Exon 1 Methylation Status of CDH13 is Associated with Decreased Overall Survival and Distant Metastasis in Patients with Postoperative Colorectal Cancer

doi:10.21203/rs.3.rs-4831937/v1

Background

Cadherin 13 (CDH13) is a member of the cadherin superfamily that exerts tumor-suppressive effects on cancers derived from epithelial cells. Although hypermethylation of CDH13 promoter has been reported in various cancers, its prognostic value for colorectal cancer (CRC) is still controversial. The methylation alterations of CDH13 within exon 1 have not yet been investigated.

Methods

A total of 49 CRC patients were recruited for the prospective study. The methylation status of CpG sites was quantified by Bisulfite Amplicon Sequencing (BSAS) in malignant tissues and adjacent non-malignant tissues. The primary endpoint of the study was overall survival (OS) after surgery. The relationship between methylation level with pathological stage and OS was also evaluated.

Results

Compared with adjacent tissues, the overall average methylation level within exon 1 was significantly increased in tumor tissues (p < 0.001). The association study showed that the hypermethylation status of the CpG1 site was non-significantly associated with the presence of distant metastasis (p = 0.032). Moreover, the hypermethylation of two CpG sites, including CpG1 (p = 0.003) and CpG5 (p = 0.032), was associated with worse OS in CRC. Co-hypermethylation of CpG1 and CpG5 sites was significantly associated with a worse clinical outcome (HR: 4.43 [95% CI:1.27–15.46]; p = 0.019) in multivariate Cox regression analysis.

Conclusion

The methylation level of CDH13 exon 1 in CRC tissue was significantly higher than in adjacent non-malignant tissues. Hypermethylation at the CpG1 site suggests a risk of distant metastasis in CRC. The hypermethylation of the CpG1 site and CpG5 site, including the co-hypermethylation of these two sites, may serve as a valuable prognostic biomarker.

colorectal cancer (CRC)

CDH13 gene

methylation

CpG site

WHAT IS KNOWN

Cadherin 13 (CDH13) exerts tumor-suppressive effects on cancers derived from epithelial cells.
Methylation of the exon 1, 5‘untranslated regions (5’ UTR) and 200 base pairs (bp) upstream the transcription start site (TSS200) are vital in gene methylation.
The prognostic value of status of methylation of CDH12 for colorectal cancer (CRC) is still controversial.

WHAT IS NEW HERE

The hypermethylation of the CpG1 site and CpG5 site, including the co-hypermethylation of these two CpG site, may serve as a valuable prognostic biomarker

Colorectal cancer (CRC) is the third most common human malignant disease and was regarded as the second leading cause of cancer deaths worldwide in 2018.¹ Although most patients undergo surgery with adjuvant chemotherapy and/or radiotherapy, the median overall survival (OS) for the most malignant CRC ranges from 4 to 6 months only.² Evidence indicates that alterations in epigenetic machinery, such as DNA methylation, are critical for cancer initiation and progression.³ Hypermethylation in cytosine-phosphate-guanine (CpG) island regions of tumor suppressor gene usually affects important biological processes, interferes with DNA repair, regulates the cell cycle and promotes the formation of tumor cells, thus impacting tumor progression and prognosis.^4,5 A series of methylated tumor suppressor genes such as transmembrane protein 240 (TMEM240)⁶, chondrolectin (CHODL)⁷ and ependymin related 1 (EPDR1)⁸ have been shown to have predictive value for CRC prognosis.

H-cadherin, encoded by the CDH13 gene, is an atypical member of a large cadherin superfamily, devoid of a transmembrane domain and anchored to the exterior surface of the plasma membrane via a glycosylphosphatidylinositol anchor.⁹ The dysfunction of CDH13 has been linked with various diseases such as cancer, neurodevelopmental disorder and atherosclerosis.¹⁰ Previous studies have indicated that loss of CDH13 expression may account for aberrant cell adhesion, cell signal transduction and cell proliferation, impacting the survival, growth and transformation of tumor cells in numerous instances of tumorigenesis, such as gastric cancer¹¹ and liver cancer¹².

