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Logo of nihpaAbout Author manuscriptsSubmit a manuscriptNIH Public Access; Author Manuscript; Accepted for publication in peer reviewed journal;
Clin Chem. Author manuscript; available in PMC Feb 25, 2010.
Published in final edited form as:
PMCID: PMC2828872
NIHMSID: NIHMS169975

COLD-PCR–Enhanced High-Resolution Melting Enables Rapid and Selective Identification of Low-Level Unknown Mutations

Abstract

BACKGROUND:

Analysis of clinical samples often necessitates identification of low-level somatic mutations within wild-type DNA; however, the selectivity and sensitivity of the methods are often limiting. COLD-PCR (coamplification at lower denaturation temperature–PCR) is a new form of PCR that enriches mutation-containing amplicons to concentrations sufficient for direct sequencing; nevertheless, sequencing itself remains an expensive mutation-screening approach. Conversely, high-resolution melting (HRM) is a rapid, inexpensive scanning method, but it cannot specifically identify the detected mutation. To enable enrichment, quick scanning, and identification of low-level unknown mutations, we combined COLD-PCR with HRM mutation scanning, followed by sequencing of positive samples.

METHODS:

Mutation-containing cell-line DNA serially diluted into wild-type DNA and DNA samples from human lung adenocarcinomas containing low-level mutations were amplified via COLD-PCR and via conventional PCR for TP53 (tumor protein p53) exons 6–8, and the 2 approaches were compared. HRM analysis was used to screen amplicons for mutations; mutation-positive amplicons were sequenced.

RESULTS:

Dilution experiments indicated an approximate 6- to 20-fold improvement in selectivity with COLD-PCR/HRM. Conventional PCR/HRM exhibited mutation-detection limits of approximately 2% to 10%, whereas COLD-PCR/HRM exhibited limits from approximately 0.1% to 1% mutant-to-wild-type ratio. After HRM analysis of lung adenocarcinoma samples, we detected 7 mutations by both PCR methods in exon 7; however, in exon 8 we detected 9 mutations in COLD-PCR amplicons, compared with only 6 mutations in conventional-PCR amplicons. Furthermore, 94% of the HRM-detected mutations were successfully sequenced with COLD-PCR amplicons, compared with 50% with conventional-PCR amplicons.

CONCLUSIONS:

COLD-PCR/HRM improves the mutation-scanning capabilities of HRM and combines high selectivity, convenience, and low cost with the ability to sequence unknown low-level mutations in clinical samples.

Characterization of early and posttreatment tumor status in cancer patients often requires the identification of low-level somatic DNA mutations and minority alleles within an excess of wild-type DNA. The ability to detect low-level unknown mutations is often limited by the method used; thus, recent efforts have focused on improving the analytical sensitivity and selectivity of PCR-based technologies for enhancing the detection and identification of mutant alleles in clinical samples. Advances have been made to improve the analytical sensitivity of methods; however, methods often become more complex with increased sensitivity. Conversely, clinical and diagnostic settings require that routine applications not only be accurate and cost-effective but also entail little effort to optimize, perform, and analyze. High-resolution melting (HRM)2 curve analysis is a simple, fast, and inexpensive method for genotyping mutations at known positions or for scanning for low-abundance unknown mutations and variants (1-14).

The detection capability of HRM is largely determined by fragment length, sequence composition, mutation identity, PCR quality, and the analytical equipment (1-14). A recent publication by Bastien and colleagues (15) has described serial-dilution experiments on the Roche LightCycler 480 that demonstrate the ability to detect mutant DNA in mixtures with wild-type DNA at concentrations as low as 1 part in 200 (0.5%) (their report represents the data as “1:200”). Nomoto et al. (16) have reported a detection capability as low as 0.1% mutant contribution in serial-dilution experiments with the Idaho Technology HR-1 HRM-analysis platform. In most studies, however, applications of HRM-based assays have generally detected mutant alleles present at 5%–10% among wild-type alleles (7, 10, 11, 16-20).

