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ABSTRACT Prostate cancer (PCa) is a worldwide disease that affects a large number of males. Although prostate-specific antigen (PSA) screening is used, the specificity is limited. This study

analyzes the sensitivity and specificity of adenomatous polyposis coli (APC) methylation for PCa detection in body fluids and tissues. Combining search results from PubMed and Embase, 19

studies were included, 5 involving body fluids and 14 involving prostate tissue, with 2344 subjects. In body fluid subgroups, the pooled sensitivity and specificity was 0.53 (95% confidence

interval (CI): 0.28–0.78) and 0.92 (95% CI: 0.86–0.95), respectively. From tissue studies, the results presented as 0.84 (95% CI: 0.70–0.92) and 0.91 (95% CI: 0.77–0.97). To confirm the

results, we conducted a further analysis by removing studies which introduced high heterogeneity due to the type of cases and controls. The same degree of sensitivity and specificity was

presented in two subgroups (urine: sensitivity 0.46, 95% CI: 0.39–0.53; specificity 0.87, 95% CI: 0.64–0.96; tissue: sensitivity 0.87, 95% CI: 0.72–0.94; specificity 0.89, 95% CI:

0.68–0.97). In addition, analysis of the interaction between APC methylation and PCa showed strong association in the whole data set (odds ratio (OR)=24.91, 95% CI: 12.86–48.24, _I_2=72.5%).

Pooling the same two main subgroups (tissue/fluid) gave a pooled OR of 33.54 (95% CI: 14.88–75.59; _I_2=70.7%) and 8.20 (95% CI: 2.84–23.74, _I_2=64.2%), respectively. From this study, the

results suggest that APC promoter methylation may be the potential testing for PCa diagnosis and provide a new viewpoint in the treatment of PCa. SIMILAR CONTENT BEING VIEWED BY OTHERS A

GENETIC STUDY TO IDENTIFY PATHOGENIC MECHANISMS AND DRUG TARGETS FOR BENIGN PROSTATIC HYPERPLASIA: A MULTI-OMICS MENDELIAN RANDOMIZATION STUDY Article Open access 04 October 2024 URINE

BIOMARKERS CAN PREDICT PROSTATE CANCER AND PI-RADS SCORE PRIOR TO BIOPSY Article Open access 05 August 2024 DETECTION OF COLORECTAL CANCER IN URINE USING DNA METHYLATION ANALYSIS Article

Open access 27 January 2021 INTRODUCTION Prostate cancer (PCa) is one of the most common cancers in the western world1 and is said to be the most frequently detected male cancer and the

second most frequent cause of male cancer deaths.2 In 2009, it was suggested that one in six men would be affected, involving 192 280 new cases of PCa and 27 360 PCa-related deaths in the

United States.3 However, significant symptoms can be found in only about half of all diagnosed patients, which indicate the low diagnosis and high mortality rate.4 With an increasing rate of

morbidity of 3% per year over several decades,5 reliable methods of diagnosis are needed urgently. In the 1990s, prostate-specific antigen (PSA) testing became widespread,6 which provided a

new approach in the diagnosis of PCa. Disappointingly, although serum PSA is generally used in PCa screening, the poor baseline values and low specificity limits its functions.7 DNA

methylation of gene promoters may provide the ideal works. There are important advantages of using DNA methylation as cancer biomarkers. In particular, methylated DNA can be detected with a

high degree of specificity and sensitivity,8 which promotes its application to minimal samples from PCa patients. To date, over 50 hypermethylated loci have been identified in PCa.9, 10

Among these loci, adenomatous polyposis coli (APC) is a well-characterized tumor-suppressor gene. The _APC_ gene is located on the long (q) arm of chromosome 5 between positions 21 and 22,

between 112 118 468 and 112 209 532 base pairs (bp). Methylation of the genes is associated with PCa. The purpose of this study was to conduct a meta-analysis of the sensitivity and

specificity of APC methylation on PCa detection in body fluid (blood and urine) and prostate tissues. The results of this article will help to provide a reliable biomarker for the diagnosis

and discrimination of PCa. We also determined whether APC methylation was correlated with pathological stage, Gleason score and PSA level among the cases. MATERIALS AND METHODS STUDY