Currently, research on DNA methylation in CpG island is mainly focused on the promoter region and exon 1. Data showed that abnormal hypermethylation of DNA in CpG island can lead to transcriptional inactivation, resulting in decreased gene expression or even no expression, thus promoting the occurrence of malignant tumors.¹³ The change in the methylation pattern of CDH13 in tumor cells was first found in the region related to the promoter, so the previous studies on aberrant methylation of CDH13 were mainly focused on the promoter.¹⁴ The role of hypermethylation in the CDH13 promoter region in CRC has been widely studied and most studies have found that CRC tumor tissues are more prone to hypermethylation than adjacent normal tissues.^15–17 Some studies reported that CDH13 methylation is related to selected clinicopathological features or poor prognosis of CRC. Wang et al. (2012) further demonstrated that the promoter methylation of CDH13 is related to poor differentiation and shorter survival time.¹⁸ However, Duan et al. (2017) showed that the promoter methylation status of CDH13 was closely related to the risk of CRC, but it was of limited value in evaluating the prognosis of CRC patients.¹⁹

The relationship between promoter methylation of CDH13 and the prognosis of CRC patients remained unclear. It has been suggested to evaluate the prognostic value of methylation in other important regions of CDH13 in patients with CRC. Indeed, Ozer et al. (2017) proposed that exon 1, 5' UTR and 200 bp upstream the transcription start sites are more crucial than other genomic regions in the internal mechanism of cancer.²⁰

In the present study, we investigated methylation levels of CDH13 exon 1 in a cohort of CRC patients by using the BSAS method. Furthermore, we aimed to assess CpG site-specific hypermethylation for accurately predicting prognosis biomarkers.

Ethical statement

This study was approved by the Institutional Review Board and Human Ethics Committee of the East Affiliated Hospital of Tongji University School of Medicine, Shanghai Province, China. Written informed consent was obtained from all related participants for sample collection and data analysis.

Study subjects and data collection

Samples from 49 patients (32 males and 17 females) with CRC confirmed by pathological diagnosis were collected from a follow-up study. These patients received surgical resection in East Hospital affiliated with Tongji University from October 2009 to June 2010 and from July 2011 to March 2012, respectively. None of the patients had any other history of cancer or received pre-operative radiotherapy or chemotherapy prior to CRC surgery. Clinical data of age, gender, tumor markers, clinic pathologic characteristics, and clinical information about disease and treatment were collected from the medical record registration system.

DNA isolation and bisulfite treatment

Genomic DNA was extracted from paraffin-embedded CRC tissues using standard phenol-chloroform extraction and ethanol precipitation protocol as previously described.²¹ High-molecular-weight genomic DNA from CRC tumor samples and corresponding normal tissue samples were purified using the QIAmp DNeasy Blood & Tissue Kit (Qiagen, Hilden, Germany) according to the manufacturer’s instructions. The yield and purity were determined using a Nanodrop 1000 Spectrophotometer (Thermo Fisher Scientific, Waltham, MA, USA). Bisulfite treatment was performed using EZ DNA Methylation-Gold TM Kit (ZYMO, California, USA). After bisulfite treatment, all unmethylated cytosine was converted to uracil while leaving methylated cytosine unchanged. Bisulfite-treated genomic DNA samples were stored at -20℃ until use.

