Related Experiment Video
Updated: Jun 17, 2025
07:59
Author Spotlight: Advancements in Molecular Biomarker Testing for Non-Squamous Non-Small Cell Lung Cancer
Published on: September 8, 2023
1.0K
Non-invasive diagnostic test for lung cancer using biospectroscopy and variable selection techniques in saliva
Camilo L M Morais1,2, Kássio M G Lima1, Andrew W Dickinson3
1Biological Chemistry and Chemometrics, Institute of Chemistry, Federal University of Rio Grande do Norte, Natal 59072-970, Brazil.
The Analyst
|August 6, 2024
Summary
A new saliva test using attenuated total reflection Fourier-transform infrared (ATR-FTIR) spectroscopy accurately detects lung cancer. This non-invasive biospectroscopy method shows high sensitivity and specificity for early lung cancer diagnosis.
Area of Science:
- Biochemistry
- Medical Diagnostics
- Spectroscopy
Background:
- Lung cancer is a leading cause of cancer mortality worldwide.
- Current diagnostic methods like CT scans and bronchoscopy have limitations for early, non-invasive detection.
- There is a critical need for rapid, precise, and reliable early detection methods for lung cancer.
Purpose of the Study:
- To develop and validate a novel non-invasive method for early lung cancer detection using saliva analysis.
- To assess the efficacy of attenuated total reflection Fourier-transform infrared (ATR-FTIR) spectroscopy combined with chemometric analysis for discriminating lung cancer patients from controls.
- To identify specific spectral biomarkers indicative of lung cancer in saliva.
Main Methods:
- Saliva samples from 1944 participants (56 lung cancer positive, 1888 controls) were collected.
- Attenuated total reflection Fourier-transform infrared (ATR-FTIR) spectroscopy was employed for sample analysis.
- Principal component analysis-quadratic discriminant analysis (PCA-QDA) and successive projections algorithm (SPA) with genetic algorithm (GA) were used for feature selection and classification.
Main Results:
- The developed GA-QDA model achieved 100.0% sensitivity and 99.1% specificity on the test set.
- Three specific wavenumbers (1422 cm⁻¹, 1546 cm⁻¹, 1578 cm⁻¹) were identified as key discriminators between lung cancer and control samples.
- These wavenumbers correspond to biochemical signatures such as C-C stretching, adenine, Amide II, and carboxylate groups.
Conclusions:
- Biospectroscopy coupled with multivariate classification algorithms offers a promising approach for non-invasive lung cancer detection.
- The saliva-based ATR-FTIR spectroscopy method demonstrates high accuracy in discriminating between lung cancer and benign conditions.
- This technique holds potential for early lung cancer screening, complementing existing diagnostic tools.
