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Stroma-derived extracellular vesicle mRNA signatures inform histological nature of prostate cancer.

ABSTRACT: Histological assessment of prostate cancer is the key diagnostic test and can predict disease outcome. This is however an invasive procedure that carries associated risks, hence non-invasive assays to support the diagnostic pathway are much needed. A key feature of disease progression, and subsequent poor prognosis, is the presence of an altered stroma. Here we explored the utility of prostate stromal cell-derived vesicles as indicators of an altered tumour environment. We compared vesicles from six donor-matched pairs of adjacent-normal versus disease-associated primary stromal cultures. We identified 19 differentially expressed transcripts that discriminate disease from normal stromal extracellular vesicles (EVs). EVs isolated from patient serum were investigated for these putative disease-discriminating mRNA. A set of transcripts including Caveolin-1 (CAV1), TMP2, THBS1, and CTGF were found to be successful in discriminating clinically insignificant (Gleason = 6) disease from clinically significant (Gleason > 8) prostate cancer. Furthermore, correlation between transcript expression and progression-free survival suggests that levels of these mRNA may predict disease outcome. Informed by a machine learning approach, combining measures of the five most informative EV-associated mRNAs with PSA was shown to significantly improve assay sensitivity and specificity. An in-silico model was produced, showcasing the superiority of this multi-modal liquid biopsy compared to needle biopsy for predicting disease progression. This proof of concept highlights the utility of serum EV analytics as a companion diagnostic test with prognostic utility, which may obviate the need for biopsy.

SUBMITTER: Shephard AP

PROVIDER: S-EPMC8485336 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Tumour-derived extracellular vesicles (EVs) play a role in tumour progression; however, the spectrum of molecular mechanisms regulating EV secretion and cargo selection remain to be fully elucidated. We have reported that cavin-1 expression in prostate cancer PC3 cells reduced the abundance of a subset of EV proteins, concomitant with reduced xenograft tumour growth and metastasis. We examined the functional outcomes and mechanisms of cavin-1 expression on PC3-derived EVs (PC3-EVs). PC3-EVs were internalized by osteoclast precursor RAW264.7 cells and primary human osteoblasts (hOBs) in vitro, stimulating osteoclastogenesis 37-fold and hOB proliferation 1.5-fold, respectively. Strikin gly, EVs derived from cavin-1-expressing PC3 cells (cavin-1-PC3-EVs) failed to induce multinucleate osteoblasts or hOB proliferation. Cavin-1 was not detected in EVs, indicating an indirect mechanism of action. EV morphology, size and quantity were also not affected by cavin-1 expression, suggesting that cavin-1 modulated EV cargo recruitment rather than release. While cavin-1-EVs had no osteoclastogenic function, they were internalized by RAW264.7 cells but at a reduced efficiency compared to control EVs. EV surface proteins are required for internalization of PC3-EVs by RAW264.7 cells, as proteinase K treatment abolished uptake of both control and cavin-1-PC3-EVs. Removal of sialic acid modifications by neuraminidase treatment increased the amount of control PC3-EVs internalized by RAW264.7 cells, without affecting cavin-1-PC3-EVs. This suggests that cavin-1 expression altered the glycosylation modifications on PC3-EV surface. Finally, cavin-1 expression did not affect EV in vivo tissue targeting as both control and cavin-1-PC3-EVs were predominantly retained in the lung and bone 24 hours after injection into mice. Taken together, our results reveal a novel pathway for EV cargo sorting, and highlight the potential of utilizing cavin-1-mediated pathways to attenuate metastatic prostate cancer.

Project description:Extracellular vesicles (EVs) are biological vectors that can modulate the metabolism of target cells by conveying signalling proteins and genomic material. The level of EVs in plasma is significantly increased in cardiometabolic diseases associated with obesity, suggesting their possible participation in the development of metabolic dysfunction. With regard to the poor definition of adipocyte-derived EVs, the purpose of this study was to characterise both qualitatively and quantitatively EVs subpopulations secreted by fat cells. Adipocyte-derived EVs were isolated by differential centrifugation of conditioned media collected from 3T3-L1 adipocytes cultured for 24 h in serum-free conditions. Based on morphological and biochemical properties, as well as quantification of secreted EVs, we distinguished two subpopulations of adipocyte-derived EVs, namely small extracellular vesicles (sEVs) and large extracellular vesicles (lEVs). Proteomic analyses revealed that lEVs and sEVs exhibit specific protein signatures, allowing us not only to define novel markers of each population, but also to predict their biological functions. Despite similar phospholipid patterns, the comparative lipidomic analysis performed on these EV subclasses revealed a specific cholesterol enrichment of the sEV population, whereas lEVs were characterised by high amounts of externalised phosphatidylserine. Enhanced secretion of lEVs and sEVs is achievable following exposure to different biological stimuli related to the chronic low-grade inflammation state associated with obesity. Finally, we demonstrate the ability of primary murine adipocytes to secrete sEVs and lEVs, which display physical and biological characteristics similar to those described for 3T3-L1. Our study provides additional information and elements to define EV subtypes based on the characterisation of adipocyte-derived EV populations. It also underscores the need to distinguish EV subpopulations, through a combination of multiple approaches and markers, since their specific composition may cause distinct metabolic responses in recipient cells and tissues.

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Stroma-derived extracellular vesicle mRNA signatures inform histological nature of prostate cancer.

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