Abstract

Finding Needles in a Haystack with Q-PCR – Rare Mutations, Single Cell Genotyping and DNA Methylation Analysis

Jorg Tost, Director, Centre National de Genotypage CEA

Quantitative PCR has evolved as a powerful tool for the analysis of biological materials, which contain the molecules of interest at very low proportions or at very limited quantity. A number of methods allowing the detection of low levels of mutations have been developed in the last years. However, although these methods have become increasingly sensitive, they can rarely identify the mutated base directly without prior knowledge on the mutated base and are often incompatible with a sequencing based read-out desirable in clinical practice. We present a modified version of the ice-COLD-PCR assay called Enhanced-ice-COLD-PCR for KRAS, BRAF and NRAS mutation detection and identification, which allows the enrichment of the most frequent mutations. This assay permits the reliable detection of down to 0.1 % mutated sequences in a wild-type background. In contrast to other COLD PCR variants, the assay is simple to set-up especially when using qPCR thermocylers with a gradient function. A single genotyping assay of the amplification product by pyrosequencing directly following the Enhanced-ice-COLD-PCR is performed to identify the mutated base. This developed two-step method is rapid, cost-effective and requires only a small amount of starting material (frozen, FFPE or plasma) permitting the sensitive detection and sequence identification of mutations within three hours. This method has been applied to different collections of cancer samples and enables detection of mutations in samples, which appear as wild-type using standard detection technologies. In addition, samples of interest are in most cases a heterogeneous mixture of cell populations, which display different DNA methylation profiles depending on the cell type and potentially even the alleles of the same cell. Very few methods are currently applicable to the analysis of DNA methylation patterns in a single cell. We will present a methylation-sensitive restriction endonuclease based method for the analysis of