Feasibility analysis of rapid gene detection using intraoperative frozen tissues: comparison of intraoperative frozen tissues with paraffin-embedded tissues in epidermal growth factor receptor gene mutation detection of lung adenocarcinoma

Background Epidermal growth factor receptor (EGFR) is the driver gene with the highest frequency of mutations in lung adenocarcinoma and can guide the development of targeted therapies. The detection of routine gene mutations must be performed after the preparation of paraffin samples in a standard polymerase chain reaction (PCR) laboratory, which is time-consuming. The Idylla™ EGFR fully automatic PCR system for rapid detection requires no special detection environment and completes the process in only 2.5 h. It has been applied to tissues embedded in paraffin. Methods The Idylla™ EGFR automated PCR system was used to detect EGFR gene mutations in intraoperative frozen fresh tissues and paraffin-embedded tissues from 47 enrolled patients with lung adenocarcinoma. The gold standard amplification refractory mutation system (ARMS) method for gene mutation detection was used for verification, and the concordance between the three detection results was compared, to investigate the feasibility of detecting rapid gene mutations in intraoperative frozen samples. Results The EGFR mutation rate in 47 fresh samples of lung adenocarcinoma was 61.7% (29/47), which is consistent with the mutation level of lung adenocarcinoma in the Asian population (38.8–64.0%). The concordance rate between the Idylla™ frozen tissues and paraffin-embedded tissues was 91.4% (43/47) when compared to the ARMS method, while the coincidence rate between the two methods was 93.6% (44/47). The three methods had a total consistency rate of 89.4% (42/47). Conclusions The Idylla™ EGFR fully automatic PCR system directly detects EGFR mutations in fresh tissues. The operation is simple, the detection time is short, and the accuracy is high. The detection time is reduced to 1/4–1/3 of the original time while meeting clinical standards for detecting the gene status of patients, thus saving crucial time for individualized and accurate treatment of patients. The method has promising clinical application prospects.