Despite its detection capability, HRM mutation scanning currently lacks the ability to identify the specific nucleotide change unless scanning is followed by sequencing of the positive samples. For determining a patient's appropriate and personalized treatment, the identification of a mutation's type and position is critical. Although Sanger sequencing is the gold standard for mutant identification, it is typically capable of detecting only those mutations present at moderate to high abundance, approximately 20% or greater (21). Pyrosequencing is another sequencing-based approach that exhibits higher analytical sensitivity, but it is limited to detecting mutations at an abundance of approximately 10% (22) and remains inadequate for identifying the low-prevalence mutations that HRM mutation scanning can successfully detect. Microfluidics digital PCR (23, 24) is another potential solution that is currently directed toward identification of low-level mutations at known DNA positions. When combined with high-throughput sequencing, it may be used to identify low-level mutations anywhere on the sequence. Next-generation sequencing is yet another potential solution, although at present this technology can be expensive and impractical as a routine method for identification and validation. Thus, for unknown mutations with abundances of <10%, many of the methods that are commonly used for identification or validation may either be impractical or have a detection capability less sensitive than HRM, and thus the mutation cannot be identified or confirmed. Consequently, the analysis of such unknown mutations becomes unclear, and it becomes difficult to determine whether an aberrant HRM profile indicates the presence of a true low-prevalence mutation or the generation of a false-positive error.

COLD-PCR (coamplification at lower denaturation temperature–PCR) (25), a recently developed approach capable of enriching low-level mutants, uses a critical denaturation temperature (Tc) during the PCR to enrich unknown mutations at any position on the amplified sequence. The Tc is lower than standard denaturation temperatures in that it preferentially denatures heteroduplexed molecules (those formed by hybridization of mutant and wild-type sequences) and amplicons possessing mutations that lower the amplicon melting temperature (Tm), such as G:C>A:T or G:C>T:A. COLD-PCR can be applied in either of 2 formats: full COLD-PCR or fast COLD-PCR (25). Full COLD-PCR enriches all possible mutations along the sequence, although the enrichment is generally lower than with fast COLD-PCR. Full COLD-PCR uses a hybridization step at an intermediate temperature during PCR cycling to allow cross-hybridization of mutant and wild-type alleles. Heteroduplexes, which melt at lower temperatures than homoduplexes, are subsequently selectively denatured at the Tc and amplified throughout the course of the PCR.

In fast COLD-PCR, the formation of heteroduplexes is not required, and mutations are enriched anywhere along the sequence as long as they lower the mutant amplicon Tm relative to that of wild-type alleles. Accordingly, fast COLD-PCR enriches mutations by exploiting the fact that the mutant amplicon has a Tm lower than that of the wild type (e.g., G:C>A:T or G:C>T:A) (23). Because mutation-containing sequences lower the Tm, use of a Tc during the PCR preferentially denatures and amplifies the mutant sequences while the wild-type sequences remain double-stranded.

The 2 COLD-PCR approaches share the attribute that the mutation enrichment is usually sufficient for downstream sequencing, thus allowing the identification of the exact nucleotide change of low-prevalence mutations (25-28), although the degree of mutation enrichment via fast COLD-PCR is usually greater. We demonstrate that compared with conventional PCR, the application of fast COLD-PCR can increase the proportion of mutation-containing sequences, thereby improving detection and selectivity, reducing the number of samples to be evaluated downstream by preliminary HRM scanning (reducing time and costs), and enabling downstream sequencing of low-prevalence unknown mutations detected via HRM scanning.

Materials and Methods

DNA AND TUMOR SAMPLES

Genomic DNA from cell lines with defined TP53 (tumor protein p53) mutations (T47D, SNU-182, HCC2157; see Table 1 in the Data Supplement that accompanies the online version of this article at http://www.clinchem.org/content/vol55/issue12) was purchased from the ATCC. Cell line SW480 (mutation in exon 8) was also purchased from this source, and genomic DNA was extracted from cultured cells. Male-genomic DNA (Promega Corporation) served as the wild-type control. Lung adenocarcinoma samples that had been snap-frozen in liquid nitrogen within 1–2 h of surgery were obtained from the Massachusetts General Hospital Tumor Bank and were used with Internal Review Board approval. After manual macrodissection, genomic DNA was isolated from the samples with the DNeasy® Blood & Tissue Kit (Qiagen).

