Characterization and Comparison of Mesenchymal Stem Cell-Derived Exosome Isolation Methods using Culture Supernatant

Exosomes are extracellular endosomal nanoparticles, which are formed under complex processes during the formation of multivesicular bodies. They are also achieved from conditioned media of a variety of cell types, especially mesenchymal stem cells (MSCs). Exosomes can modulate intracellular physiological actions via signaling molecules on the surface or secretion of components to the extracellular spaces. Furthermore, they are potentially used as crucial agents for cell-free therapy; however, their isolation and characterization can be challenging. In the current study, two methods of exosome isolation have been characterized and compared using a culture media of adipose-derived mesenchymal stem cells, namely ultracentrifugation and a commercial kit; moreover, the efficiency of these two methods was highlighted in this study. Two different isolation methods of exosomes from MSCs were used to compare the efficiency of exosomes. For both isolation methods, transmission electron microscopy, dynamic light scattering (DLS), and bicinchoninic acid (BCA) assay have been performed. The electron microscopy and DLS indicated the presence of exosomes. Moreover, the kit and ultracentrifugation isolates contained approximately comparable amounts of protein measured by the BCA. Overall, the two isolation methods had similar performances. Although ultracentrifugation is used as a gold standard for exosome isolation, the commercial kit has some advantages and can be applied alternatively according to its cost-effectiveness and time-saving properties.

Novel lncRNAs with diagnostic or prognostic value screened out from breast cancer via bioinformatics analyses

Background

Recent studies have shown that long non-coding RNAs (lncRNAs) may play key regulatory roles in many malignant tumors. This study investigated the use of novel lncRNA biomarkers in the diagnosis and prognosis of breast cancer.

Materials and Methods

The database subsets of The Cancer Genome Atlas (TCGA) by RNA-seq for comparing analysis of tissue samples between breast cancer and normal control groups were downloaded. Additionally, anticoagulant peripheral blood samples were collected and used in this cohort study. The extracellular vesicles (EVs) from the plasma were extracted and sequenced, then analyzed to determine the expressive profiles of the lncRNAs, and the cancer-related differentially expressed lncRNAs were screened out. The expressive profiles and associated downstream-mRNAs were assessed using bioinformatics (such as weighted correlation network analysis (WGCNA), Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genome (KEGG) enrichments, Receiver-Operating Characteristic (ROC) curve and survival analysis, etc.) to investigate the diagnostic and prognostic values of these EV lncRNAs and their effectors.

Results

In this study, 41 breast cancer-related lncRNAs were screen out from two datasets of tissue and fresh collected plasma samples of breast cancer via the transcriptomic and bioinformatics techniques. A total of 19 gene modules were identified with WGCNA analysis, of which five modules were significantly correlated with the clinical stage of breast cancer, including 28 lncRNA candidates. The ROC curves of these lncRNAs revealed that the area under the curve (AUC) of all candidates were great than 70%. However, eight lncRNAs had an AUC >70%, indicating that the combined one has a good diagnostic value. In addition, the results of survival analysis suggested that two lncRNAs with low expressive levels may indicate the poor prognosis of breast cancer. By tissue sample verification, C15orf54, AL157935.1, LINC01117, and SNHG3 were determined to have good diagnostic ability in breast cancer lesions, however, there was no significant difference in the plasma EVs of patients. Moreover, survival analysis data also showed that AL355974.2 may serve as an independent prognostic factor and as a protective factor.

Conclusion

A total of five lncRNAs found in this study could be developed as biomarkers for breast cancer patients, including four diagnostic markers (C15orf54, AL157935.1, LINC01117, and SNHG3) and a potential prognostic marker (AL355974.2).