Primer design and DNA methylation analysis using BSAS

As shown in Figure 1A, the CDH13 exon 1 is located on chromosome 16 (GRCh38:CHr16: 82626969-82627137). The sequences of the target DNA fragment, which contains 13 CpG sites, were obtained from the genomic sequence (GRCh38:CHr16: 82626991-82627122). The purified bisulfite‑modified DNA was amplified using the following primers containing 186 bp sequence which was designed by Meth Primer software online: CDH13 gene forward, 5’ TTTGGGAAGTTGGTTGGTTG-3 and reverse, 5’- ACAACCCCTCTTCCCTACCT -3’. The modified DNA was amplified by polymerase chain reaction (PCR) using the following conditions: 95˚C for 5 minutes and then 45 cycles of 95˚C for 15 seconds, 55˚C for 20 seconds and 72˚C for 20 seconds, followed by a 5-minute incubation at 72˚C. The PCR products were analyzed by gel electrophoresis in 1.5% agarose gel to confirm that a single band had been produced. Then, column purification and recovery were established according to the instructions of the protocol for FavorPrep GEL/PCR Purification Kit. And then a series of methylation standards were constructed, which included 100%, 80%, 60%, 40%, 20% and 0% methylated DNA. Through the construction of a second-generation sequencing library, those amplified DNA was sequenced using the 2*300 of the Illumina Miseq platform. The original image data obtained by sequencing were converted into sequence data by base calling (raw data). After quality control, the qualified sequencing results were compared with the target fragment sequence by Bowtie 2 software. Target CpG sites were evaluated by using the Methyl Kit package of the R language, which converts the amplifier sequencing diagram to numerical values and calculates the proportion of methylation at each base as a C/T ratio.

Statistical analysis

The output data includes site-specific percent methylation for each CpG in the investigated area, as well as overall average percent methylation, which was calculated as a mean value of all 13 CpG sites detected within exon 1. Overall or site-specific methylation levels of CDH13 were compared between CRC tissues and control subjects using the non-parametric Wilcoxon’s Rank Sum test. Receiver operator characteristic (ROC) curve analysis using MedCalc Software was constructed for distinguishing CRC and adjacent normal tissues. Univariate logistic regression analysis was performed to estimate the odds ratio (OR) of clinicopathological characteristics. The prognostic value of clinicopathological factors and CDH13 site-specific hypermethylation was analyzed with Kaplan-Meier survival analysis and standard log-rank test. Multivariate models were then developed that adjusted for the most important covariates. All statistical analyses were performed using GraphPad Prism v8.3.0. p<0.05 was considered statistically significant.

Clinicopathological characteristics of all 49 sample

According to the data format, the clinicopathological characteristics of all the samples are listed in Table 1.

Overall average and site-specific methylation levels of CDH13 exon 1 in CRCs

Using the BSAS method, we quantified the methylation status of 13 individual CpG sites located in the CDH13 exon 1. The aim of this analysis was to define the methylation levels of the CRC patient’s tumor and adjacent non-malignant tissue and to assess whether any of the tested sites could be considered as a potential tumor-tissue marker. As shown in Figure 1B, methylation level in all samples are presented, and percent methylation at 13 CpG sites, as well as overall average percent methylation, are significantly higher in CRCs than in comparable normal tissues, As shown in the following Table 2.

ROC curve analysis was performed to evaluate the diagnostic value of differentially methylated CpG sites. As shown in Figure 1C, 13 CpG sites showed a moderate AUC of the ROC curves, ranging from 0.729 to 0.776. Since an AUC of ≥0.75 generally indicates a marker that could potentially have clinical utility²², we combined these 13 CpG sites to improve the diagnostic power. The result indicated that a combination of these indicators increased sensitivity and specificity (AUC=0.844; p<0.0001). Age-dependent methylation has been recognized as an important physiological process^23,24; In this study, we included age in the diagnostic model, and the result revealed no significant difference in diagnostic performance compared with the combined diagnosis of the 13 CpG sites. This suggests that the methylation status of specific CpG sites in CDH13 are not promising diagnostic biomarker candidates for the differentiation of CRC tissues from surrounding non-malignant tissue.

Association between methylation level and clinicopathological characteristics in CRCs

Although the average methylation level in adjacent normal tissue was low in exon 1, it could be far beyond the average in some cases. Even in a few samples, the methylation levels in non-malignant tissues were higher than the cutoff values derived from the ROC curve analysis. This non-negligible methylation pattern suggests that a criterion must first be set up to define hypermethylation at CpG sites in order to analyze the association of CDH13 hypermethylation with clinicopathological characteristics. We set a threshold value of 25% methylation difference between tumor and non-malignant to ensure and only aberrant hypermethylation cases were assigned as positive. Next, the relationship between the methylation status of exon 1 and clinicopathological features was assessed by univariate logistic analysis. The findings are shown in Table 3. A positive correlation was observed between hypermethylation at CpG site 1 and the presence of distant metastasis, which was statistically significant (OR: 7.60 [95% CI: 1.19–48.44], p= 0.032). Considering that both site 1 and site 5 indicate poor prognosis, which is shown in Figure 2, we combined them to integrally analyze their relationship between the methylation status and clinicopathological features. A significant correlation between the co-hypermethylation of sites 1 and 5, and distant metastasis was observed (OR: 9.75 [95% CI:1.46−65.36]; p= 0.019)..