DNA from cell lines SNU-182, T47D, HCC2157, and SW480 was serially diluted into wild-type DNA to the following percentages: 0.1%, 0.25%, 0.5%, 1.0%, 2.0%, 3.0%, 4.0%, 5.0%, 6.0%, 8.0%, and 10%. In addition, several replicates of wild-type DNA (0% mutant) were included in each experiment and evaluated in parallel. After method optimization, we analyzed DNA from human lung adenocarcinoma tumor samples that had previously been shown to contain mutations in TP53 exons 7 and 8 in a range of abundances (see Table 2 in the online Data Supplement). Specifically, the lung adenocarcinoma DNA samples selected for this investigation had originally been amplified via COLD-PCR, and the mutations in TP53 exons 7 and 8 had been identified by Sanger sequencing. The mutations were independently confirmed via conventional PCR and RFLP analysis or via conventional PCR and pyrosequencing and were found to occur at approximate abundances of 1%–90% (27).

COLD-PCR CONDITIONS

The Tc for fast COLD-PCR for a given amplicon is defined by first amplifying a wild-type sample via conventional PCR and then conducting a melting-curve analysis (ramping at 0.2 °C/s from 65 °C–98 °C) to identify the Tm. The Tc is typically 1 °C below the experimentally derived amplicon Tm. Defining the Tc in this manner produces both robust PCR amplification and strong mutation enrichment. Because the Tc during COLD-PCR has to be controlled precisely (e.g., to within ±0.2 °C), it is important to use a thermocycler with high temperature precision. A SmartCycler II (Cepheid) was used in this investigation.

HRM analysis requires a saturating amount of the fluorescent dye (LCGreen Plus+; Idaho Technology) that must be incorporated during the PCR step; however, protocols previously established in our laboratory for COLD-PCR have used smaller amounts (0.1×) of LCGreen Plus+ (25). To use the COLD-PCR thermo-cycling conditions that we previously established in our laboratory while maintaining the LCGreen Plus+ concentrations recommended for accurate HRM analysis, we adopted a nested amplification strategy.

We initially performed COLD-PCR with genomic DNA (0.1× LCGreen Plus+) at the determined Tcs (see Table 3 in the online Data Supplement). Products from each initial COLD-PCR reaction were then diluted and used as template for a nested conventional PCR to achieve the recommended 1× LCGreen Plus+ dye concentration before HRM analysis. In 1 case (a 129-bp amplicon of exon 6), we also modified the COLD-PCR amplification conditions to allow use of 1× LCGreen Plus+ during direct amplification from genomic DNA and subsequent HRM screening, without the nested-PCR step.

The reaction conditions are as follows (see online Data Supplement for details). TP53 exons 6, 7, and 8 were amplified with the primers described in Table 1 in the online Data Supplement. To produce products of an appropriate length for COLD-PCR, we used 2 amplicons to span the entire length of TP53 exon 6, which exceeds 200 bp (see Table 1 in the online Data Supplement). Serial dilutions of cell-line DNA were evaluated for all amplicons; however, lung tumor DNA was evaluated only for exons 7 and 8.

COLD-PCR reactions contained 1×Phusion® HF Buffer (Finnzymes), 1.5 mmol/L MgCl2, 0.2 mmol/L of each of the 4 deoxynucleoside triphosphates (dNTPs), 0.2 μmol/L primers, 0.1×LCGreen Plus+dye, 5 U/μL Phusion® high-fidelity DNA polymerase (Finnzymes), and approximately 50 ng DNA. COLD-PCR was performed on a SmartCycler II as described in Table 3 in the online Data Supplement. COLD-PCR thermocy-cling included an initial number of PCR cycles at a conventional denaturation temperature (98 °C) to build up the intended target amplicon from genomic DNA. This initial amplification at the standard denaturation temperature was performed until the amplification reached the PCR threshold, approximately 20 cycles. The PCR was then automatically switched to use the Tc for an additional 20 cycles of amplification. Thermocycling conditions for COLD-PCR reactions and the corresponding Tcs are described in Table 3 in the online Data Supplement.

