## 5 Future Challenges and Conclusions  
Different reports have identified numerous potential EV-based biomarkers that can aid in cancer diagnosis, disease monitoring, and development of targeted therapy. Currently, \begin{table}
\begin{tabular}{c c c c} \hline \hline
**Cancer Type** & **Biomarker** & **Sample** & **Authors** \\ \hline Colorectal Cancer & Increased miR-19a and miR-92a & Serum-derived EVs & [190] \\ Colorectal Cancer & Increased let-7a, miR-1229, miR-1246, miR-150, & Serum-derived EVs & [191] \\  & miR-21, 223, and miR-23a & & \\  & Increased miR-1246, miR-4644, mir\_3976, and & & \\  & miR-4306 & & \\ Prostate Cancer & Increased miR-1246, miR-1290 and miR-375 & & \\ Prostate Cancer & Increased levels of miR-141 & & \\ Prostate Cancer & Increased miR-21-5p and let-7a-5p & & \\ Hepatocellular Carcinoma & Increased miR-21-5p, miR-92a-3p & & \\ Lung cancer & Increased miR-320 and miR-126 & & \\ Breast Cancer & Decreased miR-142-5p and miR-150-5p & & \\  & miR-200a, miR-200b, miR-200c, miR-429, & & \\  & and miR-141 & & \\ Breast Cancer & miR-338-3p, miR-340-5p, and miR124-3p & & \\  & Decresead of miR-100 and miR-125b & & \\ Ovarian Cancer & Let-7 miRNA family serum-derived EVs & & \\ Thyroid Cancer & miR-423-5p, miR-484, miR-142-5p, and miR-17-5p & & \\ Gastric Cancer & serum-derived EVs & & \\  & serum-derived EVs & & \\ Glioblastoma & Increased miR-1246 & & \\  & & & \\ Glioblastoma & Increased miR-301a & & \\  & & & \\ Glioblastoma & Increased miR-21 & & \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Summary of the miRNAs identified in EVs with potential as biomarkers of different cancers. studies in proteomics, lipidomics, and metabolomics have advanced our knowledge of the properties of EVs. However, limitations in sample quality, EV isolation methods, cargo analysis, and interpretation of results may contribute to the failure of them as biomarkers in achieving clinical utility. One of the primary challenges in characterizing cancer-specific EVs in biofluids is that samples also contain large amounts of EVs secreted by healthy cells, as well as other biomolecules (e.g., albumin, lipoproteins). Methods of isolation and analysis have limited sensitivity/specificity for detecting specific tumor-secreted EVs in biofluids because they are based on a small sample size in which EVs are diluted. Therefore, it is necessary to optimize isolation methods _in vitro_ in order to distinguish specific EV subgroups to address for specific clinical scenarios. In fact, the success of EV molecular profiling heavily relies on the isolation and separation process. Consequently, developing efficient isolation methods and enriching cancer-derived EVs or specific EV subpopulations from human biofluids are urgent in order to further advance in this field. In recent years, the field of microfluidics has allowed for the development of novel exosome purification methods, starting from small sample quantities [210]. Microfluidic platforms have been shown to sort exosomes with a high level of purity and sensitivity by reducing cost, volume of reagents consumed, and time invested in the procedure. However, microfluidics platforms have the disadvantage of their manufacturing complexity [211]. The first microfluidic platform used for the isolation of EVs relied on exosome immunoassayaffinity and unlabeled detection. It quantified the levels of EpCAM and CD24 proteins measured in relation to CD63 (+) exosome counts, with a diagnostic accuracy of 97% in ovarian cancer ascitic fluids. Another important aspect of microfluidic platforms is their potential use in the identification of specific subpopulations of EVs. Multiplex microfluidics have enabled the selective and specific capture of IV HER2 (+) in serum from breast cancer patients [212]. EVs hold great potential for disease diagnostics, which is why it is important to further know their content and cell-targeting mechanisms.