scholarly journals Detection of Circulating Tumor Cells Using Membrane-Based SERS Platform: A New Diagnostic Approach for ‘Liquid Biopsy’

Nanomaterials ◽  
2019 ◽  
Vol 9 (3) ◽  
pp. 366 ◽  
Author(s):  
Agnieszka Kamińska ◽  
Tomasz Szymborski ◽  
Evelin Witkowska ◽  
Ewa Kijeńska-Gawrońska ◽  
Wojciech Świeszkowski ◽  
...  
Keyword(s):  
Tumor Cells ◽  
Circulating Tumor Cells ◽  
Principal Component ◽  
Cell Types ◽  
Surface Enhanced Raman Spectroscopy ◽  
Statistical Technique ◽  
Diagnostic Efficiency ◽  
Multivariate Statistical ◽  
Multi Stage ◽  
Filtration Enrichment

The detection and monitoring of circulating tumor cells (CTCs) in blood is an important strategy for early cancer evidence, analysis, monitoring of therapeutic response, and optimization of cancer therapy treatments. In this work, tailor-made membranes (MBSP) for surface-enhanced Raman spectroscopy (SERS)-based analysis, which permitted the separation and enrichment of CTCs from blood samples, were developed. A thin layer of SERS-active metals deposited on polymer mat enhanced the Raman signals of CTCs and provided further insight into CTCs molecular and biochemical composition. The SERS spectra of all studied cells—prostate cancer (PC3), cervical carcinoma (HeLa), and leucocytes as an example of healthy (normal) cell—revealed significant differences in both the band positions and/or their relative intensities. The multivariate statistical technique based on principal component analysis (PCA) was applied to identify the most significant differences (marker bands) in SERS data among the analyzed cells and to perform quantitative analysis of SERS data. Based on a developed PCA algorithm, the studied cell types were classified with an accuracy of 95% in 2D PCA to 98% in 3D PCA. These results clearly indicate the diagnostic efficiency for the discrimination between cancer and normal cells. In our approach, we exploited the one-step technology that exceeds most of the multi-stage CTCs analysis methods used and enables simultaneous filtration, enrichment, and identification of the tumor cells from blood specimens.

Exploring competitiveness and wellbeing in Italy by spatial principal component analysis

2021 ◽  
pp. 141-146
Author(s):  
Carlo Cusatelli ◽  
Massimiliano Giacalone ◽  
Eugenia Nissi
Keyword(s):  
Principal Component Analysis ◽  
Principal Component ◽  
Well Being ◽  
Component Analysis ◽  
Measurement Model ◽  
Statistical Technique ◽  
Multivariate Statistical ◽  
Spatial Principal Component Analysis ◽  
Italian Provinces ◽  
Reflective Measurement

Well being is a multidimensional phenomenon, that cannot be measured by a single descriptive indicator and that, it should be represented by multiple dimensions. It requires, to be measured by combination of different dimensions that can be considered together as components of the phenomenon. This combination can be obtained by applying methodologies knows as Composite Indicators (CIs). CIs are largely used to have a comprehensive view on a phenomenon that cannot be captured by a single indicator. Principal Component Analysis (PCA) is one of the most popular multivariate statistical technique used for reducing data with many dimension, and often well being indicators are obtained using PCA. PCA is implicitly based on a reflective measurement model that it non suitable for all types of indicators. Mazziotta and Pareto (2013) in their paper discuss the use and misuse of PCA for measuring well-being. The classical PCA is not suitable for data collected on the territory because it does not take into account the spatial autocorrelation present in the data. The aim of this paper is to propose the use of Spatial Principal Component Analysis for measuring well being in the Italian Provinces.

Behavior of circulating tumor cells detected by EGF tagged SERS nanoparticles in head and neck cancer patients.

