Data from Optimization of <i>RAS/BRAF</i> Mutational Analysis Confirms Improvement in Patient Selection for Clinical Benefit to Anti-EGFR Treatment in Metastatic Colorectal Cancer

In metastatic colorectal cancer (mCRC), recent studies have shown the importance to accurately quantify low-abundance mutations of the RAS pathway because anti-EGFR therapy may depend on certain mutation thresholds. We aimed to evaluate the added predictive value of an extended RAS panel testing using two commercial assays and a highly sensitive and quantitative digital PCR (dPCR). Tumor samples from 583 mCRC patients treated with anti–EGFR- (n = 255) or bevacizumab- (n = 328) based therapies from several clinical trials and retrospective series from the TTD/RTICC Spanish network were analyzed by cobas, therascreen, and dPCR. We evaluated concordance between techniques using the Cohen kappa index. Response rate, progression-free survival (PFS), and overall survival (OS) were correlated to the mutational status and the mutant allele fraction (MAF). Concordance between techniques was high when analyzing RAS and BRAF (Cohen kappa index around 0.75). We observed an inverse correlation between MAF and response in the anti-EGFR cohort (P < 0.001). Likelihood ratio analysis showed that a fraction of 1% or higher of any mutated alleles offered the best predictive value. PFS and OS were significantly longer in RAS/BRAF wild-type patients, independently of the technique. However, the predictability of both PFS and OS were higher when we considered a threshold of 1% in the RAS scenario (HR = 1.53; CI 95%, 1.12–2.09 for PFS, and HR = 1.9; CI 95%, 1.33–2.72 for OS). Although the rate of mutations observed among techniques is different, RAS and BRAF mutational analysis improved prediction of response to anti-EGFR therapy. Additionally, dPCR with a threshold of 1% outperformed the other platforms. Mol Cancer Ther; 16(9); 1999–2007. ©2017 AACR.