Quantitative Analysis of Aberrant p16 Methylation Using Real-Time Quantitative Methylation-specific Polymerase Chain Reaction¹

The role of DNA methylation in tumorigenesis has attracted considerable attention recently (1). The detection of aberrant DNA methylation in tumors has implications for the understanding of the fundamental mechanisms of oncogenesis (1, 2) and may form the basis for new molecular assays for cancer detection and monitoring (3, 4, 5, 6). Established methods for methylation analysis include methylation-sensitive restriction enzyme treatment followed by Southern blotting (7) and PCR (8), bisulfite sequencing (9), restriction site creation by bisulfite modification (10), and MSP³ (11). The need for quantitative data has prompted some investigators to develop quantitative methods for methylation analysis (12, 13). However, these quantitative tools for methylation analysis generally require the use of gel electrophoresis and radioisotopes. The advent of real-time quantitative PCR (14, 15) has allowed the performance of nonisotopic, rapid, and highly accurate quantitative amplification analysis via the continuous optical monitoring of a fluorogenic PCR. In this study, we investigated the possibility of quantitative methylation analysis using real-time MSP.

The tumor-derived cell lines HS-Sultan, ARH-77, IM-9, RPMI 8226, NCI-H929, U266 B1, HeLa, and Raji were obtained from the American Type Culture Collection (Manassas, VA) and cultured using previously established conditions (7). DNA from cultured cell lines was extracted as described previously (7).

Eight patients with multiple myeloma were recruited with informed consent from subjects investigated at the Department of Anatomical and Cellular Pathology, Prince of Wales Hospital, Hong Kong. DNA from bone marrow aspirates was extracted as described previously (7). The study was approved by the Ethics Committee of The Chinese University of Hong Kong.

Cell lines were treated with 1–3 μm 5-aza-2′-deoxycytidine (Sigma Chemical Co., St. Louis, MO) in RPMI 1640 supplemented with 10 or 15% fetal bovine serum, as described previously (7), and cultured for 10 days.

Bisulfite conversion of DNA samples was carried out essentially as described (11) and was based on the principle that treatment of DNA with bisulfite would result in the conversion of unmethylated cytosine residues into uracil. Methylated cytosine residues, on the other hand, would remain unchanged. Thus, the DNA sequences of methylated and unmethylated genomic regions following bisulfite conversion would be different and distinguishable by sequence-specific PCR primers.

Bisulfite conversion was carried out using reagents provided in a CpGenome DNA Modification Kit (Intergen, New York, NY). One μg of DNA was treated with sodium bisulfite following the manufacturers’ recommendations. Following conversion, the bisulfite-converted DNA was resuspended in a total volume of 25 μl.

Conventional MSP was carried out as described previously (6, 11). The sense and antisense primers for the bisulfite-converted methylated sequence were p16MF (5′-TTA TTA GAG GGT GGG GCG GAT CGC-3′) and p16MR (5′-GAC CCC GAA CCG CGA CCG TAA 3′), respectively (product size, 150 bp; Ref. 11). The sense and antisense primers for the bisulfite-converted unmethylated sequence were p16U-5 (5′-TTA TTA GAG GGT GGG GTG GAT TGT-3′) and p16U-3 (5′-CAA CCC CAA ACC ACA ACC ATA A-3′), respectively (product size, 151 bp; Ref. 11). The sense and antisense primers for the unconverted wild-type sequence were p16WF (5′-CAG AGG GTG GGG CGG ACC GC-3′) and p16WR (5′-CGG GCC GCG GCC GTG G-3′), respectively (product size, 140 bp; Ref. 11). Thirty-five cycles of PCR were carried out using reagents supplied in a GeneAmp DNA Amplification Kit using AmpliTaq Gold as the polymerase (Perkin-Elmer, Foster City, CA) as described previously (6). PCR products were analyzed by agarose gel electrophoresis and ethidium bromide staining.

