Epigenetic Silencing of DAPK1and p16^INK4a Genes by CpG Island Hypermethylation in Epithelial Ovarian Cancer Patients

Abstract

Transcriptional silencing induced by hypermethylation of CpG islands in the promoter regions of genes is believed to be an important mechanism of carcinogenesis in human cancers including epithelial ovarian cancer (EOC). Previously published data on gene methylation of EOC focused mainly on single gene or on cancer tissues. Objectives of the study were to estimate the promoter hypermethylation status of DAPK1 and p16^INK4a genes in circulating blood of EOC patients and to determine their association with clinicopathological features of EOC. This case–control study included 50 EOC patients and 20 apparently healthy and age matched female controls. Isolation of genomic DNA was carried out from peripheral venous blood. Methylation in promoter region of DAPK1 and p16^INK4a genes was determined by methylation-specific PCR. Methylation of DAPK1 was occurred in 42 out of 50 cases (84.0%) and methylation of p16^INK4a gene was occurred in 34 out of 50 cases (68.0%). Methylation of both genes was occurred in 25 cases (50.0%). Occurrence of methylation in DAPK1 and p16^INK4a genes was statistically significant (p < 0.0001) in cases compared to controls. Methylation of both genes was not statistically associated with age at diagnosis, menopausal status, histopathological types and FIGO staging of EOC. Identification of the peculiar promoter hypermethylation of DAPK1 and p16^INK4a genes might be a successful approach for ancillary diagnosis of EOC at early stage in blood sample.

Introduction

Cancer has a strong genetic pathology and arises either due to accumulated somatic cell mutations or loss of functions of tumor suppressor genes. Some of the distinctive features of cancer include gain of function of certain oncogenes and loss of function of tumor suppressor genes [1]. Ovarian cancer is a lethal gynaecological malignancy and a major cause of cancer-related deaths worldwide. Timely diagnosis is demanding because of the non-specific symptoms exhibited during the early stage of ovarian cancer [2, 3]. Lot of studies have recognized association of oncogenes like RAS and tumor suppressors like p53 with ovarian cancer, [4, 5] however these being linked to innumerable of other cancers mandates devising the unique approaches for early diagnosis. One such approach can be analysing the epigenetic signatures of prominent tumour suppressor genes in a large cohort of patients and evaluate if epigenetic signatures could serve as tools for early diagnosis.

The “methylator” phenotype has been described in several haematological and solid neoplasms and involves in pathways of development, differentiation, cell-cycle control, DNA repair, detoxification and apoptosis [6]. DNA methylation occurs on the number 5 carbon of the pyrimidine ring of cytosine within the context of the CpG dinucleotide in mammalian species. DNA methylation is mediated by a family of highly concomitant DNA methyltransferase enzymes (DNMT1, DNMT3A, DNMT3B), which carry a methyl group from S-adenosyl-l-methionine to cytosines in CpG dinucleotides. DNMT1 maintains the DNA methylation patterns in somatic cells, whereas DNMT3A and DNMT3B help in DNA methylation during embryo development [7].

Tumour suppressor gene (TSG) inactivation by promoter region CpG island hypermethylation occurs in almost all cancer types and is an important mechanism of gene inactivation in cancer. The hypermethylation of the promoter CpG islands has been imputative with transcription inactivation of a number of tumour suppressor genes in tumours, which are transcribed and hypomethylated in their natural counterparts. So, hypermethylated CpG island(s) of genes have been regarded as an abnormality, suggestive to the loss of heterozygosity or other types of genetic deletion for total inactivation of the tumour suppressor genes in cancer [8]. DAPK1 [9, 10] and p16^INK4a [11, 12] genes have been frequently hypermethylated in various cancers including ovarian cancer.

DAPK1 gene encodes for death-associated protein kinase-1 which has been associated with suppression of oncogenesis process through positive mediator of apoptosis [13]. P16^INK4a gene encodes for p16^INK4a protein which is a member of cyclin dependent kinase inhibitors (CDKI) and it binds with cyclin-CDK complex and arrests the cell cycle process at G1 phase, result in inhibition of oncogenesis [14]. Ovarian cancer is linked to DNA methylation leading to silencing of tumor suppressor genes like DAPK1 and p16^INK4a and they have pathogenetic role in ovarian cancer development and progression [10, 12].

