1. bookVolumen 16 (2022): Heft 4 (August 2022)
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Promoter methylation analysis of DKK2 may be a potential biomarker for early detection of cervical cancer

Xian Zhang,
Xian Zhang,
Aihua Li,
Aihua Li,
Jie Wu,
Jie Wu,
Yu Wu,
Yu Wu,
Xiaoping Ma,
Xiaoping Ma,
Yanjun Liu,
Yanjun Liu,
Qingfa Chen und
Qingfa Chen und
Yan Zhang
Yan Zhang
Online veröffentlicht: 31 Aug 2022
Volumen & Heft: Volumen 16 (2022) - Heft 4 (August 2022)
Seitenbereich: 181 - 189
Asian Biomedicine's Cover Image
Asian Biomedicine
Zeitschriftendaten
License
Format
Zeitschrift
eISSN
1875-855X
Erstveröffentlichung
01 Jun 2007
Erscheinungsweise
6 Hefte pro Jahr
Sprachen
Englisch

Cervical cancer is the most common gynecological malignancy and is especially prevalent in young women [1]. While cervical cancer is often curable if detected at an early stage, the overall survival in patients with advanced cervical cancer remains poor. Therefore, better treatments and molecular markers related to carcinogenesis and progression that can help clinical practice are needed urgently. Screening is key for the early detection of precancerous lesions and cancer. ThinPrep cytologic tests (TCT) and human papillomavirus (HPV) detection are 2 important and commonly used methods to screen for cervical cancer [2]. TCTs are inexpensive, but their performance depends on several subjective human factors, which can lead to misdiagnosis and missed diagnosis, and poor accuracy. The sensitivity for detecting HPV is high, but most cases of HPV infection are transient, leading to poor specificity. Cytological screening strategies combined with HPV testing have contributed to a substantial reduction in the incidence and mortality of cervical cancer [3]. However, overall, the positive predictive effects are moderate, as only a small subset of people with HPV will eventually develop cervical cancer. Gene methylation analysis is a nonmorphological molecular detection method, which can provide an objective and potential shunt method for high-risk HPV-positive women. Triage tests using DNA methylation may be helpful to differentiate women who are at high risk of rapidly developing cervical cancer from women with low risk.

DNA methylation of tumor-related genes is closely related to early tumor progression, in a cancer type specific manner, and may provide information that can aid early screening of cervical cancer [4]. Aberrant promoter methylation, and epigenetic changes in tumor suppressor genes, either inactivating or silencing, are associated with tumorigenesis and progression [5,6,7,8]. In humans, DNA methylation occurs almost exclusively at the carbon 5 position on cytosine residues in CpG dinucleotides, which are concentrated in distinct GC-rich regions called “CpG islands” (CGIs) [8]. CpG island hypermethylation of tumor suppressor genes has been linked to the development of numerous human cancers, including cervical cancer [9, 10]. The Wnt/β-catenin signaling pathway is known to be regulated by several secreted antagonists, such as members of the Dickkopf (DKK) protein family (DKK1, DKK2, DKK3, and DKK4), and has a function in embryonic development and tumorigenesis [11]. DKK2, located at 4q25, functions to produce an antagonist of canonical Wnt/β-catenin through its receptor low-density lipoprotein-receptor-related protein 5/6 (LRP5/6). The DKK2 promoter has a typical CpG island and is, therefore, under epigenetic regulation through promoter CpG methylation. DKK1 and DKK2 epigenetic silencing through promoter methylation have been observed in multiple cancers, including colorectal cancer, breast cancer, Ewing sarcoma, and gastric cancer [12,13,14,15,16,17,18]. However, its precise cellular function in cancer remains elusive.

Although DKK2 plays a significant role in many tumors, its correlation with clinicopathological characteristics such as lymph node metastasis and HPV infection is still unknown in cervical cancer. Here, we evaluated the mRNA expression profiles of DKK2 and its epigenetic alterations in cervical cancer cell lines and in samples from patients with cervical cancer.

