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Abstract

BACKGROUND:

Colorectal cancer (CRC) is one of the leading causes of mortality and morbidity in the world. It is characterized by different pathways of carcinogenesis and is a heterogeneous disease with diverse molecular landscapes that reflect histopathological and clinical information. Changes in the DNA methylation status of colon epithelial cells have been identified as critical components in CRC development and appear to be emerging biomarkers for the early detection and prognosis of CRC.

OBJECTIVE:

To explore the underlying disease mechanisms and identify more effective biomarkers of CRC.

METHODS:

We compared the levels and frequencies of DNA methylation in 11 genes (Alu, APC, DAPK, MGMT, MLH1, MINT1, MINT2, MINT31, p16, RGS6, and TFPI2) in colorectal cancer and its precursor adenomatous polyp with normal tissue of healthy subjects using pyrosequencing and then evaluated the clinical value of these genes.

RESULTS:

Aberrant methylation of Alu, MGMT, MINT2, and TFPI2 genes was progressively accumulated during the normal-adenoma-carcinoma progression. Additionally, CGI methylation occurred either as an adenoma-associated event for APC, MLH1, MINT1, MINT31, p16, and RGS6 or a tumor-associated event for DAPK. Moreover, relatively high levels and frequencies of DAPK, MGMT, and TFPI2 methylation were detected in the peritumoral nonmalignant mucosa of cancer patients in a field-cancerization manner, as compared to normal mucosa from healthy subjects.

CONCLUSION:

This study identified several biomarkers associated with the initiation and progression of CRC. As novel findings, they may have important clinical implications for CRC diagnostic and prognostic applications. Further large-scale studies are needed to confirm these findings.

Keywords

Colon mucosa normal-adenoma-carcinoma DNA methylation pyrosequencing biomarkers

1. Introduction

Colorectal cancer (CRC) is one of the most commonly occurring malignancies worldwide and continues to be a major cause of cancer-related deaths, likely due to the presence of distant metastases at the time of diagnosis [1]. CRC is believed to develop primarily via the well-characterized normal mucosa-adenoma-carcinoma sequence [2], and thus, much effort is being focused on the identification and management of early-stage CRC and premalignant lesions to reduce CRC mortality. Notably, CRC is a heterogeneous group of diseases made up of entities characterized by distinct clinical, pathological, morphological, regional, and molecular features [3, 4, 5]. This heterogeneity is also a function of ethnic differences [6]. Until now, the molecular basis underlying these variations was completely unknown, emphasizing the need for the development of robust prognostic and predictive biomarkers.

The colonic epithelium has the highest level of abnormal methylation and a high predisposition to lifetime cancer risk as compared to other bodily tissues [7, 8]. A number of studies have documented that changes in mucosal DNA methylation patterns are recognized as crucial components in the initiation and progression of CRC [9, 10, 11]. It is also evident that even though a plethora of markers are available, clinicians are still not able to achieve the best possible monitoring of a patient’s disease, even when a wide panel of markers is used [12, 13]. In addition, adenoma and CRC can be classified into several subgroups based on abnormally methylated genes, known as CpG-island methylator phenotypes (CIMP) [14]. Interestingly, information on the timing, levels and frequencies of DNA methylation events during the normal colonic mucosa-adenoma-carcinoma sequence in the most frequently studied genes is limited. Moreover, many studies with heterogeneous results have focused on the methylation frequency in tumor tissue [9, 10, 11]. Herein, to address these issues, we studied the methylation levels and frequencies of 11 genes (Alu, APC, DAPK, MGMT, MLH1, MINT1, MINT2, MINT31, p16, RGS6, TFPI2) in the colonic mucosa of healthy volunteers, patients with adenomatous polyp, and patients with CRC using pyrosequencing and evaluated their substantial value for clinical applications.

2. Materials and methods

2.1 Clinical specimens

Normal colonic mucosal tissues ( $n=$ 55) and polyps ( $n=$ 89) were collected from healthy subjects and patients with adenomatous polyp, respectively, using biopsy during colonoscopy. Cancerous and matched noncancerous (apparently normal and approximately 4–5 cm away from the tumor margin) tissue pairs ( $n=$ 102) were obtained from CRC patients at the time of surgery, but they were not histologically confirmed. All participants gave written and informed consent. The study was approved by the Institutional Review Board of the Kyungpook National University Hospital (KNUH, Daegu, South Korea) (No. KNUMCBIO 14-1001). All samples were snap frozen in liquid nitrogen and stored at $-$ 80 ${}^{\circ}$ C until processing.