SELECTION We conducted a comprehensive literature search of PubMed and Embase databases using the keywords ‘prostate cancer’, ‘PCa’, ‘prostate adenocarcinoma’, ‘APC’ and ‘adenomatous

polyposis coli’. Additional studies were found via the reference lists of the identified articles. The last retrieval was conducted in October 2012. Our inclusion criteria were as follows:

(1) measurement of DNA methylation in one of the following samples: blood, plasma, serum, buffy coat, urine, ejaculates, or prostate tissues; (2) a case–control study; and (3) published in

English language. Our exclusion criteria were: (1) APC methylation conducted in the cell lines; (2) unavailable raw data on the amount of methylation among cases and controls, respectively

(some studies reported specificity and sensitivity without the exact counts); (3) review paper. The selection process for studies included in our review is shown in Figure 1. Our search

strategy and application of the inclusion/exclusion criteria resulted in a total of 19 articles that were included in the systematic review.11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22,

23, 24, 25, 26, 27, 28, 29 A description of the included studies is given in Tables 1 and 2. The following data were recorded for each study: author’s name, year of publication, sample

forms, method, 5′-3′ primers (forward and reverse, respectively), amplicon size (bp) and annealing temperature (°C), country, race, cancer clinical classification, PSA, Gleason score, type

of cases and controls, type of PCR method and other relevant characteristics of the study population. SENSITIVITY AND SPECIFICITY ANALYSIS The normalized index of methylation (NIM) and

receiver operator characteristic (ROC) curves were applied in most analyses. NIM was a color-scaled figure in which white represented NIM of zero (no methylation detected) and red defined a

NIM of 0.99 (99% of input DNA is methylated). NIM was defined in any given sample to be the ratio of the normalized amount of methylated templates at the promoter of interest to the

normalized amount of converted MYOD1 templates (NIM=[(GENE sample)/(GENE SssI)]/[(MYODI sample)/(MYOD SssI)]). Here, GENE sample and GENE SssI were said to be the number of entirely

methylated copies of the gene of interest in a given sample. Similar definitions were applied to MYOD1 sample and MYOD1 SssI. In addition, the optimal threshold for methylation was

determined on the basis of the area under the ROC curve.26 Combining the NIM and ROC curve; the numbers of the methylation were recorded. Before we conducted sensitivity and specificity

analyses, the amount of case and control methylation were collected. Among the included studies, two categories were assigned as controls: (1) patients who had negative biopsies but had

other diseases including benign prostatic hyperplasia (BPH), and (2) healthy controls. Nevertheless, biopsy-confirmed PCa and high-grade prostatic intraepithelial neoplasia (HGPIN) were

treated as cases. Thus, the true-positive (TP) samples were limited to those that had methylation within the exact cases. Meanwhile, in the case samples, the false-positive (FP) ones were

indicated to have no methylation. The same definitions was given for true negative (TN) and false negative (FN) in controls. All analyses were conducted with the Midas system in Stata. Owing

to the different types of samples in the eligible studies, we conducted a further analysis to present more robust results on APC methylation as the detection marker. In this analysis, the

fluid and tissue subgroups were processed. The types of the samples were described in detail. Among the tissue subgroup, we excluded studies that had other cancer diseases samples (such as

lung cancer and bladder cancer) because APC methylation might be also expressed in the different cancers. The analysis of the sensitivity and specificity was then conducted as above. The

same processes were applied in the fluid subgroup. ASSOCIATION ANALYSIS Odds ratios (ORs) with corresponding 95% confidence intervals (CIs) were used to describe the effect of the

association between APC methylation and PCa, pathological stage, Gleason score, and PSA levels. The pathological stages were categorized into two subgroups: T1/T2 and T3/T4.27 For the