Methods
Data mining and analyses

To compare gene expression differences between healthy donors and patients with cervical cancer, all clinicopathological data related to DKK2 expression profiles (GSE6791, GSE7803, GSE9750, and GSE7410) were carefully selected from the Gene Expression Omnibus (GEO) database, The Cancer Genome Atlas (TCGA) database (https://www.cancer.gov/about-nci/organization/ccg/research/structural-genomics/tcga), and Oncomine websites (https://www.oncomine.org/resource/login.html). GraphPad Prism was used to obtain the scatter diagram. DKK2 methylation expression data was mined in University of ALabama at Birmingham CANcer (UALCAN) databases (http://ualcan.path.uab.edu/) [19, 20]. This study was conducted following the Reporting Recommendations for Tumor Marker Prognostic Studies (REMARK) checklist [21].
Cell lines and clinical samples

Ect1/E6E7 (catalog No. AC39960) normal cervical epithelial cell and HPV-positive HeLa (catalog No. TCHu187), HPV-positive CaSki (catalog No. BNCC338223), HPV-negative HT-3 (catalog No. HTB-32), and HPV-negative C33A (catalog No. BNCC337882) cervical cancer cell lines were screened. Cells were purchased from American Type Culture Collection (ATCC) or BeNa Culture Collection (Beijing, China) and cultured in RPMI-1640 medium (Gibco).

We analyzed a series of cervical specimens with histological diagnoses collected between May 2016 and November 2017 at Liaocheng People's Hospital (Shandong, China). At the time of surgical resection or cervical biopsy, 79 invasive cervical cancer tissues and 63 cervical intraepithelial neoplasia (CIN) tissues were obtained. Of the CIN tissues, 25 were classified as low-grade CIN (low-grade squamous intraepithelial lesions, LSIL) and 38 as high-grade CIN (high-grade squamous intraepithelial lesions, HSIL), and the latter included both CIN2 and CIN3. Normal cervical tissue (29 cases) was retrieved from patients with uterine leiomyomas who underwent a hysterectomy. All samples were stored at −80 °C until analysis. Genotyping was used to detect HPV16 and HPV18 viral DNA [20]. All cases had a confirmed diagnosis, as well as confirmed HPV typing and histopathological type. Exclusion criteria included samples from patients undergoing chemotherapy or radiotherapy, immunocompromised patients, pregnancy, diagnosis of other cancers, uterine cervix operations, and chronic or acute viral infection. Documented written informed consent was provided by all patients for tissue sample collection. The present study was approved by the medical ethics committee of Liaocheng People's Hospital, China (No. 2016022), and was consistent with relevant national regulations and laws, including the People's Republic of China Regulations for the Management of Medical Institutions (promulgated by the Order No. 149 of the State Council on February 26, 1994; and revised in accordance with the Decision of the State Council on Amending Some Administrative Regulations on February 6, 2016), and international medical ethics documents, including the principles of the World Medical Association (WMA) Declaration of Helsinki and its contemporary amendments (2013).
Reverse transcription-polymerase chain reaction

DKK2 mRNA expression was examined by reverse transcription-polymerase chain reaction (RT-PCR) analysis as previously described [18]. Total RNA was extracted from cell lines, CIN, normal cervical tissues, and tumor samples using TRIzol reagent (Invitrogen). DKK2 expression level was calculated relative to that of glyceraldehyde-3-phosphate dehydrogenase (GAPDH) in each sample by RT-PCR. Primer pairs used for mRNA expression and the size of PCR products are described in Table 1. The products were separated in 2% agarose gels using a DL1000 marker set (catalog No. 3591A; Takara) marker set.