2.2 DNA extraction, bisulfite treatment, and pyrosequencing

Genomic DNA was extracted using a QIAamp DNA Mini Kit (Qiagen, Valencia, CA, USA) and was chemically modified using an EZ DNA Methylation-Gold Kit (Zymo Research, Orange, CA, USA) according to the manufacturer’s instructions. The bisulfited DNA was pyrosequenced using a PyroMark ${}^{\text{\textregistered}}$ Q96MD system (Qiagen), as previously described [15]. The bisulfite PCR primer and sequencing primer sequences are shown in Supplementary Table 1. The methylation level for each sample was calculated from the average value of examined consecutive CpGs [mC/total C $\times$ 100 (%)]. Each pyrosequencing run was repeated at least once to confirm the results.

Table 1
Comparison of mean levels and frequencies of DNA methylation in colonic mucosa of healthy normal person, patients with adenomatous polyp and patients with colorectal cancer

Gene symbol	Methylation levels (%)				Methylation frequencies (%)
	Normal	Adenoma	Cancer	$P$ -value ${}^{*}$	Normal	Adenoma	Cancer	$P$ -value ${}^{**}$
Alu1	${}^{\rm A}$ 26.70	${}^{\rm B}$ 25.94	${}^{\rm C}$ 24.84	$<$ 0.0001	${}^{\rm F}$ 0.0	${}^{\rm E}$ 4.5	${}^{\rm D}$ 13.7	$<$ 0.0001
APC	${}^{\rm B}$ 1.68	${}^{\rm A}$ 4.96	${}^{\rm A}$ 7.68	0.0009	${}^{\rm E}$ 1.8	${}^{\rm D}$ 20.2	${}^{\rm D}$ 26.5	0.0002
DAPK	${}^{\rm B}$ 7.60	${}^{\rm B}$ 7.70	${}^{\rm A}$ 30.75	$<$ 0.0001	${}^{\rm E}$ 0.0	${}^{\rm E}$ 1.1	${}^{\rm D}$ 63.7	$<$ 0.0001
MGMT	${}^{\rm C}$ 1.32	${}^{\rm B}$ 7.34	${}^{\rm A}$ 16.68	$<$ 0.0001	${}^{\rm F}$ 1.8	${}^{\rm E}$ 27.0	${}^{\rm D}$ 55.9	$<$ 0.0001
MLH1	${}^{\rm B}$ 5.17	${}^{\rm A}$ 9.42	${}^{\rm A}$ 11.35	0.0133	1.8	4.5	17.6	0.0549
MINT1	${}^{\rm B}$ 5.46	${}^{\rm A}$ 10.18	${}^{\rm A}$ 10.46	0.0049	${}^{\rm E}$ 0.0	${}^{\rm D}$ 17.6	${}^{\rm D}$ 19.1	0.0007
MINT2	${}^{\rm C}$ 4.47	${}^{\rm B}$ 9.27	${}^{\rm A}$ 13.66	$<$ 0.0001	${}^{\rm F}$ 0.0	${}^{\rm E}$ 21.3	${}^{\rm D}$ 38.2	$<$ 0.0001
MINT31	${}^{\rm B}$ 9.00	${}^{\rm A}$ 16.41	${}^{\rm A}$ 19.67	$<$ 0.0001	${}^{\rm F}$ 1.8	${}^{\rm D}$ 23.6	${}^{\rm D}$ 39.2	$<$ 0.0001
P16	${}^{\rm B}$ 2.15	${}^{\rm A}$ 5.26	${}^{\rm A}$ 6.90	0.0034	1.8	7.9	11.8	0.0932
RGS6	${}^{\rm B}$ 4.53	${}^{\rm A}$ 12.33	${}^{\rm A}$ 12.39	0.0002	${}^{\rm E}$ 1.8	${}^{\rm D}$ 32.6	${}^{\rm D}$ 39.2	$<$ 0.0001
TFPI2	${}^{\rm C}$ 6.43	${}^{\rm B}$ 23.82	${}^{\rm A}$ 46.57	$<$ 0.0001	${}^{\rm F}$ 1.8	${}^{\rm E}$ 51.7	${}^{\rm D}$ 87.3	$<$ 0.0001

* $P$ -values are for the comparison of mean methylation levels for sample groups using ANOVA following transformation of the response variable where appropriate. ** $P$ -values are for the comparison of methylation frequencies for sample groups using a chi-square test after the boundary value of methylation risk or normal grouping used mean plus or minus four times standard deviations (mean $\pm$ 4SD). Superscript ABC is a significant different group by the Tukey-Kramer method of post-hoc comparison after ANOVA. Superscript DEF is a significant different group by the Bonferroni correction of $p$ -value after compare two groups.

