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Extracellular Vesicles: Nanotechnology-Based Isolations, Characterizations, and Applications for Cancer Diagnostics...
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Extracellular Vesicles: Nanotechnology-Based Isolations, Characterizations, and Applications for Cancer Diagnostics and Monitoring

A special issue of Nanomaterials (ISSN 2079-4991). This special issue belongs to the section "Biology and Medicines".

Deadline for manuscript submissions: 23 May 2025 | Viewed by 4835

Special Issue Editor

Dr. Xiaohua Huang

E-Mail Website
Guest Editor
Department of Chemistry, The University of Memphis, Memphis, TN, USA
Interests: nanomaterials; optical imaging; surface-enhanced Raman scattering spectroscopy; circulating tumor cells; extracellular vesicles; photothermal therapy

Special Issue Information

Dear Colleagues,

Extracellular vesicles (EVs) are a heterogeneous group of nanosized cell-derived membrane-bound vesicles that are continuously released by nearly all cells. They carry nucleic acids and many proteins reflective of their parental cells, and thus, biomarkers of cancer cells can be explored through EVs. EVs are present in a variety of body fluids including plasma, urine, saliva, ascites, and cerebrospinal fluid. EVs from tumor cells can transfer oncogenic factors through intercellular communication and regulate angiogenesis, immunity, and metastasis to promote tumorigenesis and progression. Thus, EVs hold great potential for developing next-generation liquid biopsy for cancer and some other diseases. To translate EVs into clinical applications, EVs need to be well characterized, and they often require isolation from biological fluids for accurate downstream analysis. Extensive pre-clinical studies are needed to prove the feasibility of EVs for cancer diagnostics and monitoring. Nanomaterials have unique structural and functional properties that are often not available from discrete molecules and bulk materials. Nanostructures have a large surface-to-volume ratio that allows for highly efficient target interactions. The unique structure and functional properties of nanomaterials can be used to develop new assays to overcome the limitations of the traditional methods, advancing EV research and accelerating EV translation into clinic applications.

This Special Issue aims to publish research that demonstrates the latest advancements in using nanotechnology for EV isolations, characterizations, and applications for cancer diagnostics, monitoring, and treatment. We invite submission of manuscripts on, but not limited to, the following topics:

  • Nanotechnology-based methods and devices to isolate and purify EVs;
  • Nanotechnology-based technologies and sensors to characterize the molecular constituents of EVs including proteins and nucleic acids;
  • Application of nanotechnology-based EV analysis for cancer diagnostics;
  • Application of nanotechnology-based EV analysis for cancer monitoring.

Manuscript Types:

  • Article;
  • Brief Report;
  • Communication;
  • Protocol;
  • Review;
  • Technical Note.

Dr. Xiaohua Huang
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Nanomaterials is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • extracellular vesicles
  • isolation
  • characterization
  • cancer
  • diagnostics
  • monitoring
  • treatment

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Published Papers (3 papers)

