Figure 4: miRNA-seq on eMVs isolated from 2 different breast cancer cell lines (MCF7 and MDB231) with ultracentrifugation or Vn peptide isolation methods. A) Scatter plot comparing expression profiles of miRNAs contained in eMVs from MCF7 vs MDB231 and isolated by ultracentrifugation. B) Scatter plot comparing expression profiles of miRNAs contained in eMVs from MCF7 vs MDB231 and isolated by Vn peptide method. C) Venn diagram comparing miRNA expression between eMVs isolated from MCF7 and MDB 231, and between ultracentrifugation and Vn peptide methods. D) Venn diagram showing miRNA expression between eMVs isolated with Vn peptide only and from MCF7 and MDB 231. We could visualize a higher dispersion in scatter plots and venn diagrams for the reason that we compared two different cell lines presenting a differential expression in miRNA. We could also observe that differential expressions of miRNA between cell lines are similar even if we used 2 different isolation methods. Figure 5: RNA species contained in eMVs isolated by ultracentrifugation or Vn peptide method and produced by breast cancer cell line MDB231. The figure B) is an enlargement of figure A) in order to facilitate the visualization of less abundant RNA species. Proportions of RNA species are similar between isolation methods used. We also observed an enrichment of some RNA species in eMVs compared to RNA species contained in a standard cell. (rRNA represent around 1% of all RNA in eMVs while in a cell more than 90% of RNA are rRNA). Comparative Omics of extracellular microvesicles isolated using Vn* affinity peptides © Nicolas Crapoulet, Simi Chacko, Michelle Caissie, Steve Griffiths, Daniel Leger, Ian Chute, Michelle Davey, David Barnett, Sarah Melville, Awanit Kumar, Sebastien Fournier, Rodney Ouellette and Anirban Ghosh. Atlantic Cancer Research Institute, Moncton, New Brunswick, Canada Introduction We have engineered and validated a synthetic peptide (Vn96) with specific affinity for canonical heat shock proteins (HSPs) as a tool for rapid isolation and purification of HSP- containing extracellular microvesicles (eMVs). In most cancers HSP expression is exceptionally high (chaperonopathies) and found on the surface of their secreted eMVs. Thus, our method isolates cancer specific- eMVs of highest clinical value and also compares favourably in terms of efficiency, cost and platform-versatility. As part of the validation process for Vn peptides, we performed comparative genomic and proteomic characterizations of the eMV subsets obtained by Vn affinity protocol with those from established protocols such as ultracentrifugation and a commercial isolation reagent. The compatibility of Vn affinity technology with such downstream “omics” applications as next-generation sequencing (NGS) and mass spectrometry (MS) is essential for its ultimate use in the search for clinical biomarkers present in eMVs. Materials and Methods eMV isolates from conditioned media of breast cancer cell lines using Vn96 peptide were compared to those obtained by ultracentrifugation or using a commercial purification reagent. RNA samples isolated from eMVs were subsequently processed for NGS on the Ion Torrent and Proton platforms and also in parallel for hybridization to human microarrays. Total protein from eMV isolates was purified and analyzed by MS. Results Analysis of the protein profiles of eMV isolates by MS demonstrated the presence of classical eMV markers in samples isolated by Vn96 as well as the similarities of these samples to those isolated by ultracentrifugation (UCF) or commercial purification reagents. Table 1: MS results obtained from 3 different eMVs isolation methods. Proteins extracted from eMVs produced by human breast cancer MDB231 cells were resolved on SDS-PAGE and subsequently subjected to in-gel tryptic digestion, followed by analysis on nanoLC/MS-MS. MS results were interpreted with Scaffold 3 software. We could observe that we were able to identify the same set of proteins in eMVs isolated either with the ultracentrifugation method, the commercial isolation reagent or our Vn peptide method. MS results suggest also that eMV contains enzymes (shown in red) that could lead to the modification of an eMV recipient cell. RNA profiles of the eMV isolates were analyzed by NGS and microarray (data not shown), again showing similar patterns between the purification protocols. RNA and protein profiles were most consistent in the samples isolated from conditioned media, as expected, given that these represent more homogeneous populations of eMVs. Figure 3: microRNA profiling of eMVs produced in breast cancer MCF7 cells and isolated with 3 different methods. A) Scatter plot matrix of the miRNA fold change estimated between each eMV isolation methods. Dashed lines represent a 2-fold change in miRNA expression between compared samples. We could observed a good Pearson correlation between each isolation methods and the majority of miRNA identified presents a variation lower than 2 fold change. B) Venn diagram realized on miRNA profiling demonstrate, in correlation with scatter plots, that eMVs isolation methods are highly similar with less than 5% of variability. In addition, we could observe that Vn peptide method permits to identify 13 additional miRNAs compare to ultracentrifugation or commercial isolation methods. Conclusions eMV subsets isolated using the Vn96 peptide are very similar and share many of the recognized eMV markers with those isolated by established methods, at the genomic and proteomic level. Abstract Reference: Abstract No: 297 Protein Identification Probability Gene NameGene symbolUniprot IDUCF Commercial Reagent VN96 Fibronectin 1FN1P % Galectin-3-binding proteinLGALS3BPQ % AlbuminALBP % Actin betaACTBP % Histone H2AHIST1H2AHQ96KK5 100% Phosphoglycerate kinase 1PGK1P % Alpha-enolase 1ENO1P % Glyceraldehyde-3-phosphate dehydrogenaseGAPDHP % VimentinVIMP08670 NA100% Integrin beta-1ITGB1P % Isoform 2 of Annexin A2ANXA2P % Collagen alpha-1(VI) chainCOL6A1P %100%88% Pyruvate kinase isozymes M1/M2PKM2P % Histone H2BHIST1H2BCP % Alpha-2-macroglobulinA2MP %83%NA Cystatin-SCST4P % L-lactate dehydrogenase ALDHAP % Mucin 5BMUC5BQ9HC84 100%83%88% Heat shock protein HSP 90-betaHSP90AB1P % MoesinMSNP % Figure 2: Flowchart for the analysis of the high- throughput sequencing data for profiling RNA and microRNA expression. RNA libraries prepared from eMVs isolated with different methods were sequenced either on PGM or Proton platforms (Life Technologies). Normalization of long RNA was realized with Reads Per Kilobase per Million mapped reads (RPKM) and small-RNA were normalized with Trimmed Mean of M- values (TMM) or Lowess methods. AB AB A B C D Acknowledgments: ACRI is grateful for funding provided by the Atlantic Innovation Fund and for the contribution of New England Peptide Inc. References: -Théry, C., Amigorena, S., Raposo, G., & Clayton, A. (2006). Isolation and characterization of exosomes from cell culture supernatants and biological fluids. Current Protocols in Cell Biology, Taylor, D. D., & Gercel-Taylor, C. (2008). MicroRNA signatures of tumor-derived exosomes as diagnostic biomarkers of ovarian cancer. Gynecologic oncology, 110(1), Trapnell, C., Pachter, L., & Salzberg, S. L. (2009). TopHat: discovering splice junctions with RNA-Seq. Bioinformatics, 25(9), Emde, A. K., Grunert, M., Weese, D., Reinert, K., & Sperling, S. R. (2010). MicroRazerS: rapid alignment of small RNA reads. Bioinformatics, 26(1), *Vn96 patent pending Figure 1: Vn96 affinity protocol for exosome isolation.