Aberrant DNA methylation of DAPK1 and p16 gene has been found in circulating blood of ovarian cancer patients. Blood-based DNA methylation is also derived from DNA extracted from circulating whole blood cells. Ovarian cancer along with aging process causes differential gene methylation pattern in cells of hematopoietic lineage and also causes changes in cellular contents in circulating blood. Thus, epigenetic changes in peripheral blood can also detect in active ovarian cancer [15]. Collins Y et al. have also detected aberrant DAPK1 hypermethylation in peripheral blood of epithelial ovarian cancer by methylation-specific polymerase chain reaction [16].

So based on above background, objectives of study were to estimate the promoter hypermethylation status of DAPK1 and p16^INK4a genes in circulating blood of EOC patients and to determine their association with clinicopathological features of EOC. Hypermethylation of DAPK1 and p16^INK4a gene can be used as analytical markers for the development of a non-invasive and cost-effective MSP-based test, which further helps in identification of gene cellular transformation events which are associated with promoter hypermethylation in patients of EOC.

Methods

This case–control study was carried out in Molecular Oncology Laboratory of Biochemistry Department, Maulana Azad Medical College and associated Lok Nayak Hospital, New Delhi. Fifty EOC patients were taken as cases and 20 age matched apparently healthy females were taken as controls. EOC cases were assessed clinicopathologically by well-designed questionnaire, clinical examination and histopathology reports. Diagnosis of EOC was finalized by two experienced pathologists. International Federation of Gynecology and Obstetrics (FIGO) staging system was used for staging of EOC.

Selection Criteria of Patients

Inclusion Criteria

Newly diagnosed and histopathologically confirmed epithelial ovarian cancer patients were included in the study.

Exclusion Criteria

Participants present with past history of any type of cancers and metastatic cancer from any other organs were excluded from the study.

Sample Collection

Around 3 ml of venous blood was collected in EDTA vials from cases after confirming the diagnosis of EOC and also from healthy female controls.

DNA Extraction and Bisulfite Process

DNA was isolated from whole blood by commercially available Gene Aid’s DNA Mini Kit. The purity of DNA was checked on spectrophotometer by ratio of absorbance at 260 nm and at 280 nm (A₂₆₀/A₂₈₀). Samples of DNA which had A₂₆₀/A₂₈₀ ratio of 1.7–2.0 were chosen for further analysis. DNA quality was also checked on 1% agarose gel after staining with ethidium bromide (EtBr). We used Zymo kit (Zymo Research, CA, USA) for conversion of cytosine to uracil residues by bisulfite treatment. Based on their quality control and published reports it is known that bisulfite conversion kits are > 97% efficient in conversion of cytosine to uracil [17]. This process was done at 95 °C for 20 min for complete conversion of unmethylated cytosine into uracil and further DNA was stored at − 80 °C before performing MSP.

Methylation Specific PCR (MSP)

Differentiation between unmethylated (U) and methylated (M) DNA was done by MSP which used specific set of primers [18, 19] as shown in Table 1. Converted DNA, Dream Taq master mix (Fermentas) and 20 pmol of oligonucleotides were mixed and mixture of 25 µl was made to carry out MSP. MSP was programmed for 45 s at 94 °C, 50 s for 62 °C and 45 s for 72 °C, for total 45 consecutive cycles. We used adequate unmethylated negative internal control of healthy controls in our MS-PCR to reduce false positive results. Methylation status of amplified products was visualized on 3% agarose gel after staining with EtBr under UV illumination. DAPK1 methylated and unmethylated status were visualized as band size of 98 bp and 103 bp respectively (Fig. 1a). p16^INK44 methylated and unmethylated status were visualized as band size of 150 bp and 151 bp respectively (Fig. 1b). We used MSP for discriminating methylated versus unmethylated DNA fractions. The DNA signature is changed by conversion of cytosine to uracil by bisulfite conversion method and then the methylated sequences are selectively amplified with primers specific for methylation (Fig. 2).

Table 1.

