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Table of Contents   
SYSTEMATIC REVIEW  
Year : 2014  |  Volume : 25  |  Issue : 6  |  Page : 797-805
Promoter hypermethylation patterns of P16, DAPK and MGMT in Oral Squamous Cell Carcinoma: A systematic review and meta-analysis


1 Department of Oral and Maxillofacial Pathology, Saveetha Dental College, Chennai, Tamil Nadu, India
2 Department of Preventive Oncology, Research Division, Cancer Institute (WIA), Adyar, Chennai, Tamil Nadu, India

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Date of Submission16-Jul-2014
Date of Decision14-Aug-2014
Date of Acceptance15-Jan-2015
Date of Web Publication02-Mar-2015
 

   Abstract 

Background: Oral squamous cell carcinoma (OSCC) is a common cancer world-wide that is highly lethal due to its recurrence and metastasis. Methylation is a common epigenetic mechanism that leads to gene silencing in tumors and could be a useful biomarker in OSCC. The prevalence of P16, death-associated protein kinase (DAPK) and O 6 -methylguanine-DNA-methyltransferase (MGMT) promoter hypermethylation in OSCC has been evaluated for several years while the results remain controversial.
Objective: The aim of this systematic review is to critically analyze and perform a meta-analysis on the various studies in the literature that have reported the promoter hypermethylation of P16, DAPK and MGMT genes in OSCC.
Search Strategy: Articles were searched and selected through PubMed. Hand search from the relevant journals was also performed. Articles were reviewed and analyzed.
Results: The estimated prevalence of P16 methylation was 43%, DAPK methylation was 39.7% and MGMT methylation was 39.8%. Heterogeneity in methylation prevalences and correlations with the clinical outcomes of the disease prevailed in various studies.
Conclusion: We can conclude from our systematic review that a higher prevalence of methylation of P16, DAPK and MGMT occur in OSCC. Further studies are required to substantiate the role of methylation of P16, DAPK and MGMT as a marker in OSCC.

Keywords: Death-associated protein kinase, O 6 -methylguanine-DNA-methyltransferase, oral squamous cell carcinoma, P16, promoter hypermethylation

How to cite this article:
Don K R, Ramani P, Ramshankar V, Sherlin HJ, Premkumar P, Natesan A. Promoter hypermethylation patterns of P16, DAPK and MGMT in Oral Squamous Cell Carcinoma: A systematic review and meta-analysis. Indian J Dent Res 2014;25:797-805

How to cite this URL:
Don K R, Ramani P, Ramshankar V, Sherlin HJ, Premkumar P, Natesan A. Promoter hypermethylation patterns of P16, DAPK and MGMT in Oral Squamous Cell Carcinoma: A systematic review and meta-analysis. Indian J Dent Res [serial online] 2014 [cited 2019 Oct 19];25:797-805. Available from: http://www.ijdr.in/text.asp?2014/25/6/797/152208
The term "oral cancer" refers to malignancy arising from oral tissues. Carcinoma is the term for a malignant tumor of epithelial origin. Oral cancer is the most frequent cancer of the head and neck region, with squamous cell carcinoma being by far the most common single entity, accounting alone for about 90-95% of all malignancies of the oral cavity.

Oral squamous cell carcinoma (OSCC) is the sixth most common malignancy in the world. Approximately, 405,000 cases of OSCC are diagnosed each year, with a rising incidence in many countries. [1] Due to its relative high mortality and low cure rate, OSCC represents a major public health problem. The WHO acknowledged that the 5 years survival rate of these patients has not improved over the past few decades despite treatment advances. [2],[3] Early detection of OSCC is important to reduce mortality rates and to help provide successful cancer treatment.

The etiology of OSCC is multifactorial and involves intrinsic and extrinsic factors. The major risk factors include tobacco and alcohol intake, as well as human papillomavirus infection. [4],[5] These predisposing factors may lead to a wide range of genetic and epigenetic events that promote genomic instability and tumor development and progression.

