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.

Current perspectives on clinical use of exosomes as novel biomarkers for cancer diagnosis

“…Furthermore, the six molecules in emRNA including CDC42, IL32, MAX, NCF2, PDGFA and SRSF2 were upregulated in the screening and diagnosis of PCa patients compared to healthy controls ( 195 ). Similarly, Shephard et al ( 88 ) said that serum-derived EV-mRNA has great potential for the differential diagnosis of prostate cancer. Among these, increased serum-derived EV-mRNA CTGF molecule or decreased EV-mRNA CAV1 molecule were closely associated with the rate of disease progression, and the AUC values of CTGF and CAV1 were 0.8600 and 0.8100 respectively.…”

“…Among these, increased serum-derived EV-mRNA CTGF molecule or decreased EV-mRNA CAV1 molecule were closely associated with the rate of disease progression, and the AUC values of CTGF and CAV1 were 0.8600 and 0.8100 respectively. However, serum PSA could not predict disease progression, suggesting that EV-mRNA CTGF and CAV1 are superior to PSA in predicting disease progression ( 88 ). Another study proved that mRNA index of membrane matrix type 1 metalloproteinase (MT1-MMP) was significantly up-regulated in gastric cancer (GC) patients, with an AUC of 0.788, sensitivity of 63.9% and specificity of 87.1%, while the AUC value of serum CEA was only 0.655.…”

Extracellular vesicle isolation, purification and evaluation in cancer diagnosis

“…In addition, not all prostate cancer cases show elevated level of PSA in which 30% of men reach a false negative rate with PSA lower that 4 ng/ml (Ref. 73). It is also not applicable to link a specific rate of PSA level in patients with metastatic prostate cancer (Ref.…”

“…CD9, CD63 and CD81 are all expressed in EVs derived from both prostate cancer stroma and the adjacent normal stroma with only low differences in their overall levels in EVs harvested from the two sources (Ref. 73). Anti-CD63 antibody can be used for capturing exosomes isolated by size-exclusion chromatography (SEC), as implemented for patients with head and neck cancer (Ref.…”

Integrins are enriched on aberrantly fucosylated tumour‐derived urinary extracellular vesicles

“…The use of extracellular vesicles (EVs) as cancer biomarkers has received unprecedented interest in the past decade. EVs can be detected directly from biological fluids, including blood and urine, providing easily accessible biomarkers for early diagnostics (Shephard et al., 2021) and disease monitoring (Ma et al., 2019; Zhou et al., 2020). The analysis of the biomolecular composition of the EV cargo by sampling biological fluids has led to the identification of exceptionally disease‐specific biomarkers (Zhang et al., 2019).…”