Format

Send to

Choose Destination
Nanomedicine. 2012 Jul;8(5):580-9. doi: 10.1016/j.nano.2011.10.001. Epub 2011 Oct 25.

Classification of lung cancer histology by gold nanoparticle sensors.

Author information

1
The Department of Chemical Engineering and Russell Berrie Nanotechnology Institute, Technion-Israel Institute of Technology, Haifa, Israel.

Abstract

We propose a nanomedical device for the classification of lung cancer (LC) histology. The device profiles volatile organic compounds (VOCs) in the headspace of (subtypes 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 allowed significant discrimination between (i) LC and healthy cells; (ii) small cell LC and non-small cell LC; and between (iii) two subtypes of non-small cell LC: adenocarcinoma and squamous cell carcinoma. 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 and differential diagnosis of LC subtypes with detectable or unreachable lung nodules.

FROM THE CLINICAL EDITOR:

In this study, a nanomedical device that profiles volatile organic compounds (VOCs) in lung cancer cells is investigated, using a matrix of gold nanoparticle (GNP) sensors that are suitable for detecting lung cancer (LC) specific patterns of VOC profiles. This device might eventually allow early differential diagnosis of LC subtypes including unreachable lung nodules.

PMID:
22033081
PMCID:
PMC4745892
DOI:
10.1016/j.nano.2011.10.001
[Indexed for MEDLINE]
Free PMC Article

Supplemental Content

Full text links

Icon for Elsevier Science Icon for PubMed Central
Loading ...
Support Center