The genetic alterations involved in the development and progression of OSCC are caused by irreversible changes in DNA sequence including gene deletions, amplifications and mutations leading both to oncogenes activation or tumor-suppressor genes inactivation. [6],[7]

Epigenetics is another major event in the development and progression of OSCC. The epigenetic changes refer to any reversible heritable modifications in gene expression without alterations of the DNA sequence. They occur more frequently than gene mutations. [8]

Methylation is a common epigenetic mechanism that leads to gene silencing in tumors and could be a useful biomarker in OSCC. DNA methylation refers to the covalent addition of a methyl group which usually takes place at the 5' position of the cytosine residues of CpG nucleotides. The CpG dinucleotides are found in 1/80 dinucleotides in 98% of the human genome. They are usually present in regions called CpG islands, which are usually located at promoter regions of the gene. [9] CpG islands have >55% GC content and span > 500 bp. Methylation serves to decrease expression of a gene. CpG islands are often found hypermethylated in tumors, causing the transcriptional "silencing" of tumor-suppressor genes, contributing to cancer progression. On the contrary, it also serves as a mechanism of oncogene activation by hypo/demethylation.

The enzymes directly responsible for CpG island hypermethylation of tumor-suppressor genes are known as DNA-methyltransferases. The methylated-cytosine-guanine sequences are recognized by methyl-cytosine binding proteins, which in turn help in binding of histone deacetylase enzyme. This results in the removal of acetyl groups from histone. This leads to aggregation of nucleosomes to form the heterochromatin, which results in transcriptional silencing of gene.

The genes found hypermethylated in OSCC cover a wide range of cellular processes, including cell cycle control (P16, P15, P14), apoptosis (death-associated protein kinase [DAPK], RASSF1A), Wnt signaling (APC, WIF1), cell-cell adhesion (E-cadherin), and DNA-repair (O 6 -methylgua nine-DNA-methyltransferase [MGMT], hMLH1). [10]

In this review, we assessed the promoter region hypermethylation of P16, MGMT, and DAPK in OSCC.

The cyclin-dependent kinase inhibitor (CDKI) p16 belongs to INK4 family and is involved in cell cycle control. INK4 family of CDKIs include p16 (CDKN2A), p15 (CDKN2B), p18 (CDKN2C), and p19 (CDKN2D). INK4 family has selective effects on cyclin D/CDK4 and cyclin D/CDK6. P16 (INK4a) binds to cyclin D-CDK4 and thereby inhibits CDK4 and promotes the inhibitory effects of retinoblastoma protein (RB) by preventing phosphorylation of RB. CDKN2A gene maps on chromosome 9p21.3 and induces cell cycle arrest in the G1 phase.

O 6 -methylguanine-DNA-methyltransferase gene is located on chromosome 10q26, which encodes MGMT, a DNA-repair enzyme that removes O 6 -guanine-DNA adducts caused by alkylating agents. CpG island hypermethylation of the MGMT promoter region results in gene silencing with loss of MGMT repair capacity which is thought to drive cancer progression. Epigenetic silencing of MGMT has been associated with OSCCs where tobacco exposure and betel quid chewing are suspected to be etiological factors. [11] Elevated MGMT expression has been associated with resistance to alkylating chemotherapeutic agents. [12]

Death-associated protein kinase 1 gene maps on chromosome 9q34.1. DAPK encodes a pro-apoptotic calcium/calmodulin regulated serine/threonine kinase that is required for apoptosis induced by interferon-gamma (IFN-g). [13] Loss of its expression via promoter hypermethylation has been associated with the formation of metastases and advanced disease stages in multiple cancer types, including head and neck cancers. [14] Regarding OSCCs, DAPK hypermethylation has been reported as associated with an increased likelihood of lymph node involvement.


   Methods Top


0Search strategy for identification of studies

The search strategy was in accordance with the Cochrane guidelines for systematic reviews. Articles relevant to the search strategy were identified from search databases of PubMed, Medline till the year 2013. Due to the scarcity of methylation pattern studies in OSCC, we wished to exhaust all the possible articles; therefore, a timeline was not included in the search. The article search included only those published in the English literature. The internet search was also done to obtain the relevant articles of our interest. The title of the articles and abstracts was reviewed. The full text of selected articles were retrieved and further analyzed.