Primer pairs used for mRNA expression and the size of PCR products

GenePrimer information (5′-3′)Product size
DKK25′-GTACCAAGGACTGGCATTCG-3′ (F)5′-ATCTCGGTGGCAGCGCTTCT-3′ (R)169 bp
GAPDH5′-CCAGCAAGAGCACAAGAGGAA-3′ (F)5′-CAAGGGGTCTACATGGCAACT-3′ (R)114 bp
DKK2 (M)5′-AGAGTTAAATCGTCGAGATTTC-3′ (F)5′-CTAAAAACAATCAAATACGAAACG-3′ (R)146 bp
DKK2 (U)5′-GGAGAGTTAAATTGTTGAGATTTT-3′ (F)5′-ACTAAAAACAATCAAATACAAAACA-3′ (R)149 bp

DKK2, gene for Dickkopf 2; F, forward primer; GAPDH, gene for glyceraldehyde-3-phosphate dehydrogenase; M, methylated-specific primers; PCR, polymerase chain reaction; R, reverse primer; U, unmethylated-specific primers.
DNA extraction and bisulfite modification

DNA samples were extracted from tissues and cell lines. Genomic DNA (1 μg) was bisulfite-modified and purified following the guidelines described by the manufacturer. After desulfonation with NaOH and precipitation with ethanol, the final products were dissolved in 20 μL of Tris-EDTA buffer and stored at −80 °C.
Methylation-specific PCR

DKK2 gene methylation was determined using a Methylation-Gold Kit (Zymo Research). Primer pairs used for methylation analysis and PCR size products are shown in Table 1, as previously described [12, 23]. Briefly, 5 min predenaturation occurred at 95 °C, 30 s denaturation for 35 cycles, 30 s annealing at 54 °C (unmethylated-specific PCR) or 58 °C methylation-specific PCR (MSP), and 10 min extension at 72 °C. As a positive control for methylation, DNA obtained from normal tissue was methylated in vitro with M.Sssl CpG methyltransferase (New England BioLabs). A water blank (no template DNA) was also included as a negative PCR control. The products were separated in 2% agarose gels using a DL1000 marker set (catalog No. 3591A; Takara) marker set.
5-Aza-dC treatment

HeLa, CaSki, HT-3, and C33A cells (2 × 105) were treated with 10 μmol 5-Aza-2′-deoxycytidine (5-Aza-dC) (Sigma) for 96 h. After adding the demethylation treatment, the medium was changed every 24 h. RNA and DNA were isolated according to routine procedures.
Statistical analysis

SPSS Statistics for Windows (version 17.0) was used for all statistical analyses. Student t tests were performed for data mining, and χ2 or Fisher exact tests were performed for RT-PCR and MSP analyses. P < 0.05 was considered significant.
Results
DKK2 mRNA expression in cervical cancer cell lines and tumor specimens

We examined DKK2 mRNA expression in 79 normal cervical tissues (50 by data mining, 29 by RT-PCR), 9 cervical cancer lines (HT-3, C4-I, CaSki, MS751, C33A, SiHa, SW756, ME-180, and HeLa cell lines by data mining, HeLa, HT-3, C33A, and CaSki cell lines by RT-PCR), and 498 cervical cancer samples (419 by data mining, 79 by RT-PCR). Based on data from the GEO database (Figures 1A–D), DKK2 mRNA expression was lower in cervical cancer tissues compared with normal tissues (P < 0.0001 for Figures 1A, B, and D, P = 0.0004 for Figure 1C). However, based on data from the TCGA database (Figure 1E), the difference was not significant (P = 0.848), although the levels of DKK2 mRNA expression showed a similar trend to that of the GEO database. Compared with normal cervical epithelial cells, expression in cervical cancer cells including HT-3, C4-I, CaSki, MS751, C33A, SiHa, SW756, ME-180, and HeLa cervical cancer cell lines was lower, as shown in Figure 1F (P = 0.023).

