| Literature DB >> 33989735 |
Jiayi Weng1, Xiaoqiang Xiang2, Lingwen Ding3, Andrea Li-Ann Wong4, Qi Zeng5, Gautam Sethi6, Lingzhi Wang7, Soo Chin Lee8, Boon Cher Goh9.
Abstract
Cancer has risen up to be a major cause of mortality worldwide over the past decades. Despite advancements in cancer screening and diagnostics, a significant number of cancers are still diagnosed at a late stage with poor prognosis. Hence, the discovery of reliable and accurate methods to diagnose cancer early would be of great help in reducing cancer mortality. Extracellular vesicles (EVs) are phospholipid vesicles found in many biofluids and are released by almost all types of cells. In recent years, using EVs as cancer biomarkers has garnered attention as a novel technique of cancer diagnosis. Compared with traditional tissue biopsy, there are many advantages that this novel diagnostic tool presents - it is less invasive, detects early-stage asymptomatic cancers, and allows for monitoring of tumour progression. As such, EV biomarkers have great potential in improving the diagnostic accuracy of cancers and guiding subsequent therapeutic decisions. Efficient isolation and accurate characterization of EVs are essential for reliable outcomes of clinical application. However, these are complicated by the size and biomolecular diversity of EVs. In this review, we present an analysis and evaluation of the current techniques of EV isolation and characterization, as well as discuss the potential EV biomarkers for specific types of cancer. Taken together, EV biomarkers have a lot of potential as a novel method in cancer diagnostics and diagnosis. However, more work is still needed to streamline the purification, characterization and biomarker identification process to ensure optimal outcomes for patients.Entities:
Keywords: Cancer biomarker; EV characterization; EV isolation; Extracellular vesicles; Liquid biopsy
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Year: 2021 PMID: 33989735 DOI: 10.1016/j.semcancer.2021.05.011
Source DB: PubMed Journal: Semin Cancer Biol ISSN: 1044-579X Impact factor: 15.707