NEW YORK (GenomeWeb) – New research from an international team has concluded that a PCR-based technique called peptide-nucleic-acid-mediated PCR, or PNA-PCR, is significantly more sensitive than Sanger sequencing in detecting KRAS mutations in tumor tissue and plasma samples.
In a study published online this week in the Journal of Experimental & Clinical Cancer Research, researchers in China, Italy, and the US examined samples from 416 patients with metastatic colorectal cancer. Patients were enrolled in the study at a hospital in Beijing between 2007 and 2011, and received two or more cycles of chemotherapy. The investigators retrospectively searched for KRAS mutations in formalin-fixed, paraffin-embedded tissue samples from biopsy or surgical resection, as well as in plasma samples from 242 of the study participants.
The researchers compared PNA-PCR to direct sequencing using the Applied Biosystems 3100 Genetic Analyzer. They also correlated KRAS mutation detection in tissue and plasma with clinical outcomes following chemotherapy.
In FFPE tumor tissue, there was no relationship between KRAS status and clinical response or progression-free survival.
Overall survival trended toward improvement for KRAS wild-type gene status based on sequencing results. Yet this difference was only statistically significant for PNA-PCR mutation measurements.
Considering tissue and plasma results together, having wild-type genotypes in both samples led to about five months longer median overall survival, while patients with tissue and plasma samples discordant for KRAS mutations by PNA-PCR, or with mutations in both sample types, had reduced survival.
Further, PNA-PCR detected KRAS gene alterations in 41 percent of the pooled samples, while sequencing only detected mutations in 30 percent, leading the authors to conclude the PNA-PCR was a more sensitive assay. Mutations were more frequent in tissue than plasma, and mutation status in plasma was concordant with tissue in more than 70 percent of cases. Five percent of the samples showed mutations in plasma but not in tissue, a scenario the authors ascribed to tumor heterogeneity. In plasma, the KRAS mutation detection rate was 17 percent by sequencing versus 31 percent by PNA-PCR.
As described in a review from 2004, PNA-PCR uses peptide nucleic acids to clamp amplification of wild-type sequences. In the current study, PNA oligomers were used to suppress amplification of codons 12 and 13 of the wild-type KRAS gene.
Other researchers have used this technique to detect KRAS mutations in non-small cell lung cancer, and in circulating cell-free DNA, and have modified it for quantitative PCR. A similar clamping technique is also being developed by start-up DiaCarta using xenonucleic acid, or XNA. DiaCarta recently received CE marking on a number of kits that use the method to detect various cancer-related mutations, including KRAS, in whole blood samples.
The KRAS mutation is also one of the targets in Exact Science's Cologuard colorectal cancer at-home screening test, which was recently cleared by the US Food and Drug Administration after parallel review by the FDA and the Centers for Medicare & Medicaid Services. Among other biomarkers, Cologuard measures seven point mutations in KRAS cell-free tumor DNA from stool samples using a technique called Quantitative Allele-specific Real-time Target and Signal amplification, or QuARTS.
Other companies developing colorectal cancer tests measuring KRAS mutations include a collaboration between Sysmex Inostics and Merck using emulsion-based digital PCR, and Vela Diagnostics using Qiagen's Rotor-Gene Q, a thermocylcer that was recently cleared for diagnostics development as part of the QIAsymphony RGQ MDx system.
Qiagen's Therascreen KRAS RGQ PCR Kit, meanwhile, uses PCR to measure KRAS status and is approved for use as a colorectal cancer companion diagnostic for erbitux and for Amgen's Vectibix. A partnership between Amgen and Illumina also aims to develop a companion diagnostic for Vectibix based on KRAS detection, but using a next-generation sequencing-based approach on the MiSeqDx platform.