Comprehensive Validation of Snapback Primer-Based Melting Curve Analysis to Detect Nucleotide Variation in the Codon...

KRAS genotyping in tumor samples is a decisive clinical test for the anti-EGFR therapy management. However, the complexity of KRAS mutation landscape across different cancer types and the mosaic effect caused by cancer cellularity and heterogeneity make the choice of KRAS genotyping method a challenging topic in the clinical practice.

We depicted the landscape of somatic KRAS mutation in 7,844 primary tumors and 10,336 metastatic tumors across over 30 types of cancer using the Cancer Genome Atlas (TCGA) and Integrated Mutation Profiling of Actionable Cancer Targets (MSKCC-IMPACT) databases, respectively. A snapback primer assay based on melting curve analysis was developed to detect the most common somatic mutations in KRAS codons 12 and 13. The sensitivity and accuracy of the method was validated by genotyping 100 colorectal cancer (CRC) samples, in comparison with Sanger sequencing and T-A cloning sequencing.

Pancreas adenocarcinoma (somatic mutation frequency 90.6%), colorectal adenocarcinoma (42.5%), and lung adenocarcinoma (32.6%) are the top three most KRAS mutant primary cancer types. The metastatic tumors showed a higher prevalence (90.99% versus 66.31%) and diversity of KRAS mutation compared with the primary tumors. Mutations in codons 12 and 13 are the predominant genetic alteration in KRAS (84.15% for TCGA and 86.13% for MSK-IMPACT). Moreover, KRAS mutation is highly correlated with the overall survival of patients with metastatic cancer. The snapback primer assay showed a more favorable performance in enriching and detecting the KRAS codon 12 and 13 mutation (1% mutation load) compared with Sanger sequencing (20% mutation load and 7% false-negative rate).

KRAS mutation pattern is highly diverse among different cancer types and is associated with the survival of patients with metastatic cancers. The snapback primer assay is a reliable, sensitive method to detect the major mutant KRAS alleles, which might facilitate the effective cancer treatment decisions.