Primer sequence for MS-PCR used for methylation of DAPK1 and p16^INK4a genes

Primer	Primer sequence	Product size (bp)	Annealing temperature (°C)
DAPK1 (M) F1	5′GGATAGTCGGATCGAGTTAACGTC 3′	103	60
DAPK1 (M) R1	5′CCCTCCCAAACGCCGA 3′
DAPK1 (U) F2	5′GGAGGATAGTTGGATTGAGTTAATGTT 3′	98	60
DAPK1 (U) R2	5′CAAATCCCTCCCAAACACCAA 3′
p16INK4a (M) F1	5′ TTATTAGAGGGTGGGGCGGATCGC 3′	150	65
p16INK4a (M) R1	5′-GACCCCGAACCGCGACCGTAA 3′
p16INK4a (U) F2	5′ TTATTAGAGGGTGGGGTGGATTGT 3′	151	60
p16INK4a (M)R2	5′ CAACCCCAAACCACAACCATAA 3′

Fig. 1.

DAPK1and p16^INK4a methylation status in circulating blood DNA of EOC patients. a Agarose gel (3%) electrophoresis band pattern of amplified MS-PCR product for methylated DAPK1 gene, b Agarose gel (3%) electrophoresis band pattern of amplified MS-PCR product for methylated p16^INK4a gene. M methylated, U unmethylated, L ladder

Fig. 2.

Overview of the conversion of cytocine into uracil for MSP

As the primers in these procedures are designed purposely to amplify methylated DNA and not unmethylated DNA that allows to bypass the quantification procedures for the same.

Statistical Analysis

SPSS 17.0 software package was used for statistical analysis. Chi square and fisher exact test were used to find statistical difference of DAPK1 and p16^INK4a gene hypermethylation in cases and controls and their association with clinicopathological features. A p value of < 0.05 was considered as statistically significant.

Results

Baseline Features of Study Participants

Table 2 depicts baseline and clinicopathological features of study participants. There was no family history of EOC in study participants. EOC cases are divided into age group > 40 years (50%) and ≤ 40 years (50%) to determine the association of hypermethylation of genes with the age of diagnosis. Most of the patients (80%) were in late stage (stage III and IV) of FIGO staging compared to early stage. Most of the patients had serous adenocarcinoma (46%) followed by mucinous adenocarcinoma (44%), endometroid & undifferentiated (6%) and clear-cell ovarian carcinoma (2%).

Table 2.

Baseline clinicopathological features of EOC cases and controls

Parameters	Cases		Controls
	Number (n)	Percentage (%)	Number (n)	Percentage (%)
Age groups
≤ 40 years	25	50.0	26	52.0
> 40 years	25	50.0	24	48
Menopause status
Postmenopausal	16	32.0	18	36
Premenopausal	34	68.0	32	64
Histopathology
Mucinous	22	44.0	–	–
Serous	23	46.0	–	–
Clear cell	1	2.0	–	–
Endometroid	2	4.0	–	–
Undifferentiated	2	4.0	–	–
FIGO staging
Early (I and II)	10	20.0	–	–
Advanced (III and IV)	40	80.0	–	–

DAPK1 and p16^INK4a Gene Hypermethylation in Cases and Controls

Methylation frequencies of DAPK1 and p16^INK4a gene among EOC cases and healthy controls were shown in Table 3. Methylation frequencies of both genes were significantly different (p < 0.0001) between cases and controls. DAPK1 methylation was more found in EOC cases (84.0%) compared to controls (15.0%) and p16^INK4a methylation was also more prevalent in EOC cases (68.0%) compared to controls (10.0%). Thus, results indicate that DAPK1 and p16^INK4a hypermethylation strongly associated with occurrence of EOC.

Table 3.

Distribution DAPK1 and p16^INK4a gene methylation in EOC cases and controls

Gene	No. of methylated samples (n)	No. of unmethylated samples (n)	Chi square test	df	p* value	Power of tests
DAPK1 gene
Cases	42 (84.0%)	8 (16.0%)	26.69	1	< 0.0001	0.99
Controls	3 (15.0%)	17 (85.0%)
p16INK4a gene
Cases	34 (68.0%)	16 (32.0%)	16.99	1	< 0.0001	0.99
Controls	2 (10.0%)	18 (90.0%)

*Chi square test

DAPK1 and p16^INK4a Gene Hypermethylation and Age of EOC Diagnosis

Association of DAPK1 and p16^INK4a gene hypermethylation with age at diagnosis of EOC was shown in Table 4. DAPK1 hypermethylation was more found in age group of > 40 years compared to age group of ≤ 40 years (88.0% vs. 80.0%). P16^INK4a hypermethylation was also more found in age group of > 40 years compared to age group of ≤ 40 years (80.0% vs. 56.0%). But association of DAPK1 (p = 0.4) and p16^INK4a (p = 0.06) gene with age at diagnosis was non-significant.