Effect of CDH13 hypermethylation on poor survival of CRC patients

The last follow-up date for this study was April 19, 2020, with an average follow-up time of 116 months. During the follow-up period, survival data of 49 patients were obtained, of whom 27 (55.1%) died. The time from patient’s surgery to death for various reasons or the last follow-up visit was defined as the overall survival (OS) time. With the cutoff values described above, we used Kaplan-Meier survival curves and a log-rank test to determine the effect of CDH13 hypermethylation on the survival of CRC patients. In accordance with the findings shown in Figures 2M and 2N, the hypermethylation versus non-hypermethylation status of site 1 (OS, 52.0 ±12.6 months vs 94.7 ± 5.6 months on average, p=0.003) and site 5 (OS, 79.9 ± 7.3 months vs 97.0 ± 8.2 months on average, p=0.032) was associated with poor prognosis. Considering the statistical significance between tumorous hypermethylation and OS was only found in these two sites, we combined them to integrally analyze their contribution to patients’ outcomes. When we combined patients with hypermethylation at both sites, they achieved significantly worse survival than the patients without hypermethylation at both sites (57.0 ± 13.4 months vs 92.8 ± 5.8 months on average, p=0.020) (Figure 2O).

The prognostic value of clinicopathological factors and hypermethylation were analyzed by univariate and multivariate Cox regression analysis. The multivariate Cox analysis included CEA, TNM stage, lymph node metastasis and distant metastasis. To answer the question of whether the co-hypermethylation status of site 1 and site 5 contributes independently prognosis evaluation or is associated with disease factors such as CEA, TNM stage, lymph node metastasis and distant metastasis, the relationship of site-specific hypermethylation with OS was studied using multivariate Cox regression analysis. Results indicated that co-hypermethylation of sites 1 and 5 is a predictor of poor prognosis for CRC patients both in univariate analysis (HR:2.82 [95%CI: 1.13–7.04]; p=0.027) and multivariate Cox regression analysis (HR: 4.43 [95% CI: 1.27–15.46]; p=0.019) (Table 4).

DNA methylation plays a key role in CRC and has been confirmed as a new prognostic factor of the disease.²⁵ Previous studies used methods that just qualitatively analyze particular CpG sites or quantitatively analyze overall methylation levels of the promotor of the candidate gene. Due to the inconsistent research results, its correlation between methylation status and clinicopathological significance remains controversial. Currently, methylation alteration in exon has attracted more attention since the CpG site was found to frequently occur in some tumor suppressor genes and DNA methylation in transcribed regions was also correlated with gene expression.²⁶ DNA methylation of exon-encoding regions on alternative splicing has been confirmed.²⁷ Studies have shown that most of the differential methylation regions are located in the promoter regions near the transcriptional initiation site, 5' UTR and exon 1.²⁸ Li et al. (2018) have shown that it is the methylation of specific CpG sites, and not the methylation of the whole gene, is associated with clinical features and prognostic value, suggesting that site-specific methylation has different biological functions.²⁹ The analysis of exon regions would provide more detectable sites and may be novel biomarkers or therapeutic targets in cancer.²⁶

To our knowledge, this is the first study where the methylation status of CDH13 in CRC was evaluated using next-generation sequencing (NGS). BSAS is one of the most accurate methods available for quantifying DNA methylation at specific CpG sites within the target region of interest.³⁰ It is a sensitive and highly reproducible method that is uniquely suited to the analysis of a small fraction of the total DNA in clinical samples.³¹ Our data showed the overall methylation level of CDH13 exon 1 and methylation levels at all 13 CpG sites were significantly higher in CRC than in paired adjacent normal tissues, which was in line with a previous systematic study about tumor suppressor gene sequencing.^7,26

