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.