Purpose: Examination of somatic epidermal growth factor receptor (EGFR) mutations is now a diagnostic routine for treatment of cancer using EGFR tyrosine kinase inhibitors (EGFR-TKI). Circulating tumor DNA is a promising target for noninvasive diagnostics. We evaluated its utility by quantitatively detecting activating and resistant mutations, which were measured with BEAMing (beads, emulsion, amplification, and magnetics).Experimental Design: Twenty-three patients with lung cancer with progressive disease after EGFR-TKI treatment and 21 patients who had never been treated with EGFR-TKIs were studied. Their primary tumors were confirmed to have activating mutations. In the plasma DNA of each patient, the activating mutation found in the corresponding primary tumor and the T790M resistance mutation were quantified by BEAMing.Results: In 32 of 44 patients, activating mutations were detected in the plasma DNA [72.7%; 95% confidence interval (CI), 58.0%-83.6%]. The T790M mutation was detected in 10 of 23 patients in the first group (43.5%; 95% CI, 25.6%-53.4%). The ratio of T790M to activating mutations ranged from 13.3% to 94.0%. The peak of the distribution of the mutation allele fraction in the plasma DNA was in the 0.1% to 1% range.Conclusions: The major advantage of BEAMing is its ability to calculate the fraction of T790M-positive alleles from the alleles with activating mutations. This feature enables the detection of increases and decreases in the number of T790M mutations in cancer cells, regardless of normal cell DNA contamination, which may be useful for monitoring disease progression. Circulating tumor DNA could potentially be used as an alternative method for EGFR mutation detection. Clin Cancer Res; 17(24); 7808-15. Ó2011 AACR.

The detection of rare mutants using next generation sequencing has considerable potential for diagnostic applications. Detecting circulating tumor DNA is the foremost application of this approach. The major obstacle to its use is the high read error rate of next-generation sequencers. Rather than increasing the accuracy of final sequences, we detected rare mutations using a semiconductor sequencer and a set of anomaly detection criteria based on a statistical model of the read error rate at each error position. Statistical models were deduced from sequence data from normal samples. We detected epidermal growth factor receptor (EGFR) mutations in the plasma DNA of lung cancer patients. Single-pass deep sequencing (>100,000 reads) was able to detect one activating mutant allele in 10,000 normal alleles. We confirmed the method using 22 prospective and 155 retrospective samples, mostly consisting of DNA purified from plasma. A temporal analysis suggested potential applications for disease management and for therapeutic decision making to select epidermal growth factor receptor tyrosine kinase inhibitors (EGFR-TKI).

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