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Research

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15 pages, 4226 KiB  
Article
Single Vesicle Surface Protein Profiling and Machine Learning-Based Dual Image Analysis for Breast Cancer Detection
by Mitchell Lee Taylor, Madhusudhan Alle, Raymond Wilson, Jr., Alberto Rodriguez-Nieves, Mitchell A. Lutey, William F. Slavney, Jacob Stewart, Hiyab Williams, Kristopher Amrhein, Hongmei Zhang, Yongmei Wang, Thang Ba Hoang and Xiaohua Huang
Nanomaterials 2024, 14(21), 1739; https://doi.org/10.3390/nano14211739 - 30 Oct 2024
Viewed by 1435
Abstract
Single-vesicle molecular profiling of cancer-associated extracellular vesicles (EVs) is increasingly being recognized as a powerful tool for cancer detection and monitoring. Mask and target dual imaging is a facile method to quantify the fraction of the molecularly targeted population of EVs in biofluids [...] Read more.
Single-vesicle molecular profiling of cancer-associated extracellular vesicles (EVs) is increasingly being recognized as a powerful tool for cancer detection and monitoring. Mask and target dual imaging is a facile method to quantify the fraction of the molecularly targeted population of EVs in biofluids at the single-vesicle level. However, accurate and efficient dual imaging vesicle analysis has been challenging due to the interference of false signals on the mask images and the need to analyze a large number of images in clinical samples. In this work, we report a fully automatic dual imaging analysis method based on machine learning and use it with dual imaging single-vesicle technology (DISVT) to detect breast cancer at different stages. The convolutional neural network Resnet34 was used along with transfer learning to produce a suitable machine learning model that could accurately identify areas of interest in experimental data. A combination of experimental and synthetic data were used to train the model. Using DISVT and our machine learning-assisted image analysis platform, we determined the fractions of EpCAM-positive EVs and CD24-positive EVs over captured plasma EVs with CD81 marker in the blood plasma of pilot HER2-positive breast cancer patients and compared to those from healthy donors. The amount of both EpCAM-positive and CD24-positive EVs was found negligible for both healthy donors and Stage I patients. The amount of EpCAM-positive EVs (also CD81-positive) increased from 18% to 29% as the cancer progressed from Stage II to III. No significant increase was found with further progression to Stage IV. A similar trend was found for the CD24-positive EVs. Statistical analysis showed that both EpCAM and CD24 markers can detect HER2-positive breast cancer at Stages II, III, or IV. They can also differentiate individual cancer stages except those between Stage III and Stage IV. Due to the simplicity, high sensitivity, and high efficiency, the DISVT with the AI-assisted dual imaging analysis can be widely used for both basic research and clinical applications to quantitatively characterize molecularly targeted EV subtypes in biofluids. Full article
(This article belongs to the Special Issue Extracellular Vesicles: Nanotechnology-Based Isolations, Characterizations, and Applications for Cancer Diagnostics and Monitoring)
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22 pages, 5485 KiB  
Article
Peptide-Conjugated Vascular Endothelial Extracellular Vesicles Encapsulating Vinorelbine for Lung Cancer Targeted Therapeutics
by Isha Gaurav, Abhimanyu Thakur, Kui Zhang, Sudha Thakur, Xin Hu, Zhijie Xu, Gaurav Kumar, Ravindran Jaganathan, Ashok Iyaswamy, Min Li, Ge Zhang and Zhijun Yang
Nanomaterials 2024, 14(20), 1669; https://doi.org/10.3390/nano14201669 - 17 Oct 2024
Viewed by 1452
Abstract
Lung cancer is one of the major cancer types and poses challenges in its treatment, including lack of specificity and harm to healthy cells. Nanoparticle-based drug delivery systems (NDDSs) show promise in overcoming these challenges. While conventional NDDSs have drawbacks, such as immune [...] Read more.
Lung cancer is one of the major cancer types and poses challenges in its treatment, including lack of specificity and harm to healthy cells. Nanoparticle-based drug delivery systems (NDDSs) show promise in overcoming these challenges. While conventional NDDSs have drawbacks, such as immune response and capture by the reticuloendothelial system (RES), extracellular vesicles (EVs) present a potential solution. EVs, which are naturally released from cells, can evade the RES without surface modification and with minimal toxicity to healthy cells. This makes them a promising candidate for developing a lung-cancer-targeting drug delivery system. EVs isolated from vascular endothelial cells, such as human umbilical endothelial-cell-derived EVs (HUVEC-EVs), have shown anti-angiogenic activity in a lung cancer mouse model; therefore, in this study, HUVEC-EVs were chosen as a carrier for drug delivery. To achieve lung-cancer-specific targeting, HUVEC-EVs were engineered to be decorated with GE11 peptides (GE11-HUVEC-EVs) via a postinsertional technique to target the epidermal growth factor receptor (EGFR) that is overexpressed on the surface of lung cancer cells. The GE11-HUVEC-EVs were loaded with vinorelbine (GE11-HUVEC-EVs-Vin), and then characterized and evaluated in in vitro and in vivo lung cancer models. Further, we examined the binding affinity of ABCB1, encoding P-glycoprotein, which plays a crucial role in chemoresistance via the efflux of the drug. Our results indicate that GE11-HUVEC-EVs-Vin effectively showed tumoricidal effects against cell and mouse models of lung cancer. Full article
(This article belongs to the Special Issue Extracellular Vesicles: Nanotechnology-Based Isolations, Characterizations, and Applications for Cancer Diagnostics and Monitoring)
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Review

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47 pages, 10412 KiB  
Review
Magnetic–Plasmonic Core–Shell Nanoparticles: Properties, Synthesis and Applications for Cancer Detection and Treatment
by Alberto Luis Rodriguez-Nieves, Suprava Shah, Mitchell L. Taylor, Madhusudhan Alle and Xiaohua Huang
Nanomaterials 2025, 15(4), 264; https://doi.org/10.3390/nano15040264 - 10 Feb 2025
Viewed by 1494
Abstract
Nanoparticles have been widely used in cancer diagnostics and treatment research due to their unique properties. Magnetic nanoparticles are popular in imaging techniques due to their ability to alter the magnetization field around them. Plasmonic nanoparticles are mainly applied in cancer treatments like [...] Read more.
Nanoparticles have been widely used in cancer diagnostics and treatment research due to their unique properties. Magnetic nanoparticles are popular in imaging techniques due to their ability to alter the magnetization field around them. Plasmonic nanoparticles are mainly applied in cancer treatments like photothermal therapy due to their ability to convert light into heat. While these nanoparticles are popular among their respective fields, magnetic–plasmonic core–shell nanoparticles (MPNPs) have gained popularity in recent years due to the combined magnetic and optical properties from the core and shell. MPNPs have stood out in cancer theranostics as a multimodal platform capable of serving as a contrast agent for imaging, a guidable drug carrier, and causing cellular ablation through photothermal energy conversion. In this review, we summarize the different properties of MPNPs and the most common synthesis approaches. We particularly discuss applications of MPNPs in cancer diagnosis and treatment based on different mechanisms using the magnetic and optical properties of the particles. Lastly, we look into current challenges they face for clinical applications and future perspectives using MPNPs for cancer detection and therapy. Full article
(This article belongs to the Special Issue Extracellular Vesicles: Nanotechnology-Based Isolations, Characterizations, and Applications for Cancer Diagnostics and Monitoring)
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