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Extracellular Vesicle Molecular Signatures Characterize Metastatic Dynamicity in Ovarian Cancer.
Gonda, Amber; Zhao, Nanxia; Shah, Jay V; Siebert, Jake N; Gunda, Srujanesh; Inan, Berk; Kwon, Mijung; Libutti, Steven K; Moghe, Prabhas V; Francis, Nicola L; Ganapathy, Vidya.
Afiliação
  • Gonda A; Department of Biomedical Engineering, Rutgers University, Piscataway, NJ, United States.
  • Zhao N; Department of Chemical and Biochemical Engineering, Rutgers University, Piscataway, NJ, United States.
  • Shah JV; Department of Biomedical Engineering, Rutgers University, Piscataway, NJ, United States.
  • Siebert JN; Department of Biomedical Engineering, Rutgers University, Piscataway, NJ, United States.
  • Gunda S; Rutgers-Robert Wood Johnson Medical School, Rutgers University, New Brunswick, NJ, United States.
  • Inan B; School of Environmental and Biological Sciences, Rutgers University, New Brunswick, NJ, United States.
  • Kwon M; School of Environmental and Biological Sciences, Rutgers University, New Brunswick, NJ, United States.
  • Libutti SK; Rutgers Cancer Institute of New Jersey, Rutgers University, New Brunswick, NJ, United States.
  • Moghe PV; Rutgers Cancer Institute of New Jersey, Rutgers University, New Brunswick, NJ, United States.
  • Francis NL; Department of Biomedical Engineering, Rutgers University, Piscataway, NJ, United States.
  • Ganapathy V; Department of Chemical and Biochemical Engineering, Rutgers University, Piscataway, NJ, United States.
Front Oncol ; 11: 718408, 2021.
Article em En | MEDLINE | ID: mdl-34868914
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.
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Texto completo: 1 Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Ano de publicação: 2021 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Ano de publicação: 2021 Tipo de documento: Article