2012 ◽  
Vol 30 (15_suppl) ◽  
pp. e21161-e21161 ◽  
Author(s):  
Jonathan Jay Beitler ◽  
Xu Wang ◽  
Ximei Qian ◽  
Hong Wang ◽  
Zhuo Georgia Chen ◽  
...  
Keyword(s):  
Head And Neck ◽  
Tumor Cells ◽  
Circulating Tumor Cells ◽  
Single Channel ◽  
Cell Cancer ◽  
Surface Enhanced Raman Spectroscopy ◽  
Egfr Ligands ◽  
Surface Enhanced ◽  
Surface Enhanced Raman ◽  
The Mean

e21161 Background: Quantification of circulating tumor cells(CTCs) is becoming central to the management of metastatic breast, colorectal and prostate cancers and the potential to improve management of head and neck squamous cell cancer (HNSCC) patients is very high. Our group has published our experience with nanotechnology, highly specific, surface-enhanced Raman spectroscopy(SERS) and Epidermal Growth Factor Receptor(EGFR) ligands to identify 7-720 CTCs/ml in 19 samples from HNSCC patients[1]. Our goal here is to understand the clinical behavior of CTCs in HNSCC for selected patients whom we believe our single channel assay has been accurate. Methods: Our methods for detection of CTCs using EGFR ligands have been previously described[1]. After comparing CTCs in 116 patient samples with and without gross disease, we examined 8 patients with decreasing sequential single channel assays of CTCs and no evidence of disease at last follow-up. Results: For 56 samples from patients with no gross disease, the mean CTC was 94/ml. For 61 samples from patients with gross disease the mean CTC was 193/ml (p=0.002). Among our 4 samples where we had initial disease and a non-zero, no evidence of disease, second sample, the absolute and percentage decrease per month in CTC was 121/ml/month(range 43-160) and 17%/month(range 11-25%). The decrease of 121 CTC/ml/month correlated well with 5 out of 6 other data sets. Conclusions: Targeting of EGFR for detection of CTCs in HNSCC patients appears very promising. Among +EGFR HNSCC patients who appear cured, the average decrease in CTC per ml was 121 per month and 17% per month. To further enhance the sensitivity and specificity of detection of CTCs, we are developing 3 SERS nanoparticles (multiplexed SERS) to target specific and distinct targets on the CTC surface while still maintaining a single tube assay system. 1. Wang, X., et al., Detection of circulating tumor cells in human peripheral blood using surface-enhanced Raman scattering nanoparticles. Cancer Research, 2011. 71(5): p. 1526-32.

scholarly journals Detection and Classification of Multi-Type Cells by Using Confocal Raman Spectroscopy

2021 ◽  
Vol 9 ◽  
Author(s):  
Jing Wen ◽  
Tianchen Tang ◽  
Saima Kanwal ◽  
Yongzheng Lu ◽  
Chunxian Tao ◽  
...  
Keyword(s):  
Raman Spectroscopy ◽  
Raman Spectrum ◽  
Tumor Cells ◽  
Cancer Metastasis ◽  
Cell Types ◽  
Label Free ◽  
Analysis Model ◽  
Multivariate Statistical ◽  
Label Free Detection ◽  
Confocal Raman

Tumor cells circulating in the peripheral blood are the prime cause of cancer metastasis and death, thus the identification and discrimination of these rare cells are crucial in the diagnostic of cancer. As a label-free detection method without invasion, Raman spectroscopy has already been indicated as a promising method for cell identification. This study uses a confocal Raman spectrometer with 532 nm laser excitation to obtain the Raman spectrum of living cells from the kidney, liver, lung, skin, and breast. Multivariate statistical methods are applied to classify the Raman spectra of these cells. The results validate that these cells can be distinguished from each other. Among the models built to predict unknown cell types, the quadratic discriminant analysis model had the highest accuracy. The demonstrated analysis model, based on the Raman spectrum of cells, is propitious and has great potential in the field of biomedical for classifying circulating tumor cells in the future.

Comparison of Methods to Display Principal Component Analysis, Focusing on Biplots and the Selection of Biplot Axes

2016 ◽  
pp. 289-332
Author(s):  
Carla Barbosa ◽  
M. Rui Alves ◽  
Beatriz Oliveira
Keyword(s):  
Principal Component ◽  
Statistical Technique ◽  
Practical Case ◽  
Comparison Of Methods ◽  
Multivariate Statistical ◽  
New Developments ◽  
Model Complex ◽  
Components Analysis ◽  
Almost All ◽  
Selection Of

Principal components analysis (PCA) is probably the most important multivariate statistical technique, being used to model complex problems or just for data mining, in almost all areas of science. Although being well known by researchers and available in most statistical packages, it is often misunderstood and poses problems when applied by inexperienced users. A biplot is a way of concentrating all information related to sample units and variables in a single display, in an attempt to help interpretations and avoid overestimations. This chapter covers the main mathematical aspects of PCA, as well as the form and covariance biplots developed by Gabriel and the predictive and interpolative biplots devised by Gower and coworkers. New developments are also presented, involving techniques to automate the production of biplots, with a controlled output in terms of axes predictivities and interpolative accuracies, supported by the AutoBiplot.PCA function developed in R. A practical case is used for illustrations and discussions.

