No abstract

Small extracellular vesicles (sEVs) are reliable biomarkers for early cancer detection; however, conventional detection methods such as immune-based assays and microRNA analyses are not very sensitive and require sample pretreatments and long analysis time. Here, we developed a molecular imprintingbased dynamic molding approach to fabricate antibody-conjugated signaling nanocavities capable of size recognition. This enabled the establishment of an easy-to-use, rapid, sensitive, pretreatment-free, and noninvasive sEV detection platform for efficient sEV detection-based cancer diagnosis. An apparent dissociation constant was estimated to be 2.4 × 10 −16 M, which was ∼1000 times higher than that of commercial immunoassays (analysis time, 5 min/sample). We successfully used tears for the first time to detect cancer-related intact sEVs, clearly differentiating between healthy donors and breast cancer patients, as well as between samples collected before and after total mastectomy. Our nanoprocessing strategy can be easily repurposed for the specific detection of other types of cancer by changing the conjugated antibodies, thereby facilitating the establishment of liquid biopsy for early cancer diagnosis.

Background/Aim: Exosomes are produced by normal and cancer cells. Exosomes are found in the serum of cancer patients and have been used for diagnosis and prognosis. Recently tears from non-cancer patients have been found to contain exosomes. In the present report we describe tears from advanced breast-cancer patients. Materials and Methods: We found oncogenic miRNAs in the exosomes isolated from tear fluids obtained from five patients with metastatic breast cancer and compared them with tear exosomes form eight healthy volunteers. Results: Tear exosomes had a significantly higher quantity of exosome markers than serum exosomes (CD9, CD63). Tear exosomes were subjected to quantitative reverse-transcription polymerase reaction (qRT-PCR), and western blot analysis to elucidate the status of miRNAs, previously reported in serum from patients with metastatic breast cancer. qRT-PCR and western-blot analysis revealed that breast-cancer-specific miR-21 and miR-200c were highly expressed in tear exosomes from metastatic breast cancer patients in contrast to tear exosomes from healthy volunteers. Conclusion: Tear exosomes can be a potential source of diagnostic and prognostic biomarkers for metastatic breast cancer, and possibly other cancers or diseases.Exosomes are nanometer-sized (30-150 nm) extracellular vesicles that are secreted from various cells and may carry proteins, lipids, miRNAs and mRNAs within them (1, 2). In recent years, exosomes have been highlighted as an important biomarker for various diseases and mediators for cell-to-cell communication during progression, invasion, metastasis, and recurrence in many cancers (3-5). Exosomes are found in various body fluids such as plasma, serum, urea, saliva, and tears (6-9). Therefore, exosomes hold potential for being biomarkers for early detection of diseases and their prognosis. Among all body fluids, tears are the most suitable source for exosome isolation because they have less protein and debris when compared to blood and can be isolated noninvasively.Previously, tear exosomes have been used for the diagnosis of eye diseases (10). The present report is the first to characterize tear exosomes from cancer patients. Previously there was one report that characterized tear exosomes in multiple sclerosis (11). Due to the ease of tear collection and its non-invasive nature, we explored the potential of tears for breast cancer. We isolated tear exosomes from metastatic breast cancer patients and normal volunteers and analyzed oncogenic miRNAs, such as miR-21, 200c, 1246, 17-5p and 373, that have previously been detected in serum exosomes of breast cancer patients (Table I). Our results showed that exosomes from tears of breast cancer patients can be a potential source of cancer biomarkers. Materials and MethodsStudy population. We recruited 5 patients with metastatic breast cancer (mean age=58.6 years; age range=44-73 years) and 8 healthy volunteers (mean age=27 years; age range=21-38 years) (Table II) and collected their tear samples. Four out of five patients had di...