Table 4.

Association of DAPK1 and p16^INK4a gene methylation with clinicopathological features in EOC cases

Parameters	No. of cases (n = 50)	DAPK1 methylation n (%)	P* value	Power of tests	p16INK4a methylation n (%)	p* value	Power of tests
Age groups
≤ 40 years	25	20/25 (80.0)	0.4	0.11	14/25 (56.0)	0.06	0.42
> 40 years	25	22/25 (88.0)			20/25 (80.0)
Menopausal status
Post	34	29/34 (85.3)	0.7	0.16	23/34 (67.6)	0.7	0.10
Pre	16	13/16 (81.2)			11/16 (68.7)
Histopathology
Mucinous	22	20/22 (90.9)	0.3	0.33	13/22 (59.0)	0.5	0.25
Serous	23	19/23 (82.6)			16/23 (69.5)
Clear cell	01	01/01 (100.0)			1/1 (100.0)
Endometrial	02	01/02 (50.0)			2/2 (100.0)
Undifferentiated	02	01/02 (50.0)			2/2 (100.0)
FIGO staging
Early (I & II)	10	9/10 (90.0)	0.5	0.13	7/10 (70.0)	0.8	0.10
Advanced (III & IV)	40	33/40 (82.5)			27/40 (67.5)
Chemotherapy status
Pre	24	19/24 (79.1)	0.9	0.10	17/24 (70.8)	0.4	0.12
Post	15	12/15 (80.0)			9/15 (60.0)

*Chi square test and Fisher’s exact test

DAPK1 and p16^INK4a Gene Hypermethylation and Menopausal Status

DAPK1 (p = 0.7) and p16^INK4a (p = 0.7) gene hypermethylation were not significantly associated with menopausal status of EOC cases.

DAPK1 and p16^INK4a Gene Hypermethylation and Histopathological Type of EOC

DAPK1 (p = 0.3) and p16^INK4a (p = 0.5) gene hypermethylation were not significantly associated with histopathological type of EOC.

DAPK1 and p16^INK4a Gene Hypermethylation and Staging of EOC

DAPK1 hypermethylation was more prevalent in early FIGO staging (90.0%) compared to advanced staging (82.5%) of EOC. P16^INK4a hypermethylation was also more prevalent in early FIGO staging (70.0%) compared to advanced staging (67.5%) of EOC. But there was no statistically significant association of DAPK1 (p = 0.5) and p16^INK4a (p = 0.8) gene hypermethylation with staging of EOC.

DAPK1 and p16^INK4a Gene Hypermethylation and Chemotherapy Status

DAPK1 (p = 0.3) and p16^INK4a (p = 0.5) gene hypermethylation were not significantly associated with chemotherapy status in EOC patients.

Discussion

One of the main challenges in cancer therapeutics is the early diagnosis. There is not a clear proposal for the early diagnosis of cancer. Thus, novel strategies need to be planned for possible early diagnosis. One such strategy could be using the clinical specimen and evaluating them from various biochemical and pathological parameters. In this study, we evaluated the frequencies of aberrant promoter methylation of genes which are involved in DNA damage, cell cycle control, apoptosis, and xenobiotics metabolism [20]. DAPK1 and p16^INK4a genes were already reported to be common targets of aberrant hypermethylation in several cancers, including haematological cancers [21]. It has been reported that changes in the degree of methylation in DNA regulatory regions, occurred during the process of neoplastic disease, can affect the oncogenesis through silencing of the process of transcription. We observed DAPK1 and p16^INK4a genes to be commonly methylated in EOC patients.

In the present study, DAPK1 and p16^INK4a were chosen to estimate the hyper methylation of promoter regions in genomic DNA isolated from peripheral blood samples of EOC patients. The p16^INK4a gene is concerned in the regulation of the cell cycle while the DAPK1gene is committed to a process of programmed cell death. DAPK1 and p16^INK4a genes are strongly connected with the oncogenesis, by inducing the control of cell proliferation [22]. At the same time, the effect of epigenetic regulation of the DAPK1 and p16^INK4a genes in ovarian cancer has not been completely explained [23].

