Environ Res Public Health 17(12): 4260, 2020. DOI: 10.3390/ijerph17124260
    OpenUrlCrossRefPubMed
  40. ↵
    1. Singh NK,
    2. Choudhary S,
    3. Rai S,
    4. Yadav AK,
    5. Singh R
    : Association between the MTHFR (rs1801133) gene variation and serum trace elements levels (Copper and Zinc) in individuals diagnosed with neural tube defects. Clin Chim Acta 562: 119856, 2024. DOI: 10.1016/j.cca.2024.119856
    OpenUrlCrossRef
  41. ↵
    1. Finsterer J
    : Neural tube defects are not only associated with polymorphisms in MTHFR or MTR but with pathogenic variants in numerous other genes. J Indian Assoc Pediatr Surg 29(1): 86-87, 2024. DOI: 10.4103/jiaps.jiaps_112_23
    OpenUrlCrossRef
  42. ↵
    1. Pawlik P,
    2. Kurzawińska G,
    3. Ożarowski M,
    4. Wolski H,
    5. Piątek K,
    6. Słopień R,
    7. Sajdak S,
    8. Olbromski P,
    9. Seremak-Mrozikiewicz A
    : Common variants in one-carbon metabolism genes (MTHFR, MTR, MTHFD1) and depression in gynecologic cancers. Int J Mol Sci 24(16): 12574, 2023. DOI: 10.3390/ijms241612574
    OpenUrlCrossRefPubMed
  43. ↵
    1. Stengler M
    : The role of folate and MTHFR polymorphisms in the treatment of depression. Altern Ther Health Med 27(2): 53-57, 2021.
    OpenUrlPubMed
  44. ↵
    1. Wan L,
    2. Wei J
    : Early-onset schizophrenia: a special phenotype of the disease characterized by increased MTHFR polymorphisms and aggravating symptoms. Neuropsychiatr Dis Treat 17: 2511-2525, 2021. DOI: 10.2147/NDT.S320680
    OpenUrlCrossRefPubMed
  45. ↵
    1. Liao J,
    2. Wang N,
    3. Ma M,
    4. Lu T,
    5. Yan H,
    6. Yue W
    : C677T polymorphism in the MTHFR gene is associated with risperidone-induced weight gain in schizophrenia. Front Psychiatry 11: 617, 2020. DOI: 10.3389/fpsyt.2020.00617
    OpenUrlCrossRefPubMed
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Anticancer Research: 45 (5)
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Contribution of Methylenetetrahydrofolate Reductase Genotypes to Brain Tumor Risk Determination in Taiwan
CHAO-HSUAN CHEN, CHUN-CHUNG CHEN, XIAN-XIU CHEN, WEN-SHIN CHANG, CHIA-WEN TSAI, MEI-CHIN MONG, SHIH-WEI HSU, DA-TIAN BAU
Anticancer Research May 2025, 45 (5) 1861-1870; DOI: 10.21873/anticanres.17565

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Contribution of Methylenetetrahydrofolate Reductase Genotypes to Brain Tumor Risk Determination in Taiwan
CHAO-HSUAN CHEN, CHUN-CHUNG CHEN, XIAN-XIU CHEN, WEN-SHIN CHANG, CHIA-WEN TSAI, MEI-CHIN MONG, SHIH-WEI HSU, DA-TIAN BAU
Anticancer Research May 2025, 45 (5) 1861-1870; DOI: 10.21873/anticanres.17565
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Keywords

  • Brain tumor
  • genotype
  • methylenetetrahydrofolate reductase (MTHFR)
  • polymorphism
  • Taiwan
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