Real-time quantitative PCR is based on the continuous optical monitoring of the progress of a fluorogenic PCR (14, 15). In this system, apart from the two amplification primers as in conventional PCR, a dual-labeled fluorogenic hybridization probe is also included (14). One fluorescent dye serves as a reporter (FAM), and its emission spectra is quenched by a second fluorescent dye (TAMRA). During the extension phase of PCR, the 5′ to 3′ exonuclease activity of the Taq DNA polymerase (16) cleaves the reporter from the probe, thus releasing it from the quencher, resulting in an increase in fluorescent emission at 518 nm.

Three real-time MSP systems were developed for the detection and quantitation of the bisulfite-converted methylated version of the p16 gene (the p16M system; system 1), the bisulfite-converted unmethylated version of the p16 gene (the p16U system; system 2), and the unconverted wild-type version of the p16 gene (the p16W system; system 3). For system 1, the primers p16MF and p16MR (see above; Ref. 11) were used in conjunction with a fluorogenic probe p16MT [5′-(FAM)-AGT AGT ATG GAG TCG GCG GCG GG-(TAMRA)-3′]. For system 2, the primers p16UF and p16UR (see above; Ref. 11) were used in conjunction with a fluorogenic probe p16UT [5′-(FAM)-AGG TAG TGG GTG GTG GGG AGT AGT ATG GAG TTG-(TAMRA)-3′]. For system 3, the primers p16W-5 (5′-GTG GGG CGG ACC GC 3′) and p16W-3 (5′-GCC GCG GCC GTGG-3′) were used in conjunction with a fluorogenic probe, p16W-T [5′-(FAM)-AGC AGC ATG GAG CCG GCG G-(TAMRA)-3′]. The fluorogenic probes contained a 3′-blocking phosphate group to prevent probe extension during PCR.

Fluorogenic PCRs were set up in a reaction volume of 50 μl using components (except fluorogenic probes and amplification primers) supplied in a TaqMan PCR Core Reagent Kit (Perkin-Elmer, Foster City, CA). Fluorogenic probes were custom-synthesized by PE Applied Biosystems. PCR primers were synthesized by Life Technologies (Gaithersburg, MD). Each reaction contained 5 μl of 10× buffer A; 300 nm each amplification primer; 25 nm corresponding fluorogenic probe; 200 μm each dATP, dCTP, and dGTP; 400 μm dUTP; and 1.25 units of AmpliTaq Gold. The concentrations of MgCl₂ were at 2 mm for the p16M real-time MSP, 1.75 mm for the p16U real-time MSP, and 2 mm for the p16W real-time MSP. DMSO (Merck, Darmstadt, Germany) was added at final concentrations of 5% for both the p16M and p16U real-time MSPs and 10% for the p16W real-time MSP. Five μl of the converted DNA were used per real-time MSP. DNA amplifications were carried out in a 96-well reaction plate format in a PE Applied Biosystems 7700 Sequence Detector (Perkin-Elmer).

Thermal cycling was initiated with a first denaturation step of 10 min at 95°C. The subsequent thermal profile for the p16M and p16U real-time MSPs was 95°C for 15 s, 55°C for 30 s, and 72°C for 1 min. For the p16W real-time MSP, the corresponding thermal profile was 95°C for 30 s, 50°C for 1 min, and 72°C for 1 min. Data obtained following 40 cycles of amplification were analyzed. Multiple negative water blanks were included in every analysis.

A calibration curve was run in parallel with each analysis. A human plasmacytoma cell line, HS-Sultan (ATCC CRL-1484), previously shown to have p16 methylation by methylation-sensitive restriction enzymes and Southern blotting techniques (7) as well as by conventional MSP (6), was used for constructing the calibration curve for the p16M real-time MSP. Serial dilutions of HS-Sultan DNA were made in water. Similarly, peripheral blood DNA from a healthy individual previously shown to be negative for methylated p16 sequences was used for constructing the calibration curve for the p16W (prior to bisulfite conversion) and p16U (following bisulfite conversion) real-time MSP systems. A conversion factor of 6.6 pg of DNA per diploid cell was used for expressing quantitative results in genome equivalents (17). One genome equivalent was defined as the amount of a particular target sequence in a single reference cell.

