English  |  正體中文  |  简体中文  |  Items with full text/Total items : 60932/93628 (65%)
Visitors : 1252377      Online Users : 14
RC Version 7.0 © Powered By DSPACE, MIT. Enhanced by NTU Library & TKU Library IR team.
Scope Tips:
  • please add "double quotation mark" for query phrases to get precise results
  • please goto advance search for comprehansive author search
  • Adv. Search
    HomeLoginUploadHelpAboutAdminister Goto mobile version
    Please use this identifier to cite or link to this item: https://tkuir.lib.tku.edu.tw/dspace/handle/987654321/121329


    Title: Exploration of the proteomic landscape of small extracellular vesicles in serum as biomarkers for early detection of colorectal neoplasia
    Authors: Chang, Li-Chun;Hsu, Yi-Chiung;Chiu, Han-Mo;Ueda, Koji;Wu, Ming-Shiang;Kao, Chiun-How;Shen, Tang-Long
    Keywords: colorectal cancer;blood test;small extracellular vesicle;proteome, biomarker
    Date: 2021-09-13
    Issue Date: 2021-09-24 12:13:55 (UTC+8)
    Abstract: Background: Patient participation in colorectal cancer (CRC) screening via a stool test and colonoscopy is suboptimal, but participation can be improved by the development of a blood test. However, the suboptimal detection abilities of blood tests for advanced neoplasia, including advanced adenoma (AA) and CRC, limit their application. We aimed to investigate the proteomic landscape of small extracellular vesicles (sEVs) from the serum of patients with colorectal neoplasia and identify specific sEV proteins that could serve as biomarkers for early diagnosis.

    Materials and Methods: We enrolled 100 patients including 13 healthy subjects, 12 non-AAs, 13 AAs, and 16 stage-I, 15 stage-II, 16 stage-III, and 15 stage-IV CRCs. These patients were classified as normal control, early neoplasia, and advanced neoplasia. The sEV proteome was explored by liquid chromatography-tandem mass spectrometry. Generalized association plots were used to integrate the clustering methods, visualize the data matrix, and analyze the relationship. The specific sEV biomarkers were identified by a decision tree via Orange3 software. Functional enrichment analysis was conducted by using the Ingenuity Pathway Analysis platform.

    Results: The sEV protein matrix was identified from the serum of 100 patients and contained 3353 proteins, of which 1921 proteins from 98 patients were finally analyzed. Compared with the normal control, subjects with early and advanced neoplasia exhibited a distinct proteomic distribution in the data matrix plot. Six sEV proteins were identified, namely, GCLM, KEL, APOF, CFB, PDE5A, and ATIC, which properly distinguished normal control, early neoplasia, and advanced neoplasia patients from each other. Functional enrichment analysis revealed that APOF+ and CFB+ sEV associated with clathrin-mediated endocytosis signaling and the complement system, which have critical implications for CRC carcinogenesis.

    Conclusion: Patients with colorectal neoplasia had a distinct sEV proteome expression pattern in serum compared with those patients who were healthy and did not have neoplasms. Moreover, the six identified specific sEV proteins had the potential to discriminate colorectal neoplasia between early-stage and advanced neoplasia. Collectively, our study provided a six-sEV protein biomarker panel for CRC diagnosis at early or advanced stages. Furthermore, the implication of the sEV proteome in CRC carcinogenesis via specific signaling pathways was explored.
    Relation: Frontiers in Oncology 11, 732743
    DOI: 10.3389/fonc.2021.732743
    Appears in Collections:[統計學系暨研究所] 期刊論文

    Files in This Item:

    File Description SizeFormat
    Exploration of the proteomic landscape of small extracellular vesicles in serum as biomarkers for early detection of colorectal neoplasia.pdf1733KbAdobe PDF14View/Open
    index.html0KbHTML70View/Open

    All items in 機構典藏 are protected by copyright, with all rights reserved.


    DSpace Software Copyright © 2002-2004  MIT &  Hewlett-Packard  /   Enhanced by   NTU Library & TKU Library IR teams. Copyright ©   - Feedback