Fourier-Transform InfraRed (FT-IR) spectroscopy to show alterations in molecular composition of EV subpopulations from melanoma cell lines in different malignancy

Stępień, Ewa; Kamińska, Agnieszka; Surman, Magdalena; Karbowska, Dagmara; Wróbel, Andrzej; Przybyło, Małgorzata

doi:10.1016/j.bbrep.2020.100888

Cited by 23 publications

(29 citation statements)

References 44 publications

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“…A more in-depth analysis of Figure 2 shows the presence of changes in the spectral shape and in the relative intensity of several absorption bands, namely the carbohydrates and nucleic acids band at 1000–1200 cm −1 [ 16 , 19 ], the protein Amide I and II bands [ 13 , 36 , 37 ], the lipid C-H stretching band at 2800–3000 cm −1 [ 23 , 38 ], and the C=O stretching at approximately 1735 cm −1 , which has been assigned to purine base and ester groups of lipids in EV samples [ 9 , 36 , 37 ]. These bands are highlighted in green and red color in controls and patients, respectively, and are considered a major source of spectral biomarkers in EV research [ 4 , 8 , 9 , 10 , 11 , 12 , 13 , 14 , 15 , 16 , 17 , 18 , 19 , 20 , 23 ]. To investigate more in-depth the difference between the two groups, an enlarged detail of the four mentioned IR bands for controls (green) and oncologic patients (red) is reported in Figure 3 .…”

Section: Resultsmentioning

confidence: 99%

“…In this regard, Fourier-transform infrared spectroscopy (FTIR), especially in the Attenuated Total Reflection (ATR) mode, is emerging as a promising tool for label-free molecular profiling of EVs, with several papers published on the subject [ 4 , 8 , 9 , 10 , 11 , 12 , 13 , 14 , 15 , 16 , 17 , 18 , 19 , 20 ]. Most of these works involve in vitro experiments aimed at assessing sample composition and purity [ 15 , 16 ], distinguishing different EV classes [ 18 ] or EVs derived from cells under different states/phenotypes/culture conditions [ 4 , 8 , 10 , 12 , 21 , 22 , 23 ]. So far, very few FTIR papers have focused on EVs purified from biofluids of subjects enrolled in clinical studies.…”

Section: Introductionmentioning

confidence: 99%

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Machine Learning-Assisted FTIR Analysis of Circulating Extracellular Vesicles for Cancer Liquid Biopsy

Santo

Vaccaro

Romanò

et al. 2022

JPM

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Extracellular vesicles (EVs) are abundantly released into the systemic circulation, where they show remarkable stability and harbor molecular constituents that provide biochemical information about their cells of origin. Due to this characteristic, EVs are attracting increasing attention as a source of circulating biomarkers for cancer liquid biopsy and personalized medicine. Despite this potential, none of the discovered biomarkers has entered the clinical practice so far, and novel approaches for the label-free characterization of EVs are highly demanded. In this regard, Fourier Transform Infrared Spectroscopy (FTIR) has great potential as it provides a quick, reproducible, and informative biomolecular fingerprint of EVs. In this pilot study, we investigated, for the first time in the literature, the capability of FTIR spectroscopy to distinguish between EVs extracted from sera of cancer patients and controls based on their mid-IR spectral response. For this purpose, EV-enriched suspensions were obtained from the serum of patients diagnosed with Hepatocellular Carcinoma (HCC) of nonviral origin and noncancer subjects. Our data point out the presence of statistically significant differences in the integrated intensities of major mid-IR absorption bands, including the carbohydrate and nucleic acids band, the protein amide I and II bands, and the lipid CH stretching band. Additionally, we used Principal Component Analysis combined with Linear Discriminant Analysis (PCA-LDA) for the automated classification of spectral data according to the shape of specific mid-IR spectral signatures. The diagnostic performances of the proposed spectral biomarkers, alone and combined, were evaluated using multivariate logistic regression followed by a Receiving Operator Curve analysis, obtaining large Areas Under the Curve (AUC = 0.91, 95% CI 0.81–1.0). Very interestingly, our analyses suggest that the discussed spectral biomarkers can outperform the classification ability of two widely used circulating HCC markers measured on the same groups of subjects, namely alpha-fetoprotein (AFP), and protein induced by the absence of vitamin K or antagonist-II (PIVKA-II).

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Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Machine Learning-Assisted FTIR Analysis of Circulating Extracellular Vesicles for Cancer Liquid Biopsy

Santo

Vaccaro

Romanò

et al. 2022

JPM

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“…Using FTIR, Mihaly et al., analyzed EVs subpopulations and found differences in protein secondary structure and lipid content among EVs subpopulations [ 199 ]. These findings were further confirmed by analyzing EVs subpopulations enriched from cancer cell lines highlighting FTIR as an effective tool for quick EVs subpopulation characterization [ 200 , 201 ]. Recent studies reported the use of FTIR to characterize changes in the biochemical composition of EVs released from cell cultures mimicking various pathological conditions such as septic shock [ 202 ], cancer [ 201 , 203 – 206 ], AD [ 217 ] as well as the effect of cellular treatment on EV cargo [ 208 ].…”