Search methodology

The search methodology applied in PubMed was using the following keywords:

Search ((((((((hypermethylation) OR DNA hypermethylation) OR CpG island hypermethylation) OR promoter hypermethylation)) AND ((((((((((P16) OR P16 gene) OR P16 INK4a) OR P16 expression) OR inhibitory kinase4A) OR CDKN2A) OR cyclin CDKI2A) OR INK4A) OR MTS1) OR multiple tumor-suppressor 1)) OR ((((((DAPK) OR DAPK1) OR DAPK gene) OR DAPK expression) OR DAPK) OR DAPK gene)) OR (((((MGMT) OR MGMT gene) OR MGMT expression) OR MGMT) OR MGMT gene)) AND (((((((((oral cancer) OR oral carcinoma) OR oral squamous cancer) OR oral squamous carcinoma) OR oral squamous cell cancer) OR OSCC) OR squamous cell carcinoma of oral cavity) OR SCC of oral cavity) OR OSCC).

In addition, the internet search was also done using the key words "promoter hypermethylation" and "P16 DAPK and MGMT" and "OSCC." Articles in which patients had confirmed with a diagnosis of OSCC with or without the control group regardless of the stage of the tumor were considered for this review.

Selection of studies

Inclusion criteria

  • Studies that evaluated the promoter hypermethylation patterns of P16, DAPK and MGMT genes in OSCC
  • Studies in which P16, DAPK and MGMT methylation status was examined using methylation-specific PCR (MSP) or quantitative MSP or restriction-multiplex PCR or nested PCR
  • Studies in which the specimens used for methylation analysis include fresh cancer tissues samples or formalin fixed paraffin-embedded tissues
  • Studies in which the same patient population reported in several publications, only the most recent report or the most complete one with more number of sample size was included in this analysis in order to avoid overlapping between cohorts
  • Studies that have undertaken a minimal of 20 samples of OSCC patients
  • Studies in English language were included.


Exclusion criteria

  • Studies in which methylations examined in the cell lines were excluded
  • Studies conducted on animal models were excluded
  • Studies conducted on patients who were under radiotherapy and chemotherapy was excluded.
Methods of review

The selection and exclusion of the reviewed studies are summarized in [Figure 1]. The search strategy identified 16 studies that evaluated the promoter hypermethylation of P16, DAPK and MGMT genes in OSCC. The description of the individual studies is shown in [Table 1] and that of the excluded studies in [Table 2].
Figure 1: Flow chart showing selection and exclusion of the reviewed studies

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Table 1: Description of included studies

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Table 2: Description of excluded studies

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Data extraction

Once the articles to be reviewed were finalized, data were extracted from each article, tabulated and was verified and interpreted, and a meta-analysis was performed.

Outcomes

The outcomes assessed in this review examined and analyzed the promoter hypermethylation patterns of P16, DAPK and MGMT genes in OSCC.


   Results Top


0Included studies

Out of the 16 included studies, the frequencies of promoter hypermethylation of P16 gene in OSCC were evaluated in 15 studies, the frequencies of promoter hypermethylation of DAPK gene in OSCC were evaluated in five studies and the frequencies of promoter hypermethylation of MGMT gene in OSCC were evaluated in eight studies. So, three separate meta-analysis was performed to assess the methylation status of P16, DAPK and MGMT genes in OSCC. The description of the individual studies included for each meta-analysis is shown in [Table 3] [Table 4] [Table 5] respectively. The data of the studies were analyzed to check for heterogeneity and publication bias.
Table 3: Studies included in meta‑analysis of P16 methylation status

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Table 4: Studies included in meta‑analysis of DAPK methylation status

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Table 5: Studies included in meta‑analysis of MGMT methylation status

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Outcomes

Our meta-analysis data of P16 methylation status showed that the overall estimated pooled prevalence of P16 methylation among 932 OSCC cases in 15 studies was 43% (confidence interval [CI] = 40-46%). Heterogeneity of results among studies prevailed [Figure 2] and [Figure 5].
Figure 2: Chart depicting the frequency of P16 methylation found by different authors

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The funnel plot analysis for prevalence of P16 methylation in OSCC cases showed heterogeneity. Only 6 studies out of 15 fall within the funnel clearly indicating publication bias [Figure 6].

