Metastatic State of Colorectal Cancer can be Accurately Predicted with Methylome

Somayah Albaradei, Maha Thafar, Christophe Van Neste, Magbubah Essack, Vladimir B. Bajic

Research output: Chapter in Book/Report/Conference proceedingConference contribution

6 Scopus citations


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.
Original languageEnglish (US)
Title of host publicationProceedings of the 2019 6th International Conference on Bioinformatics Research and Applications
Number of pages6
ISBN (Print)9781450372183
StatePublished - May 4 2020


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