Decoding Individual Exosomes in Cancer

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PROJECT SUMMARY There is increasing recognition that extracellular vesicles (EVs)¾micrometer- or nanometer-sized lipid particles containing protein and nucleic acid cargoes (information)¾are highly promising for new diagnostics/prognostics and even have therapeutic value. There is, however, an unmet need for methods able to solve a fundamental problem confounding the exploitation of EV information in biology and medicine¾EVs are naturally highly heterogeneous particles. In this pilot (R21) project, our experimental goal is to address the need for analyzing EV heterogeneity (subpopulations) by focusing on particles called exosomes. Specifically, our new technology platform is designed to address the problem of resolving bulk exosomal subpopulations by directly correlating surface protein and nucleic acid (microRNA or miRNA) cargoes of single exosomes by performing highly multiplexed fluorescence imaging analysis. Our ultimate goal is to develop a unique imaging platform for the high-throughput, high-content analysis of the protein and nucleic acid cargoes of single exosomes (and other EVs) obtained from any biological sample. This new platform could enable novel diagnostic/prognostic “liquid biopsy” tests for managing cancers as well as other pathologies, such as neurodegenerative and cardiovascular diseases. To achieve our experimental goal, in the work for Aims 1 and 2 we will develop and optimize our imaging platform for experimental multiplexed analysis of human breast cancer cell exosomes and their miRNA cargoes. These Aims will validate our platform for in situ miRNA analysis of single exosomes from cancer cells with documented exosomal miRNA signatures. During Aim 3, we will use the validated platform to correlate the surface protein display and miRNA cargo of individual exosomes released by human breast cancer cell lines representing early- and late-stage cancers and compare these with a normal cell line control. Aim 3 will test the capability of our platform to resolve exosomal subpopulations in an original bulk sample, based on correlated signals for surface proteins and miRNA cargoes of single exosomes. We propose that our novel imaging platform has the potential to become a new diagnostic/prognostic tool for the clinical management of breast cancer, other tumor types, and other pathologies in which EV/exosomal analysis could provide clinically useful information. Recent research demonstrates that breast-cancer-cell- derived exosomes can transport cargoes that promote oncogenic or malignant phenotypes. Thus, exosomes released from breast tumors could carry information with critical diagnostic/prognostic value, which could be sampled from blood or other patient fluids (a “liquid biopsy”). This capability may also assist in developing exosome-based therapies for human tumor types.