Evaluation of Raman spectroscopy for diagnosing EGFR mutation status in lung adenocarcinoma

Area of Science:

• Biochemistry
• Molecular Biology
• Oncology

Background:

• Somatic mutations in the epidermal growth factor receptor (EGFR) gene are crucial for targeted therapy in lung adenocarcinomas.
• EGFR mutations, including E19del and L858R, predict sensitivity to tyrosine kinase inhibitors.
• Accurate and rapid detection of EGFR mutation status is essential for effective patient treatment.

Purpose of the Study:

• To investigate the potential of Raman spectroscopy (RS) for predicting EGFR mutation status in lung adenocarcinoma tissues.
• To identify specific molecular signatures associated with wild-type (wt)-EGFR, L858R, and E19del mutations using RS.
• To develop a rapid, low-cost method for EGFR mutation prediction.

Main Methods:

• DNA sequencing was used to determine EGFR mutation status in 153 lung adenocarcinoma tissues.
• Selected samples (wt-EGFR, L858R, E19del) underwent Raman spectroscopy and immunohistochemistry (IHC) analysis.
• Principal Component Analysis (PCA) and Support Vector Machine (SVM) algorithms were applied to Raman spectra for classification.

Main Results:

• Distinct Raman spectral features were observed for wt-EGFR, L858R, and E19del mutations.
• Specific Raman peaks at 675, 1107, 1127, and 1582 cm⁻¹ were increased in wt-EGFR tissues.
• Raman peaks at 1085, 1175, and 1632 cm⁻¹ (arginine-related) were slightly increased in L858R tissues.
• The PCA/SVM algorithm achieved 87.8% accuracy in differentiating L858R/E19del from wt-EGFR tissues.

Conclusions:

• Raman spectroscopy provides a simple, rapid, and low-cost method for predicting EGFR mutation status in lung adenocarcinoma.
• Molecular signatures identified by RS can serve as a basis for a novel diagnostic approach.
• This technique has the potential to aid in the clinical management of lung cancer patients.