Background Lung cancer is the most common oncological cause of death in the Western world. Early diagnosis is critical for successful treatment. However, no effective screening methods exist. A promising approach could be the use of volatile organic compounds as diagnostic biomarkers. To date there are several studies, in which dogs were trained to discriminate cancer samples from controls. In this study we evaluated the abilities of specifically trained dogs to distinguish samples derived from lung cancer patients of various tumor stages from matched healthy controls. Methods This single center, double-blind clinical trial was approved by the local ethics committee, project no FF20/2016. The dog was conditioned with urine and breath samples of 36 cancer patients and 150 controls; afterwards, further 246 patients were included: 41 lung cancer patients comprising all stages and 205 healthy controls. From each patient two breath and urine samples were collected and shock frozen. Only samples from new subjects were presented to the dog during study phase randomized, double-blinded. This resulted in a specific conditioned reaction pointing to the cancer sample. Results Using a combination of urine and breath samples, the dog correctly predicted 40 out of 41 cancer samples, corresponding to an overall detection rate of cancer samples of 97.6% (95% CI [87.1, 99.9%]). Using urine samples only the dog achieved a detection rate of 87.8% (95% CI [73.8, 95.9%]). With breath samples, the dog correctly identified cancer in 32 of 41 samples, resulting in a detection rate of 78% (95% CI [62.4, 89.4%]). Conclusions It is known from current literature that breath and urine samples carry VOCs pointing to cancer growth. We conclude that olfactory detection of lung cancer by specifically trained dogs is highly suggestive to be a simple and non-invasive tool to detect lung cancer. To translate this approach into practice further target compounds need to be identified.

e13067 Background: Lung cancer is the leading oncological cause of death in western countries. The WHO estimated 2.09 million newly diagnosed lung cancer patients in 2018 worldwide. Although early detection is crucial for patients outcome, no surveillance tools exist. Dogs have a highly sensitive olfactory system which is already used in several ways, such as drug and ketone detection. The aim of the study was to evaluate the capability of a classically conditioned domestic dog to accurately distinguish samples of lung cancer patients of all tumor stages in urine and breath from healthy controls. Methods: This monocentric clinical trial was an original study and approved by the local ethics committee. After conditioning a domestic dog with samples of 186 patients (36 cancer patients and 150 control patients), further 246 patients aged between 45 and 80 entered into the study: 41 patients with a histologically proven lung cancer comprising all different stages and 205 control samples of healthy individuals with no cancer history. Two urine and two breath samples were collected of each patient and immediately shock frozen at -80°C. Urine and breath samples were separately exposed to the dog in a randomized, double-blinded manner, resulting in a specific conditioned reaction indicating the cancer sample. Results: The dog correctly predicted cancer in 36 of 41 urine samples, corresponding to a sensitivity of 87.8% and a specificity of 97.6%. Concerning the breath samples, the dog correctly predicted cancer in 32 of 41 samples, corresponding to a sensitivity of 78% and a specificity of 95.6%. Combining both techniques, the dog correctly identified 40 of 41 cancer samples, leading to an overall sensitivity of 97.6%. The specificity is not evaluable. Conclusions: Urine and breath carry volatile organic compounds indicating cancer growth, as previously reported. Canine olfactory detection of lung cancer is a simple tool to detect lung cancer non-invasively. Further identification of target compounds for technical translation of this approach is under way, with the potential for the development of a bionic electronic nose.