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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.
