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

<div><p>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 <em>de novo</em> 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⁻¹, 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.</p> </div

PLS-DA discriminative model using Raman microspectroscopy spectra of non-metastatic (SKBR3 and MCF7) and metastatic (MDA-MB-231 and MDA-MB-435) cell lines.

<p>PLSDA classification algorithm, in which non-metastatic cells are predicted with class 0 and metastatic cells with class 1. A threshold is assigned (red line) corresponding to the best specificity and sensitivity parameters that separate groups of cells. RMSECV is represented by the error bars. A sensitivity of 90% and a specificity of 82.1% were achieved. Once the model was built, MCF10A and MDA-MB-468 were included to predict their membership. Seventy-five per cent of MCF10A and 40% of MDA-MB-468 cells are related to the metastatic group.</p

Variability in lipid metabolic genes expression and FA composition in MDA-MB-231, MDA-MB-435, MDA-MB-468, MCF7 and SKBR3 cell lines analysed by Raman microspectroscopy.

<p>A) The gene expression of SREBP-1c and ABCA1 were examined after 24 h treatment with the LXR agonist T0901317 2 µM compared to the basal conditions by RT and real-time PCR. The fold induction is represented over the pointed line. Cyclophilin A gene was used for normalization. B) Simplistic representation of the progression status of breast cancer cells used in the study: 1) MCF10A cells; 2) MCF7, SKBR3 and MDA-MB-468 and 3) MDA-MB-231 and MDA-MB-345. C) Above, brightfield image of MDA-MB-435 cells, with an asterisk indicating the position of the measurements in the cytoplasm. 60× magnification and 9 mW power were used. Down, fluorescence microscopy image of MDA-MB-435 cells stained with Nile red. 40× magnification was used. D) Measured raw Raman spectra of the cell lines where the axes are intensity (in arbitrary units) versus Raman shift (cm⁻¹). MCF10A cells were also measured. The TFA (2845 cm⁻¹) and TUFA (3015 cm⁻¹) bands are indicated with the arrows in the first spectra.</p

Raman microspectroscopy and PCA differentiate the MCF10A cells grown in confluent and sparse conditions.

<p>A) MCF10A microscopy images of the cells measured by RS in confluent and sparse conditions. Brightlight images were obtained with an inverted microscope and 10× magnification. Arrows indicate the different areas that were measured by Raman (a: confluent; b: separate cells grown at the edge of confluent cultures; c: sparse). B) PCA representation of MDA-MB-435 cells and MCF10A cells (grown in high confluence and in sparse conditions). PC 1 and 2 separate different groups of cell lines. MDA-MB-435 cells have higher PC2 scores, separated from the MCF10A. MCF10A grown in high confluence are displaced from the ones grown in sparse conditions showing higher PC1 scores. Asterisk indicates the localization of the “lipogenic phenotype” in the axis. PC1 and PC2 loadings are described down with the bands related to TFA (arrow head) and TUFA (arrow) indicated. The percentage means the variance accounted for each PC. C) Immunofluorescence images of E-cadherin and vimentin proteins in both MCF10A culture conditions. DAPI staining appears minimized inside each picture.</p

PCA scores showing the cell variability present inside each cell line and between the different cell lines.

<p>Illustration of PCA scores from MCF10A, MDA-MB-231, MDA-MB-435, MDA-MB-468, MCF7 and SKBR3 cell lines RS acquisition. SKBR3 cells are shown in the green circle and MCF7 cells in the blue circle. MDA-MB-435 and MCF10A cells are the most dispersed in the plot. On the right, the loading plots for each Principal Component, both related to fatty acid and protein content (TUFA: 3014 cm⁻¹; protein and lipid: 2940 cm⁻¹; TFA: 2871, 2890, 2846 and 2848 cm⁻¹; -CH3: 2935 cm⁻¹). Percentages in the score plots represent the variance accounted for each PC.</p

Epithelial and EMT marker gene expression in MCF7, SKBR3, MDA-MB-231, MDA-MB-468, MDA-MB-435 and MCF10A cells.

<p>A) The gene expression of epithelial cell markers (E-cadherin, cytokeratin 18) and the mesenchymal cell marker vimentin were examined by RT and real-time PCR using 200 ng of RNA. E-cadherin and CK18 are represented compared to the luminal MCF7 cell line expression and vimentin is represented compared to the MDA-MB-231 cell line. Cyclophilin A gene was used to normalize gene expression. B) Immunofluorescence staining of the epithelial E-cadherin and the mesenchymal vimentin markers in MCF7, MDA-MB-468, MCF10A, SKBR3, MDA-MB-231 and MDA-MB-435 cells. DAPI staining appears minimized in each picture. 40× magnification was used.</p

Towards Optimization of Arylamides As Novel, Potent, and Brain-Penetrant Antiprion Lead Compounds

The prion diseases caused by PrP^Sc, an alternatively folded form of the cellular prion protein (PrP^C), are rapidly progressive, fatal, and untreatable neurodegenerative disorders. We employed HTS ELISA assays to identify compounds that lower the level of PrP^Sc in prion-infected mouse neuroblastoma (ScN2a-cl3) cells and identified a series of arylamides. Structure–activity relationship (SAR) studies indicated that small amides with one aromatic or heteroaromatic ring on each side of the amide bond are of modest potency. Of note, benzamide (<b>7</b>), with an EC₅₀ of 2200 nM, was one of only a few arylamide hits with a piperazine group on its aniline moiety. The basic piperazine nitrogen can be protonated at physiologic pH, improving solubility, and therefore, we wanted to exploit this feature in our search for a drug candidate. An SAR campaign resulted in several key analogues, including a set with biaryl groups introduced on the carbonyl side for improved potency. Several of these biaryl analogues have submicromolar potency, with the most potent analogue <b>17</b> having an EC₅₀ = 22 nM. More importantly, <b>17</b> and several biarylamides (<b>20</b>, <b>24</b>, <b>26</b>, and <b>27</b>) were able to traverse the blood–brain barrier (BBB) and displayed excellent drug levels in the brains of mice following oral dosing. These biarylamides may represent good starting points for further lead optimization for the identification of potential drug candidates for the treatment of prion diseases

Discovery and Preliminary Structure–Activity Relationship of Arylpiperazines as Novel, Brain-Penetrant Antiprion Compounds

Creutzfeldt-Jakob disease and kuru in humans, BSE in cattle, and scrapie in sheep are fatal neurodegenerative disorders. Such illnesses are caused by the conversion and accumulation of a misfolded pathogenic isoform (termed PrP^Sc) of a normally benign, host cellular protein, denoted PrP^C. We employed high-throughput screening enzyme-linked immunosorbent assays to evaluate compounds for their ability to reduce the level of PrP^Sc in Rocky Mountain Laboratory prion-infected mouse neuroblastoma cells (ScN2a-cl3). Arylpiperazines were among the active compounds identified, but the initial hits suffered from low potency and poor drug-likeness. The best of those hits, such as <b>1</b>, <b>7</b>, <b>13</b>, and <b>19</b>, displayed moderate antiprion activity with EC₅₀ values in the micromolar range. Key analogues were designed and synthesized on the basis of the structure–activity relationship, with analogues <b>41</b>, <b>44</b>, <b>46</b>, and <b>47</b> found to have submicromolar potency. Analogues <b>41</b> and <b>44</b> were able to penetrate the blood–brain barrier and achieved excellent drug concentrations in the brains of mice after oral dosing. These compounds represent good starting points for further lead optimization in our pursuit of potential drug candidates for the treatment of prion diseases