Microfluidics-based EGFR mutation detection and its implication in the resource-limited clinical setting.

Area of Science:

• Oncology
• Molecular Diagnostics
• Biotechnology

Background:

• Management of lung cancer necessitates epidermal growth factor receptor (EGFR) mutational analysis for tyrosine kinase inhibitor (TKI) therapy selection.
• Accurate and efficient EGFR mutation detection is crucial for prognostic stratification and personalized treatment in non-small cell lung cancer (NSCLC).

Purpose of the Study:

• To evaluate the performance and clinical significance of an automated microfluidics-based platform for EGFR mutation detection.
• To assess the platform's concordance with conventional methods and its utility in routine diagnostics.

Main Methods:

• A two-phase study involving 174 formalin-fixed, paraffin-embedded (FFPE) NSCLC samples.
• Phase I: Validation against real-time PCR and next-generation sequencing (NGS).
• Phase II: Application of the microfluidics platform in routine diagnostics.

Main Results:

• The microfluidics platform showed 96.5% concordance with real-time PCR and 89.2% with NGS.
• It demonstrated 88.23% sensitivity and 100% specificity for EGFR mutations.
• The platform generated valid results in 94% of samples in Phase II, detecting mutations in 41% and requiring minimal tissue (2 sections, 5μm thickness).

Conclusions:

• The automated microfluidics platform is a rapid, walkaway solution for EGFR mutation detection with minimal technical skill and tissue requirements.
• It is a reliable diagnostic platform, particularly suitable for resource-limited settings, enabling efficient detection of actionable mutations.
• The study facilitated an algorithm for effective NSCLC screening, aiding judicious case triaging before multigene testing.