2.3 Statistical analysis

The comparisons of mean methylation levels were evaluated using ANOVA or independent $t$ -test. The post-hoc comparisons were analyzed using the Tukey-Kramer method in the significance of the ANOVA. After the boundary value for the methylation-positive category used mean levels plus or minus four times the standard deviations (mean $\pm$ 4SD), the proportion comparison between groups was carried out using a chi-square test. The proportion comparison between the two groups was made using a Bonferroni correction, similar to the post-test used for the ANOVA. Receiver operating characteristic (ROC) curves were generated to estimate the diagnostic efficacies of methylation levels and frequencies. The value of area under the curve (AUC) of ROC plots represents discrimination between the groups. The statistical analyses were performed using SAS 9.4 (SAS Inc., Cary, NC, USA), and the plots were constructed using R version 4.0.3 (The R Foundation for Statistical Computing, Vienna, Austria).

3. Results and discussion

3.1 CGI methylation profiling in the colonic mucosa of healthy volunteers and patients with adenomatous polyp and patients with cancer

We determined the methylation status of 11 genes (Alu, APC, DAPK, MGMT, MLH1, MINT1, MINT2, MINT31, p16, RGS6, TFPI2) in the colonic mucosa of healthy volunteers, patients with adenomatous polyp and patients with cancer using pyrosequencing and then compared their methylation levels. Aberrant DNA methylation in human cancers is characterized by focal CpG island (CGI) hypermethylation and generalized genomic hypomethylation. Alu element accounts for about 10% of the human genome and is normally heavily methylated [16], representing as a surrogate measure of genomic hypomethylation levels. The other 10 genes are known to be important tumor-suppressor genes which are commonly down-regulated in CRC specimens and have an impact on the survival of patients [9, 10, 11, 17]. Because methylation changes at CGI-associated promoter sites have high relevance for gene expression, using instrument software (PyroMark ${}^{\text{\textregistered}}$ Assay Design 2.0), we designed the pyrosequencing primers with the highest score to encompass the consecutive 4 $\sim$ 12 CpGs in promoter or first exon CGIs. To provide the internal control for total bisulfite conversion, non-CpG cytosine in the region for pyrosequencing was included where possible. The distribution and mean values of pyrosequencing measurements for all genes were shown in Supplementary Fig. 1. Compared with the healthy participants, the Alu methylation level was significantly lower in colonic tissues from patients with polyp or cancer, but the methylation levels of all other genes, with the exception of DAPK, were significantly higher (Supplementary Fig. 1 and Table 1). The high methylation level of the DAPK gene was only seen with statistical significance in tumor tissue. Interestingly, the post-hoc comparison demonstrated that the methylation levels were successively decreased or increased in colonic mucosa during the normal-adenoma-carcinoma sequence, particularly for Alu, MGMT, MINT2, and TFPI2 (Table 1). However, no significant differences in the methylation levels between polyp patients and cancer patients were observed for APC, MLH1, MINT1, MINT31, p16, and RGS6 (Table 1). Subsequently, we evaluated the methylation frequency by setting mean $\pm$ 4SD as a cut-off point for methylation-positive category, as previously described [18, 19]. No or undetectable frequency was observed in the normal mucosa for all investigated genes (Table 1). For eight genes (MLH1 and p16 excluded), the colonic mucosa from patients with polyp or cancer showed significantly high frequencies of methylation in comparison to the healthy counterparts, while DAPK exhibited a tremendous prevalence in cancer patients only (Table 1). Moreover, the Bonferroni correction established that the methylation prevalence of the Alu, MGMT, MINT2, and TFPI2 genes was gradationally increased during the normal-adenoma-carcinoma sequence (Table 1). It is likely that a similar trend was present between the levels and frequencies of methylation. Additionally, we evaluated the predictive performance of combinations of different genes to differentiate patients with adenoma and CRC from healthy subjects using ROC curve analysis. The methylation levels of five-gene panel (DAPK, hMLH1, MINT1, MINT2, and TFPI2) exhibited high sensitivity and specificity to adenoma patients (AUC 0.940, 95% CI 90.1%–97.9%), whereas a TFPI2 methylation frequency was enough to distinguish adenoma patients from healthy normal samples (AUC 0.749, 95% CI 67.8%–82.0%) (Supplementary Fig. 2A). The levels and frequencies of DAPK and TFPI2 methylation had excellent diagnostic accuracy for CRC patients, with a high AUC of 0.988 and 0.967, respectively (Supplementary Fig. 2B).

