Dataset Information

Extracellular Vesicles-Based Biomarkers Represent a Promising Liquid Biopsy in Endometrial Cancer.

ABSTRACT: Tumor-derived extracellular vesicles (EVs) are secreted in large amounts into biological fluids of cancer patients. The analysis of EVs cargoes has been associated with patient´s outcome and response to therapy. However, current technologies for EVs isolation are tedious and low cost-efficient for routine clinical implementation. To explore the clinical value of circulating EVs analysis we attempted a proof-of-concept in endometrial cancer (EC) with ExoGAG, an easy to use and highly efficient new technology to enrich EVs. Technical performance was first evaluated using EVs secreted by Hec1A cells. Then, the clinical value of this strategy was questioned by analyzing the levels of two well-known tissue biomarkers in EC, L1 cell adhesion molecule (L1CAM) and Annexin A2 (ANXA2), in EVs purified from plasma in a cohort of 41 EC patients and 20 healthy controls. The results demonstrated the specific content of ANXA2 in the purified EVs fraction, with an accurate sensitivity and specificity for EC diagnosis. Importantly, high ANXA2 levels in circulating EVs were associated with high risk of recurrence and non-endometrioid histology suggesting a potential value as a prognostic biomarker in EC. These results also confirmed ExoGAG technology as a robust technique for the clinical implementation of circulating EVs analyses.

SUBMITTER: Herrero C

PROVIDER: S-EPMC6966595 | biostudies-literature | 2019 Dec

REPOSITORIES: biostudies-literature

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Extracellular Vesicles-Based Biomarkers Represent a Promising Liquid Biopsy in Endometrial Cancer.

Herrero Carolina C de la Fuente Alexandre A Casas-Arozamena Carlos C Sebastian Victor V Prieto Martin M Arruebo Manuel M Abalo Alicia A Colás Eva E Moreno-Bueno Gema G Gil-Moreno Antonio A Vilar Ana A Cueva Juan J Abal Miguel M Muinelo-Romay Laura L

Cancers 20191212 12

Tumor-derived extracellular vesicles (EVs) are secreted in large amounts into biological fluids of cancer patients. The analysis of EVs cargoes has been associated with patient´s outcome and response to therapy. However, current technologies for EVs isolation are tedious and low cost-efficient for routine clinical implementation. To explore the clinical value of circulating EVs analysis we attempted a proof-of-concept in endometrial cancer (EC) with ExoGAG, an easy to use and highly efficient ne ...[more]

PMID: 31842290

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Project description: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).

Project description:While the field of precision oncology is rapidly expanding and more targeted options are revolutionizing cancer treatment paradigms, therapeutic resistance particularly to immunotherapy remains a pressing challenge. This can be largely attributed to the dynamic tumor-stroma interactions that continuously alter the microenvironment. While to date most advancements have been made through examining the clinical utility of tissue-based biomarkers, their invasive nature and lack of a holistic representation of the evolving disease in a real-time manner could result in suboptimal treatment decisions. Thus, using minimally-invasive approaches to identify biomarkers that predict and monitor treatment response as well as alert to the emergence of recurrences is of a critical need. Currently, research efforts are shifting towards developing liquid biopsy-based biomarkers obtained from patients over the course of disease. Liquid biopsy represents a unique opportunity to monitor intercellular communication within the tumor microenvironment which could occur through the exchange of extracellular vesicles (EVs). EVs are lipid bilayer membrane nanoscale vesicles which transfer a plethora of biomolecules that mediate intercellular crosstalk, shape the tumor microenvironment, and modify drug response. The capture of EVs using innovative approaches, such as microfluidics, magnetic beads, and aptamers, allow their analysis via high throughput multi-omics techniques and facilitate their use for biomarker discovery. Artificial intelligence, using machine and deep learning algorithms, is advancing multi-omics analyses to uncover candidate biomarkers and predictive signatures that are key for translation into clinical trials. With the increasing recognition of the role of EVs in mediating immune evasion and as a valuable biomarker source, these real-time snapshots of cellular communication are promising to become an important tool in the field of precision oncology and spur the recognition of strategies to block resistance to immunotherapy. In this review, we discuss the emerging role of EVs in biomarker research describing current advances in their isolation and analysis techniques as well as their function as mediators in the tumor microenvironment. We also highlight recent lung cancer and melanoma studies that point towards their application as predictive biomarkers for immunotherapy and their potential clinical use in precision immuno-oncology.

Dataset Information

Extracellular Vesicles-Based Biomarkers Represent a Promising Liquid Biopsy in Endometrial Cancer.

Publications

Extracellular Vesicles-Based Biomarkers Represent a Promising Liquid Biopsy in Endometrial Cancer.

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