Page 30 - SRPSKO DRUŠTVO ISTRAŽIVAČA RAKA
P. 30

Serbian Association for Cancer Research                                                       SDIRSACR

        gold standard in EVs purification is ultracentrifugation, especially with density gradient. However, it is very difficult
        to standardize all of the ultracentrifugation parameters that can affect the quality of isolated material and in this
        sense, it is nearly impossible to set up a universally standardized protocol. Furthermore, the variability among sample
        populations from the same cells and especially different sources renders this standardization even more difficult.
        Ultracentrifugation is a low-throughput method and often samples, especially from plasma are contaminated with
        lipoproteins, protein aggregates and other particles of similar size or density making them incompatible with clinical
        utilization. There is emerging experimental evidence that substantial amounts of EVs RNA and proteins are lost during
        ultracentrifugation. Additionally, using ultracentrifugation as a method of choice makes scaling-up extremely difficult if
        not completely unobtainable. Immuno-affinity-based techniques offer an advantage of selecting pathology-specific EVs
        and preserving them intact. Unfortunately, elevated costs and time constraints related to production of monoclonal
        antibodies, as well as their large dimensions render them inappropriate for scalable and high-throughput EV isolation.
        Recent scientific endeavors are aimed at developing versatile, cost-effective methodologies for scalable isolation (μL to
        mL; mL to >L) of high-purity EVs from bio-samples, which are urgently needed to open new perspectives in EVs-based
        theranostics. Novel methods for EV isolation based on single-domain antibodies as selective agents have been proven
        effective for various biological sources such as plasma and urine(33, 34, 35).


              Table 1. Examples of EV-derived biomarkers across cancer types and their diagnostic performance.




































































                                                                                                                   15
   25   26   27   28   29   30   31   32   33   34   35