The first major finding of this study was that methylation of the Alu, MGMT, MINT2, and TFPI2 genes progressively changed in colonic mucosa during the normal-adenoma-carcinoma progression. These contrary epigenetic changes have led to conviction that CGI hypermethylation may be mechanically linked to genome hypomethylation. However, this possibility is disputed by the fact that the relationship between CGI hypermethylation and genomic DNA hypomethylation is variable as independence or interdependence in various human cancers [20]. Moreover, the present study demonstrates a tendency for Alu methylation to decrease with tumor progression. In contrast, Bariol et al clearly demonstrated that CRC did not show a decrease of genomic methylation level with tumor progression [21].

The second novel finding of the current study was that CGI hypermethylation occurred either as an adenoma-associated event for APC, MLH1, MINT1, MINT31, p16, and RGS6 or a tumor-associated event for DAPK, being the first study to indicate that CGI methylation within colonic mucosa could occur in a stage-specific manner. Similarly, Kim et al.have reported that the frequent methylation of APC, MLH1, MINT1, MINT31, and p16 are presented in hyperplastic polyps and sessile serrated polyps from Korea [22]. Taken together, these results could be used to argue against a simple classification of methylated genes as age-related (type A) or cancer-specific (type C) [23]. Half of CRC patients present distant metastases at the time of diagnosis and the prognosis of advanced CRC remains poor. There is also considerable stage-independent variability in clinical outcomes due to molecular heterogeneity. Therefore, it is crucial to introduce more effective tools that will improve early diagnosis as well as prediction of disease progression. Overall, there are three kinds of distribution pattern in the alteration of DNA methylation during CRC tumorigenesis. One is a decreasing shift, alternative is an increasing shift. The latter is further subdivided into adenoma and cancer depend upon shift timing. Importantly, our observations suggest that methylation of the Alu, MGMT, MINT2, and TFPI2 genes might have substantial value as a predictive marker of progression risk and that CGI methylation of APC, MLH1, MINT1, MINT31, p16, and RGS6 or DAPK could serve excellent diagnostic biomarkers, particularly for adenoma or cancer patients, respectively.

Table 2
Comparison of mean levels and frequencies of DNA methylation between normal colonic mucosa of healthy subject and peritumoral nonmalignant colonic mucosa of CRC patients

[l]Genesymbol	Methylation levels (%)			Methylation frequencies (%)
	Normal	CRC	$P$ -value ${}^{*}$	Normal	CRC	$P$ -value ${}^{**}$
Alu1	26.70	26.20	0.0001	0.0	1.0	0.4613
APC	1.68	2.10	0.0164	1.8	2.9	0.6701
DAPK	7.60	17.02	$<$ 0.0001	0.0	34.3	$<$ 0.0001
MGMT	1.32	5.55	$<$ 0.0001	1.8	16.7	0.0053
MLH1	5.17	6.25	0.2768	1.8	2.0	0.9504
MINT1	5.46	6.90	0.0052	0.0	2.0	0.296
MINT2	4.47	6.69	$<$ 0.0001	0.0	2.0	0.296
MINT31	9.00	11.02	$<$ 0.0001	1.8	2.0	0.9504
P16	2.15	3.15	0.0009	1.8	2.9	0.6701
RGS6	4.53	5.13	0.0058	1.8	2.0	0.9504
TFPI2	6.43	19.03	$<$ 0.0001	1.8	37.3	$<$ 0.0001

* $P$ -values are for the comparison of mean methylation levels for sample groups using an independent $t$ -test following transformation of the response variable where appropriate. ** $P$ -values are for the comparison of methylation frequencies for sample groups using a chi-square test after the mean $\pm$ 4SD was set as a cut-off point for methylation-positive group.

3.2 Methylation comparison between the normal colonic mucosa from healthy volunteers and peritumoral nonmalignant mucosa from cancer patients

We contrasted the methylation levels of the same set of genes in the normal colonic mucosa from healthy controls and tumor-neighboring noncancerous mucosa from cancer patients using an independent $t$ -test. Although a narrow margin between the two groups was statistically significant for all examined genes except MLH1, a remarkable increase ( $>$ 2-fold) was detected for DAPK (2.2-fold), MGMT (4.2-fold), and TFPI2 (3.0-fold) genes (Table 2). Although the low level of CGI methylation in peritumoral normal-appearing mucosa have previously been dismissed as biologically insignificant on the grounds that they would have no measurable effect on gene expression [24], the striking difference observed in DAPK, MGMT, and TFPI2 implies that they could serve as biomarkers of risk for development of CRC. Interestingly, the methylation frequency results showed a similar phenomenon; high methylation prevalence of DAPK, MGMT, and TFPI2 were seen in the matched nonmalignant mucosa of cancer patients (Table 2).