We further explored the relationship between the aberrant hypermethylation of the CDH13 site and clinicopathological features of CRC patients. However, our research revealed that CDH13 methylation might occur in non-neoplastic tissues; a threshold should be set to confirm positive hypermethylation. Some groups have used median as a basis for cutoff value determination for prognostic methylation markers in colon adenocarcinoma.^6,27,32 However, this may be suboptimal because the existence of outliers may have a considerable impact on the distribution of methylation data in non-malignant tissues. Wang et al. (2016) set a threshold value derived from ROC curve analysis for hypermethylation positivity³³, often statistically optimal, but in our study, it is less compatible with the biological relevance. Ozer et al. (2017) found that 25% methylation change in previously determined genomic regions showed the highest inverse correlation with expression data.²⁰ Therefore, we set a threshold value at 25% to ensure that only aberrant hypermethylation cases were assigned as positive. The subsequent statistical analysis uncovered a significant correlation between CDH13 exon 1 and the presence of distant metastasis, which suggested that the hypermethylation of CDH13 was associated with CRC invasion and metastasis. Dmitrijeva et al. (2018) found that there may be CpG hypermethylation overlap sites in the process of aging and tumor.²³ No significant difference was shown in the correlation between age and hypermethylation of CpG site, which may be related to many factors, such as too small sample size; the location of the selected tumor, the selected population, etc., suggesting that the internal mechanism of the relationship between hypermethylation at CpG site and aging needs to be further studied.

To analyze the association between CDH13 hypermethylation and cancer death, we performed Kaplan-Meier survival curves and univariate Cox proportional hazard regression to determine the effect of CDH13 hypermethylation on the survival of CRC patients. Our results indicated no significant association or predictive value of overall hypermethylation concerning patient outcomes. Nevertheless, the methylation status of the CpG1 site and the CpG5 site was associated with a poor prognosis. To further evaluate whether co-hypermethylation at the CpG1 site together with the CpG5 site is an independent predictor of prognosis in patients after surgical resection of CRC, multivariate Cox regression analysis was established. The results showed that distant metastasis and CEA were independent predictors of the prognosis of CRC, comparable with the results of previous studies.^34,35 Notably, hypermethylation of site 1 together with site 5 is suggested as an independent predictor of poor prognosis for CRC patients. Thus, it can be observed that site-specific methylation analysis offers more information and fosters researchers to obtain additional details. CDH13 exon 1 hypermethylation may serve as a valuable biomarker in evaluating clinical outcomes of CRC patients.

The results of our current research demonstrated differentially methylated CpG sites in exon 1 of CDH13. The methylation status of the CpG1 site and the CpG5 site could serve as a promising and reliable prognostic biomarker. However, the published data on this subject is very limited, presented results should be confirmed on the larger number of samples.

The datasets analyzed during the current study are available from the corresponding author on reasonable request.

Acknowledgment

The authors acknowledge the staff from the Department of General Surgery, Shanghai East Hospital and Meiting Lian, Haijun Zhu, Tonghai Dou from Shanghai Amplicongene Biotech Co., Ltd. for their assistance.

Funding Source

The research is funded by the National Natural Science Foundation of China (Grant No 82160515).

Specific author contributions

Data analysis, Writing and Study Design: Pengcheng Xiang, Pengju Li; Data collection and Investigation: Xiaoqi Yuan, Xiuhao Zhao, Zitian Xiao; Review and Editing: Ewelina Biskup, Bingguan Chen; Funding Acquisition and Study Design: Junyi Han. All authors have read and agreed to the published version of the manuscript.

Disclaimers

The authors declare no conflict of interest. All the views expressed in this article are our own and not an official position of the institution or funder.

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Table 1: Baseline characteristics of 49 patients in the study.

