Detection of aberrant locomotor activity in a mouse model of lung cancer via home cage monitoring.

Introduction: Lung cancer is the first cause of cancer death in the world, due to a delayed diagnosis and the absence of efficacy therapies. KRAS mutation occurs in 25% of all lung cancers and the concomitant mutations in LKB1 determine aggressive subtypes of these tumors. The improvement of therapeutical options for KRASG12C mutations has increased the possibility of treating these tumors, but resistance to these therapies has emerged. Preclinical animal models permit the study of tumors and the development of new therapies. The DVC system was used to measure circadian activity changes indicative of lung cancer progression in KRAS and KRAS-LKB1 transgenic mouse models. Material and methods: KRAS and KRAS-LKB1 conditional transgenic animal models were bred and genotyped. The tumors were inducted using adeno-CRE-recombinase system. The mice were housed in a Digital Ventilated Cage (DVC Results: KRAS and KRAS-LKB1 mutations were induced, and the tumor formation and progression were monitored over time. As expected, the onset of the tumors in the two different breeds occurred at different times. DVC system registered the locomotion activity of the mice during the light and dark phases, reporting a strong reduction, mainly, in the dark phase. In KRAS-LKB1 models, the locomotion reduction appeared more pronounced than in KRAS models. Discussions: Transgenic animal models represent a fundamental tool to study the biology of cancers and the development of new therapies. The tumors induced in these models harbor the same genotypical and phenotypical characteristics as their human counterparts. DVC methods permit a home cage monitoring system useful for tracking animal behavior continuously 24 hours a day, 7 days a week. DVC system could determine disease progression by monitoring a single animal activity in a cage and also using group-housed animals. For these reasons, the DVC system could play a crucial role in identifying diseases at early stages and in testing new therapeutic approaches with a higher likelihood of efficacy.