Amplification data, collected by the 7700 Sequence Detector and stored in a Macintosh computer (Apple Computer, Cupertino, CA), were then analyzed using the Sequence Detection System software (Version 1.6.3) developed by PE Applied Biosystems.

The methylation index (%) in a sample was calculated using the following equation:

where M is the quantity of methylated p16 sequences measured by the p16M real-time MSP following bisulfite conversion and U is the quantity of unmethylated p16 sequences measured by the p16U real-time MSP following bisulfite conversion.

The completeness of bisulfite conversion was estimated by calculating the fractional concentration of converted DNA that remained in the wild-type sequence (%W) using the following equation:

where W is the quantity of wild-type p16 sequences measured by the p16W real-time MSP following bisulfite conversion, M is the quantity of methylated p16 sequences measured by the p16M real-time MSP following bisulfite conversion, and U is the quantity of unmethylated p16 sequences measured by the p16U real-time MSP following bisulfite conversion.

This calculation was performed for every real-time MSP analysis. The mean fractional concentration of p16W sequences following bisulfite treatment of cell line DNA was 2.9% (range, 0.02–8.2%), showing that the modification step was largely complete.

Cell lines were washed in PBS and pelleted by centrifugation. The cell pellet was resuspended in 0.5 ml of guanidinium thiocyanate solution [4 m guanidinium thiocyanate, 0.5% sarkosyl, 25 mm sodium citrate (pH 7), and 0.1 m 2-mercaptoethanol]. Total RNA was then extracted by a single-step method as described previously (18). Two μg of total RNA were reverse-transcribed and amplified using primers for the p16 gene using conditions reported previously (7). RT-PCR for β₂-microglobulin transcripts was performed to check for the integrity of the RNA samples (7).

To determine the dynamic range of real-time quantitative MSP, we prepared serial dilutions of HS-Sultan DNA containing methylated p16 sequences (6, 7); the samples were then bisulfite-converted and subjected to analysis by the p16M real-time quantitative MSP. Fig. 1 A shows that the amplification curve shifted to the right as the input target quantity was reduced. This was expected because reactions with fewer target molecules required more amplification cycles to produce a certain quantity of reporter molecules than reactions with more target molecules. The system was sensitive enough to detect down to 10 genome equivalents of methylated p16 sequence. Using wild-type and bisulfite-converted DNA from a normal individual, we showed the detection limits of the p16U and p16W real-time MSP systems to be 10 genome equivalents and 1 genome equivalent, respectively.

Fig. 1 B shows a plot of the threshold cycle (C_T) of the p16M real-time MSP against the input target quantity, with the latter plotted on a common logarithmic scale. The C_T was set at 10 SDs above the mean baseline fluorescence calculated from cycles 1 to 15 and was inversely proportional to the starting target copy number (logarithmic scale) used for amplification (14). The linearity of the graph demonstrates the large dynamic range and accuracy of real-time quantitative PCR. Similar results were obtained for the p16U and p16W systems, using bisulfite-converted and unconverted DNA, respectively, from a normal individual.

The reproducibility of bisulfite conversion followed by real-time MSP was tested by performing six replicate bisulfite conversions of HS-Sultan DNA (100 pg), followed by real-time quantitative p16M MSP analysis. The CV of the C_T values of these replicate analyses was 5.9%. The corresponding CV for the p16U system was determined using multiple bisulfite conversions of DNA from a normal individual and was calculated to be 5.6%. The analytical CV for the p16W system was 3.6%.

To validate the measurement of the methylation index, we prepared artificial mixtures of varying proportions of bisulfite-converted HS-Sultan DNA and DNA from a normal individual and subjected them to the p16M and p16U real-time MSP systems. Fig. 1 C shows a plot of the observed against the actual input methylation indices. The correlation coefficient was 0.983.

DNA samples extracted from eight cell lines (ARH-77, HS-Sultan, IM-9, RPMI 8226, NCI-H929, U266 B1, HeLa, and Raji) were subjected to real-time MSP analysis using the p16M and p16U systems. The amplification plots of these real-time MSPs are shown in Fig. 2. Only methylated p16 sequences were detected in DNA from HS-Sultan, NCI-H929, Raji, RPMI 8226, and U266 B1. Only unmethylated p16 sequences were detected in DNA from HeLa. A mixture of methylated and unmethylated p16 alleles was detected for IM-9 and ARH-77. Conventional gel-based MSP was also carried out for DNA extracted from these cell lines and the results were completely concordant (results not shown).

