Your email was sent successfully. Check your inbox.

An error occurred while sending the email. Please try again.

Proceed reservation?

Export
  • 1
    In: Hepatology, Ovid Technologies (Wolters Kluwer Health), Vol. 77, No. 3 ( 2023-03), p. 774-788
    Abstract: The sensitivity of current surveillance methods for detecting early‐stage hepatocellular carcinoma (HCC) is suboptimal. Extracellular vesicles (EVs) are promising circulating biomarkers for early cancer detection. In this study, we aim to develop an HCC EV‐based surface protein assay for early detection of HCC. Approach and Results: Tissue microarray was used to evaluate four potential HCC‐associated protein markers. An HCC EV surface protein assay, composed of covalent chemistry‐mediated HCC EV purification and real‐time immuno‐polymerase chain reaction readouts, was developed and optimized for quantifying subpopulations of EVs. An HCC EV ECG score, calculated from the readouts of three HCC EV subpopulations ( E pCAM + CD63 + , C D147 + CD63 + , and G PC3 + CD63 + HCC EVs), was established for detecting early‐stage HCC. A phase 2 biomarker study was conducted to evaluate the performance of ECG score in a training cohort ( n  = 106) and an independent validation cohort ( n  = 72). Overall, 99.7% of tissue microarray stained positive for at least one of the four HCC‐associated protein markers (EpCAM, CD147, GPC3, and ASGPR1) that were subsequently validated in HCC EVs. In the training cohort, HCC EV ECG score demonstrated an area under the receiver operating curve (AUROC) of 0.95 (95% confidence interval [CI], 0.90–0.99) for distinguishing early‐stage HCC from cirrhosis with a sensitivity of 91% and a specificity of 90%. The AUROCs of the HCC EV ECG score remained excellent in the validation cohort (0.93; 95% CI, 0.87–0.99) and in the subgroups by etiology (viral: 0.95; 95% CI, 0.90–1.00; nonviral: 0.94; 95% CI, 0.88–0.99). Conclusion: HCC EV ECG score demonstrated great potential for detecting early‐stage HCC. It could augment current surveillance methods and improve patients’ outcomes.
    Type of Medium: Online Resource
    ISSN: 0270-9139
    Language: English
    Publisher: Ovid Technologies (Wolters Kluwer Health)
    Publication Date: 2023
    detail.hit.zdb_id: 1472120-X
    Library Location Call Number Volume/Issue/Year Availability
    BibTip Others were also interested in ...
Close ⊗
This website uses cookies and the analysis tool Matomo. Further information can be found on the KOBV privacy pages