Abstract 2765: Extracellular vesicle (EV) RNA transcriptome analysis: An optimized RNA-Seq workflow reveals distinctive transcript structures

Abstract Introduction: Extracellular vesicles (EVs) are crucial membrane-bound particles containing DNA, RNA, proteins, metabolites, and bioactive molecules, which serve as conduits for essential cell-to-cell communication. EV RNA studies often focus on miRNAs due to their prevalence, potentially overlooking non-miRNA transcripts. A wide array of RNA species are found in EVs, including long non-coding RNAs (lncRNAs), messenger RNAs (mRNAs), and small non-coding RNAs (sncRNAs); many linked to disease. To gain molecular insights into the EV transcriptome, we devised a novel protocol for isolating EV RNA, enabling comprehensive RNA-Sequencing (RNA-Seq) profiling. Methods: We used six cell lines (A549, Jurkat, MCF-7, HeLa, HEK293, and NTERA-2) to demonstrate our workflow and results. Our protocol involves EV precipitation from a minimal volume (1.4mL) of conditioned cell culture media prepared with exosome-depleted FBS, followed by EV lysis using SingleShot Cell Lysis reagent which preserves RNAs of all sizes. In each experiment, cellular RNA from the source cells was prepared as a control. Whole transcriptome libraries were constructed using the SEQuoia Complete Stranded RNA Library Prep Kit with ten microliters of EV RNA lysate. Libraries were sequenced on the Illumina NextSeq 1000. After secondary sequence analysis, we visualized transcript differences in EV and cellular transcripts on the UCSC genome browser. Novel qPCR assays were developed as an orthogonal method to confirm the transcript structure observations. Results: Our EV RNA-Seq workflow identified diverse RNA biotypes, including miRNAs and numerous sncRNAs in both cellular and EV transcriptomes. Notably, within EVs, our study revealed distinct structural configurations in many sncRNA transcripts that were not observed in the originating cell lines. These novel structural findings were confirmed using 1-step quantitative reverse transcription polymerase chain reaction (RT-qPCR) with custom assays designed for several transcripts. These findings are consistent across tested cell lines and other methods of EV and EV RNA isolation. Discussion and Conclusion: Many sncRNAs which we observed to have unique transcript structures are known components of ribonucleoprotein (RNP) complexes. Given their proposed role in cell-to-cell communication, we hypothesize that the pivotal element of EVs in intercellular communication may be the incorporation of these unique RNA transcripts as components of the RNP complex. Our efficient EV RNA-Seq workflow reduces sample handling, preserves RNA samples and allows for detection of RNAs of varying sizes. This will allow researchers to uncover the complex landscape of the EV transcriptome. Citation Format: Srikanth Perike, Angelica Olcott, Cissy Jiang, Linda Lingelbach, Elizabeth Dreskin. Extracellular vesicle (EV) RNA transcriptome analysis: An optimized RNA-Seq workflow reveals distinctive transcript structures [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 2765.