24 research outputs found
Unravelling 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.Peer ReviewedPostprint (author's final draft
Identification of individual exosome-like vesicles by surface enhanced Raman spectroscopy
Exosome-like vesicles (ELVs) are a novel class of biomarkers that are receiving a lot of attention for the detection of cancer at an early stage. In this study the feasibility of using a surface enhanced Raman spectroscopy (SERS) based method to distinguish between ELVs derived from different cellular origins is evaluated. A gold nanoparticle based shell is deposited on the surface of ELVs derived from cancerous and healthy cells, which enhances the Raman signal while maintaining a colloidal suspension of individual vesicles. This nanocoating allows the recording of SERS spectra from single vesicles. By using partial least squares discriminant analysis on the obtained spectra, vesicles from different origin can be distinguished, even when present in the same mixture. This proof-of-concept study paves the way for noninvasive (cancer) diagnostic tools based on exosomal SERS fingerprinting in combination with multivariate statistical analysis
Unravelling the Encapsulation of DNA and Other Biomolecules in HAp Microcalcifications of Human Breast Cancer Tissues by Raman Imaging
Microcalcifications are detected through mammography screening and, depending on their morphology and distribution (BI-RADS classification), they can be considered one of the first indicators of suspicious cancer lesions. However, the formation of hydroxyapatite (HAp) calcifications and their relationship with malignancy remains unknown. In this work, we report the most detailed three-dimensional biochemical analysis of breast cancer microcalcifications to date, combining 3D Raman spectroscopy imaging and advanced multivariate analysis in order to investigate in depth the molecular composition of HAp calcifications found in 26 breast cancer tissue biopsies. We demonstrate that DNA has been naturally adsorbed and encapsulated inside HAp microcalcifications. Furthermore, we also show the encapsulation of other relevant biomolecules in HAp calcifications, such as lipids, proteins, cytochrome C and polysaccharides. The demonstration of natural DNA biomineralization, particularly in the tumor microenvironment, represents an unprecedented advance in the field, as it can pave the way to understanding the role of HAp in malignant tissues
Validation of a Simple, Rapid, and Cost-Effective Method for Acute Rejection Monitoring in Lung Transplant Recipients
Despite advances in immunosuppression therapy, acute rejection remains the leading cause of graft dysfunction in lung transplant recipients. Donor-derived cell-free DNA is increasingly being considered as a valuable biomarker of acute rejection in several solid organ transplants. We present a technically improved molecular method based on digital PCR that targets the mismatch between the recipient and donor at the HLA-DRB1 locus. Blood samples collected sequentially post-transplantation from a cohort of lung recipients were used to obtain proof-of-principle for the validity of the assay, correlating results with transbronchial biopsies and lung capacity tests. The results revealed an increase in dd-cfDNA during the first 2 weeks after transplantation related to ischemia-reperfusion injury (6.36 ± 5.36%, p < 0.0001). In the absence of complications, donor DNA levels stabilized, while increasing again during acute rejection episodes (7.81 ± 12.7%, p < 0.0001). Respiratory tract infections were also involved in the release of dd-cfDNA (9.14 ± 15.59%, p = 0.0004), with a positive correlation with C-reactive protein levels. Overall, the dd-cfDNA percentages were inversely correlated with the lung function values measured by spirometry. These results confirm the value of dd-cfDNA determination during post-transplant follow-up to monitor acute rejection in lung recipients, achieved using a rapid and inexpensive approach based on the HLA mismatch between donor and recipient
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
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
Fructose derived oligosaccharides prevent lipid membrane destabilization and DNA conformational alterations during vacuum-drying of Lactobacillus delbrueckii subsp. bulgaricus
Dehydration of lactic acid bacteria for technological purposes conducts to multilevel damage of bacterial cells. The goal of this work was to determine at which molecular level fructose-oligosaccharides (FOS) and sucrose protect Lactobacillus delbrueckii subsp. bulgaricus CIDCA 333 during the vacuum-drying process. To achieve this aim, the cultivability and metabolic activity of vacuum-dried bacteria were firstly determined (plate counting and absorbance kinetics). Then, the membrane integrity and fluidity were assessed using propidium iodide and Laurdan probes (general polarization -GP-), respectively. Finally, bacterial structural alterations were determined using high throughput methods (fluorescence confocal microscopy and Raman spectroscopy coupled to Multivariate Curve Resolution analysis -MCR-). The vacuum-drying process directly affected the microorganism's cultivability and membrane integrity. Non-dehydrated cells and sugar protected bacteria (both with FOS or sucrose) presented high GP values typical from the gel state, as well as phospholipids microdomains laterally organized along the cytoplasmic membrane. On the contrary, bacteria dehydrated without protectants presented low GP values and greater water penetration, associated with membrane destabilization. Raman spectroscopy of vacuum-dried cells revealed DNA conformational changes, B-DNA conformations being associated to non-dehydrated or sugar protected bacteria, and A-DNA conformations being higher in bacteria vacuum-dried without protectants. These results support the role of FOS and sucrose as protective compounds, not only acting at the membrane organizational level but also preventing conformational alterations of intracellular structures, like DNA.Fil: Romano, Nelson Gastón. Provincia de Buenos Aires. Gobernación. Comisión de Investigaciones Científicas. Centro de Investigación y Desarrollo en Criotecnología de Alimentos. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Centro de Investigación y Desarrollo en Criotecnología de Alimentos. Universidad Nacional de La Plata. Facultad de Ciencias Exactas. Centro de Investigación y Desarrollo en Criotecnología de Alimentos; ArgentinaFil: Marro, Monica. Instituto de Ciencias Fotónicas
; EspañaFil: Marsal, Maria. Instituto de Ciencias Fotónicas
; EspañaFil: Loza Álvarez, Pablo. Instituto de Ciencias Fotónicas
; EspañaFil: Gomez Zavaglia, Andrea. Provincia de Buenos Aires. Gobernación. Comisión de Investigaciones Científicas. Centro de Investigación y Desarrollo en Criotecnología de Alimentos. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Centro de Investigación y Desarrollo en Criotecnología de Alimentos. Universidad Nacional de La Plata. Facultad de Ciencias Exactas. Centro de Investigación y Desarrollo en Criotecnología de Alimentos; Argentin
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
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<sup>−1</sup>, and related to lipid and protein content at 2940 cm<sup>−1</sup>. 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