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Dynamic Landscape of Extracellular Vesicle-Associated Proteins Is Related to Treatment Response of Patients with Metastatic Breast Cancer

ABSTRACT: Breast cancer is the leading cause of cancer death in women. The majority of these deaths are due to disease metastasis, in which cancer cells disseminate to multiple organs and disrupt vital physi-ological functions. It is widely accepted that breast cancer cells secrete extracellular vesicles (EVs), which contain dynamic molecular cargo that act as versatile mediators of intercellular communication. Therefore, EVs secreted by breast cancer cells could be involved in the development of metastatic disease and resistance to treatment. Moreover, changes in EV cargo could reflect the effects of therapy on their parent tumor cells. The aim of this feasibility study was to quantitatively profile the proteomes of EVs isolated from blood samples taken from treatment sensitive and resistant metastatic breast cancer patients to identify proteins associated with responses. Three serial blood samples were collected from three patients with metastatic breast cancer receiving systemic therapy including a responder, a non-responder, and a mixed-responder. EVs were isolated from plasma using size exclusion chromatography and their protein cargo was prepared for tandem mass tag (TMT)-labelling and quantitative analyses using two-dimensional high-performance liquid chromatography followed by tandem mass spectrometry. After filtering, we quantitatively identified 286 proteins with high confidence using a q value of 0.05. Of these, 149 were classified as EV associated candidate proteins and 137 as classical, high abundant plasma proteins. After comparing EV protein abundance between the responder and non-responder, we identified 35 proteins with unique deregulated abundance patterns that was conserved at multiple time points. We propose that this proof-of-concept approach can be used to identify proteins which have potential as predictors of metastatic breast cancer response to treatment.

INSTRUMENT(S): Q Exactive Plus

ORGANISM(S): Homo Sapiens (ncbitaxon:9606)

SUBMITTER: Katie Meehan Matthew D. Dun

PROVIDER: MSV000087527 | MassIVE | Thu May 27 06:51:00 BST 2021

REPOSITORIES: MassIVE

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Project description:Circulating extracellular vesicles (EVs) contain molecular footprints - lipids, proteins, metabolites, RNA, and DNA - from their cell of origin and may provide non-invasive access for detection, characterization, and monitoring of diseases. Consequently, EV-associated RNA and proteins have gained widespread interest in developing liquid-biopsy assays for cancer. Yet, an integrative proteo-transcriptomic landscape of EVs and a direct comparison with their cell of origin remains relatively unexplored. Here, we report that EVs enrich for distinct molecular cargo and their proteo-transcriptome does not linearly correlate with their cell of origin. Our sub-cellular compartment analyses revealed that EV enrich 2-6 times more cytoskeletal and extracellular proteins, while their donor cells cargo 3-10 times more nuclear and mitochondrial proteins. EVs predominantly enrich (40-60%) for small RNA between ~15-200 nucleotides, which include miRNAs, siRNAs, tRNA, 5S rRNAs, and snRNAs, associated with cell differentiation, development, and Wnt signaling signatures. Finally, our integrated proteo-transcriptomic analyses reveal that EVs are enriched with specific small RNAs (RNY3, vtRNA, and MIRLET-7) and their complementary proteins (YBX1, IGF2BP2, SRSF1/2). These analyses suggest that RNA-protein complexes may constitute a functional interaction network inside EVs to protect and regulate access to EV-RNA. To ensure that our analyses are unbiased and independent of the cell of origin, EV isolation methods, site of experimentation, site of data generation, and methodologies applied for RNAseq and mass spectrometry, we have generated and curated comprehensive datasets of proteomics and transcriptomics from a total of 12 cancer cell lines, their EVs, and prostate cancer patientsÕ serum EVs (A detailed description is provided in Fig. 1). These combined analyses demonstrated that irrespective of the cell of origin and other aforementioned conditions, EVs enrich for distinct RNA and protein signatures that do not linearly correlate with their cell of origin.

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Dynamic Landscape of Extracellular Vesicle-Associated Proteins Is Related to Treatment Response of Patients with Metastatic Breast Cancer

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