Gleason score, a score of 7 was used as a cutoff. PSA levels were dichotomized as less or greater than 4 ng/ml. On the basis of individual study ORs, pooled OR was estimated. According to

the heterogeneity statistic _I_2, a fixed effect or a random-effects model was selected: a fixed effect model was used when _I_2<50%, otherwise a random-effects model was used. In

addition, when the results of the constituent studies differed among themselves, the effects incorporated an estimate of the inter-study variance and therefore provided wider 95% CI. At the

same time, the _I_2-based _Q_ statistic was used, which describes the weighted sum of the squared difference between the overall effect size and the effect size from each study, to assess

heterogeneity (_P_<0.10 as the standard).30 ROC ANALYSIS To assess whether variation in the threshold definition of a positive result produced an association between sensitivity and

specificity values across studies, we calculated the summary receiving operating characteristic (S-ROC) curve.31 The logits of the TP and FP rates were used to estimate the linear regression

of the log-OR from each study. Independent analysis of pooled sensitivity and specificity using standard methods for binary data were used when the regression between these quantities was

null. All data used a log-odds scale (eg, for specificities, the effect size used was log (Spec/(1-Spec)).32 Finally, due to the heterogeneity between studies, we performed the Cochrane Q

test of heterogeneity for each analysis (based on deviations of observed log-odds from the common log-odds). The analyses were conducted using Stata 9.0 (Stata Corporation, College Station,

TX, USA), and all _P_-values were two-tailed. RESULTS CHARACTERISTICS After retrieving search results from the PubMed and Embase databases with the associated keywords, there were 157 and

484 articles retrieved from PubMed and Embase, respectively, on PCa and APC methylation/gene. Among these, we identified 95 relevant studies that described PCa and APC methylation. There

were 11 and 29 articles that used fluid (urine, blood or others) samples and tissues, respectively; 55 references were conference abstracts, non-experimental studies or otherwise not

available, and were removed, resulting in 40 articles. While reading the full texts, 21 articles were removed. Six could not provide data on the methylation among fluid samples (urine and

blood), and33, 34, 35, 36, 37, 38 15 of the 29 articles using tissues had no raw data (the specific numbers of cases and controls with methylation were unclear, which made it difficult to

calculate the data required for sensibility and specificity) or studied other factors such as the _TMPRSS2_ gene and urothelial carcinomas.39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51,

52, 53 Finally, 19 studies met the inclusion criteria and were included.11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29 Among these 19 studies, 5 involved body

fluid (blood, urine and so on)11, 12, 13, 14, 15 and the remaining 14 articles involved sample tissues.16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29 Ten studies used quantitative

real-time methylation-specific PCR (QMSP) to detect APC methylation,11, 13, 14, 18, 19, 21, 22, 23, 25, 26 seven were conducted using the method of methylation-specific PCR (MSP),12, 15, 17,

20, 24, 27, 29 and two studies used pyrosequencing.16, 28 All cases were of PCa or HGPIN and were hospitalized, while controls were limited to be BPH, healthy subjects or those who had

genitourinary cancer (bladder carcinoma) with a healthy prostate. In regard to the type of cases, 14 studies were PCa,11, 12, 13, 14, 15, 16, 18, 19, 20, 23, 24, 27, 28, 29 and five were a

mixture of PCa, HGPIN and metastasis or other cancer tissues.17, 21, 22, 25, 26 Among the controls, eight studies were normal, biopsy negative, or non-tumor12, 13, 14, 15, 17, 25, 26, 29

nine were BPH,16, 18, 19, 20, 21, 23, 24, 27, 28 and two were a combination of BPH, normal subjects and bladder carcinoma.11, 22 In addition, 14 were Caucasian,11, 12, 13, 14, 15, 18, 19,

20, 21, 22, 23, 25, 26, 29 four were Asian,16, 17, 24, 27 and one involved mixed races from different continents28 who came from United States, United Kingdom, Portugal, Germany, Korea,

Japan, France, and China. SPECIFICITY AND SENSITIVITY OF APC PROMOTER METHYLATION USING DIFFERENT TYPES OF SAMPLES All the results are shown in Table 3. The pooled specificity for all

included studies was 0.91 (95% CI: 0.82–0.95), and the pooled sensitivity was 0.78 (95% CI: 0.63–0.88). For the traditional biomarker, the sensitivity of PSA varied, but the specificity was

generally low at about 20%,32, 54 which suggested that the APC methylation test has a much higher specificity than the PSA test. There was no evidence of publication bias (_P_=0.33). In

addition, we classified all samples into two groups according to specimen type (fluid/tissue). Among the fluid studies (urine/blood), the pooled sensitivity and specificity was 0.53 (95% CI:

