Circulating EVs have gained considerable interest as biomarkers across many diseases, particularly in the oncology field. Studies have reported that EV-associated molecules have promising outcomes, with many showing prognostic potential which is at least comparable to the prognostic power of circulating tumour cells. Subsequently, investigations based on EV miRNAs, mRNAs or surface proteins have flooded the biomarker research space. Meanwhile, the best source of DNA-based markers remains under debate.
In a study by Tkach et al. (2022) published in PNAS, the authors addressed this question by exploring EV-associated DNA and its utility in the diagnosis of metastatic hormono-dependent breast cancer.
In the study, blood samples were collected from healthy donors and women who had both ER+ (estrogen receptor positive) and HER2- (human epidermal growth factor receptor 2 negative) metastatic breast cancer. Samples were processed and analysed as follows:
Furthermore, EV protein-based analysis was performed by assessing the distribution of 37 EV surface proteins, via flow cytometry fluorescent bead/antibody multiplex assays.
Results from this study revealed that EV-rich pools had lower amounts of total cell-free DNA associated with normal physiology compared to unprocessed plasma, EV intermediate and EV poor pools. Furthermore, no differences in total cell-free DNA were detected between EV-rich pools from healthy controls and those with breast cancer. These results were further confirmed through the quantification of cell DNA ,which showed that cell DNA was depleted from EV-rich pools in healthy individuals or significantly lower in EV-rich pools compared to other EV pools or plasma in cancer patients.
In cancer-associated physiology, known tumour mutations in ctDNA were more abundant in unprocessed plasma than any individual qEV-derived EV pool or the sum of all pools, suggesting that the separation of plasma fractions results in some ctDNA loss (Figure 1). On the other hand, EV mtDNA, which has been associated with therapy resistance, was found more in EV-rich pools and unprocessed plasma in healthy individuals but enriched only in unprocessed plasma in cancer patients. This indicates that circulating mtDNA is more likely recovered from EVs in healthy plasma, but not in breast cancer patients, thus, the isolation of plasma EVs form tDNA analysis did not improve disease monitoring.
Another important finding was related to an assessment of membrane-exposed EV proteins, where four proteins were significantly enriched in EVs from breast cancer patients compared to healthy donors. Using flow cytometry, the samples were classified with a pipeline that analysed the distribution of these four enriched proteins (CD326, CD146, CD105 and CD14) with the criteria of 3 or more enriched markers to determine cancer positivity. This approach achieved a sensitivity of 78% and a specificity of 100% with a sample size of 9.
The analysis of DNA markers in isolated small EVs did not provide any useful prognostic or diagnostic information for breast cancer, and DNA markers were more effectively detected in unprocessed plasma. However, these results do not rule out the possibility of large EVs carrying biomarker DNA or that other nucleic acids, such as RNA, may have value in diagnosing this specific cancer. Nevertheless, four EV surface-associated proteins showed promising biomarker potential. When accompanied by reliable EV isolation, the detection of these proteins via commercial kits could be made amenable to routine clinical practice.
Different subtypes of EVs differentially carry and express molecules with biomarker value, but there can also be non-EV components that co-isolate with EVs and associate with biomarker cargoes. As a result, the challenges for research remain, accurately separating EVs of interest, identifying the signature expression of EV molecules associated with the condition or stage, and assessing the EV biomarker value in terms of sensitivity and specificity in comparison to other samples that are easier to obtain, such as unprocessed plasma. While there is along road from EV biomarker discovery to clinical application, starting the research with appropriate tools for EV isolation can greatly help overcoming some of the technical hurdles. Researchers must identify reliable methods for separating EVs of interest and ensuring their purity. By doing so, they can increase the accuracy and reliability of their findings, which can ultimately lead to the successful translation of EV biomarkers into clinical practice.
qEV columns are highly effective at removing soluble protein from complex EV-containing samples. This is an important feature given the presence of soluble protein can interfere with downstream analysis. To learn more about the benefits of using qEV columns for EV isolation and how they can help reduce variation in EV isolation and boost EV biomarker research, visit: 4 Reasons to Use qEV Columns for Extracellular Vesicle Isolation.