Figure 1

DKK2 mRNA expression in cervical cells and tissues. (A–E) RT-PCR analysis of DKK2 mRNA expression in cervical normal and cancer tissues. **P < 0.01 compared with normal tissues. (F) RT-PCR analysis of DKK2 mRNA expression in normal cervical epithelial cell lines and in 9 human cervical cancer cell lines. *P < 0.05 compared with normal cervical epithelial cell lines. (G) RT-PCR analysis of DKK2 mRNA relative expression in normal cervical epithelial cell lines and 4 human cervical cancer cell lines (Hela, Caski, HT-3, and C33A cell lines). **P < 0.01 compared with normal cervical epithelial cell lines. (H) DKK2 mRNA expression in LSIL, HSIL, tumor, and normal cervical tissues. The PCR products were separated in 2% agarose gels using a DL1000 marker set (catalog No. 3591A; Takara) marker set; the band of interest is between markers 100 bp and 200 bp at 169 bp. DKK2, Dickkopf 2; GAPDH, glyceraldehyde-3-phosphate dehydrogenase; H, HSIL; L, LSIL; N, normal; RT-PCR, reverse transcription-polymerase chain reaction; T, tumor; TCGA, The Cancer Genome Atlas; bp, base pairs

We then examined DKK2 mRNA expression both in cervical cancer cell lines and in tissue samples. Our RT-PCR analysis indicated that DKK2 mRNA expression was weak in HPV-negative C33A cells, and silenced in HPV-negative HT-3 cells and HPV-positive CaSki and HeLa cells, as compared with the normal cervical epithelial cell line Ect1/E6E7 (Figure 1G). All 29 normal cervical tissues, and 46 of 63 (73.0%) CIN samples, showed DKK2 mRNA expression (Table 2). Among 79 cervical cancer samples analyzed, only 25 of 79 (31.6%) showed DKK2 mRNA expression. The positive rate of DKK2 mRNA expression in cervical cancer decreased significantly compared to that in HSIL (χ2 = 5.999, P = 0.014). The positive rate of DKK2 mRNA expression in HSIL was significantly lower than that in normal cervical samples (χ2 = 17.385, P = 0.00003), and LSIL (χ2 = 15.318, P = 0.001). The RT-PCR results for the 2 normal cervical tissues (N1, N2), 2 LSIL (L1, L2), 2 HSIL (H1, H2), and 11 primary tumors (T1 to T11) analyzed are shown in Figure 1H.

DKK2 mRNA expression and methylation in cervical neoplasms

DiagnosisnmRNA expression (%)PMethylation (%)P
Normal2929/29 (100) 0/29 (0)
LSIL2525/25 (100)0.000031/25 (4.0)0.005
HSIL3821/38 (55.2)0.0019/38 (23.7)0.037
Cervical cancer7925/79 (31.6)0.01441/79 (51.9)0.004

DKK2, Dickkopf 2; HSIL, high-grade squamous intraepithelial lesions; LSIL, low-grade squamous intraepithelial lesions.
Correlation of DKK2 inactivation with its promoter hypermethylation

We then examined the status of DKK2 promoter methylation in HeLa, HT-3, C33A, and CaSki cell lines by MSP. DKK2 hypermethylation was detected in all 4 cell lines (Figure 2A). Of these 4 cell lines, the C33A cell line showed the weakest DKK2 mRNA expression, although both unmethylated and methylated bands were detected. Correlation analysis between DKK2 silencing and promoter hypermethylation was performed by treating cell lines with 10 μM 5-Aza-dC induction for 4 d, followed by promoter methylation level analysis. DNA-demethylating agent treatment significantly led to DKK2 demethylation and re-expression of the transcript among all 4 cell lines analyzed (Figure 2B).