COLD-PCR amplicons were diluted and subsequently used as template in a nested conventional PCR. Nested conventional-PCR amplification (primer sequences are presented in Table 1 in the online Data Supplement) was performed on an Eppendorf Master-cycler®, and successful amplifications were verified by electrophoresis on 20-g/L agarose gels. Reagent conditions for the nested conventional PCR were as follows: 1×manufacturer-supplied Flexi® PCR buffer (Promega), 1.5–2.8 mmol/L MgCl2, 0.2 mmol/L dNTPs, 0.2 μmol/L primers, 1.0×LCGreen Plus+dye, and 5 U/μL GoTaq® DNA polymerase (Promega).

To evaluate the mutation selectivity of COLD-PCR, we repeated all experiments in parallel with conventional PCR instead of COLD-PCR; we used the 2-step protocol described above without changing any of the other conditions. All samples were amplified and examined in duplicate.

HRM FOR MUTATION ANALYSIS

Approximately 10 μL of each PCR product, with a 20-μL oil overlay, was subjected to HRM analysis on the LightScanner® HR96 system (Idaho Technology). Melting curves were analyzed by the LightScanner software, with Call-IT® 2.0 used to discern the presence of a mutation. Amplicons from mutation-containing DNA were directly compared with several wild-type reference samples of male-genomic DNA that were amplified in parallel. PCR products were subsequently subjected to exonuclease I/shrimp alkaline phosphatase digestion and sequenced at the Molecular Biology Core Facility, Dana-Farber Cancer Institute. Sequencing chromatograms were evaluated with the BioEdit™ biological sequence alignment editor (http://www. mbio.ncsu.edu/BioEdit/BioEdit.html). Approximate estimates of the mutant nucleotide's abundance relative to the wild-type nucleotide were calculated from the peak heights of the chromatograms.

Results

SERIAL-DILUTION EXPERIMENTS

TP53 exon 6

We examined 2 regions of TP53 exon 6: a 111-bp amplified region containing the SNU-182 cell-line mutation (G>T) and a second region (129 bp) that contained the T47D cell-line mutation (C>T). After COLD-PCR amplification and subsequent HRM analyses of serial dilutions of mutant DNA into wild-type DNA, we used the LightScanner Call-IT 2.0 software to generate fluorescence difference curve plots relative to wild-type DNA. Conventional PCR/HRM was performed in parallel to facilitate comparison with COLD-PCR/HRM results. Fig. 1A depicts the difference curves produced by conventional PCR and COLD-PCR for the 111-bp exon 6 amplicon. Depicted are 2 replicates for each mutation-containing sample and 10 replicates of wild-type samples. After conventional PCR, mixtures with the SNU-182 mutation could be differentiated from the set of 10 wild-type samples down to a mutant abundance of 2%. In contrast, after COLD-PCR, SNU-182 DNA diluted into wild-type DNA to 0.1% abundance was still clearly differentiated from the wild-type DNA melting curves. Thus, for the 111-bp amplicon of exon 6, the COLD-PCR/HRM analysis produced an approximately 20-fold improvement in mutation detection compared with the conventional PCR/HRM analysis (see Table 4 in the online Data Supplement).

Fig. 1
Comparison of COLD-PCR and conventional PCR for detection of G>T mutation in TP53 exon 6 from cell line SNU-182

To determine the approximate degree of mutant enrichment and to evaluate our ability to sequence a low-level mutation, we performed Sanger sequencing. The sequencing chromatograms are presented in Fig. 1B. Despite the inherent detection capability of conventional PCR/HRM screening, we were unable to identify the mutant by direct sequencing, even at the highest mutant concentration examined (10% mutant abundance); however, after COLD-PCR amplification and sequencing, we were able to reliably identify the SNU-182 mutant in a 2% mixture, and examination of the sequencing chromatograms indicated a mutation abundance of approximately 40% (Fig. 1B).