Determining the metastatic potential of circulating tumor cells.

2012 ◽  
Vol 30 (15_suppl) ◽  
pp. e21051-e21051
Author(s):  
Rhiana Menen ◽  
Emmett Pinney ◽  
Katarina Kolostova ◽  
Vladimir Bobek ◽  
Atsushi Suetsugu ◽  
...  
Keyword(s):  
Chick Embryo ◽  
Tumor Cells ◽  
Circulating Tumor Cells ◽  
Laser Scanning ◽  
Fluorescent Protein ◽  
Fold Increase ◽  
Metastatic Potential ◽  
Cell Types ◽  
Rapid Identification ◽  
Cancer Prognosis

e21051 Background: Knowledge of the metastatic potential of circulating tumor cells would be useful for cancer prognosis and also be a rationale for targeting metastatic CTCs for therapy. Methods: Using immunomagnetic beads, CTCs were rapidly isolated from the circulation of mice orthotopically implanted with human PC-3 prostate cancer cells stably expressing green fluorescent protein (GFP). The PC-3–GFP CTCs were then expanded in culture in parallel with the parental PC-3–GFP cell line. Both cell types were then inoculated onto the chorioallentoic membrane (CAM) of chick embryos. Eight days later, embryos were harvested and the brains were processed for frozen sections. The IV-100 intravital laser scanning microscope enabled rapid identification of fluorescent metastatic foci within the chick embryonic brain. Results: Inoculation of embryos with PC-3–GFP CTCs resulted in a 3 to 10-fold increase in brain metastasis when compared to those with the parental PC-3–GFP cells (p<0.05 in all animals). Thus, PC-3–GFP CTCs have increased metastatic potential compared to their parental counterparts. Conclusions: The chick embryo represents a rapid, sensitive, imageable assay of metastatic potential for CTCs. The chick embryo assay has future clinical application for individualizing patient therapy based on the metastatic profile of their CTCs.

scholarly journals The biology and clinical potential of circulating tumor cells

2019 ◽  
Vol 53 (2) ◽  
pp. 131-147 ◽  
Author(s):  
Taja Lozar ◽  
Klara Gersak ◽  
Maja Cemazar ◽  
Cvetka Grasic Kuhar ◽  
Tanja Jesenko
Keyword(s):  
Tumor Cells ◽  
Circulating Tumor Cells ◽  
Liquid Biopsy ◽  
Clinical Utility ◽  
Cancer Metastasis ◽  
Predictive Biomarkers ◽  
Cell Types ◽  
Biological Properties ◽  
Great Promise ◽  
Blood Draw

Abstract Background Tumor cells can shed from the tumor, enter the circulation and travel to distant organs, where they can seed metastases. These cells are called circulating tumor cells (CTCs). The ability of CTCs to populate distant tissues and organs has led us to believe they are the primary cause of cancer metastasis. The biological properties and interaction of CTCs with other cell types during intravasation, circulation in the bloodstream, extravasation and colonization are multifaceted and include changes of CTC phenotypes that are regulated by many signaling molecules, including cytokines and chemokines. Considering a sample is readily accessible by a simple blood draw, monitoring CTC levels in the blood has exceptional implications in oncology field. A method called the liquid biopsy allows the extraction of not only CTC, but also CTC products, such as cell free DNA (cfDNA), cell free RNA (cfRNA), microRNA (miRNA) and exosomes. Conclusions The clinical utility of CTCs and their products is increasing with advances in liquid biopsy technology. Clinical applications of liquid biopsy to detect CTCs and their products are numerous and could be used for screening of the presence of the cancer in the general population, as well as for prognostic and predictive biomarkers in cancer patients. With the development of better CTC isolation technologies and clinical testing in large prospective trials, increasing clinical utility of CTCs can be expected. The understanding of their biology and interactions with other cell types, particularly with those of the immune system and the rise of immunotherapy also hold great promise for novel therapeutic possibilities.