Variable	Classification	Number	Frequency (%)
Age (yrs)	<65	24	51.0
	≥65	25	49.0
Gender	Male	32	65.3
	Female	17	34.7
Tumor location	Colon	24	51.0
	Rectum	25	49.0
Differentiation	High-Moderate	37	75.5
	Moderate-Low	12	24.5
Tumor stage	T1	3	6.1
	T2	4	8.2
	T3	30	61.2
	T4	12	24.5
Lymph node metastasis	N0	25	51.0
	N1	14	28.6
	N2	10	20.4
Distant metastasis	M0	43	87.8
	M1	6	12.2
Tumor stage (TNM)	I	6	12.2
	II	17	34.8
	III	20	40.8
	IV	6	12.2
Vascular vessel permeation	Absent	28	57.1
	Present	21	42.9
Nerve invasion	Absent	32	65.3
	Present	17	34.7

Table 2: Methylation level in all samples.

	Tumor	Normal	P
Site1	10.25(3.39-22.30)	2.99(2.06-5.52)	<0.001
Site2	17.36(6.24-28.53).	5.07(3.27-8.98)	<0.001
Site3	24.68(10.43-50.00)	9.38(6.65-15.62)	<0.001
Site4	18.05(6.48-37.37)	5.60(3.65-9.72)	<0.001
Site5	28.57(12.24-51.99)	10.75(7.62-16.02)	<0.001
Site6	37.87(13.71-56.12)	12.59(9.97-18.20)	<0.001
Site7	36.69(13.61-55.67)	13.02(8.78-17.87)	<0.001
Site8	33.26(12.91-52.70)	9.73(7.48-15.65)	<0.001
Site9	35.64(15.07-56.28)	12.45(8.99-19.21)	<0.001
Site10	31.28(9.34-49.81)	7.29(5.30-12.90)	<0.001
Site11	32.76(11.73-53.74)	10.37(7.80-17.84)	<0.001
Site12	25.98(7.78-49.44)	6.84(3.91-12.40)	<0.001
Site13	26.12(7.63-52.07)	6.99(4.60-12.07)	<0.001
Overall	29.93(9.85-48.04)	9.50(6.41-14.62)	<0.001

Table 3. Univariate associations of site-specific and overall methylation status of exon 1 in colorectal cancer with clinicopathological characteristics (odds ratio and 95% CI). CA, cancer antigen; CEA, carcinoembryonic antigen.

