Small extracellular vesicles-derived signatures – a non-invasive longitudinal screening tool in ovarian cancer

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. Rutgers University researchers show the promise of a sEV-derived signature as a non-invasive longitudinal screening tool in ovarian cancer.

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.

Plasma-derived sEV gene expression in a mouse model of ovarian cancer

Representative fluorescent imaging of SKOV-3/RFP cells in tumor-bearing and non-tumor-bearing mice in (A) Week 1, (B) Week 2, and (C) Week 3. Scatter plots of ΔCq values at (D) Week 1 for tumor- (blue, n=4) and non-tumor-bearing samples (red, n=3), (E) Week 2 for tumor- (blue, n=5) and non-tumor-bearing samples (red, n=4), and (F) Week 3 for tumor (blue, n=9) and non-tumor-bearing samples (red, n=3). Heat maps showing the percentage of detected Cq values at (G) Week 1, (H) Week 2, and (I) Week 3. (J) Scatter plot of ΔCq values for tumor-bearing samples over Weeks 1-3 of tumor development; (K) Heat map showing the percentage of detected Cq values in tumor-bearing samples for Weeks 1, 2, and 3. p values for unpaired two-tailed t-test are labeled in the graphs. The number of non-detected (n.d.) Cq values in each experimental group are listed underneath the corresponding scatter plots. Heat maps in g, h, i, and k indicate the absence/presence of the target gene (percentage of detected Cq values) in each experimental group. *p<0.05, **p<0.01, ***p<0.001, ****p<0.0001.

These results highlight the potential of sEVs in monitoring ovarian cancer progression and metastatic development. The researchers identified a 7-gene panel in sEVs derived from plasma, serum, and ascites that overlapped with an established metastatic ovarian carcinoma signature. They 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, the researchers were unable to establish a definitive signature due to low sample number. Taken together these 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.

Gonda A, Zhao N, Shah JV, Siebert JN, Gunda S, Inan B, Kwon M, Libutti SK, Moghe PV, Francis NL, Ganapathy V. (2021) Extracellular Vesicle Molecular Signatures Characterize Metastatic Dynamicity in Ovarian CancerFront Onco 11(1) , 4827. [article]

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