Defining the relationship between cellular and extracellular vesicle content in breast cancer via an integrative multi-omic analysis

Much recent research has been dedicated to exploring the utility of extracellular vesicles (EVs) as circulating disease biomarkers. Underpinning this work is the assumption that the molecular cargo of EVs directly reflects the originating cell. Few attempts have been made, however, to empirically validate this on the -omic level. To this end, researchers at the University of Queensland have performed an integrative multi-omic analysis of a panel of breast cancer cell lines and corresponding EVs. Whole transcriptome analysis validated that the cellular transcriptome remained stable when cultured cells are transitioned to low serum or serum-free medium for EV collection. Transcriptomic profiling of the isolated EVs indicated a positive correlation between transcript levels in cells and EVs, including disease-associated transcripts. Analysis of the EV proteome verified that HER2 protein is present in EVs, however neither the estrogen (ER) nor progesterone (PR) receptor proteins are detected regardless of cellular expression. Using multivariate analysis, the researchers derived an EV protein signature to infer cellular patterns of ER and HER2 expression, though the ER protein could not be directly detected. Integrative analyses affirmed that the EV proteome and transcriptome captured key phenotypic hallmarks of the originating cells, supporting the potential of EVs for non-invasive monitoring of breast cancers.

Exploratory analysis of RNA sequencing data from breast cancer cell-derived EVs

(A) Log2 normalised expression of ESR1, PGR and ERBB2 transcripts in each sample, (B) principal component analysis (PCA) plot of RNA expression data. Each bar represents a single sample, colours represent cellular ER and HER2 expression. (C) Volcano plots (−log10 p value against log2 fold-change) of differential transcript expression between EVs derived from (i) ER+ vs. ER−, (ii) HER2+ vs. HER2− and (iii) triple negative (TNBC) vs. non-TNBC cell lines. Each point represents a single protein. Grey represents no significant expression difference, colour (turquoise, purple or red, respectively) represents a significant expression difference (adjusted p value <0.05). A subset of differentially expressed genes of interest are labelled with gene symbol, along with the ESR1 (ER), PGR (PR) and ERBB2 (HER2) transcripts. (D) Heatmap showing unsupervised hierarchical clustering of samples based on normalised expression of transcripts in the PAM50/ProSigna subtyping signature described in ref. [45]. Distance measure for clustering of both rows and columns was Pearson’s correlation.

Lane RE, Korbie D, Khanna KK, Mohamed A, Hill MM, Trau M. (2024) Defining the relationship between cellular and extracellular vesicle (EV) content in breast cancer via an integrative multi-omic analysis. Proteomics [Epub ahead of print]. [article]

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