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Oct 19, 2012

Lipid Profiles Predict Breast Cancer Aggressiveness

  • Scientists have developed a method they claim can determine the likely aggressiveness of breast cancer cells based on their lipid components. The approach uses Raman microspectroscopy to characterize the lipid composition of breast cancer cells, and then applies multivariate statistical analyses and a computer algorithm to classify the cells as metastatic or non-metastatic based on their lipid profiles.

    The metabolism of cancer cells relative to non-cancerous cells is altered to support rapid growth and proliferation, and one of the clearest indicators that this is occurring is the ramping up of fatty acid production as the tumor cell increases production of the components needed to build new cell membranes for accelerated cell division, report Spanish investigators at the Institut d'Investigació Biomèdica de Bellvitge, L'Hospitalet de Llobregat (IDIBELL), and the Institut de Ciències Fotòniques (ICFO). In fact, prior work has already correlated the activation of de novo lipogenesis with poorer prognosis and shorter disease-free survival for a number of tumor types.

    The investigators, led by IDIBELL’s Claudia Nieva, M.D., and Angels Sierra, M.D., thus hypothesized that the lipid content of breast cancer cells might be an indirect measure of a variety of functions coupled to breast cancer progression, and developed the Raman spectroscopy-based method to exploit this feature and differentiate between more aggressive and less aggressive cancer cells based on their lipid expression profiles. They claim their initial studies have now shown that when applied to a range of breast cancer cell lines with different degrees of malignancy, their approach differentiated metastatic cells and non-metastatic cells with a sensitivity of 90% and specificity of 82.1%.

    “The combination of multivariate statistical techniques applied to the Raman spectral data (principal component analysis and partial least squares discriminant analyses) provided a powerful quantitative method to discriminate cancer phenotypes,” they report in their published paper in PLoS One. “Moreover, principal component analysis clearly distinguished cells with the epithelial-to-mesenchymal transition (EMT) phenotype, which is widely linked with breast cancer cell aggressiveness…Our results suggest that the lipid phenotype of these cells is a signal of the proclivity to mesenchymal transition related to the high aggressiveness and metastatic spread…The algorithm for the discrimination of the metastatic ability is a first step towards the stratification of breast cancer cells using this quick and reactive tool.” 


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