0.28–0.78) and 0.92 (95% CI: 0.86–0.95), respectively. For the tissue studies, the pooled sensitivity and specificity was 0.84 (95% CI: 0.70–0.92) and 0.91 (95% CI: 0.77–0.97),

respectively. Publication bias results are showed in Table 3. The S-ROC curve is showed in Figure 2. In the extra analysis of the sensitivity and specificity, among the studies, we excluded

those that would likely introduce high heterogeneity due to different types of cases and controls. Finally, one study13 and four articles19, 20, 22, 26 in the fluid and tissue subgroups,

respectively, with different samples. The pooled specificity (0.90, 95% CI: 0.77–0.96) and pooled sensitivity (0.78, 95% CI: 0.59–0.90) were similar to the previous results. In addition, in

the urine subgroup, the sensitivity was lower (0.45, 95% CI: 0.39–0.53) and the specificity was 0.92 (95% CI: 0.84–0.96). The similar results were presented in the tissue subgroups

(sensitivity 0.87, 95% CI: 0.72–0.94; specificity 0.89, 95% CI: 0.68–0.97), which suggested a high level of sensitivity and specificity. ASSOCIATION BETWEEN APC PROMOTER METHYLATION AND

PATHOLOGICAL STAGE, GLEASON SCORE, AND PSA LEVELS IN PCA CASES We also conducted an analysis of the relationship between the pathological stage, Gleason score, and PSA levels among PCa cases

and APC promoter methylation. Details are shown in Table 4. We found no significant association between groups with the appropriate models except for the pathological stage (OR=0.42, 95%

CI: 0.25–0.70, _I__2_=0.0%). Finally, the association between APC promoter methylation and PCa was conducted and the pooled OR was 24.91 (95% CI: 12.86–48.24, _I_2=72.5%), with pooled ORs of

33.54 (95% CI: 14.88–75.59, _I_2=70.7%) and 8.20 (95% CI: 2.84–23.74, _I_2=64.2%) in the tissue and fluid groups, respectively (Figure 3). DISCUSSION DESCRIPTION Although there were have

been many studies about of the sensitivity and specificity of APC promoter methylation in relation to PCa, a summary meta-analysis has not been reported. To confirm the real function of APC

promoter methylation in predicting PCa, this study is required. This meta-analysis is based on 19 studies containing a total of 1600 cases and 744 controls. The major finding of this study

has demonstrated that APC promoter methylation may be associated with PCa. With the high sensitivity and specificity, it would be an ideal biomarker in diagnosing PCa. POOLED SPECIFICITY AND

SENSITIVITY ANALYSIS With the strong association (OR=24.91, 95% CI: 12.86−48.24, _I_2=72.5%), we conducted the specificity and sensitivity analysis. For all included studies, either in the

whole data set (pooled specificity 0.90, 95% CI: 0.80–0.95; pooled sensitivity 0.78, 95% CI: 0.63–0.88) or from subgroup analysis (fluid: specificity 0.92, 95% CI: 0.86–0.95; sensitivity

0.53, 95% CI: 0.28–0.78; tissue: specificity 0.91, 95% CI: 0.77–0.97; sensitivity 0.84, 95% CI: 0.70–0.92), the specificity and sensitivity of the test seemed to be high as an biomarker,

which suggests a greater directive function in diagnosis with the biomarker of APC methylation. However, due to differences between cases and controls between studies, we removed some

studies to make the data more homogeneous. These results suggested no major changes, and therefore provide support to our conclusion. As we have proposed above, the PSA test had varying high

sensitivity and poor specificity (about 20%). Therefore, according to our results, APC methylation with high specificity may increase the veracity of diagnosis when combined with the PSA

test. For sensitivity, only the fluid subgroup was lower than the PSA test. Due to the high pooled specificity, we propose the following: (1) because of the high sensitivity of the PSA test,

potential patients would be screened out. Likewise, APC promoter methylation would need to be detected with high specificity among those patients who were positive in the PSA test. If the

results of both tests were elevated among patients, future biopsies may be warranted. In this way, not only would the diagnosis be elevated, but also the weakness of the PSA test would be

remedied. (2) For the tissue subgroup, because of the level of sensitivity (0.84/0.87) and specificity (0.91/0.89) in two analyses, we suggest that the APC methylation test might be a better

test to distinguish PCa among the tissue. Although the biopsy was the gold standard in diagnosing PCa, there were still some errors when we did not obtain the cancer tissue well. With the

