These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.


Pubmed for Handhelds

PUBMED FOR HANDHELDS

Search MEDLINE/PubMed

  • Title: Exosomal let-7d-3p and miR-30d-5p as diagnostic biomarkers for non-invasive screening of cervical cancer and its precursors.
    Author: Zheng M, Hou L, Ma Y, Zhou L, Wang F, Cheng B, Wang W, Lu B, Liu P, Lu W, Lu Y.
    Journal: Mol Cancer; 2019 Apr 02; 18(1):76. PubMed ID: 30940131.
    Abstract:
    Cervical cancer screening through detection and treatment of high-grade cervical intraepithelial neoplasia (CIN) is most successful in cancer prevention. However, the accuracy of the current cervical cancer screening tests is still low. The aim of this study was to develop a more accurate method based on circulating exosomal miRNAs. The miRNA sequencing was performed to identify candidate exosomal miRNAs as diagnostic biomarkers in 121 plasma samples from healthy volunteers, cervical carcinoma patients, and CIN patients. A panel with eight differentially expressed exosomal miRNAs was identified to distinguish patients in the CIN II+ group (including advanced CIN II patients) from those in the CIN I- group (including CIN I patients and healthy volunteers). Let-7d-3p and miR-30d-5p showed significant difference between cervical tumors and adjacent normal tissues (P < 0.005), exhibited a consistent trend in plasma samples, and were further validated in 203 independent plasma samples. Integrating these two miRNAs yielded an AUC value of 0.828 to distinguish patients in CIN II+ group from those in CIN I- group. Further integrating them into a cytological test-based model resulted in a higher AUC of 0.887, while the AUC value based on the cytological test alone was 0.766. In summary, plasma exosomal miR-30d-5p and let-7d-3p are valuable diagnostic biomarkers for non-invasive screening of cervical cancer and its precursors. Further validation using large sample sizes is required for clinical diagnosis.
    [Abstract] [Full Text] [Related] [New Search]