Our experiments with the 129-bp amplicon of exon 6 produced results similar to those obtained with the 111-bp amplicon. Fig. 2A shows that the T47D mutation was detectable by HRM down to 3% mutant after conventional PCR; however, after COLD-PCR, the T47D mutation remained detectable in a mixture as low as 0.1% mutant. Included in Fig. 2A are 2 replicates for each mutation-containing sample and 6 replicates of wild-type samples. Only one of the 2 replicates in each of the 0.1% and 0.25% mutant mixtures could be differentiated from the 6 wild-type control samples; thus, the lower limit of detection for the 129-bp amplicon was a mixture of approximately 0.5% mutant. Detection of the T47D mutation in the 0.5% sample after COLD-PCR indicated an approximately 6-fold improvement in HRM detection selectivity over that of conventional PCR (see Table 4 in the online Data Supplement). Sequencing analysis (Fig. 2B) of the 129-bp amplicon of TP53 exon 6 revealed that the T47D mutant in a 10% mixture was not detectable after conventional PCR; however, after COLD-PCR amplification, the C>T T47D mutation was clearly detected in the mixture of 4% mutant; the sequencing chromatograms indicated an abundance of approximately 36%.

Fig. 2
Comparison of COLD-PCR and conventional PCR for detection of C>T mutation in TP53 exon 6 from cell line T47D

TP53 exon 7

A 149-bp region of TP53 exon 7 was amplified via both conventional PCR and COLD-PCR and subsequently analyzed by HRM and the LightScanner Call-IT 2.0 software. Most serial dilutions of HCC2157 DNA into wild-type DNA were undetectable by HRM after conventional PCR; only the sample with 10% HCC2157 DNA could be differentiated from the 10 replicate wild-type control samples (Fig. 3A). In contrast, the dilution with 1% HCC2157 DNA amplified by COLD-PCR could be clearly differentiated from the set of wild-type DNA samples; for this amplicon, HRM analysis of COLD-PCR amplicons provided a 10-fold advantage in selectivity over that of amplicons produced by conventional PCR (see Table 4 in the online Data Supplement).

Fig. 3
Comparison of COLD-PCR and conventional PCR for detection of C>T mutation in TP53 exon 7 from cell line HCC2157

Fig. 3B presents the chromatograms for mutation identification after COLD-PCR and Sanger sequencing. Evaluation of the conventional PCR chromatograms revealed that the C>T mutation was only barely detectable in the 10% HCC2157 sample. After COLD-PCR, however, the HCC2157 mutation was detectable in a mixture of 3% mutant to a degree equivalent to that of the sample with 10% mutant after conventional PCR.

TP53 exon 8

The SW480 cell line (G>A mutation) was serially diluted into wild-type DNA and amplified via COLD-PCR. Conventional PCR/HRM analysis was performed in parallel for comparison with COLD-PCR/HRM results. After conventional PCR, the lower limit of HRM detection of the mutation was a dilution with 5% mutant (Fig. 4A). One replicate of the 3% mutation mixture was scored as “unknown” by the Call-IT 2.0 software; however, the other 3% replicate remained indistinguishable from the wild-type melting profiles. In contrast, the COLD-PCR sample with a 0.25% abundance of the SW480 mutation was easily differentiated from the wild-type samples—a >10-fold improvement in mutation detection (see Table 4 in the online Data Supplement). The 0.1% SW480 concentration was not evaluated in this analysis.

Fig. 4
Comparison of COLD-PCR and conventional PCR for detection of G> A mutation in TP53 exon 8 from cell line SW480

Both conventional-PCR and COLD-PCR amplicons were subsequently sequenced (Fig. 4B). The G>A mutation was identified only in the conventional-PCR amplicons with a 10% abundance of the SW480 mutation. After COLD-PCR, however, the concentration of the sample with 2% SW480 mutation was enriched to approximately 26%, and the mutation could be clearly identified.