high sensitivity and specificity, the APC methylation test could be used to complement the biopsy, which would decrease the rate of FNs. (3) It has been said that methylation genes might

help identify new targets in the individual treatment of some diseases,55 and our study may provide stronger evidence of the potential function of these genes in finding a cure for PCa. In

addition, although in our analysis we did not find any evidence of publication bias, we should not ignore the potential bias that could affect the results. Nevertheless, regardless of the

possible bias, we suggest that studies of the function of methylation in identifying and curing the cancers cannot be neglected. LIMITATIONS The present study has several limitations. First,

the validation assay of the gene promoter methylation used in each study was different (MSP/QMSP/other). In addition, primers selected from different regions of the same CpG Island may have

different sensitivities and specificities (Table 1). Second, the thresholds identified by the ROC and INM were determined from individual trials, which may lead to different definitions of

methylation. Third, the sample collection time varied widely among the studies. Finally, as mentioned above, we analyzed associations between gene methylation and pathological stage, Gleason

score, PSA levels, and other factors, thereby decreasing our statistical power due to multiple testing. CONCLUSION PCa is a worldwide disease that affects a large number of men and leads to

a serious conclusion. To diagnose and interpose this disease early may indicate a good prognosis. Although the PSA test has been applied in disease diagnosis, its poor specificity limits

its function. On the basis of the studies available, this meta-analysis has demonstrated that APC methylation might be an ideal biomarker for screening and identifying PCa when combined with

the PSA test to decrease the rate of unnecessary biopsy. However, given the heterogeneity between the studies and insufficient evidence, the real function of APC methylation in disease

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references ACKNOWLEDGEMENTS This study was supported by grants from the Key Opening laboratory subject of Guangxi medical science experiment center (KFJJ2011-22). DISCLAIMER The funders had

no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. AUTHOR INFORMATION Author notes * Yang Chen, Jie Li and Xiaoxiang Yu: These

authors contributed equally to this work AUTHORS AND AFFILIATIONS * Center for Genomic and Personalized Medicine, Guangxi Medical University, Nanning, China Yang Chen, Jie Li, Shuai Li, 

Zengnan Mo & Yanling Hu * Institute of Urology and Nephrology, the People's Liberation Army 303 Hospital of Guangxi, Nanning, China Xiaoxiang Yu * Medical Research Center, Guangxi

Medical University, Nanning, China Xuerong Zhang & Yanling Hu * Institute of Urology and Nephrology, First Affiliated Hospital of Guangxi Medical University, Nanning, China Zengnan Mo

Authors * Yang Chen View author publications You can also search for this author inPubMed Google Scholar * Jie Li View author publications You can also search for this author inPubMed Google

Scholar * Xiaoxiang Yu View author publications You can also search for this author inPubMed Google Scholar * Shuai Li View author publications You can also search for this author inPubMed 

Google Scholar * Xuerong Zhang View author publications You can also search for this author inPubMed Google Scholar * Zengnan Mo View author publications You can also search for this author

inPubMed Google Scholar * Yanling Hu View author publications You can also search for this author inPubMed Google Scholar CORRESPONDING AUTHORS Correspondence to Zengnan Mo or Yanling Hu.

ETHICS DECLARATIONS COMPETING INTERESTS The authors declare no confict of interest. RIGHTS AND PERMISSIONS Reprints and permissions ABOUT THIS ARTICLE CITE THIS ARTICLE Chen, Y., Li, J., Yu,

X. _et al._ _APC_ gene hypermethylation and prostate cancer: a systematic review and meta-analysis. _Eur J Hum Genet_ 21, 929–935 (2013). https://doi.org/10.1038/ejhg.2012.281 Download

citation * Received: 23 August 2012 * Revised: 09 November 2012 * Accepted: 21 November 2012 * Published: 09 January 2013 * Issue Date: September 2013 * DOI:

https://doi.org/10.1038/ejhg.2012.281 SHARE THIS ARTICLE Anyone you share the following link with will be able to read this content: Get shareable link Sorry, a shareable link is not

currently available for this article. Copy to clipboard Provided by the Springer Nature SharedIt content-sharing initiative KEYWORDS * hypermethylation * methylation * prostate cancer *

adenomatous polyposis coli