Our meta-analysis data of DAPK methylation status showed that the overall estimated pooled prevalence of DAPK methylation among 330 OSCC cases in five studies was 39.7% (CI = 15.0-64.3%). Heterogeneity of results among studies prevailed [Figure 3] and [Figure 7].
Figure 3: Chart depicting the frequency of death-associated protein kinase methylation found by different authors

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The funnel plot analysis for prevalence of DAPK methylation in OSCC cases showed heterogeneity. None of the studies fall inside the funnel clearly indicating publication bias [Figure 8].

Our meta-analysis data of MGMT methylation status showed that the overall estimated pooled prevalence of MGMT methylation among 509 OSCC cases in eight studies was 39.8% (CI = 25.2-54.3%). Heterogeneity of results among studies prevailed [Figure 4] and [Figure 9].
Figure 4: Chart depicting the frequency of O6-methylguanine-DNAmethyltransferase methylation found by different authors

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The funnel plot analysis for prevalence of MGMT methylation in OSCC cases showed heterogeneity. Five studies out of eight fall inside the funnel indicating little publication bias [Figure 10].
Figure 5: Forrest plot of P16 promoter methylation in oral squamous cell carcinoma

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Figure 6: Funnel plot of studies with P16 promoter methylation

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Figure 7: Forrest plot of DAPK promoter methylation in oral squamous cell carcinoma

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Figure 8: Funnel plot of studies with death-associated protein kinase promoter methylation

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Figure 9: Forrest plot of O6-methylguanine-DNA-methyltransferase promoter methylation in oral squamous cell carcinoma

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Figure 10: Funnel plot of studies with O6-methylguanine-DNAmethyltransferase promoter methylation

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Correlation of studies with clinicopathological data

Yakushiji et al. reported that there was no statistical significance on comparing methylation of P16 with clinicopathological stages. [16]

Ogi et al. reported that methylation of P16 correlated with younger age (P = 0.043) and T-category (P = 0.038). [18]

Viswanathan et al. reported that abnormal methylation of P16 and MGMT was detected in tumors irrespective of stage and location in the oral cavity. [19]

Kulkarni and Saranath reported that there was no significant association between the clinicopathological profile of the patients, including the size of the tumor, presence of lymph node metastasis, differentiation of the tumors, tumor-node-metastasis staging of the cancer, and sex or age of the patients, and hypermethylation of P16, DAPK and MGMT. [20]

Ishida et al. reported that tumor size, degree of differentiation, clinical stage, and frequency of metastasis to nodes were significantly associated with hypermethylation of P16. He reported that there was no significant correlation between MGMT and clinicopathological factors. He also reported that an apparent correlation between overall gene hypermethylation status of P16 and MGMT, tobacco use, alcohol consumption, and concurrent exposure to both substances was observed. [21]

Kato et al. reported that there was no relationship between methylation status of P16 and MGMT with clinicopathological features. [23]

Sailasree et al. reported that promoter methylation of P16 was associated with tumor size, nodal involvement and increased disease recurrence. [24]

Supic et al. reported that there was no correlation of methylation status of P16, DAPK and MGMT genes with clinicopathological features but reported that hypermethylation of P16 gene promoter showed tendency of increase with age, with cutoff point selected according to the median value of 58. [25]

Kordi-Tamandani et al. reported that there was no correlation of methylation status of MGMT with clinical features (age and sex) and stages of cancer. He also reported that MGMT methylation may be considered as a potential molecular marker for the poor survival in advanced OSCC. [27]

Su et al. reported that the hypermethylation status of P16, DAPK and MGMT in tumors did not depend on clinicopathological features such as gender, lifestyle, tumor stage, recurrence, or histologic differentiation. Nevertheless, he reported that the mean age of patients with hypermethylated P16 was lesser than those without (P = 0.027). Multiple logistic regression predicted patients with hypermethylated P16 have higher risks of lymph node invasion (adjusted odds ratio [OR] = 6.21, P = 0.030) in young patients and distant metastasis (adjusted OR = 19.23, P = 0.007) in older patients. Moreover, P16 promoter hypermethylation was significantly associated with shortened disease-free survival (P = 0.034) in older patients. [28]