We also performed a similar experiment to investigate the effect of fast COLD-PCR on Tm-increasing mutations, such as A>G or A>T. Fig. 1 in the online Data Supplement presents chromatograms obtained from samples in which we titrated a Tm-increasing single-nucleotide polymorphism into wild-type DNA, amplified the samples by both conventional PCR and fast COLD-PCR, and subjected them to HRM analyses. This A>G single-nucleotide polymorphism (codon 213) in the 129-bp amplicon of TP53 exon 6 is heterozygous. We subsequently diluted it into wild-type DNA to generate approximately 10% and 5% concentrations of the G allele. All G-allele abundances (50%, 10%, and 5%) were clearly distinguishable from the major A allele in both conventional-PCR and COLD-PCR amplicons. The A allele was amplified somewhat more than the G allele during fast COLD-PCR, although this enrichment was not as pronounced as expected. A potential explanation for these observations is that the late stages of fast COLD-PCR lead to inherent formation of A:G and T:C heteroduplexes. These heteroduplexed molecules would then denature in subsequent fast COLD-PCR cycles at a lower Tm than the homoduplexed molecules. Consequently, the fast COLD-PCR would effectively enrich these heteroduplexes for the remainder of the PCR.

ANALYSIS OF LUNG ADENOCARCINOMA TUMOR SAMPLES

TP53 exon 7

To further evaluate the COLD-PCR/ HRM method, we also analyzed DNA from human lung adenocarcinoma tumor samples for mutations in TP53 exons 7 and 8. For exon 7, we evaluated 9 lung tumor samples and wild-type DNA via HRM with both conventional PCR and COLD-PCR. These 9 DNA samples were recently evaluated in our laboratory by COLD-PCR and direct sequencing and were deemed to be an appropriate initial test of the COLD-PCR/HRM methodology for clinical samples (27). Two adenocarcinoma samples, TL98 and TL137, contained no TP53 exon 7 mutations, whereas the remaining 7 samples harbored TP53 mutations over a range of abundances. These mutations were verified independently with RFLP or pyrosequencing methodologies (27).

The results of HRM analyses of the conventional-PCR and fast COLD-PCR amplicons for the mutation-negative adenocarcinoma samples TL98 and TL137 remained negative for mutation detection; we therefore scored them as wild type, along with the male-genomic control samples (Fig. 5). Analyses of TL134, TL125, and TL97, however, revealed the presence of mutations in TP53 exon 7 (Fig. 5A). These mutations exhibited melting profiles that were highly aberrant compared with the wild-type control samples (Fig. 5A); they were also detectable with conventional PCR and sequencing (data not shown). After mutation enrichment via COLD-PCR, the shapes of the melting curves changed, although they remained clearly differentiated from those of the male-genomic control samples (Fig. 5A). HRM analysis is based on a heteroduplex-analysis approach. In some situations, homozygous variants can produce melting curves that are almost identical to the wild-type melting curve, as predicted by nearest-neighbor thermodynamic models (4). Because the abundance of Tm-decreasing mutations increases throughout the process of fast COLD-PCR enrichment, it is possible that a mutant at high abundance could become less differentiated from the wild-type samples. As we have demonstrated, however, even an abundant mutant with an initial abundance of approximately 90% (TL125) remains distinguishable from the wild type, even after enrichment by COLD-PCR.

Fig. 5
Comparison of COLD-PCR and conventional PCR for detection of TP53 exon 7 amplicons from human lung adenocarcinoma DNA samples

The most pronounced difference in fluorescence between the conventional PCR and COLD-PCR results was apparent in the melting curves of samples TL119, TL121, TL96, and TL78. Conventional PCR/HRM analysis permitted detection of mutations in these lung tumor samples in conventional-PCR amplicons, although TL78 had a melting curve quite similar to that of wild-type DNA. After COLD-PCR/HRM analysis, however, the difference in fluorescence between tumor DNA and wild-type DNA was magnified in the TL119, TL121, and TL96 samples (Fig. 5A). The improved HRM detection was consistent with the mutation enrichment that is evident after direct sequencing of the mutation-positive amplicons. As is apparent in the sequencing chromatograms (Fig. 5B), although the mutations were not identified when conventional-PCR amplicons were sequenced, they were identified reliably in the COLD-PCR sequencing chromatograms.

