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    Metastatic State of Colorectal Cancer can be Accurately Predicted with Methylome

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    Type
    Conference Paper
    Authors
    Albaradei, Somayah
    Thafar, Maha
    Van Neste, Christophe
    Essack, Magbubah
    Bajic, Vladimir B.
    KAUST Department
    Computer Science Program
    Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
    KAUST Grant Number
    BAS/1/1606-01-01
    URF/1/1976
    Date
    2020-04-17
    Online Publication Date
    2020-04-17
    Print Publication Date
    2019-12-19
    Permanent link to this record
    http://hdl.handle.net/10754/664683
    
    Metadata
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    Abstract
    Colorectal cancer (CRC) appears to be the third most common cancer as well as the fourth most common cause of cancer deaths in the world. Its most lethal states are when it becomes metastatic. It is of interest to find tests that can quickly and accurately determine if the patient has already developed metastasis. Changes in methylation profiles have been found to be characteristic of cancers at different stages and can therefore be used to develop diagnostic panels. We developed a deep learning (DL) model (Deep2Met) using methylation profiles of patients with CRC to predict if the cancer is in its metastatic state. Results suggest that our method achieves an AUPR and an average F-score of 96.99% and 94.71%, respectively, making Deep2Met potentially useful for diagnostic purposes. The DL model Deep2Met we developed, shows promise in the diagnosis of CRC based on methylation profiles of individual patients.
    Citation
    Albaradei, S., Thafar, M., Van Neste, C., Essack, M., & Bajic, V. B. (2019). Metastatic State of Colorectal Cancer can be Accurately Predicted with Methylome. Proceedings of the 2019 6th International Conference on Bioinformatics Research and Applications. doi:10.1145/3383783.3383792
    Sponsors
    This work has been supported by the King Abdullah University of Science and Technology (KAUST) Base Research Fund (BAS/1/1606-01-01) to VBB, and KAUST Office of Sponsored Research (OSR) under Awards No CCF ? URF/1/1976-30-01
    Publisher
    ACM
    Conference/Event name
    6th International Conference on Bioinformatics Research and Applications, ICBRA 2019
    ISBN
    9781450372183
    DOI
    10.1145/3383783.3383792
    Additional Links
    https://dl.acm.org/doi/10.1145/3383783.3383792
    ae974a485f413a2113503eed53cd6c53
    10.1145/3383783.3383792
    Scopus Count
    Collections
    Conference Papers; Computer Science Program; Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division

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