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Quantification of epidermal growth factor receptor (EGFR) mutation may be a predictor of EGFR-tyrosine kinase inhibitor treatment response.


ABSTRACT:

Background

Epidermal growth factor receptor (EGFR) gene mutation is a reliable predictive factor for response to EGFR-tyrosine kinase inhibitors (TKIs). The quantified EGFR value may also predict response and survival within an EGFR mutated group.

Methods

We conducted a retrospective study of 836 lung cancer patients. The patient sample was divided into two groups based on the mean delta cycle threshold (?Ct) value. EGFR mutation tests using peptide nucleic acid (PNA)-mediated clamping polymerase chain reaction (PCR) were performed. The efficiency of PCR clamping was determined by measuring the Ct value and EGFR quantification was determined by the corrected ?Ct value.

Results

EGFR mutation positivity was 30.1% and there were 235 single activating mutations. In this mutation group, the higher corrected ?Ct value (? mean value) group showed better objective response (70.9% vs. 54.9%, P?=?0.022) and clinical benefit rates (86.4% vs. 68.3%, P?=?0.003) than the lower group. In addition, corrected ?Ct values were significantly and inversely correlated with disease response (r?=?-0.184, P?=?0.017). In multivariate analysis, both female gender (P?=?0.014) and higher corrected ?Ct value (P?=?0.012) were independent predictive factors for better clinical benefit rate. The higher corrected ?Ct value group had a tendency for longer progression-free survival than the lower group (P?=?0.050).

Conclusion

The corrected ?Ct value, which refers to EGFR quantification by PNA-mediated PCR clamping, can predict better clinical response to EGFR-TKI therapy. However, further study is warranted to determine its value as a biomarker to reflect survival.

SUBMITTER: Park HY 

PROVIDER: S-EPMC5093171 | biostudies-literature | 2016 Nov

REPOSITORIES: biostudies-literature

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Quantification of epidermal growth factor receptor (EGFR) mutation may be a predictor of EGFR-tyrosine kinase inhibitor treatment response.

Park Ha Young HY   Oh Hyung Joo HJ   Kim Ki-Hyun KH   Kim Tae-Ok TO   Park Cheol-Kyu CK   Shin Hong-Jun HJ   Lim Jung-Hwan JH   Kwon Yong-Soo YS   Oh In-Jae IJ   Kim Yu-Il YI   Lim Sung-Chul SC   Kim Young-Chul YC   Choi Yoo-Duk YD  

Thoracic cancer 20160901 6


<h4>Background</h4>Epidermal growth factor receptor (EGFR) gene mutation is a reliable predictive factor for response to EGFR-tyrosine kinase inhibitors (TKIs). The quantified EGFR value may also predict response and survival within an EGFR mutated group.<h4>Methods</h4>We conducted a retrospective study of 836 lung cancer patients. The patient sample was divided into two groups based on the mean delta cycle threshold (∆Ct) value. EGFR mutation tests using peptide nucleic acid (PNA)-mediated cla  ...[more]

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