The third novel finding of the current study was the presence of relatively high levels and frequencies of DAPK, MGMT, and TFPI2 methylation in the tumor-adjacent nonmalignant mucosa of cancer patients in a field-cancerization manner, suggesting that mucosal DNA methylation could be an important marker of, or even a biological prelude to, colorectal carcinogenesis. Additionally, the methylation pattern of these biomarkers could be advantageous for discrimination of CRC patients from healthy persons. A field defect of widespread epigenetic alteration was well demonstrated in colonic normal-appearing tissue [25, 26]. Unlike most of the studies of frequently methylated genes in CRC were performed on the corresponding nonmalignant tissues of CRC patients [27, 28, 29], our findings have provided additional information on the methylation prevalence in the normal colonic mucosa of healthy participants. Lastly, our results support the recent finding that the differences in methylation levels within normal colonic tissue are quantitative rather than qualitative [29].

Collectively, although the present study was limited by the small number of sample cases and the lack of analysis of mRNA expressions according to methylation levels, it has demonstrated the serial accumulation of methylation levels and frequencies of several genes in colonic tissue during the normal-adenoma-carcinoma sequence and the presence of a gene-specific starting point in aberrant CGI methylation. In addition, significant degrees of levels and frequencies of methylation were detectable in the peritumoral, normal-appearing colonic mucosa from CRC patients for a subset of genes. Therefore, these results suggest that mucosal DNA methylation of the genes we identified might be associated with the progression of colorectal adenoma or carcinoma and that they could hold significant potential for diagnostic and prognostic applications to CRC. Moreover, the current findings provide novel insights into the clinical management of pyrosequencing-derived methylation levels. However, further studies with a large number of patients are required to confirm these findings.

Authors’ contributions

	BK	HSL	SWJ	SYP	GSC	WKL	SH	DHL	DSK
Conception	X								X
Interpretation or analysis of data	X	X	X	X	X	X	X	X	X
Preparation of manu- script	X								X
Revision for important intellectual content	X	X				X		X	X
Supervision									X

Ethics approval and consent for participation and publication

This study was conducted with the approval of IRB, KNUH (No. KNUMCBIO 14-1001). Participants were provided their written informed consent to participate in this study and to publish all associated data.

Supplementary data

The supplementary files are available to download from http://dx.doi.org/10.3233/CBM-203259.

sj-pdf-1-cbm-10.3233_CBM-203259.pdf - Supplemental material

Supplemental material, sj-pdf-1-cbm-10.3233_CBM-203259.pdf

Footnotes

Acknowledgments

This work was supported by Biomedical Research Institute grant, Kyungpook National University Hospital (2019). This research was supported by a grant of the Korea Health Technology R&D Project through the Korea Health Industry Development Institute (KHIDI), funded by the Ministry of Health & Welfare, Republic of Korea (grant number: HI15C0001).

Conflict of interest

None.

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Progressive alteration of DNA methylation of Alu,MGMT,MINT2,and TFPI2 genes in colonic mucosa during colorectal cancer development

Abstract

BACKGROUND:

OBJECTIVE:

METHODS:

RESULTS:

CONCLUSION:

Keywords

1. Introduction

2. Materials and methods

2.1 Clinical specimens

2.2 DNA extraction, bisulfite treatment, and pyrosequencing

Table 1 Comparison of mean levels and frequencies of DNA methylation in colonic mucosa of healthy normal person, patients with adenomatous polyp and patients with colorectal cancer

3. Results and discussion

3.1 CGI methylation profiling in the colonic mucosa of healthy volunteers and patients with adenomatous polyp and patients with cancer

Table 2 Comparison of mean levels and frequencies of DNA methylation between normal colonic mucosa of healthy subject and peritumoral nonmalignant colonic mucosa of CRC patients

Authors’ contributions

Ethics approval and consent for participation and publication

Supplementary data

sj-pdf-1-cbm-10.3233_CBM-203259.pdf - Supplemental material

Footnotes

Acknowledgments

Conflict of interest

References

Table 1
Comparison of mean levels and frequencies of DNA methylation in colonic mucosa of healthy normal person, patients with adenomatous polyp and patients with colorectal cancer

Table 2
Comparison of mean levels and frequencies of DNA methylation between normal colonic mucosa of healthy subject and peritumoral nonmalignant colonic mucosa of CRC patients