Section: Characterization Of Evs Molecular Contentmentioning

confidence: 86%

“…These findings were further confirmed by analyzing EVs subpopulations enriched from cancer cell lines highlighting FTIR as an effective tool for quick EVs subpopulation characterization [ 200 , 201 ]. Recent studies reported the use of FTIR to characterize changes in the biochemical composition of EVs released from cell cultures mimicking various pathological conditions such as septic shock [ 202 ], cancer [ 201 , 203 – 206 ], AD [ 217 ] as well as the effect of cellular treatment on EV cargo [ 208 ]. In addition, IR of single microvesicles by coupling IR and AFM have been reported [ 209 ] (Table 2) .…”

Section: Characterization Of Evs Molecular Contentmentioning

confidence: 86%

Recent advances in optical label-free characterization of extracellular vesicles

et al. 2022

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Extracellular vesicles (EVs) are complex biological nanoparticles endogenously secreted by all eukaryotic cells. EVs carry a specific molecular cargo of proteins, lipids, and nucleic acids derived from cells of origin and play a significant role in the physiology and pathology of cells, organs, and organisms. Upon release, they may be found in different body fluids that can be easily accessed via noninvasive methodologies. Due to the unique information encoded in their molecular cargo, they may reflect the state of the parent cell and therefore EVs are recognized as a rich source of biomarkers for early diagnostics involving liquid biopsy. However, body fluids contain a mixture of EVs released by different types of healthy and diseased cells, making the detection of the EVs of interest very challenging. Recent research efforts have been focused on the detection and characterization of diagnostically relevant subpopulations of EVs, with emphasis on label-free methods that simplify sample preparation and are free of interfering signals. Therefore, in this paper, we review the recent progress of the label-free optical methods employed for the detection, counting, and morphological and chemical characterization of EVs. We will first briefly discuss the biology and functions of EVs, and then introduce different optical label-free techniques for rapid, precise, and nondestructive characterization of EVs such as nanoparticle tracking analysis, dynamic light scattering, atomic force microscopy, surface plasmon resonance spectroscopy, Raman spectroscopy, and SERS spectroscopy. In the end, we will discuss their applications in the detection of neurodegenerative diseases and cancer and provide an outlook on the future impact and challenges of these technologies to the field of liquid biopsy via EVs.

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“…In fact, this technique is able to detect subtle changes in the molecular structure of nucleic acids, lipids, proteins, and carbohydrates in biological samples, thus defining a specific biomolecule fingerprinting. FT-IR spectroscopy has been utilized to identify and distinguish subpopulations of EVs derived from melanoma cells with different malignant grades [ 28 ], and it has been fruitfully applied to reveal differences at the single vesicle level between EVs derived from colon normal epithelial cells and colon cancer cells [ 23 ]. Moreover, FT-IR spectra were used to characterize EVs isolated from biological fluids and consistently different spectral signatures were identified for salivary cancer and healthy individual derived-EVs [ 29 ], for blood from prostate cancer and healthy patient derived-EVs [ 30 ], and for blood derived-EVs isolated from Alzheimer’s disease affected and control subjects [ 31 ].…”

Section: Discussionmentioning

confidence: 99%

FT-IR Spectral Signature of Sensitive and Multidrug-Resistant Osteosarcoma Cell-Derived Extracellular Nanovesicles

Perut

Graziani

Roncuzzi

et al. 2022

Cells

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Osteosarcoma (OS) is the most common primary bone cancer in children and adolescents. Despite aggressive treatment regimens, the outcome is unsatisfactory, and multidrug resistance (MDR) is a pivotal process in OS treatment failure. OS-derived extracellular vesicles (EVs) promote drug resistance to chemotherapy and target therapy through different mechanisms. The aim of this study was to identify subpopulations of osteosarcoma-EVs by Fourier transform infrared spectroscopy (FT-IR) to define a specific spectral signature for sensitive and multidrug-resistant OS-derived EVs. EVs were isolated from sensitive and MDR OS cells as well as from mesenchymal stem cells by differential centrifugation and ultracentrifugation. EVs size, morphology and protein expression were characterized. FT-IR/ATR of EVs spectra were acquired in the region of 400–4000 cm−1 (resolution 4 cm−1, 128 scans). The FT-IR spectra obtained were consistently different in the EVs compared to cells from which they originate. A specific spectral signature, characterized by a shift and a new band (1601cm−1), permitted to clearly distinguish EVs isolated by sensitive and multidrug-resistant OS cells. Our data suggest that FT-IR spectroscopy allows to characterize and define a specific spectral signature for sensitive and MDR OS-derived EVs.

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Fourier-Transform InfraRed (FT-IR) spectroscopy to show alterations in molecular composition of EV subpopulations from melanoma cell lines in different malignancy

Cited by 23 publications

References 44 publications

Machine Learning-Assisted FTIR Analysis of Circulating Extracellular Vesicles for Cancer Liquid Biopsy

Machine Learning-Assisted FTIR Analysis of Circulating Extracellular Vesicles for Cancer Liquid Biopsy

Recent advances in optical label-free characterization of extracellular vesicles

FT-IR Spectral Signature of Sensitive and Multidrug-Resistant Osteosarcoma Cell-Derived Extracellular Nanovesicles

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