Smellprints in lung Cancer; the role of ENose in diagnosis and Treatment (SCENT):
part 3. Acute effects on smellprints of chemotherapy in patients with lung cancer.

Lung cancer is one of the leading causes of cancer related death worldwide.
This disease 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). Most patients with NSCLC present with advanced, often incurable,
disease (stages IIIA, IIIB and IV) at the time of diagnosis. For these patients
as well as for patients with SCLC the standard treatment is chemotherapy, with
or without radiotherapy. The response on chemotherapy, however, varies between
individual patients. Therefore, the challenges for optimal treatment in these
patients lay in the possibility of predicting chemotherapy response in the
individual patient, developing customized chemotherapeutic combinations and
limiting severe side effects.
During the last few years the analysis of exhaled breath has been proposed as a
novel option for detection and management of lung cancer. Exhaled breath
contains a complex mixture of several hundreds of volatile organic compounds
(VOCs). Many VOCs, principally alkanes and benzene derivates, have been
identified in breath from patients with lung cancer and changes in individual
VOCs have been observed after surgical removal of the tumour, suggesting that
VOCs in exhaled breath might reflect tumour activity,
After the introduction of electronic noses, the sampling of exhaled breath and
its VOC-pattern has become readily available, due to their ability to allow
on-board analysis and discrimination of *smellprints* by composite nano-sensors
arrays (*breatheomics*). This is based on pattern recognition without analyzing
the individual molecular components. The first studies using eNose technology
in detecting lung cancer have demonstrated promising diagnostic accuracy and
the intriguing possibility of an easily available panel of biomarkers
(smellprint) reflecting tumour activity, emphasize the importance of
prospective studies focussing on the value of electronic noses not only for
diagnostic but also for predictive or follow up purposes.
Therefore in the present study, we hypothesize that chemotherapy-induced
changes in exhaled metabolites in lung cancer can be detected by changes in VOC
profiles (smell-prints) measured by the eNose.

1 The primary objective is to investigate whether the eNose can discriminate
the smellprints obtained before and after 1 cycle of chemotherapy in patients
with specific histological types of lung cancer (NSCLC: adenocarcinoma,
squamous cell carcinoma and SCLC)

2 The secondary objectives are:
a) To investigate whether the eNose can discriminate between the baseline
smellprints of patients with different histological types of lung cancer
(NSCLC: adenocarcinoma, squamous cell carcinoma and SCLC)
b) To investigate whether the pre-chemotherapy smellprint is related to:
i. the stage of the disease according to the stage grouping of the Mountain
classification (NSCLC) [21] or division into LD or ED (SCLC) [2].
ii. metabolic activity of the disease as assessed by Standard Uptake Value
(SUV) on PET-CT scan.
c) To investigate whether the potential change in smellprint after 1 cycle of
chemotherapy is related to tumour response (determined after the second cycle
of chemotherapy) according to the RECIST criteria.

prospective, observational study

first cycle of chemotherapy for lung cancer. Patients were already scheduled
for this treatment after staging work-up.
NSCLC: cisplatin/gemcitabin
SCLC: cisplatin/etoposide

All patients will visit the pulmonary function department 3 times. At each
visit 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 per visit will not exceed
20 min.

these lung cancer groups are chosen, because they are the most common subtypes
and at this moment prediction who will benefit most by chemotherapy
(individual-level) is not possible. We might learn in a non invasive manner
more about tailoring therapy.