Kaur et al. reported that P16 promoter methylation was significantly associated with nodal involvement (P = 0.04, OR = 3.3, 95% CI = 1.1-10.2). [29]

Wong et al. reported that frequencies of P16, DAPK, and MGMT gene promoter hypermethylation did not differ based on the tumor site (P > 0.05). Promoter hypermethylation rates of the P16, DAPK, and MGMT genes were not correlated with tumor size, differentiation, betel nut chewing, tobacco smoking, or alcohol consumption (P > 0.05). Methylation rates of MGMT (50%) and DAPK (55.6%) in metastasized OSCC were higher than those of MGMT (23.9%) and DAPK (41.3%) in nonmetastasized OSCC. He also reported that hypermethylated P16 promoters were found in 63% of nonmetastasized tumors and in 77.8% of metastatic tumors (but was not statistically significant). [30]


   Discussion Top


Oral squamous cell carcinoma is the sixth most common malignancy in the world. Due to its relative high mortality and low cure rate, OSCC represents a major health problem. Early detection of OSCC is important to reduce mortality rates and to help provide successful cancer treatment. Carcinogenesis is a multistep process. The genetic and epigenetic alterations are involved in the development and progression of OSCC.

Gene-specific promoter alterations are common epigenetic aberrations found in human tumors. Hypermethylation of CpG islands in promoter regions is one of the important mechanisms for inactivation of tumor-suppressor genes involving apoptosis, cell cycle control, DNA-repair, cell-cell adhesion and Wnt signaling. The prevalence of P16, DAPK and MGMT promoter hypermethylation in OSCC has been evaluated for several years while the results remain controversial.

The effects of methylation have been studied in various genes over recent years, extracting genetic material from cells in tumors and potentially malignant disorders, saliva, serum, or healthy tissue adjacent to the tumor. This is because methylation can be detected in tumors and potentially malignant disorders and even in clinically and histologically healthy tissue adjacent to the tumor, suggesting that methylation may occur early in oral carcinogenesis and might serve as an early marker of the disease. [39]

P16/INK4A is known as one the most important tumor-suppressor genes which plays an important role in regulating the cell cycle. Hypermethylation of the CDKN2A promoter region has been extensively evaluated in oral cancers with the frequency of hypermethylation being reported from 28% to 86%. [15],[20] Aberrant methylation of P16 gene has not been detected in noncancer controls. [19],[ 34]

Tran et al. reported that in betel chewing individuals with oral cancer, P16 methylation was detected in 63% of OSCCs and 67% of verrucous carcinomas. [22]

A correlation was also found between P16 methylation and higher-grade dysplasia. [35] In studies on precancerous lesions, it was reported that P16 methylation was not related to the malignant transformation of lichen planus but was significantly associated with the malignant transformation of leukoplakia, especially in relation to tobacco use. [6]

Death-associated protein kinase encodes a serine/threonine kinase that is required for apoptosis induced by IFN-g. Sanchez-Cespedes et al. reported that the promoter hypermethylation of DAPK has been associated with the formation of metastasis and advanced stages of cancer. [14]

Supic et al. reported that the detection of DAPK promoter hypermethylation at resection margins of oral tumors has been significantly associated with decreased overall survival, suggesting that it may have utility as a biomarker for guiding patient follow-up strategies.

O 6 -methylguanine-DNA-methyltransferase is a DNA-repair gene that protects from toxicity and mutations that occur by alkylating agents through the removal of O 6 -guanine-DNA adducts. MGMT hypermethylation has been reported for many cancer types.

Zuo et al. reported that MGMT promoter hypermethylation has also been associated with poorer outcomes for oral cancer, including a greater likelihood of nodal metastases, tumor recurrence, and decreased survival. [40]

Although many studies have reported the prevalence of P16, DAPK and MGMT gene hypermethylation in OSCC, the results remain inconclusive with the reasons of small sample size. Thus, a meta-analysis was performed by pooling data from published studies, which can increase the statistical power.