Figure 2

DKK2 methylation level in cervical cancer cell lines and tissues. (A) MSP analysis of DKK2 hypermethylation in Hela, Caski, HT-3, and C33A cervical cancer cell lines. (B) DKK2 expression after treatment with 5-Aza-dC for 4 d in cervical cancer cell lines. GAPDH was used as a housekeeping control gene. (C) DKK2 methylation levels in TCGA samples analyzed by data mining. **P < 0.01 compared with normal tissues. (D) MSP analysis of DKK2 CGIs methylation frequency in primary cervical cancer tissues. CGIs, CpG islands; DKK2, Dickkopf 2; GAPDH, glyceraldehyde-3-phosphate dehydrogenase; M or MSP, methylation-specific polymerase chain reaction (PCR); TCGA, The Cancer Genome Atlas; U, unmethylated-specific PCR.

We then examined DKK2 methylation status in cervical tissues. Methylation levels were significantly higher in cervical cancer tissues, as shown in TCGA samples (Figure 2C, P < 0.0001). MSP analysis was then performed to confirm the overall frequency of DKK2 methylation in cervical cancer. DKK2 promoter hypermethylation was detected in 41 of 79 cases (51.9%) of cervical cancer tissues. However, methylation status was only found in 10 of 63 CIN cases (12.7%), and no methylation status was detected in normal cervical cases (Figure 2D). The positive rate of DKK2 methylation in cervical cancer was significantly higher than that in HSIL (χ2 = 8.346, P = 0.004), whereas the positive rate of DKK2 methylation in HSIL was significantly higher than that in normal cervical samples (χ2 = 7.934, P = 0.005) and in LSIL samples (χ2 = 4.375, P = 0.037) (Table 2). Positive DKK2 mRNA expression in cervical cancer cases without methylation (47.4%) was significantly higher than that of cervical cancer tissues with promoter hypermethylation (17.1%) (χ2 = 8.368, P = 0.002).
Clinicopathological importance of DKK2 promoter hypermethylation

The correlation between DKK2 hypermethylation and the primary clinicopathological characteristics of cervical cancer, including histology, stage, lymph node metastasis, HPV infection, and differentiation, was investigated further. DKK2 methylation (76.5% vs 45.2%, respectively, χ2 = 5.239, P = 0.022) and DKK2 mRNA expression (11.8% vs 37.1%, respectively, χ2 = 3.958, P = 0.047) are significantly different between patients with or without lymph node metastasis (Table 3). The rate of detection of DKK2 methylation in HPV16/18-positive patients in the cervical cancer group (66.7%) was significantly higher than that in HPV16/18-negative patients (36.0%) (χ2 = 6.279, P = 0.015). The rate of detection of DKK2 methylation in HPV16/18-positive patients (24.1%) in the precancerous lesion group was slightly higher than that in HPV16/18-negative patients (13.0%) (χ2 = 1.016, P = 0.482) (Table 4). No significant association was detected between DKK2 hypermethylation and other cervical cancer clinicopathological characteristics, such as clinical stage (P = 0.32), histology (P = 0.55), and tumor grade (P = 0.17) (Table 3).

DKK2 mRNA expression, DKK2 promoter methylation and clinicopathological characteristics of cervical cancer

Clinical statusnDKK2 mRNA expressionDKK2 methylation
+ P+ P
Clinical stage
Stage IA22813 (46.4%)15 (53.6%)0.09912 (42.9%)16 (57.1%)0.32
Stage IB1+IB2419 (22.0%)32 (78.0%) 22 (53.7%)19 (46.3%)
Stage IIA103 (30.0%)7 (70.0%) 7 (70.0%)3 (30.0%)
Histology
Squamous cell carcinoma7021 (30.0%)49 (70.0%)0.3836 (51.4%)34 (48.6%)0.55
Adenocarcinoma94 (44.4%)5 (55.6%) 5 (55.6%)4 (44.4%)
Tumor grade
Grade 1155 (33.3%)10 (66.7%)0.816 (40.0%)9 (60.0%)0.17
Grade 24212 (28.6%)30 (71.4%) 20 (47.6%)22 (52.4%)
Grade 3228 (36.4%)14 (63.6%) 15 (68.2%)7 (31.8%)
Lymph node metastasis
Negative6223 (37.1%)39 (62.9%)0.04728 (45.2%)34 (54.8%)0.022
Positive172 (11.8%)15 (88.2%) 13 (76.5%)4 (23.5%)

DDK2, Dickkopf 2.

