BackgroundThe focus of this study is to identify particular microRNA (miRNA) signatures in exosomes derived from plasma of 435 human epidermal growth factor receptor 2 (HER2)-positive and triple-negative (TN) subtypes of breast cancer (BC).MethodsFirst, miRNA expression profiles were determined in exosomes derived from the plasma of 15 TNBC patients before neoadjuvant therapy using a quantitative TaqMan real-time PCR-based microRNA array card containing 384 different miRNAs. Forty-five miRNAs associated with different clinical parameters were then selected and mounted on microRNA array cards that served for the quantification of exosomal miRNAs in 435 BC patients before therapy and 20 healthy women. Confocal microscopy, Western blot, and ELISA were used for exosome characterization.ResultsQuantification of 45 exosomal miRNAs showed that compared with healthy women, 10 miRNAs in the entire cohort of BC patients, 13 in the subgroup of 211 HER2-positive BC, and 17 in the subgroup of 224 TNBC were significantly deregulated. Plasma levels of 18 exosomal miRNAs differed between HER2-positive and TNBC subtypes, and 9 miRNAs of them also differed from healthy women. Exosomal miRNAs were significantly associated with the clinicopathological and risk factors. In uni- and multivariate models, miR-155 (p = 0.002, p = 0.003, respectively) and miR-301 (p = 0.002, p = 0.001, respectively) best predicted pathological complete response (pCR).ConclusionOur findings show a network of deregulated exosomal miRNAs with specific expression patterns in exosomes of HER2-positive and TNBC patients that are also associated with clinicopathological parameters and pCR within each BC subtype.Electronic supplementary materialThe online version of this article (10.1186/s12916-018-1163-y) contains supplementary material, which is available to authorized users.

Specific microRNAs (miRNAs) are packaged in exosomes that regulate processes in tumor development and progression. The current study focuses on the influence of exosomal miRNAs in the pathogenesis of epithelial ovarian cancer (EOC). MiRNA profiles were determined in exosomes from plasma of 106 EOC patients, eight ovarian cystadenoma patients, and 29 healthy women by TaqMan real‐time PCR‐based miRNA array cards containing 48 different miRNAs. In cell culture experiments, the impact of miR‐200b and miR‐320 was determined on proliferation and apoptosis of ovarian cancer cell lines. We report that miR‐21 (P = 0.0001), miR‐100 (P = 0.034), miR‐200b (P = 0.008), and miR‐320 (P = 0.034) are significantly enriched, whereas miR‐16 (P = 0.009), miR‐93 (P = 0.014), miR‐126 (P = 0.012), and miR‐223 (P = 0.029) are underrepresented in exosomes from plasma of EOC patients as compared to those of healthy women. The levels of exosomal miR‐23a (P = 0.009, 0.008) and miR‐92a (P = 009, 0.034) were lower in ovarian cystadenoma patients than in EOC patients and healthy women, respectively. The exosomal levels of miR‐200b correlated with the tumor marker CA125 (P = 0.002) and patient overall survival (P = 0.019). MiR‐200b influenced cell proliferation (P = 0.0001) and apoptosis (P < 0.008). Our findings reveal specific exosomal miRNA patterns in EOC and ovarian cystadenoma patients, which are indicative of a role of these miRNAs in the pathogenesis of EOC.

Background Genome-wide DNA methylation profiling has recently been developed into a tool that allows tumor classification in central nervous system tumors. Extracellular vesicles (EVs) are released by tumor cells and contain high molecular weight DNA, rendering EVs a potential biomarker source to identify tumor subgroups, stratify patients and monitor therapy by liquid biopsy. We investigated whether the DNA in glioblastoma cell-derived EVs reflects genome-wide tumor methylation and mutational profiles and allows non-invasive tumor subtype classification. Methods DNA was isolated from EVs secreted by glioblastoma cells as well as from matching cultured cells and tumors. EV-DNA was localized and quantified by direct stochastic optical reconstruction microscopy. Methylation and copy number profiling was performed using 850k arrays. Mutations were identified by targeted gene panel sequencing. Proteins were differentially quantified by mass spectrometric proteomics. Results Genome-wide methylation profiling of glioblastoma-derived EVs correctly identified the methylation class of the parental cells and original tumors, including the MGMT promoter methylation status. Tumor-specific mutations and copy number variations (CNV) were detected in EV-DNA with high accuracy. Different EV isolation techniques did not affect the methylation profiling and CNV results. DNA was present inside EVs and on the EV surface. Proteome analysis did not allow specific tumor identification or classification but identified tumor-associated proteins that could potentially be useful for enriching tumor-derived circulating EVs from biofluids. Conclusions This study provides proof of principle that EV-DNA reflects the genome-wide methylation, CNV and mutational status of glioblastoma cells and enables their molecular classification.