	Site 1^a	Site 2^a	Site 3^a	Site 4^a	Site 5^a
Gender^b	1.73 (0.31–9.68)	1.56 (0.35–6.84)	1.62 (0.48–5.44)	1.87 (0.53–6.55)	1.43 (0.42–4.81)
Age^c	0.28 (0.06–1.35)	1.02 (0.25–4.12)	1.29 (0.40–4.22)	0.99 (0.30–3.27)	1.65 (0.49–5.52)
Tumor location^d	0.29 (0.05–1.60)	0.83 (0.22-3.20)	0.46 (0.15–1.47)	0.45 (0.14–1.45)	0.38 (0.12–1.24)
Tumor size^e	0.70 (0.15–3.30)	1.65 (0.43–6.37)	2.40 (0.75–7.65)	2.38 (0.73–7.69)	1.42 (0.45–4.46)
Differentiation^f	2.13 (0.43–10.69)	1.21 (0.26–5.54)	1.47 (0.40–5.43)	1.85 (0.49–6.89)	1.64 (0.44–6.10)
CEA^g	0.86 (0.19–3.93)	0.68 (0.18–2.60)	0.95 (0.31–2.96)	0.97 (0.31–3.07)	1.14 (0.36–3.58)
CA19-9^h	1.86 (0.38–9.20)	1.05 (0.23–4.76)	1.20 (0.34–4.30)	1.52 (0.42–5.48)	1.35 (0.38–4.84)
Tumor invasionⁱ	1.44 (0.49–4.25)	0.59 (0.26–1.36)	1.33 (0.43-4.16)	0.93 (0.44–1.93)	0.92 (0.44–1.90)
Lymph node metastasis^j	3.83 (0.69–21.30)	2.16 (0.54–8.64)	1.27 (0.41–3.94)	1.80 (0.56–5.75)	1.50 (0.48–4.73)
Distant metastasis^k	7.60 (1.19–48.44)*	1.89 (0.30–12.01)	3.06 (0.50–18.58)	3.73 (0.61–22.80)	3.38 (0.55–20.55)
Tumor stage^l	8.11 (0.91–71.94)	2.96 (0.68–12.91)	1.04 (0.50–2.16)	1.96 (0.60–6.35)	1.61 (0.51–5.09)
Vascular vessel permeation	1.41 (0.31–6.45)	1.15 (0.30–4.42)	1.00 (0.32–3.14)	1.35 (0.42–4.30)	1.16 (0.37–3.66)
Nerve invasionⁿ	2.15 (0.46–9.99)	1.10 (0.27–4.45)	0.90 (0.27–2.96)	1.17 (0.35–3.88)	1.02 (0.31–3.38)
	Site 6	Site 7	Site 8	Site 9	Site 10
Gender^b	2.09 (0.63–6.91)	2.36 (0.70–7.95)	1.84 (0.56–6.05)	1.83 (0.55–6.16)	2.08 (0.62-6.99)
Age^c	0.85 (0.27–2.74)	0.94 (0.29–2.97)	1.07 (0.33–3.41)	1.47 (0.45–4.80)	0.82 (0.26–2.64)
Tumor location^d	0.79 (0.26–2.42)	0.56 (0.18–1.74)	0.67 (0.22–2.05)	0.39 (0.12–1.25)	0.66 (0.21–2.04)
Tumor size^e	1.56 (0.50–4.85)	2.10 (0.67–6.60)	1.29 (0.42–4.00)	1.46 (0.47–4.52)	1.25 (0.40–3.87)
Differentiation^f	1.33 (0.36–4.95)	1.65 (0.44–6.15)	1.48 (0.40–5.51)	2.05 (0.55–7.70)	1.18 (0.32–4.33)
CEA^g	1.49 (0.48–4.60)	1.09 (0.36–3.35)	1.27 (0.41–3.92)	1.11 (0.36–3.45)	0.94 (0.30–2.88)
CA19-9^h	1.60 (0.44–5.84)	1.30 (0.37–4.65)	0.77 (0.22–2.74)	1.63 (0.46–5.85)	1.46 (0.41–5.21)
Tumor invasionⁱ	1.13 (0.55–2.32)	1.01 (0.49–2.07)	0.87 (0.42–1.79)	1.03 (0.50–2.12)	1.17 (0.56–2.42)
Lymph node metastasis^j	1.09 (0.36–3.35)	1.08 (0.35–3.32)	0.67 (0.22–2.05)	1.50 (0.48–4.65)	1.77 (0.57–5.51)
Distant metastasis^k	1.91 (0.32–11.55)	2.30 (0.38–13.92)	0.96 (0.17–5.27)	2.78 (0.46–16.84)	2.53 (0.42–15.30)
Tumor stage^l	1.07 (0.35–3.29)	1.09 (0.36–3.35)	0.66 (0.21–2.04)	1.56 (0.50–4.85)	1.82 (0.58–5.67)
Vascular vessel permeation	1.86 (0.59–5.93)	1.78 (0.57–5.58)	1.10 (0.36–3.41)	1.70 (0.54–5.34)	1.05 (0.34–3.26)
Nerve invasionⁿ	1.43 (0.44–4.69)	1.28 (0.39–4.14)	1.62 (0.49–5.32)	1.64 (0.50–5.38)	1.45 (0.44–4.71)
	Site 11	Site 12	Site 13	Overall	Sites 1&5
Gender^b	1.43(0.44–4.69)	1.83(0.55–6.16)	2.12(0.61–7.42)	2.40(0.69–8.40)	1.39(0.24–8.05)
Age^c	1.17(0.34–3.76)	1.03(0.32–3.31)	1.65(0.49–5.52)	1.29(0.40–4.22)	0.38(0.07–1.91)
Tumor location^d	0.66(0.21–2.04)	0.55(0.18–1.73)	0.38(0.12–1.24)	0.32(0.10–1.06)	0.14(0.02–1.25)
Tumor size^e	1.25(0.40–3.87)	1.46(0.47–4.52)	1.01(0.32–3.17)	1.70(0.54-5.34)	0.91(0.18–4.57)
Differentiation^f	1.18(0.32–4.33)	1.31(0.36–4.84)	0.66(0.17–2.57)	1.47(0.40-5.43)	2.75(0.52–14.59)
CEA^g	0.94(0.30–2.88)	0.80(0.26–2.47)	0.81(0.26–2.55)	0.95(0.31-2.96)	0.62(0.12–3.12)
CA199^h	0.96(0.27–3.42)	1.07(0.30–3.83)	1.35(0.38-4.84)	1.83(0.51-6.59)	1.13(0.19–6.67)
Tumor invasionⁱ	1.02(0.49–2.09)	1.03(0.50–2.12)	0.92(0.44-1.90)	0.91(0.44-1.87)	1.13(0.39–3.27)
Lymph node metastasis^j	1.27(0.41–3.92)	1.50(0.48–4.65)	1.07(0.34-3.35)	1.27(0.41-3.94)	3.03(0.53–17.39)
Distant metastasis^k	2.53(0.41–15.30)	2.78(0.46–16.84)	3.38(0.55–20.55)	3.06(0.50–18.58)	9.75(1.46–65.36)*
Tumor stage^l	1.30(0.42–4.01)	1.56(0.50–4.85)	1.14(0.36–3.58)	1.33(0.43–4.16)	6.60(0.73–59.68)
Vascular vessel permeation	1.05(0.34–3.26)	0.87(0.28–2.71)	1.16(0.37–3.66)	1.41(0.45–4.41)	1.00(0.20–5.04)
Nerve invasionⁿ	1.01(0.31–3.27)	1.14(0.35–3.72)	1.02(0.31–3.38)	1.30(0.40-4.25)	1.50(0.29–7.65)

