Smellprints in lung Cancer; the role of ENose in diagnosis and Treatment (SCENT):
part 2. Identification of patients with lung cancer and breast cancer.

Lung and breast cancer are leading causes of cancer-related death. Early
detection of lung cancer is considered crucial to decrease mortality, and in
particular non-invasive diagnostic strategies aimed at identifying biomarkers
of lung cancer are of great interest. Lung cancer is clinically divided into
two sub-types, small cell lung cancer, (SCLC; 10-15% of lung cancer cases), and
non-small cell lung cancer (NSCLC (subdivided into mainly adenocarcinoma and
squamous cell carcinoma); 85-90% of cases). It has been shown that distinct
biochemical markers have been found in the exhaled breath of patients with lung
and breast cancer that could be discriminated from those of controls,
suggesting that VOC analysis might be used as a non invasive marker of these
cancers. The electronic noses based on pattern recognition without analyzing
the individual molecular components might be sufficient for diagnostic
objectives. In the present study we will use the results obtained in the SCENT
study part 1 (*differences in smellprints between patients with non small cell
lung cancer and breast cancer*). In that study the electronic nose will be
trained to develop the algorithm to discriminate patients with confirmed
diagnoses of non small cell lung cancer or breast cancer from controls. On the
condition that such a discriminating algorithm can be deduced from the results
of part 1, in this study (part 2 of the SCENT study) we will test the
hypothesis that smellprints can identify and classify newly presented patients
prospectively into the categories of non small cell lung cancer (NSCLC) and
breast cancer

1. To determine the diagnostic accuracy of the electronic nose in the
identification of lung cancer in new (referred for suspicion of lung cancer)
patients based on the algorithm developed in the SCENT study part 1
(training-set).
2. To determine the diagnostic accuracy of the electronic nose in the
identification of breast cancer in new (referred for suspicion of breast
cancer) patients based on the algorithm developed in the SCENT study part 1
(training-set).

diagnostical study.

All persons, patients and controls, will visit the pulmonary function
department once. They first will complete a questionnaire obtaining information
about medical history, smoking history en actual medical condition. Then
exhaled breath collection will take place after 5 min tidal breathing VOC
filtered room air. Finally spirometry will be performed. Total time will not
exceed 20 min.

Both groups (breast cancer and lung cancer) are chosen, because they are
leading causes of death and both have much better perspectives when diagnosed
at early stage. eNose technology might be of great value in the screening and
monitoring of these two cancers.