Relationship between HR-HPV infection type and DKK2 methylation rate

GroupHR-HPV (+)nDKK2 methylationP
n%
Cervical cancer 0.015
HPV16/18(+)483266.7
HPV16/18(−)25936
Precancerous lesions 0.48
HPV16/18(+)29724.1
HPV16/18(−)23315

HPV, human papillomavirus; HR-HPV, high-risk HPV.
Discussion

In the present study, we investigated DKK2 expression profiles and epigenetic alterations in cervical cancer. DKK2 mRNA expression was reduced in cell lines of cervical cancer and cancer tissues, whereas DKK2 hypermethylation was upregulated. In addition, DKK2 mRNA expression was restored after 5-Aza-dC treatment of cell lines of cervical cancer. The study suggests DKK2 silencing is strongly associated with its promoter hypermethylation.

The activated Wnt/β-catenin signaling pathway plays an important role in cervical cancer. CpG island promoter hypermethylation has been shown to inactivate extracellular Wnt antagonists in cervical cancer [22, 23]. CpG island methylation can be widely found in the human genome, but only a subset of loci plays important roles in tumorigenesis. These implicated genes are known to be involved in multiple cellular signaling pathways such as apoptosis, cell cycle regulation, development, differentiation, invasion, and metastasis. As CpG island methylation occurs early and methylated alleles can be detected in a sensitive manner in carcinogenesis, detection of methylation may be a promising tool for early detection of cancer [24]. DKK2, a Wnt antagonist, contributes to tumorigenesis in multiple cancers [12, 13, 25,26,27,28]. In the present study, RT-PCR showed reduced expression of DKK2 mRNA in cervical cancer compared with either normal cervical samples or HSIL samples. Further, through MSP analysis DKK2 is found to be methylated in most patients diagnosed with cervical cancer, while it is not in HSIL and normal cervical samples. Collectively, the data demonstrate that DKK2 is predominantly methylated in cervical cancer. DKK2 methylation status and gene expression level showed a significant inverse correlation.

Methylation of the DKK1 promoter in patients with cervical squamous cell carcinoma is related to high-risk HPV infection and histological differentiation, tumor size, lymph node metastasis, and International Federation of Gynecology and Obstetrics (FIGO) staging, while the degree of methylation of DKK1 is not related to the type of high-risk HPV infection [14]. Paired PAX1 methylation was found to be a valuable biomarker for cervical cancer screening, a commonly used method in our hospital, with a 77% sensitivity and 92% specificity of CIN3+ versus normal [29]. A high methylation rate of DKK2 was significantly associated with poor overall survival, and a multivariate Cox proportional hazards model revealed that methylation of DKK2 is an independent adverse prognostic factor [28]. In the present study, significant DKK2 hypermethylation was detected in lymph node-positive cervical cancer. The methylation rate of the DKK2 promoter was 76.5% in cervical cancer specimens with lymph node metastasis, and only 45.2% in cervical cancer specimens without lymph node metastasis, indicating a significant difference between the 2 groups.

HPV infection accounts for over 90% of cervical cancer cases, and the high-risk types of HPV are associated with 87%–88% of squamous cell carcinomas [30]. A triage test using DNA methylation may be helpful to differentiate women who are at high risk of developing cervical cancer rapidly from women with low risk. In the case of HSIL, the combination of HPV genotyping and methylation marker analysis can not only overcome the limitations of cytological examination but also increase diagnosis accuracy. The present study indicated that among HR-HPV-positive cervical cancer patients, the methylation rate of DKK2 in HPV16/18-positive patients was more greatly enhanced than that in HPV16/18-negative patients.