*p<0.05; ^aOR, odds ratio with 95% confidence interval; ^bgender (male; female); ^cage (<65 years; ≥65 years); ^dtumor location (colon; rectum); ^eTumor size (≤5 cm; >5 cm); ^fDifferentiation (well-moderate; moderate-poor); ^gCEA (≤5ng/ml; >5ng/ml); ^hCA199 (≤27ng/ml;>27ng/ml); ⁱtumor invasion (T1−T2; T3−T4); ^jlymph node metastasis (yes vs no); ^kdistant metastasis (yes vs no); ^ltumor stage (I−II; III−IV); ^mvascular vessel permeation (yes vs no); ⁿverve invasion (yes vs no).

Table 4. Prognostic value of clinicopathological factors and co-hypermethylation of site 1 and site 5 in univariate and multivariate Cox regression analysis (n=49). CEA, carcinoembryonic antigen.

	Univariate analysis		Multivariate analysis
	HR		HR
Variable	(95% CI)	p	(95% CI)	p
CEA
≤5 ng/ml	1.00 (reference)		1.00 (reference)
>5 ng/ml	3.95 (1.66−9.40)	0.002	5.07 (1.72−14.98)	0.003
Lymph node metastasis
Absent	1.00 (reference)		1.00 (reference)
Present	2.92 (1.30–6.55)	0.009	1.35 (0.19–9.67)	0.766
Distant metastasis
Absent	1.00 (reference)		1.00 (reference)
Present	16.10 (4.80−53.94)	<0.001	4.55 (1.09−18.93)	0.037
Tumor stage
I−II	1.00 (reference)		1.00 (reference)
III−IV	4.08 (1.71−9.73)	0.002	2.36 (0.26−21.19)	0.444
Methylation status of sites 1 & 5
Non-hypermethylation	1.00 (reference)		1.00 (reference)
Co-hypermethylation	2.82 (1.13–7.04)	0.027	4.43 (1.27–15.46)	0.019

No competing interests reported.

Exon 1 Methylation Status of CDH13 is Associated with Decreased Overall Survival and Distant Metastasis in Patients with Postoperative Colorectal Cancer

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