Mutant allele frequency predicts lung cancer TKI response

Published on August 28, 2014 at 5:15 PM · No Comments

By Lynda Williams, Senior medwireNews Reporter

Tyrosine kinase inhibitor (TKI) sensitivity may be predicted by the frequency of a point mutation in the epidermal growth factor receptor (EGFR) gene, suggests a study of Japanese patients with advanced lung adenocarcinoma.

Akira Ono, from Shizuoka Cancer Center in Japan, and co-workers investigated the relationship between the L858R mutation in exon 21 in 48 patients with advanced EGFR-mutation positive lung cancer and their response to TKI therapy.

The researchers assessed EGFR mutation status in histology samples using both pyrosequencing and the Cycleave polymerase chain reaction technique.

The L858R mutation was identified in 94% of patients using both techniques and in 6% of patients using only pyrosequencing, with a median mutant allele frequency (MAF) for L858R of 18.5%.

The researchers were then able to calculate the area under the receiver operating characteristic curve of the discordance in L858R mutation. A median MAF for L858R of 9% was found to be 100% sensitive and 99% specific for detection of the mutation.

Further analysis of 29 patients with advanced EGFR mutant-positive lung adenocarcinoma who were treated with gefitinib or erlotinib showed that the response rate to TKI treatment was significantly predicted by MAF of L858R.

The median MAF of L858R was 18.0%; 79.1% of patients with a MAF of at least 9% responded to TKI therapy compared with just 20.0% of patients with an MAF of less than 9%.

“In practice, we would not exclude patients with an MAF of 9% or less from receiving TKIs”, the team writes in the Annals of Oncology.

“But for those patients, we may need to develop new treatment strategies such as combination therapy because EGFR-TKI alone may not be effective enough.”

Recommending further research into MAF using highly sensitive techniques such as digital polymerase chain reaction, they conclude: “The potential applications of quantified MAF might include the identification of candidates for decision-making at the time of the acquisition of resistance such as T790M during EGFR-TKI therapy.”

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