As the prevalence of cancer is escalating, there is an increased demand for early and sensitive diagnostic tools. A major challenge in early detection is the lack of specific biomarkers, and a readily accessible, sensitive and rapid detection method. To meet these challenges, cancer-derived small extracellular vesicles (sEVs) have been discovered as a new promising cancer biomarker due to the high abundance of sEVs in body fluids and their extensive cargo of biomarkers. Additionally, surface-enhanced Raman scattering (SERS) presents a sensitive, multiplexed, and rapid method that has gained attraction with recent studies showing promising results from patient samples for the multiplex detection of cancer sEVs. Various label-based SERS multiplex assays have been developed in the field of SERS including bead assays, lateral flow immunoassays, microfluidic devices, and artificial intelligence (AI)-based label-free SERS chips, targeting multiple surface proteins to ensure comprehensive multiplex diagnostics. These assays hold promise for enabling early detection, quantification, and subtyping of cancer-derived sEVs for cancer diagnostic applications. This review aims to provide a summary of the recent advances in the field of SERS multiplex assays for detection, quantification, and subtyping of sEVs to facilitate cancer diagnosis. This review further provides unique insights into the use of sEVs as a biomarker and aims to address the issues surrounding their translation from laboratories to clinics.
Download full-text PDF |
Source |
---|---|
http://dx.doi.org/10.1039/d4nr04014g | DOI Listing |
Trop Med Health
January 2025
LaoLuxLab/Vaccine Preventable Diseases Laboratory, Institut Pasteur du Laos, Vientiane, Laos.
Background: Individuals with latent tuberculosis infection (LTBI) have a high risk of active infection, morbidity and mortality. Healthcare workers are a group who have increased risk of infection and onward transmission to their patients and other susceptible individuals; however, LTBI is often undiagnosed, and individuals are asymptomatic. Interferon gamma release assays (IGRA) can detect evidence of TB infection in otherwise asymptomatic individuals and are a good indication of LTBI.
View Article and Find Full Text PDFMicrobiome
January 2025
Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia.
Background: Accurate classification of host phenotypes from microbiome data is crucial for advancing microbiome-based therapies, with machine learning offering effective solutions. However, the complexity of the gut microbiome, data sparsity, compositionality, and population-specificity present significant challenges. Microbiome data transformations can alleviate some of the aforementioned challenges, but their usage in machine learning tasks has largely been unexplored.
View Article and Find Full Text PDFChin Med
January 2025
Department of Integrated Traditional Chinese and Western Medicine, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, Hubei, China.
Background: This research aims to explore the anti-obesity potential of Wu-Mei-Wan (WMW), particularly its effects on adipose tissue regulation in obese mice induced by a high-fat diet (HFD). The study focuses on understanding the role of heat shock factor 1 (HSF1) in mediating these effects.
Methods: HFD-induced obese mice were treated with WMW.
Reprod Health
January 2025
Department of Public Health, Institute of Tropical Medicine, Antwerp, Belgium.
Background: Over one-third of the global stillbirth burden occurs in countries affected by conflict or a humanitarian crisis, including Afghanistan. Stillbirth rates in Afghanistan remained high in 2021 at over 26 per 1000 births. Stillbirths have devastating physical, psycho-social and economic impacts on women, families and healthcare providers.
View Article and Find Full Text PDFCell Commun Signal
January 2025
Centre of Postgraduate Medical Education, Centre of Translation Research, Department of Biochemistry and Molecular Biology, ul. Marymoncka 99/103, Warsaw, 01-813, Poland.
Background: Renal cell cancer (RCC) is the most common and highly malignant subtype of kidney cancer. Mesenchymal stromal cells (MSCs) are components of tumor microenvironment (TME) that influence RCC progression. The impact of RCC-secreted small non-coding RNAs (sncRNAs) on TME is largely underexplored.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!