The Lipid Phenotype of Breast Cancer Cells Characterized by Raman Microspectroscopy: Towards a Stratification of Malignancy

Although molecular classification brings interesting insights into breast cancer taxonomy, its implementation in daily clinical care is questionable because of its expense and the information supplied in a single sample allocation is not sufficiently reliable. New approaches, based on a panel of small molecules derived from the global or targeted analysis of metabolic profiles of cells, have found a correlation between activation of de novo lipogenesis and poorer prognosis and shorter disease-free survival for many tumors. We hypothesized that the lipid content of breast cancer cells might be a useful indirect measure of a variety of functions coupled to breast cancer progression. Raman microspectroscopy was used to characterize metabolism of breast cancer cells with different degrees of malignancy. Raman spectra from MDA-MB-435, MDA-MB-468, MDA-MB-231, SKBR3, MCF7 and MCF10A cells were acquired with an InVia Raman microscope (Renishaw) with a backscattered configuration. We used Principal Component Analysis and Partial Least Squares Discriminant Analyses to assess the different profiling of the lipid composition of breast cancer cells. Characteristic bands related to lipid content were found at 3014, 2935, 2890 and 2845 cm 21, and related to lipid and protein content at 2940 cm(-1). A classificatory model was generated which segregated metastatic cells and non-metastatic cells without basal-like phenotype with a sensitivity of 90% and a specificity of 82.1%. Moreover, expression of SREBP-1c and ABCA1 genes validated the assignation of the lipid phenotype of breast cancer cells. Indeed, changes in fatty acid unsaturation were related with the epithelial-to-mesenchymal transition phenotype. Raman microspectroscopy is a promising technique for characterizing and classifying the malignant phenotype of breast cancer cells on the basis of their lipid profiling. The algorithm for the discrimination of metastatic ability is a first step towards stratifying breast cancer cells using this rapid and reagent-free tool

Unraveling the metabolic progression of breast cancer cells to bone metastasis by coupling Raman spectroscopy and a novel use of MCR-ALS algorithm

Raman spectroscopy (RS) has shown promise as a tool to reveal biochemical changes that occur in cancer processes at the cellular level. However, when analyzing clinical samples, RS requires improvements to be able to resolve biological components from the spectra. We compared the strengths of Multivariate Curve Resolution (MCR) versus Principal Component Analysis (PCA) to deconvolve meaningful biological components formed by distinct mixtures of biological molecules from a set of mixed spectra. We exploited the flexibility of the MCR algorithm to easily accommodate different initial estimates and constraints. We demonstrate the ability of MCR to resolve undesired background signals from the RS that can be subtracted to obtain clearer cancer cell spectra. We used two triple negative breast cancer cell lines, MDA-MB 231 and MDA-MB 435, to illustrate the insights obtained by RS that infer the metabolic changes required for metastasis progression. Our results show that increased levels of amino acids and lower levels of mitochondrial signals are attributes of bone metastatic cells, whereas lung metastasis tropism is characterized by high lipid and mitochondria levels. Therefore, we propose a method based on the MCR algorithm to achieve unique biochemical insights into the molecular progression of cancer cells using RS

GRP94 Is Involved in the Lipid Phenotype of Brain Metastatic Cells

Metabolic adaptation may happen in response to the pressure exerted by the microenvironment and is a key step in survival of metastatic cells. Brain metastasis occurs as a consequence of the systemic dissemination of tumor cells, a fact that correlates with poor prognosis and high morbidity due to the difficulty in identifying biomarkers that allow a more targeted therapy. Previously, we performed transcriptomic analysis of human breast cancer patient samples and evaluated the differential expression of genes in brain metastasis (BrM) compared to lung, bone and liver metastasis. Our network approach identified upregulation of glucose-regulated protein 94 (GRP94) as well as proteins related to synthesis of fatty acids (FA) in BrM. Here we report that BrM cells show an increase in FA content and decreased saturation with regard to parental cells measured by Raman spectroscopy that differentiate BrM from other metastases. Moreover, BrM cells exerted a high ability to oxidize FA and compensate hypoglycemic stress due to an overexpression of proteins involved in FA synthesis and degradation (SREBP-1, LXR alpha, ACOT7). GRP94 ablation restored glucose dependence, down-regulated ACOT7 and SREBP-1 and decreased tumorigenicity in vivo. In conclusion, GRP94 is required for the metabolic stress survival of BrM cells, and it might act as a modulator of lipid metabolism to favor BrM progression

