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Sensitive Detection of KRAS Mutations Using E nhanced‐ ice ‐ COLD ‐ PCR Mutation Enrichment and Direct Sequence Identification
Author(s) -
How Kit Alexandre,
Mazaleyrat Nicolas,
Daunay Antoine,
Nielsen Helene Myrtue,
Terris Benoît,
Tost Jörg
Publication year - 2013
Publication title -
human mutation
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.981
H-Index - 162
eISSN - 1098-1004
pISSN - 1059-7794
DOI - 10.1002/humu.22427
Subject(s) - kras , biology , cold pcr , pyrosequencing , mutation , polymerase chain reaction , genotyping , microbiology and biotechnology , sequence (biology) , computational biology , genetics , gene , point mutation , genotype
A number of methods allowing the detection of low levels of KRAS 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. Here, we present a modified version of the ice ‐ COLD ‐ PCR assay called E nhanced‐ ice ‐ COLD ‐ PCR ( E ‐ ice ‐ COLD ‐ PCR ) for KRAS mutation detection and identification, which allows the enrichment of the six most frequent KRAS mutations. The method is based on a nonextendable chemically modified blocker sequence, complementary to the wild‐type (WT) sequence leading to the enrichment of mutated sequences. This assay permits the reliable detection of down to 0.1% mutated sequences in a WT background. A single genotyping assay of the amplification product by pyrosequencing directly following the E ‐ ice ‐ COLD ‐ PCR is performed to identify the mutated base. This developed two‐step method is rapid and cost‐effective, and requires only a small amount of starting material permitting the sensitive detection and sequence identification of KRAS mutations within 3 hr. This method is applied in the current study to clinical colorectal cancer samples and enables detection of mutations in samples, which appear as WT using standard detection technologies.