Transcriptomic analysis of small extracellular vesicles in metastatic breast cancer

Introduction: Small extracellular vesicles (sEVs) are emerging as a valuable liquid biopsy tool for cancer, complementing cell-free DNA and circulating tumour cells. These nanoscale, membrane-bound particles, secreted by all cell types, carry DNA, RNA, proteins, and lipid cargo that reflect their cellular origin. sEV-RNAs are implicated in cancer progression, metastasis, and therapeutic resistance. We demonstrate a workflow for isolating sEV-RNAs from plasma for RNA sequencing. Methods: We used sensitive MCF7 and fulvestrant-resistant MCF7 (FULVR-MCF7) breast cancer cell lines to optimise a workflow that combines ExoGAG technology for EV isolation with the Ion AmpliSeq™ Transcriptome gene expression kit (AmpliSeq TM ) for profiling sEVs on the Ion Torrent S5XL system. AmpliSeq TM detects 20,802 mRNA targets from low RNA inputs, making it suitable for analysing the limited RNA from sEVs. The ExoGAG-AmpliSeq™ workflow was validated using sEV-RNA samples from the plasma of 5 patients with metastatic breast cancer (mBCa) and 3 healthy female controls. Results: Evaluation of different cell line RNA concentrations (500pg - 10ng) demonstrated that a 1ng RNA input yielded robust sequencing output, with high mapped reads and accurate measurement of AmpliSeq target regions and gene detection comparable to the standard 10ng input. We then applied the workflow to compare ExoGAG-isolated sEV-RNA from exosome-depleted FBS cell culture medium of MCF7 and FULVR-MCF7 cell lines using 1ng RNA input. All samples met library quality control metrics, and sequencing yielded an average of 12 million reads per sample. Technical replicates of MCF7 and FULVR sEVs RNA samples showed minimal variation in raw gene read counts (Pearson's r ≥ 0.95). Differential gene expression analysis using DESeq2 identified 1331 significantly differentially expressed genes (FDR < 0.05), with 680 upregulated and 651 downregulated. Gene Ontology analysis indicated downregulation of sensory perception and metabolite transport pathways, and upregulation of antiviral and immune signalling pathways, including type I interferon and lymphocyte activation. These findings highlight altered intercellular communication associated with drug resistance. In the mBCa patient samples, 248 genes showed significant expression changes, with 83 upregulated and 165 downregulated relative to healthy controls. HLA-B and ENPP1, both associated with EV and exosome biology, and AGAP2, linked to endosomal trafficking for vesicle formation, ranked among the top 10 significant genes. Pathway analysis showed these genes were significantly enriched in biological pathways involved in system development, intracellular signal transduction, and regulation of cellular processes. Conclusions: The ExoGAG-AmpliSeq™ workflow is feasible for recovering and analysing plasma-derived sEV-RNA and developing gene signatures as breast cancer biomarkers.