The potential role of serum extracellular vesicle derived small RNAs in AML research as non-invasive biomarker

Abstract

Background: Extracellular vesicles (EV) are cell-derived vesicles released by all cells in health and disease. Accordingly, EVs are also released by cells in acute myeloid leukemia (AML), a hematologic malignancy characterized by uncontrolled growth of immature myeloid cells, and these EVs likely carry markers and molecular cargo reflecting the malignant transformation occurring in diseased cells. Monitoring antileukemic or proleukemic processes during disease development and treatment is essential. Therefore, EVs and EV-derived microRNA (miRNA) from AML samples were explored as biomarkers to distinguish disease-related patterns ex vivo or in vivo.

Methodology: EVs were purified from serum of healthy (H) volunteers and AML patients by immunoaffinity. EV surface protein profiles were analyzed by multiplex bead-based flow cytometry (MBFCM) and total RNA was isolated from EVs prior to miRNA profiling via small RNA sequencing.

Results: MBFCM revealed different surface protein patterns in H versus AML EVs. miRNA analysis showed individual as well as highly dysregulated patterns in H and AML samples.

Conclusions: In this study, we provide a proof-of-concept for the discriminative potential of EV derived miRNA profiles as biomarkers in H versus AML samples.

Fig. 1. Characterization of serum derived EVs from H and AML samples by MBFCM. MBFCM allows the detection of EVs (co-) expressing 37 different antigens in a semi-quantitative manner. Results (median APC fluorescence intensities) detected by MBFCM in H (left side, (A)) and AML (right side, (B)) serum samples are displayed. Results are given as mean ± SD.

Fig. 2. Quantification and comparison of EV surface marker expressions from serum derived EVs in H and AML samples with MBFCM. Serum samples were analyzed by multiplex bead-based flow cytometry (MBFCM). Selected several lineage associated EV marker expression on serum from 5 H and 5 AML samples are shown by violin plots (with all individual points) of median APC intensities. Longdash horizontal lines means ‘median data’, dotted horizontal line means ‘quartile data’. For statistical comparison of two groups applying two-way analysis of variance (ANOVA) with Benjamini–Hochberg adjustments were analyzed.

Fig. 3. Small RNA species in serum derived EVs of H and AML samples. Assignment of small RNA sequencing results to different RNA species from isolated EVs in 5 H and 5 AML serum samples: (A) reads mapping to miRNA, tRNA, snoRNA, snRNA and rRNA, (remained) unmapped, short (shorter than 16 nucleotides) and no-adapter (no adapter detectable). (B) Relative frequencies of reads that mapped to miRNA, tRNA, snoRNA, snRNA and rRNA (uncharacterized unmapped reads were excluded). (C) Mapping distribution of RNA reads. (D) Relative mapping distribution of RNA reads (uncharacterized unmapped reads were excluded).

Fig. 4. Profiling and characterization of DESeq2-normalized miRNA data derived from EVs in H and various expression patterns of miRNAs with more than 20 DESeq2-normalized read counts derived from EVs in H and AML serum samples: (A) Venn diagram of distinct miRNA patterns detected in H and AML samples. (B) Heatmap and hierarchical cluster analysis of H from AML samples. (C) Log₂ fold change (FC) of overlapping miRNAs (136) between H and AML samples.

Fig. 5. Selected 10 DESeq2-normalized miRNAs derived from EVs in H and AML serum samples given are up or down regulated miRNAs derived from EVs in AML vs. H serum samples: (A) 5 miRNAs (miR-10a-5p, miR-155-5p, miR-100-5p, miR-146b-5p, let-7a-5p) were up regulated. (B) 5 miRNAs (miR-185-5p, miR-4433b-3p, miR-199a-5p, miR-451a, miR-151a-3p) were down regulated.