Classification of the Lung Cancer Histology by Gold Nanoparticle Sensors
Cette étude présente un dispositif à base de nanoparticules d'or pour la détection non invasive d'un cancer du poumon et l'identification du sous-type de cancer
We propose a non-invasive nanomedical device for the classification of lung cancer (LC) histology. The device profiles volatile organic compounds (VOCs) in the headspace of (sub-types of) LC cells, using gold nanoparticle (GNP) sensors that are suitable for detecting LC specific patterns of VOC profiles, as determined by gas chromatography/mass spectrometry analysis. Analyzing the GNP sensing signals by support vector machine analysis allowed significant discrimination between: (i) LC and healthy states; (ii) small cell LC (SCLC) and non-small cell LC (NSCLC); and between (iii) two sub-types of NSCLC: adenocarcinoma and squamous cell carcinomas. The discriminative power of the GNP sensors was then linked with the chemical nature and composition of the headspace VOCs of each LC state. These proof-of-concept findings could totally revolutionize LC screening and diagnosis and might eventually allow early, non-invasive differential diagnosis of LC sub-types with undetectable or unreachable lung nodules.
Nanomedicine : nanotechnology, biology, and medicine , résumé, 2010