In the present study, a total of 16 articles were selected based on inclusion and exclusion criteria, from which the pooled prevalence of methylation in OSCC cases was calculated. Three separate meta-analysis was performed to assess the methylation status of P16, DAPK and MGMT genes in OSCC.

Our meta-analysis data of P16 methylation status showed that the overall estimated pooled prevalence of P16 methylation among 932 OSCC cases in 15 studies was 43% (CI = 40-46%). Heterogeneity of results among studies prevailed. From the present analysis, we found that Kulkarni and Saranath, Tran et al., Supic et al., Ohta et al. and Wong et al. studies showed a higher P16 methylation prevalence which range from 58% to 67% and Ogi et al., Viswanathan et al., Sailasree et al. and Su et al. studies showed a lower P16 methylation prevalence which range from 23% to 29%.

Our meta-analysis data of DAPK methylation status showed that the overall estimated pooled prevalence of DAPK methylation among 330 OSCC cases in five studies was 39.7% (CI = 15.0-64.3%). Heterogeneity of results among studies prevailed. From the present analysis, we found that Kulkarni and Saranath study showed a higher DAPK methylation prevalence which was 68.3% and Ogi et al. study showed a lower DAPK methylation prevalence which was 7% only.

Our meta-analysis data of MGMT methylation status showed that the overall estimated pooled prevalence of MGMT methylation among 509 OSCC cases in eight studies was 39.8% (CI = 25.2-54.3%). Heterogeneity of results among studies prevailed. From the present analysis, we found that Kulkarni and Saranath, Kato et al. and Kordi-Tamandani et al. studies showed a higher MGMT methylation prevalence which range from 52% to 74% and Ishida et al. and Su et al. studies showed a lower MGMT methylation prevalence which range from 12% to 21%.

The heterogeneity in methylation patterns in different studies may arise from difference in age, gender, ethnicity, and sample size, the location of the study group, smoking status, other adverse habits status, tumor stages, histopathology types and methods of methylation detection.

Despite significant epigenetic alterations found in OSCC, hypermethylation prevalences and correlations with the clinical outcomes of the disease in various studies are inconsistent. These differences probably reflect the heterogeneity of OSCC in their histology and clinical behavior, with different etiologies and associated risk factors, and known tissue and tumor-type specificity of methylation pattern. OSCCs originated from different locations of the oral region showed different methylation pattern.

The higher percentage of methylation in India may reflect the inherent differences in the prevalent molecular pathway in a majority of the chewing tobacco-associated cancers, as compared to oral cancers in USA, UK, Japan, and other developed countries, where the cancer is primarily associated with tobacco smoking and with/without alcohol consumption. [20]

To summarize, multiple studies show that a higher prevalence of methylation of P16, DAPK and MGMT occur in OSCC and the promoter hypermethylation of P16, DAPK and MGMT can be used for early detection of oral cancer and play a role in oral cancer progression.

Limitations of the review

We acknowledge the potential presence of publication bias within this review. The number of articles reviewed is minimal. This is due to the scarcity of studies available in promoter methylation pattern in OSCC. Our search also included publications in the English literature only. No unpublished data were included. The data used for pooled analysis were taken from published articles instead of original data. Further studies must be performed with similar outcome measures that could be compared in order to generate a more homogenous group of data. This could aid in giving better systematic reviews in the future in this field of study.


   Conclusion Top


We can conclude from our systematic review that a higher prevalence of methylation of P16, DAPK and MGMT genes occur in OSCC cases. The promoter hypermethylation of P16, DAPK and MGMT genes play a role in oral cancer progression and can be used for early detection of oral cancer.

Heterogeneity in methylation patterns in different studies prevail which may arise from difference in age, gender, ethnicity, and sample size, the location of the study group, smoking status, other adverse habits status, tumor stages, histopathology types and methods of methylation detection.

Further studies must be performed with large sample sizes and with similar outcome measures that could be compared in order to generate a more homogenous group of data. This could aid in giving better systematic reviews in the future in this field of study.

 
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Correspondence Address:
K R Don
Department of Oral and Maxillofacial Pathology, Saveetha Dental College, Chennai, Tamil Nadu
India
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Source of Support: None, Conflict of Interest: None


DOI: 10.4103/0970-9290.152208

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