The DNA methylation of CpG-rich promoters could be a reason for transcriptional silencing [24]. Methylation of cytosine at CpG sites in p16^INK4a gene promoter, leads to silenced p16^INK4a expression, has been found in many cell lines [25] and some primary carcinomas of varied origins including ovarian carcinoma [26] and so p16^INK4a tumour suppressor gene plays a monitor role in the passage of cells through the G1 to S phase of the cell cycle by binding to cyclin-dependent kinase 4 and inhibiting its effect on cyclin D1 [27].

DAPK1 is a calcium-calmodulin regulated protein kinase involved in multiple cellular pathways including cell survival, motility apoptosis and autophagy [28]. Promoter hypermethylation and homozygous deletion of DAPK1 are the major alternative mechanisms of DAPK protein abnormality in malignancy [29]. DAPK1 hypermethylation has been found in the tissue sample of ovarian tumors by multiplex MethyLight assay in north Indian population [30]. According to published PubMed biomedical literature, there is no published report till date where DAPK1 and p16 methylation status in blood samples of EOC patients by MSP has been evaluated for cancer prognostics.

In the previous studies of methylation, most researchers carried out southern analysis & digestion of methylation-sensitive enzymes to detect methylation or used ovarian tissue sample. We used MSP to detect methylation of DAPK1 and p16^INK4a gene. MSP detects even very less numbers of methylated alleles in small samples of DNA compared to southern blot analysis. MSP also identifies all the CpG sites in the gene compared to methylation detection by specific restriction enzymes which detect methylation sites in particular sequence of genes only. So MPS is a very accurate and simple method to detect methylation status of CpG rich region in blood sample compared to other methods.

Table 5 represents the individual and collective percentage of DAPK1 and p16^INK4a promoter hypermethylation in EOC patients. We found 84% patients to be methylated for DAPK1 gene and 68% for p16^INK4a gene and both were highly significant with p values of < 0.0001. However, there was no association found with various clinicopathological features like age at diagnosis, menopausal status histopathological type and staging of EOC. In summary, this work reports that DNA methylation screening in blood holds significant promise as a future diagnostic or risk prediction tool and warrants further higher CpG-coverage studies to fully clarify this role as elaborated by Teschendorff et al. [15].

Table 5.

Percentage of DAPK1 and p16^INK4a gene methylation in EOC cases

Gene methylation	No. of patients (n)	Percentage (%)
DAPK1 methylation	42/50	84.0
p16INK4a methylation	34/50	68.0
DAPK1 and p16INK4a methylation	25/50	50.0
No methylation	2/50	4.0

Limitations of the Study

Instead of cell free DNA, we used DNA from whole blood as theoretically it would also echo the properties of tumor genomic DNA. Limited sample size is another drawback of the study. Study on large sample size would have been ideal and statistically more conclusive, but the caveat was limited availability of EOC patients with the exclusion criteria (patients with a history of previous cancer or metastasized cancer from any other site(s) were excluded from the study).

Conclusion

We conclude that methylation signatures of both DAPK1 and p16^INK4a genes can serve as possible markers for early detection of ovarian cancer. Though, large cohorts studies may be desired to further validate the role of DAPK1 and p16^INK4a genes in ovarian cancer and to associate the appearance of methylation with the clinicopathological features.

Abbreviations

EOC

Epithelial ovarian cancer

DAPK1

Death associated protein kinase 1

PCR

Polymerase chain reaction

MSP

Methylation specific PCR

Authors Contribution

Guarantor: MZ; Design and conception: MZ, RM, AS; Collection and gathering of data: MZ, DS; Clinical monitoring and laboratory detection: MZ, DS, SG, MB, MS; Data analysis and interpretation: MZ, DS, IK, RM; Manuscript preparation: MZ, DS, IK; Approval of manuscript: All authors.

Funding

We did not receive any funding for this research work.

Compliance with Ethical Standards

Conflict of interest

The author(s) declared no conflicts of interest.

Ethical Approval

The study was approved by ethical committee of local institute. Study has been performed in accordance with the ethical standards of national research committee and or institutional committee and in accordance with the 1964 declaration of Helsinki and its later amendments.

Informed Consent

Informed consent was obtained from all participants of the study.