TP53 exon 8

A 135-bp region from TP53 exon 8 was analyzed with another set of 9 lung adenocarcinoma samples and with wild-type control DNA. In the TP53 exon 8 amplicon, the lung tumor samples TL5, TL18, TL15, and TL14 exhibited easily distinguishable and highly aberrant melting profiles, compared with the wild-type DNA control samples (Fig. 6A). After COLD-PCR amplification, the melting profile shapes changed but remained clearly distinguishable from the wild-type control samples (Fig. 6A). As mentioned above, it is possible that high-abundance mutants may become less differentiated from the wild type if enrichment is quite strong and if their homoduplex melting curves are comparable to the wild-type melting curve (4). Sequencing analysis of these amplicons revealed that the mutations remained clearly visible in the chromatograms of both conventional-PCR and COLD-PCR amplicons (data not shown).

Fig. 6
Comparison of COLD-PCR and conventional PCR for detection of TP53 exon 8 amplicons from human lung adenocarcinoma DNA samples

The most pronounced improvement in fluorescence difference was apparent for the COLD-PCR amplicons of TL86, TL82, TL6, and TL8. After conventional PCR, 3 samples (TL86, TL82, and TL6) fell into the “unknown” category after automated analysis with the LightScanner software (Fig. 6A). The “unknown” category indicates the potential presence of a mutation, although the melting curve profile may not differ appreciably from that of the wild-type controls. Along with TL8, these 3 mutations exhibited melting curve profiles similar to the profile of the wild-type DNA control samples when they were amplified by conventional PCR. After amplification via COLD-PCR, however, the mutation enrichment produced an increased difference in fluorescence compared with the wild-type DNA control samples (Fig. 6A). COLD-PCR/HRM analysis produced melting curves that were clearly differentiated from those of the control samples, increasing the confidence in the HRM scoring.

Sanger sequencing confirmed mutant enrichment in the 135-bp COLD-PCR amplicons compared with conventional-PCR amplicons; representative mutant enrichment is apparent in the sequencing chromatograms for TL86, TL82, TL6, and TL8 (Fig. 6B; Fig. 2 in the online Data Supplement). COLD-PCR revealed a G>T mutation in TL86, a G>A mutation in TL82, a G>T mutation in TL6, and a G>T mutation in TL8. For all 4 samples (TL86, TL82, TL6, and TL8), the mutation was not identified in the sequencing chromatograms of conventional-PCR amplicons.

Discussion

In our screening experiments with DNA with mutations serially diluted into wild-type DNA and our experiments with lung adenocarcinoma samples, we have demonstrated a highly improved HRM mutation-detection capability through the increased selectivity of amplification via COLD-PCR. Specifically, HRM was capable of detecting mutant abundances of approximately 2%–10% with conventional PCR, whereas substitution of COLD-PCR increased HRM selectivity by 6- to 20-fold, allowing the detection of mutations at abundances of 0.1%–1%. In addition to increasing detection selectivity, the use of COLD-PCR for amplicons from TP53 exons 6–8 permitted successful downstream sequencing and the identification of both mutation type and position in samples with approximate mutant abundances of 2%–4%, compared with the current Sanger sequencing limit of 20% after conventional PCR. Thus, substituting COLD-PCR for conventional PCR improved the ability to identify low-abundance mutations via Sanger sequencing by approximately 5- to 10-fold.

The result with lung tumor sample TL78 may represent the lower limit for mutation identification of the TP53 exon 7 amplicon with the current approach. Although the TL78 amplicon exhibited an aberrant melting profile after COLD-PCR relative to that of the male-genomic control, sequencing of the COLD-PCR amplicons did not reveal a mutation. Considering that the melting curve for conventional PCR/HRM is close to that of wild-type DNA and shows only a slight improvement after COLD-PCR, it is possible that TL78 contains a mutation at very low abundance that remains undetectable even after COLD-PCR and sequencing (i.e., <3% according to the serial dilution experiments presented in Fig. 3). Further optimization of COLD-PCR to increase the degree of enrichment would be beneficial for identifying mutations at very low prevalences.

