Abstract 6709: Utility of RNA sequencing for transcriptome analysis of small extracellular vesicles derived from blood sera of colorectal cancer patients

Introduction: Currently used molecular diagnostic tests for colorectal cancer (CRC) are underperforming and more sensitive, non-invasive biomarkers are needed. Long non-coding RNAs (lncRNA) and microRNA (miRNA) have shown potential as diagnostic biomarkers. Unfortunately, the identification of non-coding RNA circulating biomarkers in blood serum is significantly burdened by abundant RNA specimens from disrupted blood cells. Recently, small extracellular vesicles (sEVs) emerged as potential reservoirs of clinically relevant biomarkers, including lncRNAs and miRNAs. In theory, sEVs protect RNAs from degradation and might serve as a source of intact RNA for further analyses. However, there is a lack of evidence supporting the superior quality of RNA extracted from sEVs over RNA from whole blood serum. This study aimed to analyze the RNA content of blood serum and the sEVs derived from the blood serum of CRC patients and healthy controls using RNA sequencing. Moreover, small RNA sequencing was used to evaluate the difference in miRNA profiles of sEVs and corresponding blood sera of CRC patients and healthy controls. Methods: Spin-column chromatography (Exiqon), precipitation-based method (Norgen), and size-exclusion chromatography (iZON) were used to extract sEVs from blood sera. The concentration of sEVs was measured by dynamic light scattering (DLS), the size was evaluated by electron microscopy (EM), and sEV-specific content was analyzed by western blot and qRT-PCR. RNA was extracted using the column-based method. Next-generation sequencing (NGS) analyses of blood serum and sEVs extracted from blood serum included samples from 10 CRC patients and 10 healthy controls for RNAseq, and 5 CRC patients and 5 healthy controls for small RNAseq. Differential expression analysis was carried out in R using DESeq2 package. Results: DLS and EM showed that size-exclusion chromatography yielded the purest population of sEVs characterized according to ISEV recommendations. Extraction of sEVs and subsequent RNA extraction and sequencing library preparation from ultra-low input samples were optimized. Over 30k different RNAs were identified in the sEVs derived from blood sera of CRC patients and healthy controls, including lncRNAs, miRNAs, and protein-coding RNAs. A detailed comparison of the transcriptome of blood sera and corresponding sEVs is a part of the poster. Conclusion: sEVs could serve as a source of RNA biomarkers; however, proper characterization and optimal meth