We acknowledge that the present study also has some limitations. In the precancerous lesion group, the difference was not statistically significant. The correlation between DKK2 methylation level and HPV subtype needs to be investigated further by including a larger sample size. In addition, the population included in the present study was drawn from patients in hospitals, not from a population that would be screened. The real-world screening value of DKK2 methylation detection for cervical cancer needs further population-based research and discussion.
Conclusion

DKK2 epigenetic changes may play a key role in the development of cervical cancer, suggesting a potential value of DKK2 hypermethylation as a triage test for screening, early diagnosis, or predicting the risk of cervical cancer.

Figure 1

DKK2 mRNA expression in cervical cells and tissues. (A–E) RT-PCR analysis of DKK2 mRNA expression in cervical normal and cancer tissues. **P < 0.01 compared with normal tissues. (F) RT-PCR analysis of DKK2 mRNA expression in normal cervical epithelial cell lines and in 9 human cervical cancer cell lines. *P < 0.05 compared with normal cervical epithelial cell lines. (G) RT-PCR analysis of DKK2 mRNA relative expression in normal cervical epithelial cell lines and 4 human cervical cancer cell lines (Hela, Caski, HT-3, and C33A cell lines). **P < 0.01 compared with normal cervical epithelial cell lines. (H) DKK2 mRNA expression in LSIL, HSIL, tumor, and normal cervical tissues. The PCR products were separated in 2% agarose gels using a DL1000 marker set (catalog No. 3591A; Takara) marker set; the band of interest is between markers 100 bp and 200 bp at 169 bp. DKK2, Dickkopf 2; GAPDH, glyceraldehyde-3-phosphate dehydrogenase; H, HSIL; L, LSIL; N, normal; RT-PCR, reverse transcription-polymerase chain reaction; T, tumor; TCGA, The Cancer Genome Atlas; bp, base pairs
DKK2 mRNA expression in cervical cells and tissues. (A–E) RT-PCR analysis of DKK2 mRNA expression in cervical normal and cancer tissues. **P < 0.01 compared with normal tissues. (F) RT-PCR analysis of DKK2 mRNA expression in normal cervical epithelial cell lines and in 9 human cervical cancer cell lines. *P < 0.05 compared with normal cervical epithelial cell lines. (G) RT-PCR analysis of DKK2 mRNA relative expression in normal cervical epithelial cell lines and 4 human cervical cancer cell lines (Hela, Caski, HT-3, and C33A cell lines). **P < 0.01 compared with normal cervical epithelial cell lines. (H) DKK2 mRNA expression in LSIL, HSIL, tumor, and normal cervical tissues. The PCR products were separated in 2% agarose gels using a DL1000 marker set (catalog No. 3591A; Takara) marker set; the band of interest is between markers 100 bp and 200 bp at 169 bp. DKK2, Dickkopf 2; GAPDH, glyceraldehyde-3-phosphate dehydrogenase; H, HSIL; L, LSIL; N, normal; RT-PCR, reverse transcription-polymerase chain reaction; T, tumor; TCGA, The Cancer Genome Atlas; bp, base pairs

Figure 2

DKK2 methylation level in cervical cancer cell lines and tissues. (A) MSP analysis of DKK2 hypermethylation in Hela, Caski, HT-3, and C33A cervical cancer cell lines. (B) DKK2 expression after treatment with 5-Aza-dC for 4 d in cervical cancer cell lines. GAPDH was used as a housekeeping control gene. (C) DKK2 methylation levels in TCGA samples analyzed by data mining. **P < 0.01 compared with normal tissues. (D) MSP analysis of DKK2 CGIs methylation frequency in primary cervical cancer tissues. CGIs, CpG islands; DKK2, Dickkopf 2; GAPDH, glyceraldehyde-3-phosphate dehydrogenase; M or MSP, methylation-specific polymerase chain reaction (PCR); TCGA, The Cancer Genome Atlas; U, unmethylated-specific PCR.
DKK2 methylation level in cervical cancer cell lines and tissues. (A) MSP analysis of DKK2 hypermethylation in Hela, Caski, HT-3, and C33A cervical cancer cell lines. (B) DKK2 expression after treatment with 5-Aza-dC for 4 d in cervical cancer cell lines. GAPDH was used as a housekeeping control gene. (C) DKK2 methylation levels in TCGA samples analyzed by data mining. **P < 0.01 compared with normal tissues. (D) MSP analysis of DKK2 CGIs methylation frequency in primary cervical cancer tissues. CGIs, CpG islands; DKK2, Dickkopf 2; GAPDH, glyceraldehyde-3-phosphate dehydrogenase; M or MSP, methylation-specific polymerase chain reaction (PCR); TCGA, The Cancer Genome Atlas; U, unmethylated-specific PCR.