The calculated methylation indices for these cell lines were as follows: HS-Sultan, 100%; HeLa, 0%; IM-9, 0.4%; ARH-77, 78%; NCI-H929, 100%; Raji, 100%; RPMI 8226, 100%; and U266 B1, 100%. RT-PCR analysis indicated that the five cell lines with a methylation index of 100% (HS-Sultan, NCI-H929, Raji, RPMI 8226, and U266 B1) did not have detectable level of p16 transcription (results not shown). Positive RT-PCR signals, however, were observed for HeLa, IM-9 and ARH-77, with a signal intensity that was inversely correlated with the methylation index (results not shown).

The correlation between the methylation index and the transcriptional status of the p16 gene was studied using the cell lines HeLa, Raji, RPMI 8226, HS-Sultan, and NCI-H929. Expression of the p16 gene was monitored by RT-PCR following demethylation treatment using different concentrations of 5-aza-2′-deoxycytidine (Fig. 3). The corresponding methylation indices are shown in Fig. 3 under the corresponding lanes of the gel. A reduction in the methylation index was observed with increasing concentrations of 5-aza-2′-deoxycytidine, indicating increasing demethylation. The methylation index was negatively correlated with p16 transcription, with p16 mRNA detectable when the methylation index was ≤85% (Fig. 3).

DNA from bone marrow aspirates from 8 patients with multiple myeloma was analyzed with both conventional MSP and real-time quantitative MSP. Of the eight cases, methylated p16 sequences were detected by both techniques in five. No methylated p16 sequences were detected in the remaining three cases. As a control, unmethylated p16 sequences were found in bisulfite-converted DNA in all eight cases. The median methylation index in the five cases with detectable aberrant p16 methylation was 0.32% (interquartile range, 0.06–0.37%).

In this study, we have developed a novel method for quantitative methylation analysis using real-time MSP. This method has the combined advantages of MSP (high specificity and sensitivity; Ref. 11) and real-time PCR (rapidity, large dynamic range, and anticontamination properties; Refs. 14 and 15).

In the first part of our study, we tested the real-time MSP systems using cell lines that were well-characterized with regard to the methylation status of the p16 promoter region (7). The data obtained using the real-time MSP systems were completely concordant with conventional MSP results and also with data obtained using methylation-sensitive restriction enzymes and Southern blotting (7). The real-time systems, however, were much more rapid and were able to generate results in a convenient 96-well format that was amenable to large-scale analysis.

Quantitative results generated by real-time MSP are dependent on a number of parameters, as follows: the efficiency of the bisulfite conversion step, including DNA loss during the process and the completeness of bisulfite modification (parameter 1); the copy number of methylated and unmethylated target molecules (parameter 2); and the methylation density of the primer and probe binding sites (parameter 3). Variability in parameter 1 is compensated by the use of the methylation index, which essentially compares methylated and unmethylated sequences that have been successfully converted. The dependence of quantitative MSP on parameter 2 is clearly seen in Fig. 1, B and C, where MSP results accurately reflect the number of input target molecules. The effect of parameter 3 can be seen for the cell lines HS-Sultan, RPMI 8226, U266 B1, NCI-H929, ARH-77, and IM-9, for which the methylation density has been extensively studied (7). These previous data indicate that HS-Sultan, RPMI 8226, U266 B1, and NCI-H929 are more heavily methylated than ARH-77, which, in turn, is more heavily methylated than IM-9 (7). These results are consistent with the methylation indices measured by real-time MSP, as follows: HS-Sultan, RPMI 8226, U266 B1, and NCI-H929, 100%; ARH-77, 79%; and IM-9, 0.4%.

