A new paradigm of e-NOSE technology for the non-invasive and early lung cancer diagnostics

• Published in: Chemical engineering journal (Lausanne, Switzerland : 1996) Vol. 512; p. 162155
• Main Authors: Saini, Arzoo, Yadav, Neelam
• Format: Journal Article
• Language: English
• Published: Elsevier B.V 15.05.2025
• Subjects: Biomarkers; Biosensors; Detection methods; e-NOSE; Lung cancer; Machine learning algorithms; Biomarkers; Machine learning algorithms; e-NOSE; Biosensors; Lung cancer; Detection methods
• ISSN: 1385-8947
• DOI: 10.1016/j.cej.2025.162155

Figure: Diagrammatic depiction of the working and principle of e-NOSE devices and their applications in detecting VOC biomarkers specific to lung cancer. [Display omitted] •Lung cancer is one of the leading causes of neoplastic mortality.•Various VOCs act as non-invasive metabolic biomarkers.•e-NOSE devices offer rapid and precise lung cancer diagnostics.•Advanced sensors and machine learning algorithms enhance accuracy and reliability. Lung cancer remains a global burden owing to its complex pathogenicity, involvement of numerous risk factors, and late-stage detection. Early diagnosis is essential for providing effective treatment and improving survival outcomes. However, existing diagnostic techniques exhibit several limitations including invasive procedures, lower sensitivity, specificity, and expensive. Therefore, it necessitates for the development of intricate diagnostic strategies to aid in early and acute detection of lung cancer. With the advancements in the sensing technology and nanotechnology integrated with advanced AI algorithms, electronic nose (e-NOSE) devices have emerged as promising alternatives. These devices are capable of identifying target metabolic fingerprints of volatile organic compounds (VOCs) biomarkers associated with lung cancer. The e-NOSE devices are becoming a remarkable state-of-art diagnostic tools by providing highly sensitive, rapid, and real-time detection of VOC biomarkers for the non-invasive detection of lung cancer. This review article provides a comprehensive overview of lung cancer pathogenicity, e-NOSE technology, including its components, working principles, and applications in the early detection of lung cancer, distinguishing lung cancer from healthy as well as from other disease, and also in discriminating lung cancer stages and subtypes. A critical comparative analysis of the recently developed e-NOSE devices for lung cancer diagnostics is also provided. These studies demonstrate the prospects of e-NOSE system in clinical applications as a potential frontline screening tool. This article also aims to decipher the associated challenges and provide future prospects of e-NOSE technology to become an integral component of next-generation lung cancer diagnostics.