DKK2 mRNA expression and methylation in cervical neoplasms

Diagnosis n mRNA expression (%) P Methylation (%) P
Normal 29 29/29 (100) 0/29 (0)
LSIL 25 25/25 (100) 0.00003 1/25 (4.0) 0.005
HSIL 38 21/38 (55.2) 0.001 9/38 (23.7) 0.037
Cervical cancer 79 25/79 (31.6) 0.014 41/79 (51.9) 0.004

Relationship between HR-HPV infection type and DKK2 methylation rate

Group HR-HPV (+)n DKK2 methylation P
n %
Cervical cancer 0.015
HPV16/18(+) 48 32 66.7
HPV16/18(−) 25 9 36
Precancerous lesions 0.48
HPV16/18(+) 29 7 24.1
HPV16/18(−) 23 3 15

DKK2 mRNA expression, DKK2 promoter methylation and clinicopathological characteristics of cervical cancer

Clinical status n DKK2 mRNA expression DKK2 methylation
+ P + P
Clinical stage
Stage IA2 28 13 (46.4%) 15 (53.6%) 0.099 12 (42.9%) 16 (57.1%) 0.32
Stage IB1+IB2 41 9 (22.0%) 32 (78.0%) 22 (53.7%) 19 (46.3%)
Stage IIA 10 3 (30.0%) 7 (70.0%) 7 (70.0%) 3 (30.0%)
Histology
Squamous cell carcinoma 70 21 (30.0%) 49 (70.0%) 0.38 36 (51.4%) 34 (48.6%) 0.55
Adenocarcinoma 9 4 (44.4%) 5 (55.6%) 5 (55.6%) 4 (44.4%)
Tumor grade
Grade 1 15 5 (33.3%) 10 (66.7%) 0.81 6 (40.0%) 9 (60.0%) 0.17
Grade 2 42 12 (28.6%) 30 (71.4%) 20 (47.6%) 22 (52.4%)
Grade 3 22 8 (36.4%) 14 (63.6%) 15 (68.2%) 7 (31.8%)
Lymph node metastasis
Negative 62 23 (37.1%) 39 (62.9%) 0.047 28 (45.2%) 34 (54.8%) 0.022
Positive 17 2 (11.8%) 15 (88.2%) 13 (76.5%) 4 (23.5%)

Primer pairs used for mRNA expression and the size of PCR products

Gene Primer information (5′-3′) Product size
DKK2 5′-GTACCAAGGACTGGCATTCG-3′ (F)5′-ATCTCGGTGGCAGCGCTTCT-3′ (R) 169 bp
GAPDH 5′-CCAGCAAGAGCACAAGAGGAA-3′ (F)5′-CAAGGGGTCTACATGGCAACT-3′ (R) 114 bp
DKK2 (M) 5′-AGAGTTAAATCGTCGAGATTTC-3′ (F)5′-CTAAAAACAATCAAATACGAAACG-3′ (R) 146 bp
DKK2 (U) 5′-GGAGAGTTAAATTGTTGAGATTTT-3′ (F)5′-ACTAAAAACAATCAAATACAAAACA-3′ (R) 149 bp

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