The dependence of the methylation index on both parameters 2 and 3 suggests numerous applications of real-time MSP. For example, real-time MSP may be used for the monitoring of changes in methylation density during neoplastic progression (19). Another example is the use of this technology in the quantitation of tumor-derived DNA in the plasma or serum of cancer patients (5, 6). However, in many of the potential applications of quantitative MSP, it is likely that one of these parameters may be the predominant one that is of interest. The system can be modified to be more dependent on either parameter 2 or 3 by the alteration in primer or probe sequences.

Existing quantitative methods for methylation analysis include Ms-SNuPE (12) and COBRA (13). Both of these methods require post-PCR processing, gel electrophoresis, and the handling of radioisotopes. COBRA, in addition, requires the use of restriction enzymes (13). Real-time MSP, on the other hand, does not require any post-PCR processing, is nonisotopic, and does not need restriction enzyme treatment. It is likely, however, that, for certain applications, Ms-SNuPE or COBRA may be used in conjunction with real-time MSP. For example, Ms-SNuPE can be used for the initial detailed elucidation of the methylation status of individual CpG sites. This information can then be used to design real-time MSP systems that can subsequently be used for large-scale sample analysis.

The biological relevance of the methylation index, as measured by real-time MSP, was illustrated by correlating the methylation index with p16 mRNA expression. Thus, the cell lines HS-Sultan, Raji, RPMI 8226, U266 B1, and NCI-H929, which all had a methylation index of 100%, had no detectable p16 expression by RT-PCR analysis. In contrast, the cell lines HeLa, IM-9, and ARH-77, with methylation indices of 0, 0.4, and 78%, all showed p16 expression, with a level of transcription that was inversely correlated with the methylation index.

To further demonstrate the biological implication of methylation index measurement, we applied real-time MSP to cell lines that had been treated with the demethylating agent, 5-aza-2′-deoxycytidine. As expected, treatment with the demethylating agent resulted in a reduction in the methylation index (Fig. 3). Our data once again showed an inverse relationship between p16 gene expression and the methylation index. The highest methylation index observed in this study that was compatible with p16 transcription was 85% (Fig. 3). We envision real-time MSP having a possible future application in the evaluation of novel demethylating agents, which may have potential clinical application in cancer treatment.

Recently, there has been considerable interest in the use of methylation analysis in the clinical detection of tumors, such as the analysis of aberrant p16 methylation in sputum (3) or bronchoalveolar lavage fluid (4) for lung cancer diagnosis and methylation analysis in the plasma/serum of lung (5) and liver cancer (6) patients. Real-time MSP will provide a quantitative dimension for this type of analysis and may allow one to follow the progress of patients and to assess the effect of treatment. In addition, the suitability of real-time PCR to large-scale application, due to its rapidity and resistance to carryover contamination, may also catalyze the widespread use of methylation analysis in clinical practice. The establishment of real-time quantitative MSP also provides a valuable tool for investigators to study the various technical parameters affecting MSP, ranging from bisulfite conversion and primer/probe design to DNA amplification conditions. This development will be very useful for optimizing protocols, which will allow the reliable use of MSP to different clinical specimen types.

Because aberrant promoter methylation of the p16 gene has been described in numerous cancers (2), the real-time MSP systems described here can be applied to many malignancies. Furthermore, the principles involved in the development of the current p16 MSP systems can also be used to develop similar real-time quantitative systems for aberrant methylation affecting other tumor suppressor genes. In addition, because real-time PCR has the ability to accommodate multiple fluorescent labels (20), it is possible that real-time MSP assays for multiple genes can be combined in a time-efficient multiplex format.

In this study, we have demonstrated the potential clinical utility of real-time MSP by applying the technique to bone marrow aspirates from patients with multiple myeloma. Aberrant promoter methylation of the p16 gene has been reported in this malignancy (21). The results obtained using conventional and real-time MSP were completely concordant. In addition, real-time MSP was able to provide an additional quantitative parameter, namely, the methylation index, for these samples, which might be useful for the follow-up of these patients.

In addition to detecting aberrant methylation in cancer, real-time quantitative MSP may also have application for studying other biological processes involving DNA methylation. For example, quantitative MSP would be a useful tool in the monitoring of methylation patterns of imprinted genes during development and in the quantitative analysis of clonality by the measurement of X-inactivation patterns.