Preliminary characterization of an experimental breast cancer cells brain metastasis mouse model by MRI/MRS

• Autor(a) principal: Simões, R.
• Data de Publicação: 2008
• Outros Autores: Martinez-Aranda, A., Martín, B., Cerdán, S., Sierra, A., Arús, C.
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
• Texto Completo: http://hdl.handle.net/10316/7816; https://doi.org/10.1007/s10334-008-0114-6

Abstract Purpose Chemotherapy increases survival in breast cancer patients. Consequently, cerebral metastases have recently become a significant clinical problem, with an incidence of 30–40% among breast carcinoma patients. As this phenomenon cannot be studied longitudinally in humans, models which mimic brain metastasis are needed to investigate its pathogenesis. Such models may later be used in experimental therapeutic approaches. Material and methods/results We report a model in which 69% of the animals (9/13 BALB/c nude mice) developed MR-detectable abnormal masses in the brain parenchyma within a 20 to 62-day time window post intra-carotid injection of 435-Br1 human cells. The masses detected in vivo were either single (7 animals) or multiple (2 animals). Longitudinal MR (MRI/MRS) studies and post-mortem histological data were correlated, revealing a total incidence of experimental brain metastases of 85% in the cases studied (11/13 animals). ADC maps perfectly differentiated edema and/or CSF areas from metastasis. Preliminary MRS data also revealed additional features: decrease in N-acetyl aspartate (NAA) was the first MRS-based marker of metastasis growth in the brain (micrometastasis); choline-containing compounds (Cho) rose and creatine (Cr) levels decreased as these lesions evolved, with mobile lipids and lactate also becoming visible. Furthermore, MRS pattern recognition-based analysis suggested that this approach may help to discriminate different growth stages. Conclusions This study paves the way for further in vivo studies oriented towards detection of different tumor progression states and for improving treatment efficiency.