Dataset Information

Extracellular Vesicle Molecular Signatures Characterize Metastatic Dynamicity in Ovarian Cancer.

ABSTRACT:

Background

Late-stage diagnosis of ovarian cancer, a disease that originates in the ovaries and spreads to the peritoneal cavity, lowers 5-year survival rate from 90% to 30%. Early screening tools that can: i) detect with high specificity and sensitivity before conventional tools such as transvaginal ultrasound and CA-125, ii) use non-invasive sampling methods and iii) longitudinally significantly increase survival rates in ovarian cancer are needed. Studies that employ blood-based screening tools using circulating tumor-cells, -DNA, and most recently tumor-derived small extracellular vesicles (sEVs) have shown promise in non-invasive detection of cancer before standard of care. Our findings in this study show the promise of a sEV-derived signature as a non-invasive longitudinal screening tool in ovarian cancer.

Methods

Human serum samples as well as plasma and ascites from a mouse model of ovarian cancer were collected at various disease stages. Small extracellular vesicles (sEVs) were extracted using a commercially available kit. RNA was isolated from lysed sEVs, and quantitative RT-PCR was performed to identify specific metastatic gene expression.

Conclusion

This paper highlights the potential of sEVs in monitoring ovarian cancer progression and metastatic development. We identified a 7-gene panel in sEVs derived from plasma, serum, and ascites that overlapped with an established metastatic ovarian carcinoma signature. We found the 7-gene panel to be differentially expressed with tumor development and metastatic spread in a mouse model of ovarian cancer. The most notable finding was a significant change in the ascites-derived sEV gene signature that overlapped with that of the plasma-derived sEV signature at varying stages of disease progression. While there were quantifiable changes in genes from the 7-gene panel in serum-derived sEVs from ovarian cancer patients, we were unable to establish a definitive signature due to low sample number. Taken together our findings show that differential expression of metastatic genes derived from circulating sEVs present a minimally invasive screening tool for ovarian cancer detection and longitudinal monitoring of molecular changes associated with progression and metastatic spread.

SUBMITTER: Gonda A

PROVIDER: S-EPMC8637407 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature

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Publications

Extracellular Vesicle Molecular Signatures Characterize Metastatic Dynamicity in Ovarian Cancer.

Gonda Amber A Zhao Nanxia N Shah Jay V JV Siebert Jake N JN Gunda Srujanesh S Inan Berk B Kwon Mijung M Libutti Steven K SK Moghe Prabhas V PV Francis Nicola L NL Ganapathy Vidya V

Frontiers in oncology 20211118

<h4>Background</h4>Late-stage diagnosis of ovarian cancer, a disease that originates in the ovaries and spreads to the peritoneal cavity, lowers 5-year survival rate from 90% to 30%. Early screening tools that can: i) detect with high specificity and sensitivity before conventional tools such as transvaginal ultrasound and CA-125, ii) use non-invasive sampling methods and iii) longitudinally significantly increase survival rates in ovarian cancer are needed. Studies that employ blood-based scree ...[more]

PMID: 34868914

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Project description:BackgroundRecent studies have suggested a crucial role of mesenchymal stem cell (MSC)-derived extracellular vesicles (EVs) in ovarian cancer treatment. We, therefore, set out to explore the mechanism through which MSC-derived EVs delivered microRNA-424 (miR-424) to influence the development of ovarian cancer.MethodsBioinformatics analyses were first performed to screen ovarian cancer-related differentially expressed genes and to predict regulatory miRNAs. Then, dual-luciferase reporter gene assay was carried out to verify the relationship between miR-424 and MYB. Subsequently, the characterized MSCs and isolated EVs were co-cultured with ovarian cancer cells, followed by determination of the expression patterns of miR-424, MYB, vascular endothelial growth factor (VEGF), and VEGF receptor (VEGFR), respectively. In addition, the effects of EVs-delivered miR-424 on the proliferation, migration, invasion and tube formation of ovarian cancer cells were assessed using gain- and loss-of-function approaches. Lastly, tumor xenograft was induced in nude mice to illustrate the influence of EVs-loaded miR-424 on ovarian cancer in vivo.ResultsOur data exhibited that MYB was highly-expressed and miR-424 was poorly-expressed in ovarian cancer. More importantly, MYB was identified as a target gene of miR-424. Additionally, the transfer of miR-424 by MSC-derived EVs was found to repress the proliferation, migration, and invasion of ovarian cancer cells, with a reduction in the expressions of VEGF and VEGFR. Furthermore, MSC-derived EVs over-expressing miR-424 could inhibit the proliferation, migration, and tube formation of human umbilical vein endothelial cells, and also suppressed tumorigenesis and angiogenesis of ovarian tumors in vivo.ConclusionCollectively, our findings indicate that MSC-derived EVs transfer miR-424 to down-regulate MYB, which ultimately led to the inhibition of the tumorigenesis and angiogenesis of ovarian cancer. Hence, this study offers a potential prognostic marker and a therapeutic target for ovarian cancer.

Project description:BackgroundResistance to chemotherapy continues to be a challenge when treating epithelial ovarian cancer (EOC), contributing to low patient survival rates. While CA125, the conventional EOC biomarker, has been useful in monitoring patients' response to therapy, there are no biomarkers used to predict treatment response prior to chemotherapy. Previous work in vitro showed that plasma gelsolin (pGSN) is highly expressed in chemoresistant EOC cell lines, where it is secreted in small extracellular vesicles (sEVs). Whether sEVs from tumour cells are secreted into the circulation of EOC patients and could be used to predict patient chemoresponsiveness is yet to be determined. This study aims to identify if sEV-pGSN in the circulation could be a predictive biomarker for chemoresistance in EOC.MethodsSandwich ELISA was used to measure pGSN concentrations from plasma samples of 96 EOC patients (primarily high grade serous EOC). sEVs were isolated using ExoQuick ULTRA and characterized using western blot, nanoparticle tracking analysis, and electron microscopy after which pGSN was measured from the sEVs. Patients were stratified as platinum sensitive or resistant groups based on first progression free interval (PFI) of 6 or 12 months.ResultsTotal circulating pGSN was significantly decreased and sEV-pGSN increased in patients with a PFI ≤ 12 months (chemoresistant) compared to those with a PFI > 12 months (chemosensitive). The ratio of total pGSN to sEV-pGSN further differentiated these groups and was a strong predictive marker for chemoresistance (sensitivity: 73.91%, specificity: 72.46%). Predetermined CA125 was not different between chemosensitive and chemoresistant groups and was not predictive of chemoresponsiveness prior to treatment. When CA125 was combined with the ratio of total pGSN/sEV-pGSN, it was a significant predictor of chemoresponsiveness, but the test performance was not as robust as the total pGSN/sEV-pGSN alone.ConclusionsTotal pGSN/sEV-pGSN was the best predictor of chemoresponsiveness prior to treatment, outperforming the individual biomarkers (CA125, total pGSN, and sEV-pGSN). This multianalyte predictor of chemoresponsiveness could help to inform physicians' treatment and follow up plan at the time of EOC diagnosis, thus improving patients' outcomes.

Dataset Information

Extracellular Vesicle Molecular Signatures Characterize Metastatic Dynamicity in Ovarian Cancer.

Background

Methods

Conclusion

Publications

Extracellular Vesicle Molecular Signatures Characterize Metastatic Dynamicity in Ovarian Cancer.

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