scholarly journals Exploratory data inference for detecting mastitis in dairy cattle

2020 ◽  
Vol 42 ◽  
pp. e46394
Author(s):  
Rodes Angelo Batista da Silva ◽  
Héliton Pandorfi ◽  
Gledson Luiz Pontes de Almeida ◽  
Marcos Vinícius da Silva
Keyword(s):  
Dairy Cattle ◽  
Principal Component ◽  
Subclinical Mastitis ◽  
Statistical Technique ◽  
Clinical Mastitis ◽  
Physiological Data ◽  
Multivariate Statistical ◽  
Component Technique ◽  
Physiological Variables ◽  
Exploratory Data

The aim of this study was to employ the principal component technique to physiological data and environmental thermohygrometric variables correlated with detection of clinical and subclinical mastitis in dairy cattle. A total of 24 lactating Girolando cows with different clinical conditions were selected (healthy, and with clinical or subclinical mastitis). The following physiological variables were recorded: udder surface temperature, ST (°C); eyeball temperature, ET (°C); rectum temperature, RT (°C); respiratory frequency, RF (mov. min-1). Thermohygrometric variables included air temperature, AirT (°C), and relative humidity, RU (%). ST was determined by means of thermal images, with four images per animal, on these quarters: front left side (FL), front right side (FR), rear right side (RR) and rear left side (RL), totaling 96 images. Exploratory data analysis was run through multivariate statistical technique with the employment of principal components, comprehending nine variables: ST on the FL, FR, RL and RR quarters; ET, RT; RF, AirT and RU. The representative quarters of the animals with clinical and subclinical mastitis showed udder temperatures 8.55 and 2.46° C higher than those of healthy animals, respectively. The ETs of the animals with subclinical and clinical mastitis were, respectively, 7.9 and 8.0% higher than those of healthy animals. Rectum temperatures were 2.9% (subclinical mastitis) and 5.5% (clinical mastitis) higher compared to those of healthy animals. Respiratory frequencies were 40.3% (subclinical mastitis) and 61.6% (clinical mastitis) higher compared to those of healthy animals. The first component explained 91% of the total variance for the variables analyzed. The principal component technique allowed verifying the variables correlated with the animals' clinical condition and the degree of dependence between the study variables.

The Status of Surface Water in West Tripura District, India: An Approach by Using Water Quality Index and Multivariate Statistical Technique

2021 ◽  
Vol 18 (2) ◽  
pp. 27-36
Author(s):  
Biplab Roy ◽  
Ajay Kumar Manna
Keyword(s):  
Water Quality ◽  
Surface Water ◽  
Water Quality Index ◽  
Quality Index ◽  
Principal Component ◽  
Statistical Technique ◽  
Total Hardness ◽  
Multivariate Statistical ◽  
And Cluster Analysis ◽  
Entropy Weighted

The present investigation provides a better interpretation of surface water (rivers, ponds, bills, lakes, etc.) quality utilising entropy weighted water quality index (EWWQI) and different multivariate statistical techniques. Eleven physicochemical parameters including alkalinity, dissolved oxygen (DO), pH, total dissolved solids (TDS), electrical conductivity (EC), calcium (Ca), turbidity, magnesium (Mg), total hardness (TH), chloride (Cl-), and iron (Fe) were analysed and monitored at 23 sampling sites (in December 2018) of West Tripura district. Experimental outcomes of turbidity followed by Fe contamination exceeded recommended WHO standard limit. The maximum values of Fe and turbidity were estimated as 8.745 mg/L and 797.7 NTU, respectively. WQI values confirmed that most of the monitoring locations had poor water quality except three reported areas (S7, S14, and S15) but without Fe and turbidity, estimated WQI confirmed drinkable water condition for entire samples. Multivariate statistical approaches like correlation analysis, principal component analysis (PCA) and cluster analysis (CA) were applied to explore water quality. PCA outcomes recognised three principal factors explaining almost 85% of the total variance. CA investigated three major clusters of 23 sampling sites namely less polluted, highly polluted and moderately polluted zone. Confirming all above, the surface water at the monitoring locations is a major concern which may lead to serious health issues in local people.

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