Early cancer detection remains a critical determinant of patient survival; however, traditional tissue biopsies are heavily constrained by invasive physical risks, tumor heterogeneity, and longitudinal sampling limitations. Consequently, modern oncology is shifting toward the liquid biopsy paradigm. While circulating tumor cells (CTCs) and circulating tumor DNA (ctDNA) face sensitivity limits in early-stage localized disease, exosomes—nanoscale extracellular vesicles (30–160 nm)—offer a robust alternative. Actively secreted by living, hyper-proliferative tumor cells, exosomes provide a highly abundant, real-time molecular snapshot of the tumor microenvironment.Within these vesicles, exosomal microRNAs (miRNAs) have emerged as exceptional diagnostic and prognostic biomarkers. Shielded from systemic RNase degradation by a tough lipid bilayer membrane, these miRNAs are actively and specifically sorted into exosomes via pathways like ESCRT to drive angiogenesis, modulate local stroma, and establish pre-metastatic niches.Clinically, combinatorial exosomal miRNA panels have demonstrated immense efficacy, achieving high diagnostic sensitivity and specificity across breast, lung, and colorectal malignancies. Furthermore, they serve as an effective "molecular clock" for tracking minimal residual disease (MRD) and monitoring acquired therapeutic resistance.Despite these clinical breakthroughs, widespread translation is currently hindered by methodological bottlenecks. Unstandardized pre-analytical variables (such as hemolysis and anticoagulant interference), lipoprotein contamination during isolation, and the failure of traditional cellular normalization controls create significant data variance. Overcoming these hurdles requires strict adherence to MISEV guidelines, the transition to absolute quantification via droplet digital PCR (ddPCR), and the integration of emerging single-vesicle profiling and point-of-care testing (POCT) platforms to firmly establish exosomal liquid biopsies as a standardized tool in clinical pathology.