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Sniffing Out Lung Cancer: Biomimetic Breath Analysis via a Deep Eutectic Solvent-Driven Colorimetric Sensor Array.
Shiva Pesaran1, Zahra Shojaeifard1, Javad Tashkhourian1
1Chemistry Department, Shiraz University, Shiraz 71454, Iran.
Analytical Chemistry
|December 8, 2025
Summary
A new paper-based sensor array detects lung cancer biomarkers in breath using deep eutectic solvents. This noninvasive tool shows high accuracy in identifying cancer patients, offering a promising screening method.
Area of Science:
- Analytical Chemistry
- Biomedical Engineering
- Environmental Science
Background:
- Lung cancer is a leading cause of death globally, with diagnosis often delayed due to a lack of noninvasive early detection methods.
- Current diagnostic tools for lung cancer can be invasive, costly, or lack accessibility, hindering early intervention and patient outcomes.
Purpose of the Study:
- To develop and validate a novel, cost-effective, and noninvasive paper-based sensor array for detecting lung cancer-specific volatile organic compounds (VOCs) in exhaled breath.
- To assess the sensor array's accuracy in distinguishing lung cancer patients from healthy individuals and those with other respiratory diseases.
Main Methods:
- A paper-based colorimetric sensor array utilizing deep eutectic solvents (DES) and pH indicators was designed to capture and detect lung cancer VOCs.
- Breath samples from 91 participants (lung cancer patients, noncancer respiratory disease patients, and healthy controls) were analyzed using a portable collection system.
- Statistical analyses, including linear discriminant analysis (LDA), hierarchical cluster analysis (HCA), and ROC curves, were employed to evaluate sensor performance.
Main Results:
- The sensor array achieved 93% accuracy in discriminating lung cancer patients from noncancerous individuals, with 98% sensitivity and specificity.
- The system demonstrated 87% accuracy in differentiating lung cancer from other respiratory conditions, addressing a significant clinical need.
- The use of hydrophobic DES enhanced sensor stability and selectivity by minimizing moisture interference and amplifying VOC interactions.
Conclusions:
- The developed paper-based sensor array presents a highly accurate, rapid, and noninvasive method for early lung cancer detection through breath analysis.
- This cost-effective technology holds significant potential for widespread application in large-scale lung cancer screening programs.
- The sensor array offers a transformative alternative to conventional diagnostic approaches, potentially improving patient survival rates through earlier diagnosis.
