Non-invasive Detection of Breast Cancer by Breath Analysis

The goal of this prospective observational study is to compare the exhaled breath profiles of patient with invasive breast cancer and control subjects in the perspective of a diagnostic application in oncology.

The main question it aims to answer is whether the exhaled breath profile of breast cancer patients can be discriminate from the exhaled breath of control subjects.

Participants to the study are recruited in a first discovery series including about 500 subjects and in a following independent validation series including more than 400 subjects. Breath samples are collected in a dedicated room using sampling bags and following anti-Covid-19 measures. Only authorized personnel could access the sampling room which was equipped with a HEPA Filter air purification system. Sampling bags are made of Nalophan® tubular foil and 2 taps, one in which the study participant inflated with their breath and sealed after use, while the second is used to introduce breath samples into the analyzer. Bags are sterilized with the Sterrad™ system with H2O2 vapors before use. To contain the potentially infectious particulate included in the participant exhaled breath, an electrostatic filter is mounted on the tap of the bag used to inflate it with breath. All participants are supplied with a leaflet explaining aims and technical/clinical information of the study. At each breath sampling, study participants are asked not to smoke, eat, drink (except for water), brush their teeth or use lipstick for at least 2 h before breath collection to minimize the presence of contaminant molecules in exhaled breath.

Breath profiling is performed by mass spectrometry analysis using an untargeted approach. Breath samples are profiled by Secondary Electrospray ionization - High resolution Mass Spectrometry (SESI-HR-MS) using a high resolution instrumentation (LTQ Orbitrap Elite,Thermo Fisher Scientific) equipped with a SuperSESI ionization source (Fossiliontech).

Data analysis is based on our previous work (Martínez-Lozano el al., 2015 J Breath Res 9:031001) and will be implemented with machine learning and other Artificial Intelligence (AI) methods.

Once all the breath profiles will be collected and analysed, researchers will compare data from patient with breast cancer and data from tumor-free subjects to identify methods and patterns able to specifically identify the pathological breath samples and discriminate them from the control breath samples.