Aislamiento y caracterización funcional de dos factores de transcripción bZIP de maíz

La fitohormona Acido Abscisico (ABA) es una reguladora de procesos importantes como son el desarrollo de la semilla, dormancia y posterior germinación y también interviene en la respuesta adaptativa de tejidos vegetativos frente a estreses ambientales de sequía, salinidad y frío. Muchos de los efectos del ABA están mediados por cambios en la expresión génica principalmente a nivel de transcripción. Entre estos genes se encuentran los denominados lea (late embryogenesis abundant), como el rab28. Este gen contiene en su promotor 2 elementos ABRE (ABA responsive element) necesarios para su inducción durante la embriogénesis y en respuesta al ABA. Estudios de footprinting in vivo han mostrado que a estos elementos se unen factores de la familia bZIP. En este trabajo presentamos el aislamiento y la caracterización de dos factores de transcripción de la familia de las bZIP, denominados EmBP-2 y ZmBZ. Se ha analizado la expresión de los factores a nivel de mRNA y de proteína, su interacción in vitro con los elementos ABRE del gen rab28, su actividad in vivo sobre la expresión del gen rab28 en tejidos embrionarios y vegetativos y los mecanismos que pueden modificar su actividad, como el estado de fosforilación y su localización subcelular. Nuestros resultados apuntan a que estos factores tienen un papel regulador de la expresión del gen rab28 a través del elemento ABRE

The Lipid Phenotype of Breast Cancer Cells Characterized by Raman Microspectroscopy: Towards a Stratification of Malignancy

Although molecular classification brings interesting insights into breast cancer taxonomy, its implementation in daily clinical care is questionable because of its expense and the information supplied in a single sample allocation is not sufficiently reliable. New approaches, based on a panel of small molecules derived from the global or targeted analysis of metabolic profiles of cells, have found a correlation between activation of de novo lipogenesis and poorer prognosis and shorter disease-free survival for many tumors. We hypothesized that the lipid content of breast cancer cells might be a useful indirect measure of a variety of functions coupled to breast cancer progression. Raman microspectroscopy was used to characterize metabolism of breast cancer cells with different degrees of malignancy. Raman spectra from MDA-MB-435, MDA-MB-468, MDA-MB-231, SKBR3, MCF7 and MCF10A cells were acquired with an InVia Raman microscope (Renishaw) with a backscattered configuration. We used Principal Component Analysis and Partial Least Squares Discriminant Analyses to assess the different profiling of the lipid composition of breast cancer cells. Characteristic bands related to lipid content were found at 3014, 2935, 2890 and 2845 cm 21, and related to lipid and protein content at 2940 cm(-1). A classificatory model was generated which segregated metastatic cells and non-metastatic cells without basal-like phenotype with a sensitivity of 90% and a specificity of 82.1%. Moreover, expression of SREBP-1c and ABCA1 genes validated the assignation of the lipid phenotype of breast cancer cells. Indeed, changes in fatty acid unsaturation were related with the epithelial-to-mesenchymal transition phenotype. Raman microspectroscopy is a promising technique for characterizing and classifying the malignant phenotype of breast cancer cells on the basis of their lipid profiling. The algorithm for the discrimination of metastatic ability is a first step towards stratifying breast cancer cells using this rapid and reagent-free tool