The COLD-PCR reactions for TP53 exon 7 generally exhibited a lower degree of mutation enrichment and detection selectivity than the other amplicons we evaluated for this report. This result is most likely explained by the existence of 2 melting domains in the PCR amplicon. COLD-PCR functions most efficiently for amplicons that possess a single melting domain, because the specific Tc is derived from the Tm. Consequently, amplicons with >1 melting domain will possess >1 denaturation temperature, and thus a single Tc will be inappropriate for enriching mutations across the entire amplicon. The mutation in the HCC2157 cell line lies approximately in the middle of the 2 melting domains. We therefore speculate that the degree of enrichment was adequate to allow sequencing of mutant mixtures as low as 3% mutant (an approximate 6-fold increase in sensitivity over conventional PCR and sequencing); however, the enrichment could potentially be improved by redesigning the primer set to produce an amplicon with a single melting domain. Similarly, mutation scanning with HRM itself appears to be more sensitive when amplicons possessing a single melting domain are examined.

Because the type and position of TP53 mutations often define their prognostic value (29) and because functional studies can reveal whether they are “driver” or “passenger” mutations, sequencing of HRM-identified TP53 mutations in tumor biopsies or surgical samples is a necessity (30). Certain TP53 mutations in tumors have been associated with a poor prognosis for a range of cancers, including lung cancer (29, 31), and loss of TP53 function has been correlated with the onset of multidrug resistance (32). The strategy of using HRM as a preliminary scanning method and subsequently sequencing only those samples with aberrant HRM profiles reduces the sequencing load appreciably. The COLD-PCR/HRM approach we have described provides a convenient and low-cost method for the detection and identification of low-prevalence somatic mutations in tumors. Furthermore, the use of alternative sequencing strategies to identify the mutations after HRM, such as COLD-PCR/pyrosequencing, may further facilitate the identification of the type and position of a mutation.

Although we evaluated the use of fast COLD-PCR in this work, the approach should be applicable in principle to full COLD-PCR as well. The application of full COLD-PCR before HRM analysis would allow identification of all types of mutations, including the minority (approximately 30%) of lung tumor TP53 mutations that retain or increase the amplicon Tm (not evaluated with the present fast COLD-PCR approach) (33). Full COLD-PCR would be the most appropriate approach in a clinical setting where it is important to identify all mutations (i.e., no false negatives), whereas fast COLD-PCR would be more appropriate when high sensitivity is the most important factor, such as in the identification and tracing of tumor biomarkers (e.g., tracing tumor-identified mutations in plasma).

We have presented an approach for scanning for unknown low-prevalence mutations. This approach uses HRM followed by Sanger sequencing–based identification. The application of COLD-PCR before HRM improved the detection selectivity of HRM and simultaneously enabled sequencing of mutation-positive candidates with melting curves that would otherwise fall close to the melting curve of wild-type DNA if conventional PCR were applied. With this improvement, the combination of COLD-PCR and HRM could become an important routine screening tool for mutations at very low abundances because of its speed, ease of use, and low cost. It holds promise as a clinically and diagnostically useful approach.

Supplementary Material

Supplementary Tables

Supplementary figures

Acknowledgments

We thank Jason McKinney and Idaho Technology Inc. for their assistance and contribution to the project. This manuscript was previously published in abstract form for the American Association of Cancer Research annual conference (2009).

Role of Sponsor: The funding organizations played no role in the design of study, choice of enrolled patients, review and interpretation of data, or preparation or approval of manuscript.

Footnotes

2Nonstandard abbreviations: HRM, high-resolution melting; COLD-PCR, coamplification at lower denaturation temperature–PCR; Tc, critical denaturation temperature; Tm, melting temperature; dNTP, deoxynucleoside triphosphate.

Authors' Disclosures of Potential Conflicts of Interest: Upon manuscript submission, all authors completed the Disclosures of Potential Conflict of Interest form. Potential conflicts of interest:

Employment or Leadership: None declared.

Consultant or Advisory Role: None declared.

Stock Ownership: None declared.

Honoraria: None declared.

Research Funding: This project was supported by T32-CA009078 from the National Cancer Institute (C.A. Milbury), the JCRT Foundation (J. Li), and NIH grants CA-138280 and CA-111994.

Expert Testimony: None declared.

Disclaimer: The contents of this report are the responsibility of the authors and do not necessarily represent the official views of the NIH.

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