Learn More
UNLABELLED 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(More)
UNLABELLED We report on a new concept for profiling genetic mutations of (lung) cancer cells, based on the detection of patterns of volatile organic compounds (VOCs) emitted from cell membranes, using an array of nanomaterial-based sensors. In this in-vitro pilot study we have derived a volatile fingerprint assay for representative genetic mutations in(More)
A highly sensitive and fast-response array of sensors based on gold nanoparticles, in combination with pattern recognition methods, can distinguish between the odor prints of non-small-cell lung cancer and negative controls with 100% accuracy, with no need for preconcentration techniques. Additionally, preliminary results indicate that the same array of(More)
BACKGROUND Volatile organic compounds (VOCs) are potential biomarkers for cancer detection in breath, but it is unclear if they reflect specific mutations. To test this, we have compared human bronchial epithelial cell (HBEC) cell lines carrying the KRAS(V12) mutation, knockdown of TP53 or both with parental HBEC cells. METHODS VOC from headspace above(More)
Mapping molecular sub-types in breast cancer (BC) tumours is a rapidly evolving area due to growing interest in, for example, targeted therapy and screening high-risk populations for early diagnosis. We report a new concept for profiling BC molecular sub-types based on volatile organic compounds (VOCs). For this purpose, breath samples were collected from(More)
  • 1